Endophytic Fungi from Sorghum bicolor (L.) Moench

Journal of Agricultural Science and Technology B Volume 8, Number 5, May 2018 (Serial Number 69)

David Publishing

David Publishing Company www.davidpublisher.com

Publication Information:

Journal of Agricultural Science and Technology B (Earlier title: Journal of Agricultural Science and Technology, ISSN 1939-1250) is published monthly in hard copy (ISSN 2161-6264) by David Publishing Company located at 616 Corporate Way, Suite 2-4876, Valley Cottage, NY 10989, USA.

Aims and Scope:

Journal of Agricultural Science and Technology B, a monthly professional academic journal, particularly emphasizes new research results in agronomy, forestry, aquaculture, fisheries, food science, all aspects of crop physiology, modeling of crop and forest systems, engineering solutions and so on. Articles interpreting practical application of up-to-date technology are also welcome.

Editorial Board Members (in alphabetical order):

Catherine W. Gitau (Australia) Dharmatilleke Bandula Kelaniyangoda (Sri Lanka) Ekachai Chukeatirote (Thailand) Erin K. Espeland (USA) Farzana Perveen (Pakistan) Francesco Contò (Italy) Francesco Montemurro (Italy) Genhua Niu (USA) Gulshan Mahajan (India) Idress Hamad Attitalla (Libya) Jang Ho Son (Korea) Jagadish Timsina (Bangladesh) Jelena Bošković (Serbia) Manoj K. Shukla (USA) Mehmet Musa Özcan (Turkey) M. S. Qureshi (Pakistan) Milad Manafi (Iran) Mehmet Rüştü Karaman (Turkey) Noureddine Benkeblia (Algeria) Natraj Krishnan (USA) Olivier A. E. Sparagano (UK) Ozlem TOKUSOGLU (Turkey) Renato S. Pacaldo (USA) Ram C. Bhujel (Thailand) Shoil M. Greenberg (USA) Sanjeev Kumar Chauhan (India) Shri Mohan Jain (Finland) Thai Ngoc Chien (Vietnam) T. Chatzistathis (Greece) Vasudeo P. Zambare (USA) Vasileios Fotopoulos (Greece) Young Jung Kim (Korea) Yusuf Bozkurt (Turkey) Zeki Candan (Turkey) Manuscripts and correspondence are invited for publication. You can submit your papers via web submission, or E-mail to [email protected]. Submission guidelines and web submission system are available at http://www.davidpublisher.com.

Editorial Office:

616 Corporate Way, Suite 2-4876, Valley Cottage, NY 10989, USA Tel: 1-323-984-7526, 323-410-1082 Fax: 1-323-984-7374, 323-908-0457 E-mail: [email protected], [email protected], [email protected] Copyright©2018 by David Publishing Company and individual contributors. All rights reserved. David Publishing Company holds the exclusive copyright of all the contents of this journal. In accordance with the international convention, no part of this journal may be reproduced or transmitted by any media or publishing organs (including various websites) without the written permission of the copyright holder. Otherwise, any conduct would be considered as the violation of the copyright. The contents of this journal are available for any citation. However, all the citations should be clearly indicated with the title of this journal, serial number and the name of the author.

Abstracted/Indexed in:

Chemical Abstracts Service (CAS), USA Ulrich’s Periodicals Directory, USA Chinese Database of CEPS, American Federal Computer Library Center (OCLC), USA China National Knowledge Infrastructure (CNKI), China Chinese Scientific Journals Database, VIP Corporation, Chongqing, China Norwegian Social Science Data Services (NSD), Norway Index Copernicus, Poland Universe Digital Library Sdn Bhd (UDLSB), Malaysia Google Scholar PBN (Polish Scholarly Bibliography) Electronic Journals Library AcademicKeys CiteFactor (USA)

Subscription Information:

Price (per year) Print $1200 David Publishing Company 616 Corporate Way, Suite 2-4876, Valley Cottage, NY 10989, USA Tel: 1-323-984-7526, 323-410-1082 Fax: 1-323-984-7374, 323-908-0457 E-mail: [email protected] Digital Cooperative Company: www.bookan.com.cn

D

DAVID PUBLISHING

David Publishing Company www.davidpublisher.com

Journal of Agricultural Science and Technology B Volume 8, Number 5, May 2018 (Serial Number 69)

Contents Research Papers 267

Endophytic Fungi from Sorghum bicolor (L.) Moench: Influence of Genotypes and Crop Systems and Evaluation of Antimicrobial Activity Ruth Terezinha Rodrigues, Márcia Marília de Souza Silva, Douglas Moreira de Oliveira, Josimar Bento Simplício, Cynthia Maria Carneiro Costa and Virginia Medeiros de Siqueira

278

Effects of PEG Priming and Fungicide Treatment on Kenaf (Hibiscus cannabinus L.) Seed Germination In-Sok Lee, Chan-Ho Kang, Suk-Ju Kwon and Young-Eun Na

290

Impact of Irrigation Water Salinity on Germination and Seedling Growth of Egyptian Barley Cultivars Farid Hellal, Ahmad Amer, Kadria EL Azab and Raafat Zewainy

303

Relationships among Bean Yield Traits in Some Cacao (Theobroma cacao L.) Genotypes Adenuga Olalekan Omotayo, Adepoju Abigail Funlayo, Olaniyi Olayinka Olufemi and Balogun Shamsudeen Tomiwa

311

Soil Attributes in Anthropized Hygrophilous Forest in Northern Minas Gerais State, Brazil Maria das Dores Magalhães Veloso, Luiz Arnaldo Fernandes, Marly Antonielle de Ávila, Yule Roberta Ferreira Nunes and Leidivan Almeida Frazão

320

Effect of Browsing on the Growth of Jojoba Seedlings in the Dry-Lands of Kenya Shadrack Kinyua Inoti

327

Fortification of Pasta Using Different Plant Sources R. Saraswathi and R. Sahul Hameed

D

Journal of Agricultural Science and Technology B 8 (2018) 267-277 doi: 10.17265/2161-6264/2018.05.001

DAVID PUBLISHING

Endophytic Fungi from Sorghum bicolor (L.) Moench: Influence of Genotypes and Crop Systems and Evaluation of Antimicrobial Activity Ruth Terezinha Rodrigues, Márcia Marília de Souza Silva, Douglas Moreira de Oliveira, Josimar Bento Simplício, Cynthia Maria Carneiro Costa and Virginia Medeiros de Siqueira Federal Rural University of Pernambuco, Academic Unit of Serra Talhada, 56909-535, Serra Talhada, Pernambuco, Brazil Abstract: Endophytic fungi (EF) colonize plant tissues without causing damage; this relationship brings benefits to both, including a greater resistance to environmental stresses, but the influence of genotypes and culture system in endophytic community is still unraveled. Thus, this work aimed to study EF from Sorghum bicolor and correlate to its genotypes submitted to different culture systems; their potential to produce antimicrobial compounds was also evaluated. To optimize the production of metabolites, four isolates were submitted to liquid medium and the crude extracts of different culture times were analyzed. EF of leaves of Qualimax and SF15 genotypes were isolated after superficial disinfection. Fungal identification was made using classical taxonomy. As results, the traditional system presented the lowest number EF isolates, while the minimum system showed the highest. The genera Aspergillus, Fusarium, Penicillium, Cladosporium, Curvularia and Syncephalastrum were found; Aspergillus spp. was pointed out as a predominant endophyte of genotype Qualimax. Among the 25 endophytes submitted antimicrobial activity assay in solid medium, 21 presented antibacterial activity against at least one bacterium with the highest inhibition zone of 29.3 mm of diameter against Staphylococcus aureus. All EF submitted to liquid medium kept the capacity to produce antibacterial metabolites. In conclusion, regardless of genotype and culture system, sorghum is colonized by different EF, mainly Aspergillus spp. EF from leaves of S. bicolor produce antibacterial compounds and their biotechnological applications can be explored in future. Key words: Plant microbiome, genotypes, sorghum, semi-arid, antimicrobial compounds.

1. Introduction Sorghum bicolor (L.) Moench (Family Poaceae) is popularly known in Brazil as “sorgo” or “milho-zaburro” and represents one of the most important fodder supports for livestock in the Brazilian semi-arid region, once it is a crop of high potential for production of green mass in this climatic condition. Additionally, S. bicolor is a xerophytic plant with low requirements in soil fertility and high tolerance to drought and saline stresses [1]. Due to the advantages in its use for forage, different genotypes of sorghum has been introduced in the market, but information about these genotypes and Corresponding author: Virginia Medeiros de Siqueira, professor, research fields: environmental microbiology, endophytic fungi, bioprospection and bioactive compounds.

their interactions with microorganisms, such as endophytic fungi (EF), have been poorly reported [2]. Diverse researches about fungi associated with well-characterized and economically important plants often reveal new taxa and new distributions of the known species. These studies contribute to the knowledge of interactions between different plants and microorganisms, contribute to the study of biodiversity, and reveal possible microorganisms that can be biotechnologically exploited [3, 4]. In addition, researches in this area can also provide a better understanding of the different types of genotypes submitted to different crop systems and their influence in the plant endophytic microbiota. In recent years, several studies have been carried out to explore the diversity of EF of crop plants, as well as the application of these microorganisms in the

268

Endophytic Fungi from Sorghum bicolor (L.) Moench: Influence of Genotypes and Crop Systems and Evaluation of Antimicrobial Activity

improvement of banana, passion fruit, citrus, sugar cane, for example [5-7]. Zida et al. (2014) [8] recently published interesting results about EF of S. bicolor in Burkina Faso in Africa, but researches about EF of S. bicolor are still rare in Brazil, thus arising the need for studies in this area. The present work aimed to study EF associated with two genotypes of forage S. bicolor submitted to three different crop systems in the Brazilian northeastern semi-arid region, in the municipality of Serra Talhada, state of Pernambuco. In addition, the potential production of antimicrobial compounds by the EF was also evaluated.

according to Araújo et al. (2002) [9]. For elimination of epiphytic microorganisms, the plant material was submitted to the surface sterilization process in which sorghum leaves were washed in running water, followed by immersion in 70% ethanol for 1 min, in sodium hypochlorite (2%-2.5% active chlorine) for 4 min, in 70% ethanol for 30 s and washed three distilled and sterilized water. After superficial sterilization, the samples were cut

into

0.5

cm2

fragments

and

aseptically

transferred to Petri dishes containing Sabouraud Dextrose Agar (SDA) culture medium (peptone 10 g/L, dextrose 40 g/L, agar 15 g/L, pH 5.6), supplemented with chloramphenicol (100 μg/mL) to

2. Materials and Methods

suppress

bacterial

growth.

Petri

dishes

were

2.1 Cropping Systems, Genotypes and Sample Collection

incubated at 28 °C up to 30 d, checked daily and any

Two sorghum genotypes (Qualimax and SF-15) submitted to three different crop systems (conventional, minimum cultivation and no-tillage) composed the experimental treatments. The collection of plant material was carried out at the Experimental Station of the Institute of Farming Research of Pernambuco (IPA), Serra Talhada, state of Pernambuco, Brazil. Leaves of five healthy adult plants from each genotype submitted to a different crop system were randomly collected, labeled and placed into plastic bags previously autoclaved. From each sorghum plant, three leaves were randomly selected, from which five fragments were removed, thus totaling 15 leaf fragments of each individual plant, and 75 leaf fragments of each genotype. Two genotypes submitted to three cropping system were analyzed, totaling 450 fragments of sorghum leaves. The samples were sent under refrigeration to the Laboratory of Microbiology of the Federal Rural University of Pernambuco, Academic Unit of Serra Talhada, Brazil, for further analyses.

preserved for further identification. Percentage

2.2 Isolation, Quantification and Identification of EF Endophytic

fungal

isolation

was

performed

fungal colony present was isolated, purified and colonization was defined as the total number of fragments colonized by fungi in relation to the total number of fragments  100 [10]. The control of surface sterilization efficiency was confirmed by the inoculation of the last wash water in Petri dishes with the Agar Nurtrient (AN) culture medium (peptone 5 g/L, yeast extract 3 g/L, sodium chloride 5 g/L, agar 15 g/L, pH 6.8). The identification of EF was done using macroscopic characteristics of the colonies (color, aspect, consistency and presence of pigmentation) and microscopic characteristics (morphology of vegetative and reproductive structures). The following literature was used for identification [11-15]. Potato Dextrose Agar (PDA) (potato infusion 200 g/L, dextrose 20 g/L, agar 15 g/L, pH 5.6), SDA and Water Agar were utilized and incubation was at 28 ± 2 °C during up to 30 d. 2.3 Screening and Agar Plug Assay Twenty five purified EF were selected and submitted to agar plug assay [16] which is a technique that permits a rapid and qualitative selection of the


fungi capable to inhibit other microorganisms.

269

separate fungal biomass. After this, 20 μL of the

The fungi were grown on SDA at 28 °C during 7 d

supernatant was used for the antimicrobial activity

and, after this period, discs (6 mm diameter) of

test using the disk diffusion method [17]. The tests

mycelium agar were cut and transferred onto the

were performed in triplicate and the measurements of

culture media Müeller-Hinton Agar (peptone 3.0 g/L,

the inhibition zones were expressed in millimeters by

2+

peptone of casein 17.5 g/L, agar 15 g/L, Ca

20-25

means of triplicates.

2+

g/L, Mg 10-12.5 g/L, pH 7.4) previously spread with microorganisms

test:

(ATCC-6538),

Bacillus

Staphylococcus

aureus

subtilis

(UFPEDA-16),

Escherichia coli (ATCC-25922)

and Klebsiella

pneumoniae

(ATCC-29665).

Petri

dishes

were

incubated at 37 °C for 24 h and the antimicrobial activity was confirmed by the visualization and measurement of inhibition zones. The tests were performed in triplicate and the measurements of the inhibition zones were expressed in millimeters by means of triplicates. 2.4 Fermentation and Disk Diffusion Assay The EF that showed the best activity in the agar plug assay were evaluated in liquid culture medium at different time of cultivation. This provides a way to confirm if the fungi are still able to produce the bioactive compound in liquid culture medium and select the best time for the production of the bioactive metabolites. For this, five plugs (6 mm in diameter) of fungal growing culture were inoculated into 500 mL Erlenmeyer flasks containing 250 mL of Broth Sabouraud. The cultures were submitted to a rotary shaker at 180 rpm at room temperature (28 ± 2 °C) during 120 h. After 72, 96 and 120 h of cultivation, an aliquot of 10 mL were transferred into plastic tubes and centrifuged at 225 g for 15 min to

3. Results and Discussion 3.1 Quantification and Diversity of EF As all living organisms, plants are colonized by a wide variety of microorganisms that constitute their microbiome. The sum of the plant plus its microbiome composes the holobiont, which present interdependent and complex dynamics such as the ecological systems of higher organisms [18]. The holobiont of a vegetable is a good example of how the interaction between the plant and its microbiome brings advantages to its constituents. In the case of plants, the microbiome is composed of the rhizosphere, phylosphere and endosphere [19]; endophytic microorganisms compose the endosphere. From 450 fragments of leaves of S. bicolor, 107 fragments of genotype Qualimax and 81 fragments of genotype SF-15 were colonized by EF, representing a colonization rate of 47.5% and 36%, respectively. The SF-15 genotype presented the higher number of EF (38) when submitted to conventional planting, followed by Qualimax that presented 37 EF when submitted to both conventional and minimum cultivation systems. It was registered the lowest colonization rate (17.3%) in SF-15/no-tillage sorghum (Table 1).

Table 1 Quantification* of endophytic fungi (EF) from leaves of two genotypes of Sorghum bicolor submitted to different crop systems. Crop system No-tillage Minimum cultivation Conventional Total

Qualimax 33 37 37 107

*Number of fungal colonies.

Colonization rate (%) 44.0 49.3 49.3 47.5

SF-15 13 30 38 81

Colonization rate (%) 17.3 40.0 50.6 36

270


Based on their macromorphological characteristics, 61 fungal isolates were selected and purified, from which 31 were taxonomically identified. The genera Aspergillus, Fusarium, Penicillium, Cladosporium, Curvularia and Syncephalastrum were found as endophytic of leaves of sorghum (Tables 2 and 3). Thirty isolates were classified as “filamentous fungi” or “yeast” because they did not develop reproductive structures. Among the identified fungal isolates, Aspergillus was the genera presented in all analyzed conditions (except for genotype SF-15/minimum cultivation) Table 2

with 14 occurrences, 11 from genotype Qualimax and three from genotype SF-15; A. niger was the most presented species. Zida et al. (2014) [8] found different results in a study about EF from leaves, roots and stem of sorghum that showed Fusarium, Curvularia and Penicillium as the most represented genera, but not Aspergillus. These same authors also pointed out Leptosphaeria sacchari, Gloeocercospora sorghi, Acremonium and Bipolaris as endophytic fungal commonly isolated from sorghum leaves, and Penicillium, Curvularia and Fusarium as not specific to a given host tissue. In a study about EF from roots

EF isolated from leaves of S. bicolor–genotype Qualimax.

Isolate number 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 54 55 56 57 58 59 60 61

Crop system

No-tillage

Minimum cultivation

Conventional system

Identification A. niger A. flavus Curvularia sp. A. niger Fusarium sp. A. flavus A. niger A. niger Zygomycota Filamentous fungi Filamentous fungi Filamentous fungi Filamentous fungi Filamentous fungi Fusarium sp. Fusarium sp. Filamentous fungi Filamentous fungi A. niger Filamentous fungi Cladosporium sp. Cladosporium sp. Zygomycota A. costaricaensis Filamentous fungi Filamentous fungi A. niger Filamentous fungi A. niger Aspergillus sp. Filamentous fungi Penicillium sp.

Endophytic Fungi from Sorghum bicolor (L.) Moench: Influence of Genotypes and Crop Systems and Evaluation of Antimicrobial Activity Table 3

271

EF isolated from leaves of S. bicolor–genotype SF-15.

Isolate number 24 25 26 27 28 29 30 40 41 42 43 44 45 46 47 48 49 50 51 52 31 32 33 34 35 36 37 38 39

Crop system

No-tillage

Minimum cultivation

Conventional system

of S. bicolor in semi-arid of Pernambuco, Brazil, Fusarium and Curvularia were predominant [20]. Fusarium, Cladosporium and Curvularia occurred in leaves of both sorghum genotypes analyzed in the present study, confirming that these genera commonly establish mutualist association with plants, although they are also reported as phytopathogenic [21]. Fusarium for example is commonly found as phytopathogen as well as endophyte, i.e., without causing any apparent damage to the plant, what proves that a microorganism can live only part of its life cycle as an endophyte and develop different types of association, what may lead to the production of different metabolites [22]. Many biotic and abiotic factors influence in

Identification Filamentous fungi Filamentous fungi Cladosporium sp. Filamentous fungi A. niger Filamentous fungi Filamentous fungi Cladosporium sp. Filamentous fungi Fusarium sp. Filamentous fungi Filamentous fungi Filamentous fungi Penicillium sp. Filamentous fungi Filamentous fungi Filamentous fungi Syncephalastrum sp. Zygomycota Zygomycota Filamentous fungi Filamentous fungi Cladosporium sp. Yeast Zygomycota A. flavus Filamentous fungi Aspergillus sp. Curvularia sp.

endophytic community of the same vegetal species, such as geographical location, climate, agricultural practices, plant tissue and microbial soil composition, thus EF occupy millions of unique ecological niches in many environments [23, 24]. These factors play an important role in determining the structure and composition in the communities present in the endosphere [25]. Different methods of study, such as culture-independent methods, also influence in the endophytic community. Thus, each research may show a core group of species consistently isolated from any given host as well as long lists of incidental species, including new taxa [26]. Characteristics of plant host are also important features that influence endophytic community

272


composition. S. bicolor (L.) Moench is a well-known crop and its rusticity, high biomass production and great tolerance to water deficit are often mentioned [27]. By the other hand, research about how sorghum genotype influences in its endophytic community composition are scarce. Studies in this area have shown that monoculture, cultivation techniques and plant genotype change bacterial and fungal diversity in soil [28-31]. Microbial community in soil may reflect in endophytic fungal composition, but more detail work is necessary to correlate plant genotype and cultivation systems with endophytic fungal communities of sorghum. Qualimax genotype is a hybrid obtained by the crossing of saccharine and dry stems varieties and when compared to others sorghum genotypes it is considered superior due to its high adaptability to regions of harsh climate [27]. The results stand out Aspergillus spp. as a predominant endophyte of Qualimax. Aspergillus is a ubiquitous genus that produces asexual spores named conidia and its members possess the ability to grow under a wide range of temperature, pH, osmotic pressure, carbon source and oxygen concentration, and can establish different symbiotic relationships, such as parasitism, saprophytism and mutualism [32]. As a versatile and well-adapted fungus, it is possible that Aspergillus is overlapping other fungal genera more sensitive to biotic variations such as the characteristics of the Qualimax genotype. Semi-arid region of Brazilian Northeast characterized by high temperatures, with an annual average of 25 °C, and a low annual average rainfall of approximately 450 mm [33]. EF that habit tissues of plants in semi-arid regions are well adapted to such conditions, making then an important source for agricultural appliance aimed to increase crop production under saline and drought stresses, for example [34]. Despite the recognized importance of EF for crops such as sorghum, researches focus mostly on diversity

and biotechnological application of endophytic bacteria [35]; what emphasizes the lack of studies about EF, and even more in semi-arid region. Additionally, when the objective of the research is the plant microbiota, it is important not to exclude any group of microorganism, but consider the interactions between bacteria and fungi endophytes [36, 37]. 3.2 Antibacterial Activity 3.2.1 Screening and Agar Plug Assay Among the 25 EF tested, 23 showed antimicrobial activity against at least one of the bacteria, Gram-positive or Gram-negative (Table 4). Four fungal isolates A. niger (19), A. niger (58), Zygomycota (51) and A. flavus (06) did not show any antimicrobial activity. The inhibition zones varied from 6.3 mm up to 29.3 mm of diameter. Fusarium sp. (16) showed the best result against B. subtillis with an inhibition zone of 29.3 mm, as well as Penicillium sp. (61) against S. aureus, followed by Aspergillus sp. (38) with an inhibition zone of 28.3 mm against B. subtillis and 25.3 mm against S. aureus (Table 4). It was also observed that Syncephalastrum sp. (50), Fusarium sp. (42), Aspergillus sp. (59), A. niger (07) and Penicillium sp. (46) inhibited the growth of all bacteria, thus representing a wide spectrum of action. EF inhabit the interior of plant tissues; this constant interaction, associated with abiotic factors, generates the production of metabolites as response [38]. These metabolites may have biotechnological applications, as they are biologically active, including enzymes [39], amino acids, vitamins, antibiotics, pigments [40, 41], antitumor agents [42], plant growth factors [43], anthelmintics and antifungals [44]. The results of the present research show that EF from S. bicolor produce antibacterial compounds. According to Schulz and Boyle [45], most species of Acremonium, Alternaria, Cladosporium, Fusarium, Phoma, Pleospora and Phomopsis are considered a rich source of compounds of biotechnological

Endophytic Fungi from Sorghum bicolor (L.) Moench: Influence of Genotypes and Crop Systems and Evaluation of Antimicrobial Activity Table 4

273

Inhibitions zones of EF against bacteria.

EF (no) A. flavus (02) A. flavus (36) A. flavus (06) A. niger (53) A. niger (19) A. niger (56) A. niger (58) A. niger (08) A. niger (04) A. niger (01) A. niger (07) Aspergillus sp. (59) Aspergillus sp. (38) Curvularia sp. (03) Fusarium sp. (42) Fusarium sp. (05) Fusarium sp. (16) Penicillium sp. (46) Penicillium sp. (61) Syncephalastrum sp. (50) Zygomycota (52) Zygomycota (51) Filamentous fungi (48) Filamentous fungi (18) Filamentous fungi (37)

E. coli 10.3 19.3 18.3 19.0 16.6 13.0 16.0 19.7 19.0 6.3 14.0 11.7 14.3 11.3 13.0 11.7 18.3 18.3

Inhibition zones - Ø mm K. pneumonie S. aureus 23.6 20.6 20.6 20.3 21.3 17.0 17.3 21.0 12.3 14.3 19.3 19.7 19.7 19.7 21.6 25.6 6.7 15.0 13.3 15.7 8.3 12.5 18.6 23.6 13.3 15.7 14.0 29.3 9.3 11.2 3.0 9.3 22.3 18.3 12.3 23.6

B. subtilis 21.3 21.3 28.3 16.7 29.3 16.7 25.0 16.0 -

- : no inhibition.

interest because of their production of new metabolites. The current study presented that Aspergillus sp. showed antibacterial activity against S. aureus, B. subtilis, E. coli and K. pneumoniae. The genus Aspergillus is also notable for producing a wide variety of both primary and secondary metabolites, including amino acids, vitamins, pigments and antibiotics [46]. The endophyte Fusarium sp. (42) was also isolated in the present study and inhibited the growth of all test bacteria, and Fusarium sp. (16) which also inhibited all bacteria, but not E. coli. In a similar study, isolates of the medicinal plant Aquilaria sinensis were tested and found that species of the genus Fusarium inhibited the growth of B. subtilis, S. aureus and E. coli [47].

The variety of secondary metabolites produced by a single endophyte has not been estimated yet [48]. Some studies report that certain EF produce compounds equally present in their hosts, for example some enzymes (cellulase and lignase) produced by Xylaria sp. and growth factors such as gibberellin produced by Fusarium; and also antitumor substances such as taxol in Taxomyces andreanae, among others. This fact suggests a transposition of genes between plants and fungi into a real in vivo genetic engineering [49, 50]. 3.2.2 Fermentation and Disk Diffusion Assay Aiming to optimize the production of metabolites, four isolates were cultured in liquid medium and the crude extracts at different times were analyzed. Syncephalastrum sp. (50), A. niger (56), A. niger (07)

274


and Aspergillus sp. (59) were selected since they had higher inhibition zones as well as a wide spectrum in the agar plug assay. Aspergillus sp. (59) showed inhibition zone of 25.7 mm against E. coli and 23.3 mm against S. aureus, both at 120 h, followed by Syncephalastrum sp. (50) with a 26.7 mm mean inhibition zone at 96 h against S. aureus and 23.3 mm against B. subtillis (Table 5). A. niger (56) had the lowest inhibition with a halo of 5.7 mm against K. pneumoniea at 72 h, and reached only 9 mm at 120 h. In general, it was observed that there was an increase even if discrete in the production of the antimicrobial compound in liquid medium along cultivation time (Table 5). Microorganisms control the biosynthesis of metabolites using regulatory mechanisms to avoid overproduction. In some cases, the regulatory mechanisms process low levels that are undesirable for biotechnological application, then the optimization of physical and/or chemical factors can increase the output of the bioactive compounds [51]. In order to proceed with bioprospecting, it is necessary to verify if the microorganism still produces the bioactive compound in liquid culture medium, since it is under this condition that experiments are conducted in industrial scales. Large-scale production brings Table 5

benefits such as higher production of microbial biomass and consequently greater production of the compound of interest [52]. In this work, culturing time was the optimization factor evaluated, i.e., the crude extracts of fungi that showed the best results in agar plug assay were evaluated after 72, 96 and 120 h of culture in liquid medium. The best results were showed by Aspergillus sp. (59) and A. niger (56) that after 120 h of culture showed inhibition zones of 23.3 mm and 25.3 mm against S. aureus, respectively, and 25.7 mm and 26.3 mm against E. coli, respectively. A similar research developed by Siqueira et al. (2011) [26] found that between 72 h and 96 h, pH 5-7 and malt extract culture medium were the best culture conditions for the production of the bioactive compounds. Among 16 EF submitted to the fermentation test, 10 exhibited antimicrobial activity. From these, 90% showed activity against S. aureus, 30% against B. subtilis and 10% against K. pneumoniae, with inhibition halos varying from 13 mm to 25 mm. Merlin et al. (2013) [53] conducted a research that aimed the optimization of culture conditions and the results showed that 9 d of incubation was the ideal time for the production of antibacterial metabolites, at the 10th day the production was slightly lower. The

The antimicrobial activity of the fermentation liquid.

Time (h)

S. aureus

E. coli

B. subtilis

K. pneumonie

72 96 120 72 96 120 72 96 120 72 96 120

59

56

21.3 19.3 23.3 25.0 24.7 25.7 17.0 16.0 18.7 21.0 18.3 20.3

23.3 20.7 25.3 24.7 24.0 26.3 8.3 9.3 12.7 5.7 7.3 9.0

A. niger (56); A. niger (07); Aspergillus sp. (59); Syncephalastrum sp. (50).

EF 50 Inhibition zones (mm) 24.0 26.7 26.7 9.7 12.3 12.3 23.3 25.0 25.0 10.0 12.0 12.0

07 18.7 20.0 20.0 11.0 11.7 11.7 18.7 18.7 18.7 12.3 10.7 10.7


production of antibacterial compounds follows the kinetics of fungal growth, so the highest production of a secondary metabolite often occurs during the sporulation stage of the microorganism [54]. Oliveira et al. (2011) [55] used fungal extracts obtained directly from the fermented culture medium kept under agitation for 9 d and there was a greater number of susceptible bacteria with mean inhibition zones ranging from 6.0 mm to 12.5 mm in diameter against Salmonella enterica and S. aureus. As well as, a study developed by Wenzel et al. (2013) [56] in which the extracts obtained from the fermented medium presented antimicrobial activity against E. coli and S. enterica. In the present study, all fungi tested in liquid medium maintained their ability to produce the antibacterial compound under this condition. In general, it was observed that inhibition zones increased when the culture time was longer. Although this result is expected once inasmuch as longer cultivation time the greater the fungal biomass, studies indicate that a substantial reduction in the production of these molecules in axenic culture is common. In other words, no more interaction with the host or with other organisms may imply that there is no need to produce the compound anymore [57]. Thus, the results obtained in this work show a good potential of these fungi to be used in future experiments on a larger scale.

4. Conclusions Several studies have revealed the positive effect of EF to its hosts, including higher resistance to abiotic and biotic stresses. Although their importance and their application in agriculture and biotechnology are recognized, there are few studies about EF from sorghum in Brazilian semi-arid region. In the present work, Aspergillus spp. composed the major fraction of EF, mainly from Qualimax genotype. This result indicates that characteristics of the plant may induce a selection of better-adapted fungi, which may interfere

275

other fungal species and diminish the diversity of the endophytic community.

References [1]

Gomes, S. O., Pitombeira, J. B., Neiva, J. N., and Cândido, M. J. D. 2006. “Agronomic Behavior and Chemical-Bromatological Composition of Forage Sorghum Cultivars in the State of Ceará.” Rev. Cienc. Agron. 37: 221-7. (in Portuguese) [2] Arnold, A. E., Maynard, Z., Gilbert, G. S., Coley, P. D., and Kursar, T. A. 2000. “Are Tropical Endophytes Fungi Hyperdiverse?” Rev. Ecology Letters. 3: 267-74. [3] Strobel, G., and Daisy, B. 2003. “Bioprospecting for Microbial Endophytes and Their Natural Products.” Microbiology and Molecular Biology Review 67: 491-502. [4] Tan, R. X., and Zou, W. X. 2001. “Endophytes: A Rich Source of Functional Metabolites.” Nat. Prod. Rep. 18: 448-59. [5] Pocasangre, L., Sikora, R. A., Vilich, V., and Schuster, R. P. 2000. “Survey of Banana Endophytic Fungi from Central America and Screening for Biological Control of the Burrowing Nematode (Radopholus similis).” Acta. Horticulturae 53: 283-90. [6] Araújo, W. L., Maccheroni, J. W., Aguilar-Vildoso, C. I., Barroso, P. A. V., Saridakis, H. O., and Azevedo, J. L. 2001. “Variability and Interactions between Endophytic Bacteria and Fungi Isolated from Leaf Tissues of Citrus Rootstocks.” Can J. Microbiol 47: 229-36. [7] Luz, J. S., Silva, R. L. O., Silveira, E. B., and Cavalcante, U. M. T. 2006. “Enzymatic Activity of Endophytic Fungi and Effect on Growth Promotion of Yellow Passion Fruit Seedlings.” Revista Caatinga 19 (2): 128-34. (in Portuguese) [8] Zida, E. P., Thio, I. G., Néya, B. J., O’Hanlon, K., Deleuran, L. C., Wulff, E. G., Lund, O. S., Shetty, P. H., and Boelt, B. 2014. “Fungal Endophytes of Sorghum in Burkina Faso: Occurrence and Distribution.” African Journal of Microbiology Research 8 (46): 3782-93. [9] Araújo, W. L., Lima, S. O. A., Azevedo, J. L., Macron, J. L., Sobral, J. K., and Lavaca, P. T. 2002. “Manual: Isolation of Endophytic Microorganisms.” CALQ, Piracicaba. (in Portuguese) [10] Carroll, G. C., and Carroll, F. E. 1978. “Studies on the Incidence of Coniferous Needle Endophytes in the Pacific Northwest.” Can. J. Bot. 56: 3034-43. [11] Booth, C. 1971. The Genus Fusarium. Commonwealth Mycological Institute, Kew, Surrey, England. [12] Ellis, M. B. 1971. Dematiaceous Hyphomycetes. Commowealth Mycological Institute, Kew, England, 608.

276


[13] Ellis, M. B. 1976. More Dematiaceous Hyphomycetes. Commowealth Mycological Institute, Kew, England, 507. [14] Barnett, H. L., and Hunter, B. B. 1987. Illustrated Genera of Imperfect Fungi. 4th edition. The American Phytopathological Society, St. Paul, Minessota, USA. [15] Hanlin, R. T. 2000. Illustrated Genera of Ascomycetes. Volume II. The American Phytopathological Society, Minessota, USA. [16] Ichikawa, T., Ishikura, T., and Ozaki, A. 1971. “Improvement of Kasugamycin-Producing Strain by the Agar Piece Method and the Prototroph Method.” Folia. Microbiol.16: 218. [17] Bauer, A. M., Kirby, W. M. M., Sherris, J. C., and Turck, M. 1996. “Antibiotic Susceptibility Testing by a Standardized Single Disk Method.” Am. J. Clin. Pathol. 43: 493-6. [18] Vandenkoornhuyse, P., Quaiser, A., Duhamel, M., and Dufresne, A. 2015. “The Iimportance of the Microbiome of the Plant Holobiont.” New Phytol. 206: 1196-206. [19] Schlaeppi, K., and Bulgarelli, D. 2015. “The Plant Microbiome at Work.” Current Review 28 (3): 212-7. [20] Silva, R. M. F., Silva, M. I. S., Oliveira, R. J. V., Calvacanti, M. A. Q., Tabosa, J. N., and Bezerra, J. L. 2015. “Preliminary Studies of Endophytic Fungi on Roots of Sorghum bicolor L. Moench, Collected in Goiana/PE.” In Annals of the XXXV Brazilian Congress of Soil Sciences, ISBN 978-85-86504-14-3 Natal, RN, Brasil. (in Portuguese) [21] Marin-Felix, Y., Groenewa, J. Z., Cai, L., Chen, Q., Marincowitz, S., Barnes, I., Bensch, K., Braun, U., Camporesi, E., Damm, U., de Beer, Z. W., Dissanayake, A., Edwards, J., Giraldo, A., Hernández-Restrep, M., Hyde, K. D., Jayawardena, R. S., Lombard, L., Luangsa-ard, J., McTaggart, A. R., Rossman, A. Y., Sandoval-Denis, M., Shen, M., Shivas, R. G., Tan, Y. P., van der Linde, E. J., Wingfield, M. J., Wood, A. R., Zhang, J. Q., Zhang, Y., and Crous, P. W. 2017. “Genera of Phytopathogenic Fungi: GOPHY 1.” Stud. Mycol. 86 (March): 99-216. doi: 10.1016/j.simyco.2017.04.002. [22] Bernardi-Wenzel, J. 2012. “Isolation and Antagonistic Activity of Soybean Endophytic Fungi (Glycine max (L.) Merrill).” SaBios-Journal of Health and Biology 7 (3): 1. [23] Bandara, W. M. M. S., Seneviratne, G., and Kulasooriya, S. A. 2006. “Interactions among Endophytic Bacteria and Fungi: Effects and Potentials.” J. Biosci. 31 (5): 645-50. [24] Stone, J. K., Polishook, J. D., and White-Júnior, J. F. 2004. “Endophytic Fungus.” In Biodiversity of Fungi; Inventory and Monitoring Methods, Mueller, J. M., Bills, G. F., and Foster, M. S. (eds), San Diego: Elsevier Academic Press, 241-70. [25] Seghers, D., Wittebolle, L., Top, E. M., Verstraete, W., and Siciliano, S. D. 2004. “Impact of Agricultural

[26]

[27]

[28]

[29]

[30]

[31]

[32]

[33]

[34]

[35]

[36]

Practices on the Zea mays L. Endophytic Community.” Applied and Environmental Microbiology 70 (3): 1475-82. Siqueira, V. M., Conti, R., Araújo, J. M. E., and Souza-Motta, C. M. 2011. “Endophytic Fungi from the Medicinal Plant Lippia sidoides Cham. and Their Antimicrobial Activity.” Symbiosis 53: 89-95. Costa, R. F., Pires, D. A. A., Moura, M. M. A., Sales, E. C. J., Rodrigues, J. A. S., and Rigueira, J. P. S. 2016. “Agronomic Characteristics of Sorghum Genotypes and Nutritional Values of Silage.” Animal Sciences 38 (2): 127-33. Liang, M. Q., Zhang, C. H. F., Peng, C. H. L., Lai, Z. L., Chen, D. F., and Chen, Z. H. 2010. “Plant Growth Community Structure and Nutrient Removal in Monoculture and Mixed Constructed Wetlands.” Rev. Ecol. Eng. 37: 309-16. Schlemper, T. R., Leite, M. F. A., Lucheta, A. R., Shimels, M., Bouwmeester, H. J., van Veen, J. A., and Kuramae, E. E. 2017. “Rhizobacterial Community Structure Differences among Sorghum Cultivars in Different Growth Stages and Soils.” FEMS Microbiology Ecology 93 (8): 1-11. Schlemper, T. R., van Veen, J. A., and Kuramae, E. E. 2017. “Co-variation of Bacterial and Fungal Communities in Different Sorghum Cultivars and Growth Stages Is Soil Dependent.” Microb. Ecol. 76 (1): 205-14. https://doi.org/10.1007/s00248-017-1108-6. Gałązka, A., and Grządziel, J. 2018. “Fungal Genetics and Functional Diversity of Microbial Communities in the Soil under Long-Term Monoculture of Maize Using Different Cultivation Techniques.” Front. Microbiol. 9: 76. doi: 10.3389/fmicb.2018.00076. Bennett, J. W. 2010. “An Overview of the Genus Aspergillus.” In Aspergillus: Molecular Biology and Genomics, Caister Academic Press. Moura, M. S. B., Galvincio, J. D., Brito, L. T. L., Souza, L. S. B., Sá, I. I. S., and Silva, T. G. F. 2007. “Climate and Rainwater in the Semi-arid.” In Potentialities of Rainwater in the Brazilian Semi-arid, Brito, L. T. L., Moura, M. S. B., and Gama, G. F. B. (eds), Petrolina, Embrapa Semi-Árido, 37-59. (in Portuguese) Singh, L. P., Gill, S. S., and Tuteja, N. 2011. “Unraveling the Role of Fungal Symbionts in Plant Abiotic Stress Tolerance.” Plant Signal. Behav. 6 (2): 175-91. Maropola, M. K. A., and Ramond, J. B. 2015. “Impact of Metagenomic DNA Extraction Procedures on the Identifiable Endophytic Bacterial Diversity in Sorghum bicolor (L.) Moench.” Journal of Microbiological Methods 112 (2015): 104-17. doi: 10.1016/j.mimet.2015.03.012. Lackner, G., Moebius, N., and Hertweck, C. 2011.


[37]

[38]

[39]

[40]

[41]

[42]

[43]

[44]

[45] [46]

[47]

“Endofungal Bacterium Controls Its Host by and Hrp Type III Secretion System.” The ISME Journal 5 (2): 252-61. Hoffman, M. T., Gunatilaka, M. K., Wijeratne, K., Gunatilaka, L., and Arnold, A. E. 2013. “Endohyphal Bacterium Enhances Production of Indole-3-Acetic Acid by a Foliar Fungal Endophyte.” PLoS ONE 8 (9): e731-32. Pusztahelyi, T., Holb, I. J., and Pócsi, I. 2015. “Secondary Metabolites in Fungus-Plant Interactions.” Front Plant Sci. 6: 573. doi: 10.3389/fpls.2015.00573. Santos, T. T., and Varavallo, M. A. 2011. “Application of Endophytic Microorganisms in Agriculture and in the Production of Substances of Economic Interest.” Semina: Biological and Health Sciences 32 (2): 199-212. (in Portuguese) Demain, A. L. 1992. “Microbial Secondary Metabolism: A New Opportunity for Industry.” Ciba Foundation Symposium 3-23. Pimentel, M. R., Molina, G., Dionísio, A. P., Maróstica-Jr, M. R., and Pastore, G. M. 2011. “The Use of Endophytes to Obtain Bioactive Compounds and Their Application in Biotransformation Process.” Biotechnology Research International, Article ID 576286. doi:10.4061/2011/576286. Wang, J., Li, G., Lu, H., Zheng, Z., Huang, Y., and Su, W. 2000. “Taxol from Tubercularia sp. Strain TF5, an Endophytic Fungus of Taxus mairei.” FEMS-Microbiology Letters 193: 249-53. Alexopoulos, C. J., and Mims, C. W. 1996. Introductory Mycology. 4th edition. John Wiley & Sons INC, USA, 869. Cragg, M. G., and Newman, D. J. 2005. “Biodiversity: A Continuing Source of Novel Drug Leads.” Pure and Applied Chemistry 77: 7-24. Schulz, B., and Boyle, C. 2005. “The Endophytic Continuum.” Mycological Research 109: 661-86. Houbraken, J., Vries, R. P. E., and Samson, R. A. 2014. “Modern Taxonomy of Biotechnologically Important Aspergillus and Penicillium Species.” Adv. Appl. Microbiol 86: 199-249. Cui, J. L., Guo, S. X., and Xiao, P. G. 2011. “Antitumor and Antimicrobial Activities of Endophytic Fungi from Medicinal Parts of Aquilaria sinensis.” Journal of

[48]

[49]

[50]

[51]

[52]

[53]

[54]

[55]

[56]

[57]

277

Zhejiang University (Biomedicine & Biotechnology) 12 (5): 385-92. Azevedo, J. L., Maccheori, W. J., Araújo, W. L., and Pereira, J. O. 2002. “Endophytic Microorganisms and Their Role in Tropical Plants.” In Biotechnology: Advances in Agriculture and Agroindustry, Serafini, L. A., Barros, N. M., and Azevedo, J. L. (eds), Caxias do Sul: EDUCS. Azevedo, J. L. 1998. “Endophytic Microorganisms.” In Microbial Ecology, Melo, I. S., and Azevedo, J. L. (eds), Jaguariúna: EMBRAPA, 117-37. Pamphile, J. A., and Azevedo, J. L. 2002. “Molecular Characterization of Endophytic Strains of Fusarium verticillioides (Fusarium moniliforme) from Maize (Zea mays L.).” World Journal of Microbiology & Biotechnology 18 (5): 391-6. Mathan, S., Subramanian, V., and Nagamony, S. 2013. “Optimization and Antimicrobial Metabolite Production from Endophytic Fungi Aspergillus terreus KC 582297.” Eur. J. Exp. Biol 3: 138-44. Kusari, S. M. 2011. “Are We Ready for Industrial Production of Bioactive Plant Secondary Metabolites Utilizing Endophytes?” Natural Product Reports 28: 1203-7. Merlin, J. N., Christhudas, I. V. S., Kumar, P. P., and Agastian, P. 2013. “Optimization of Growth and Bioactive Metabolite Production: Fusarium solani.” Asian J. Pharm. Clin. Res. 6 (3): 98-103. Takahashi, J. A., and Lucas, E. M. F. 2008. “Occurrence and Structural Diversity of Fungal Metabolites with Antibiotic Activity.” New Chemistry 31 (7): 1807-13. Oliveira, F. B. M., Lima, L. M., Moura, M. E. B., Nunes, B. M. V. T., and Oliveira, B. M. 2011. “Indiscriminate Use of Antibiotics and Microbial Resistance: A Reflection on the Treatment of Hospital Infections.” Revista Interdisciplinar NOVAFAPI 4 (4): 72-7. (in Portuguese) Wenzel, J. B., Almeida-Moresco, A. A., Boas, E. V., Burin, F. A. G., and Souza, R. O. 2013. “Enzymatic and Antimicrobial Activity of Endophytic Fungi Isolated from Soybean.” Biológicas & Saúde3 (9): 1-15. Scherlach, K., and Hertweck, C. 2009. “Triggering Cryptic Natural Product Biosynthesis in Microorganisms.” Organic & Biomolecular Chemistry 7: 1753-60.

D


DAVID PUBLISHING

Effects of PEG Priming and Fungicide Treatment on Kenaf (Hibiscus cannabinus L.) Seed Germination In-Sok Lee, Chan-Ho Kang, Suk-Ju Kwon and Young-Eun Na Jeollabuk-do Agricultural Research & Extension Services, Iksan City 54591, Korea Abstract: An experiment was conducted in the Jeollabuk-do Agricultural Research and Extension Services, Korea from February to June 2017, to study the effect of polyethylene glycol (PEG) on the germination of kenaf seeds variety ‘Jangdae’, which treated with seven PEG concentrations (0%, 10%, 20%, 25%, 30%, 35% and 40%) for 24 h at 20 °C in the dark, and evaluate the effect of fungicide on surging kenaf seed germination in the field. Results showed that the critical concentration rate needed to hasten germination based on germination percentage, times to reach 50% of the final germination rate (T50) and mean no. of days to germination (MDG) is using 10% PEG. A maximum germination rate of 83.8% using hydro-priming (HP) (seed treated with HP) was observed during the first 12 h of treatment. The control’s (Jangdae seed) germination increased sharply and reached a maximum germination rate of 53.2% on the 21st day in the field. After 21 d, germination of all priming treatments ranged from 13.8% to 26.3%. The palisade layer (PAL) after priming treatment was more damaged than that of the control. Also, a significant difference on the acid level between the control and PEG priming treatment (p < 0.05) was observed. It was also found out that seed modifications after priming could affect in the field. A fungicide called “Tiram” was used after priming to help kenaf seeds decrease T50 and MDG, and increase germination percentage. Results showed that application of fungicide after priming optimizes seed germination and vigor. Therefore, it is recommended to invigorate the kenaf seed before planting. Key words: Kenaf, priming, polyethylene glycol, fungicide.

1. Introduction Kenaf (Hibiscus cannabinus L.) belongs to family Malvaceae is a common warm season annual fiber plant native to India and Africa [1]. Although kenaf is a tropical plant, its cultivars are now well adapted to a wide geographical and climatic range [2]. Kenaf plants have been widely used for the production of paper, biocomposites, fiber boards, bioplasticsand in the textile industry. It is an important cordage crop in many developing countries such as USA and Japan used for fiber production and forage. Kenaf was introduced in Korea in the 60’s but, limited use in the country. In recent years, its value in Korea has been increasing for forage, biomass production and fuel. Kenaf can reach heights of 4-6 m depending on environmental conditions and requires 140-150 d to Corresponding author: In-Sok Lee, Ph.D., research field: crop cultivation. Running title: Agricultural Properties of Kenaf Seed Treated with PEG and Fungicide

complete maturity. Seed production is limited to frost-free areas for the late ripening variety. Its stalk is composed of two distinct fibers, the bast and the core, which is approximately 35% and 65% of mass, respectively [3]. The bast is characterized as a bark with long fibers and the core being physically similar to balsawood, containing soft, short fibers. They lose germination capacity after harvest because of high seed oil content. Under conditioned storage of 20 °C and 10% humidity, kenaf remained viable for about eight months [4]. However, its viability loss is faster under hot and humid climates with an average ambient temperature of 35 °C and humidity above 60% [5]. A kenaf variety called ‘Jangdae’ released by the Korea Atomic Energy Research Institute (KAERI) is an early maturing variety and has low germination rate which is a major limitation for commercially use in Korea. The rapid and uniform field emergences of seeds are the two important conditions to increase quality, yield and profit in annual crops. Slow germination

Effects of PEG Priming and Fungicide Treatment on Kenaf (Hibiscus cannabinus L.) Seed Germination

ability of some seeds results to smaller seedlings and consequently smaller plants. This also makes such seedlings more vulnerable to soil-borne diseases [6]. A seed represents an amalgam of individuals, each with different germination vigor, but uniform performance of seeds of cultivated plants is seldom achieved [7]. Because of this, seed priming has become a common treatment to increase the rate and uniformity of emergence in many vegetable and flower species resulting to a more rapid and uniform germination when the seeds are re-imbibed [8]. Seed priming has been used to accelerate germination, uniform seedling emergence and improve germination performance under temperature or drought stresses [9, 10]. Seed osmopriming using polyethylene glycol (PEG) had improved the germination potential of some herbaceous perennials [11], pigeonpea [12], brassica [13] and carrot [14]. However, the secret to successful seed priming is ceasing the priming treatment at the right time to allow re-drying, hence each species must be investigated for optimal priming treatments and treatment durations [15]. Previous results showed that chemical agent treatments to kenaf seeds could be used to decrease seedling damage caused by pathogens [16, 17]. Fungicides evaluated by Whiteley [18] did not reduce germination of kenaf seed; but no beneficial effects were shown. Field studies by White et al. [19] indicated that seedling emergence was higher for chemically-treated kenaf seeds, while laboratory tests indicated that treatments had no effect on germination. If seeds are primed with various priming materials, the outer tissue of seeds is weakened, causing seeds to be attacked by many pathogens. So, there is a need to use fungicide to prevent the seeds from having a poor quality. Thus, the main objective of this study was performed to investigate the effect of PEG on improving germination percentage of kenaf seeds (Jangdae), identify the cause of low priming effect and evaluate the effect of fungicide on surging kenaf seed

279

germination.

2. Materials and Methods 2.1 Seed and Other Materials Preparation The kenaf variety used was “Jangdae” from the KAERI. The experiment was conducted in Agri-Food Processing, Agricultural Research and Extension Services, Iksan from February to April, 2017. Seeds, weighing 12 g for each treatment were sterilized by soaking in NaOCl solution for 10 min and dried for 30 min. Twistpack Ⓐ 400 (Twist pack 3, ACE Industry, Pocheon, Korea) containers were purchased at a store. 2.2 Germination Tests to PEG in Laboratory Condition In the conduct of PEG (Polyethylene glycol 6000, Aldrich, Darmstadt, Germany) test, an osmopriming agent solution, seeds were treated with seven PEG concentrations (0%, 10%, 20%, 25%, 30%, 35% and 40%) for 24 h at 20 °C in the dark in an incubator (HB-302S-4, Hanbaek Scientific Co., Bucheon, Korea). Three replicates with 20 seeds each were placed in Twist pack Ⓐ 400 (Twist pack 3, ACE Industry, Pocheon, Korea) container with two filter paper soaked with 7 mL test solutions, and germinated for 72 h at 25 °C with lights in the incubator. Germination was recorded at the same time daily. The seed have germinated when it was > 2 mm and the seed coat ruptured, plumule and radicle came out. After 3 d of germination, a picture was taken to compare growth phase of plants. The times to reach 50% of the final germination rate (T50) and the mean no. of days to germination (MDG) were recorded to evaluate germination performance. 2.3 Germination Tests to PEG in Field Condition Kenaf was planted on 1st May, 2017 in a deep loamy fertile soil and sown at a density of about 25,000 plants/10a. The beds were 10 m and 1.5 m wide with each bed having seven planted rows 0.2 m apart. The field was cleaned and treated with 3 kg

280


pendimethalin herbicide/10a and 15-10-10 NPK granular fertilizer/10a, which was partially modified from Ref. [20], applied into the upper 10 cm of the soil before planting. The plots were designed by completely randomized block with three replicates. The kenaf seeds were treated with seven PEG concentrations (0%, 10%, 20%, 25%, 30%, 35% and 40%) for 24 h at 20 °C in the dark in an incubator (HB-302S-4, Hanbaek Scientific Co., Bucheon, Korea). The primed seeds were left for 2 h to allow the seed surface to dry and were then sown in the field. Germination was scored for 21 d. A seed has germinated when the leaves come out. Biomass yield was measured at 160 d after sowing using a two digit balance and expressed in ton/10a. 2.4 Scanning Electron Microscope (SEM) Image The seeds were air-dried for 48 h at 30 °C. Each was then fastened using a nipper before cutting vertically to avoid mechanical injury for the vertical section filming. The specimen were air-dried for 20 h at 80 °C to shoot, then was placed on aluminum stub and plated with gold by using a gold ion sputtering device (Jeol, JFC-1100E, Fine Coat, Tokyo, Japan) at 10 mA for 400 s. A palisade layer (PAL) of seeds plated with gold were observed using an SEM (Jeol, JSM-5410LV, Tokyo, Japan) at condition of 15 kV [21]. 2.5 Acid Value The acid value of kenaf seed was determined according to Korean Food Standards Codex [22]. One gram samples were weighed in 200 mL Erlenmeyer flask and dissolved in 100 mL of ethanol:diethyl ether mixture (1:1, v/v) for 1 min and titrated with 2-3 drops of 0.1 N potassium hydroxide solution, using 1% phenolphthalein as an indicator. Simultaneously, a blank test (ethanol:diethyl ether mixture = 1:1, v/v) was carried out and then acid value was calculated. Analyses were carried out in triplicate and the acid value was the mg KOH used to neutralize 1.0 g of

sample. 2.6 Evaluation of Fungicide Effect on Surging Seed Germination in Soil To evaluate the fungicide effect on surging seed germination in soil, the previous treatment method was modified. A fungicide “Tiram” (30 mL/kg) with a brand name Saechong was used. Kenaf seed was coated with Tiram and soaked in Tiram solution according to trial designs. The trial designs consisted of five treatments such as the control (seed unprimed), hydro-priming (HP) for 12 h (H12), combination of HP for 6 h + Tiram immersion for 6 h (H6T6), Tiram immersion for 12 h (T12), and combination of HP for 12 h + Tiram coating (H12TC). The treated seeds were planted one at a time in a pot with 105 holes. Germination was scored every day for 7 d. A seed has germinated when the leaves come out. The T50 and MDG were noted to evaluate germination performance. Plant height was measured using ruler and expressed in centimeter at 7 d after sowing. 2.7 Field Growth Conditions during the Experimental Period The experimental field is situated in Iksancity. During the experimental period, from 1st May 2017 to 15th October 2017, the average minimum temperature in the area was 17.3 °C and average maximum temperature was 25.3 °C, with a total of 580 mm rainfall (Table 1). The optimum temperature for kenaf to grow ranges from 20 °C to 27 °C [23] and rainfall of 500-600 mm [24]. Thus, the climatic conditions in Iksancity are very suitable to raise kenaf. The primary weeds in the field were tumble pigweed (Amaranthus albus L.), purslane (Portulaca oleracea, Purslane) and removed throughout the growing season by hand weeding. 2.8 Statistics Results were analyzed for analysis of variance

Effects of PEG Priming and Fungicide Treatment on Kenaf (Hibiscus cannabinus L.) Seed Germination Table 1

281

Climatic conditions of field during the experimental period.

Region

Temperature (°C) Av. maximum 25.3

Av. minimum 17.3

Iksan

Rainfall (mm)

Av. 22.5

580

Av.: average.

(ANOVA) using SAS Enterprise Guide 4.2 (Statistical

survived. Significant difference in survival rate of the

Analysis System, 2009, SAS Institute Inc., Cary, NC,

seedlings was recorded among treatments. The 90%

USA). Means were compared at 5% significance level

survival rate of at 20% and 25% PEG treatment were

using Duncan’s multiple comparison.

significantly greater than that of the other treatments. Ismail et al. [26] stated that a higher germination

3. Results and Discussion

percentage

3.1 Effect of PEG on Germination Percentage in Laboratory Test Germination of Jangdae seed, early maturing variety, was generally poor in the control condition based on kenaf seed maturity compared to the late maturing variety imported from foreign countries such as China (Fig. 1). This indicates the need for kenaf seed to use a priming technique like PEG to hasten germination uniformity and capability. Table 2 illustrates the final germination rate against time. At the first 12 h of treatment, the maximum germination rate was 83.8% using HP as compared to the control’s (seed unprimed with HP and PEG) germination percentage of 0%. The highest germination rate was recorded in 10% PEG between 24 h and 48 h. At 72 h, the first seedlings to germinate died from fungal infection, resulting to a decrease in germination. It is concluded

that

10%

PEG

was

the

critical

concentration to surge germination. This method reduced the time required to initiate seed germination. Kim et al. [25] reported that the pasture seed

was

obtained

with

PEG

treatment

compared to the control. PEG was the preferred osmoticum because it is inert and the embryo cannot take up its large molecular size [7]. PEG’s composition hinders too much water absorption by the seed. Excessive water absorption by the seeds hampers seed germination. Also, Davision and Bray [27] suggested that PEG treatment induced various proteins synthesis related with germination. The earlier germinated seedlings after priming treatment such as HP and 10% PEG died first. Previous studies on cotton and kenaf showed a strong association between rapid germination and seed coat susceptibility to mold growth, seed rot and diseased seedling roots [16, 28]. Germination synchronization, shoot length and leaf unfolding of primed seed were greater than those of the control. Also, main root or hair root appeared faster in the treated seeds and grew abundantly compared to the control (Fig. 1). Enhanced effect, which hastens germination rate and growth progress, was greatest at HP and 10% PEG compared to the control (Fig. 1).

germination increased at 10%-30% PEG treatment. These results are attributed to chemical effects of PEG causing the cell wall to lose thus increasing water uptake of cells. The most probable mechanism for PEG

enhancement

of

germination

is

the

intensification of mass transfer and easier access of water to the interior of the cell wall structure. Results after 72 h were obtained from seedlings that had

3.2 Effects of PEG on Surging both T50 and MDG in Laboratory Test Results showed that the T50 of the control was 22 times, while at HP and 10% PEG treatment, nine times was sufficient to reach T50 which is 2-3 times lower than that of the control (Table 3). The T50 of the other PEG treatments was also lower than that of the

282


Table 2 Response of kenaf seed germination at various polyethylene glycol (PEG) concentrations and different time immersions in H2O solution. PEG (%) Control HP 10 20 25 30 35 40 12 0d 83.8a 78.8ab 65.0b 21.3c 0d 0d 0d 24 48.8b 90.0a 96.3a 93.8a 83.8a 56.3b 57.5b 57.5b 48 85.0b 91.3ab 96.3a 95.0a 91.3ab 83.8b 90.0ab 91.3ab 72 72.5c 77.5bc 86.3ab 90.0a 90.0a 80.0abc 88.8a 83.8ab The different letters for each row show significant difference (p < 0.05) using Duncan’s multiple range test. Control: seed unprimed with hydro-priming (HP) and PEG; HP: seed primed with hydro-priming; 72 h means a survival rate of seedlings. Hours

Fig. 1 Comparison of seedlings at various polyethylene glycol (PEG) concentrations after 3 d of germination in H2O condition. Cont.: unprimed seeds; 0% PEG: hydro-priming (HP).

control. MDG decreased from 1.43 d which is the maximum for the control and 0.55 d being the minimum for HP (Table 3). These data indicate that the T50 and MDG were significantly affected by the PEG priming during germination. Previous study demonstrated that the increase in the germination rate and MDG of primed barley seeds may be due to the initial metabolic events in primed seeds [29]. Li et al. [30] reported that the seed primed with PEG showed a fast MDG, resulting in improving the germination rate rather than an increase in the germination percentage. It appeared that PEG treatment might induce various proteins synthesis related with germination [27]. 3.3 Effect of PEG on Germination Percentage in Field Test The results of the germination percentage in the field after PEG treatment is presented in Table 4. After sowing kenaf seeds, it rained on the 10th (40 mm) and the 21st (15 mm) days. The germination percentage of HP on the 6th day was significantly higher than the others (Table 4). After raining of 40 mm on the 10th day, the germination percentage of the control on the 11th day exceeded that of other treatments. Thereafter, the control’s (Jangdae seed)

germination in the field was increased sharply and reached a maximum of 53.2% on the 21st day when it rained for 15 mm a day. After the 21st day, there was no significant difference in the germination of all the experimental plots (Table 4). Daniel et al. [5] demonstrated that HP of kenaf seeds for 24 h enhanced seed germination and vigor. However, it has been observed that there was a significant difference in germination among varieties after priming. So, the variety difference between the result and previous study [5] indicated different outcomes. 3.4 Effect of PEG on Biomass Yield in Field Test Results showed that biomass yields of different priming treatment plots (Hydro and PEG) were lower than that of the control (Jangdae) in 150 d (Fig. 2). No significant difference was also observed among the priming treatment plots. The biomass yield depends on the germination percentage (Table 4). Hence, it is very important to apply an optimum plant density so as to obtain the highest yield. In this study, kenaf was planted with sowing density of 25,000 plants/10a. Previous studies reported that the best planting density was 40,000 plants/10a [31]. This difference is attributed to the cultivar and climatic condition such as

Effects of PEG Priming and Fungicide Treatment on Kenaf (Hibiscus cannabinus L.) Seed Germination Table 3

283

T50 and MDG of kenaf seed at various PEG concentrations in 48 h.

PEG (%) GP T50 (times) MDG Control 85.0b 22 1.43 HP 91.3ab 9 0.55 10 96.3a 9 0.59 20 95.0a 10 0.67 25 91.3ab 14 0.97 30 83.8b 21 1.33 35 90.0ab 21 1.36 40 91.3ab 21 1.37 The different letters for each column show significant difference (p < 0.05) using Duncan’s multiple range test. GP: germination percentage in 48 h; T50: times to reach 50% of the final germination rate; MDG: mean no. of days to germination; Control: seed unprimed with HP and PEG; HP: seed primed with hydro-priming. Table 4

Germination rate of kenaf seed at various PEG concentrations on the 6th, 11th, 14th and 21st days.

Germination percentage (%) 6th day 11th day 14th day 21st day Control 0.3b 14.1a 50.5a 53.2a 0(HP) 3.0a 9.4b 25.3b 21.5b 10 0.0b 8.8b 24.2b 23.6b 20 0.3b 8.4b 25.9b 26.3b 25 0.3b 3.7b 11.4b 14.5b 30 0.3b 5.4b 13.8b 13.8b 35 0.7b 7.4b 24.9b 27.3b 40 0.3b 5.4b 26.3b 26.9b The different letters for each column show significant difference (p < 0.05) using Duncan’s multiple range test. Control: Jangdae seed unprimed with HP and PEG; HP: seed primed with hydro-priming. PEG

Fig. 2 Yield of kenaf at various PEG concentrations at 150 d in the field. The different letters for each bar graph show significant difference using Duncan’s multiple range test. JD: control (unprimed seeds); Hydro: HP (seed primed with hydro-priming).

284


rainfall and temperature. 3.5 Identification of Cause of Low Priming Effect in Field Test Tables 2 and 4 showed that it is possible to determine the priming effect to increase germination percentage in growth chamber condition, but not in soil condition. Thus, the cause of low priming effect in soil was also identified. In the SEM image of tissue before and after priming treatment, there was a significant difference in the PAL (Fig. 3). The PAL (white parenthesis) after priming treatment was more

damage than that of the control (Fig. 3). More damage in PAL, the more loss of solutes from the seeds, which indicates the degree of membrane deterioration resulting from seed aging [32]. The oil content of kenaf seed has been reported to be around 20%-24%, which could result to losing its germination capacity [5]. Acid level is increased by fatty acid oxidation and is an indicator of oxidation degree. Results showed that the acid level for the control and Hydro are statistically the same but increased sharply at 10% PEG (p < 0.05) (Fig. 4). This could be attributed to the fatty acid oxidation posed by environment stresses

Fig. 3 Scanning electron microscope (SEM) image of the cross section of kenaf seed coat after PEG priming treatment for 24 h. PAL = palisade layer; control = unprimed seed.

Fig. 4 Acid value difference of kenaf seeds after 24 h at various PEG concentrations. The different letters for each bar graph show significant difference (p < 0.05) using Duncan’s multiple range test. Control: seed unprimed with HP and PEG; Hydro: HP (seed primed with hydro-priming).


[33, 34]. Thus, findings showed that priming treatment over 20% PEG to kenaf seed is not suitable for improving the germination percentage. The study showed that tissue disintegration and fatty acid’s oxidation of kenaf seed after priming had significantly negative effects on germination in soil. 3.6 Effects of Fungicide Treatment on Kenaf Seed Germination in Soil Test To overcome the problem of priming treatment on surging seed germination, a fungicide called Tiram was used after priming. The single treatment of HP and combination of HP and Tiram had a significant effect on decreasing T50 (Fig. 5). Among the treatments, the H6T6 was the highest (Fig. 5). With respect to MDG, the HP and combination of HP and Tiram treatment germinated at a significantly faster rate than the control. The H6T6 showed the fastest level (Fig. 6). In the final germination percentage, single treatment of HP and combination of HP and

285

Tiram had an increasing effect compared to the control (Fig. 7). The H12TC treatment has the highest germination percentage which is 42.44% as compared to the others which ranged from 25.5% to 36.2% (Fig. 7). In plant height evaluation, all treatments resulted higher than the control (Fig. 8). Based on the final germinate on percentage, it appeared that there is a close connection between Tiram treatment and improvement of germination percentage. According to Ref. [16], the stand establishment of kenaf after fungicide treatment soared. It was concluded that fungicide treatment could help kenaf seed improve germination percentage and stand establishment by protecting the seeds from seed- and soil-borne pathogens. In conclusion, the study performed with kenaf suggested that the seeds can be applied with a technique called H12TC, which is a combination of HP and Tiram-coating, to boost germination. Finally, the technique called H12TC is recommended to improve the economic yield of kenaf.

Fig. 5 T50 difference of kenaf seeds after 72 h at various treatments. The different letters show significant difference (p < 0.05) using Duncan’s multiple range test. Control: seed unprimed with HP and PEG; H12: HP treatment for 12 h; H6T6: HP treatment for 6 h, followed by treatment in Tiram solution for 6 h; T12: treatment in Tiram solution for 12 h; H12TC: HP treatment for 12 h, followed by coating with Tiram suspension. The solid line indicates the average from 1st to 3rd.

286


Fig. 6 Mean no. of days to germination (MDG) difference of kenaf seeds after 4 d at various treatments. The different letters show significant difference (p < 0.05) using Duncan’s multiple range test. Control: seed unprimed with HP and PEG; H12: HP treatment for 12 h; H6T6: HP treatment for 6 h, followed by treatment in Tiram solution for 6 h; T12: treatment in Tiram solution for 12 h; H12TC: HP treatment for 12 h, followed by coating with Tiram suspension. The solid line indicates the average from 1st to 3rd.

Fig. 7 Germination percentage of kenaf seeds after 7 d at various treatments. The different letters show significant difference (p < 0.05) using Duncan’s multiple range test. Control: seed unprimed with HP and PEG; H12: HP treatment for 12 h; H6T6: HP treatment for 6 h, followed by treatment in Tiram solution for 6 h; T12: treatment in Tiram solution for 12 h; H12TC: HP treatment for 12 h, followed by coating with Tiram suspension. The solid line indicates the average from 1st to 3rd.


287

Fig. 8 Plant height of kenaf seedlings after 7 d at various treatments. The different letters show significant difference (p < 0.05) using Duncan’s multiple range test. Control: seed unprimed with HP and PEG; H12: HP treatment for 12 h; H6T6: HP treatment for 6 h, followed by treatment in Tiram solution for 6 h; T12: treatment in Tiram solution for 12 h; H12TC: HP treatment for 12 h, followed by coating with Tiram suspension. The solid line indicates the average from 1st to 3rd.

4. Conclusions The present study showed that a germination, T50, MDG, shoot length and leaf unfolding of kenaf seed were significantly influenced by priming technique like HP and PEG. Results represented that the optimum priming condition to hasten germination uniformity and capability of kenaf seed is 10% PEG in laboratory test. However, the germination percentage in the field after PEG treatment was different compared to the results of previous treatment. Hence, the authors analyzed SEM image and acid level of kenaf seeds to deepen its understanding. Tissue disintegration and fatty acid’s oxidation of kenaf seed after priming had significantly negative effects on germination in soil. This is the first report to identify the cause of low priming effect in field test. To overcome the problem of priming treatment on surging seed germination in field test, a fungicide called Tiram was used after priming. Of four treatments, H12TC (a combination of HP and

Tiram-coating) can be used as a good priming technology to help kenaf seed improve germination percentage and stand establishment by protecting the seeds from seed- and soil-borne pathogens.

Acknowledgments This work was supported in part with grants from the Korea South-East Power Company.

References [1]

[2]

[3]

[4]

Yazan, L. S., Foo, J. B., Ghafar, S. A. A., Chan, K. W., Tahir, P. M., and Ismail, M. 2011. “Effect of Kenaf Seed Oil from Different Ways of Extraction towards Ovarian Cancer Cells.” Food Bioprod. Process. 89 (4): 328-32. Danalatos, N. G., and Archontoulis, S. V. 2010. “Growth and Biomass Productivity of Kenaf (Hibiscus cannabinus L.) under Different Agricultural Inputs and Management Practices in Central Greece.” Ind. Crop Prod. 32: 231-40. Columbus, E. P., and Fuller, M. J. 1999. “Factors Affecting Kenaf Fiber and Core Separation.” In Kenaf Properties, Processing and Products. Oktibbeha, Mississippi: Mississippi State University Press. Carberry, P. S., and Abrecht, D. G. 1990. “Germination

288

[5]

[6] [7]

[8]

[9]

[10]

[11]

[12]

[13]

[14]

[15]

[16]

[17]

Effects of PEG Priming and Fungicide Treatment on Kenaf (Hibiscus cannabinus L.) Seed Germination and Elongation of the Hypocotyls and Radicle of Kenaf (Hibiscus cannabinus L.) in Response to Temperature.” Field Crops Research 24 (4): 227-40. Daniel, I. O., Adeniyan, O. N., Adetumbi, J. A., Okelana, M. A., Olakojo, S. A., Ajala, M. O., Aluko, O. A., and Adekoya, M. A. 2012. “Hydro-Priming Improved Germination and Vigour of Kenaf (Hibiscus cannabinus L.) Seeds.” Food Agriculture and Environment 10 (2): 760-3. Bennett, M. A. 1998. “The Use of Biologicals to Enhance Vegetable Seed Quality.” Seed Technol. 20: 198-208. McDonald, M. B. 2000. “Seed Priming.” In Seed Technology and Its Biological Basis. LLC. Boca Raton, Florida: CRC Press. Gurusinghe, S. H., Cheng, Z., and Bradford, K. J. 1999. “Cell Cycle Activity during Seed Priming Is not Essential for Germination Advancement in Tomato.” J. Exp. Bot. 50: 101-6. Janmohammadi, M., Dezfuli, P. M., and Sharifzadeh, F. 2008. “Seed Invigoration Techniques to Improve Germination and Early Growth of Inbred Line of Maize under Salinity and Drought Stress.” General and Applied Plant Physiology 4: 215-26. Jahangir, M. M., Amjad, M., Afzal, I., Iqbal, Q., and Nawaz, A. 2009. “Lettuce Achene Invigoration through Osmopriming at Supraoptimal Temperature.” Pakistan Journal of Agricultural Sciences 46: 1-6. Finnerty, T. L., Zajicek, J. M., and Hussey, M. A. 1992. “Use of Seed Priming to Bypass Stratification Requirements of Three Aquilegia Species.” HortScience 27: 310-3. Nayyar, H., and Malik, C. P. 1993. “Alleviation of Drought Stress in Pigeonpea with Mixtalol Seed Priming.” Agric. Sci. 13: 27-30. Rao, S. C., and Phillips, W. A. 1993. “Effect of Seed Priming and Soil Residueon Seedling Emergence and Forage Production of Brassicas.” Journal of Sustainable Agriculture 3: 89-98. Duman, I., and Esiyok, D. 1998. “Effect of Pre-sowing PEG and KH2PO4 Treatment on Germination Emergence and Yield of Carrot.” Turk. J. Agric. For. 22: 445-9. Bradford, K. J. 1986. “Manipulation of Seed Water Relations via Osmotic Priming to Improve Germination under Stress Conditions.” HortScience 21: 1105-12. Cook, C. G., Hickmanb, M. V., Webber, C. L., Sij, J. W., and Scotte, A. W. 1992. “Fungicide Treatment Effects on Kenaf Seed Germination and Stand Establishment.” Industrial Crops and Products 1: 41-5. Presley, J. T., Summers, T. E., and Crandall, B. S. 1964. “The Anthracnose Disease of Kenaf and Its Control.” In Proceedings of the 2nd International Kenaf Conference, 19-33.

[18] Whiteley, E. L. 1968. “Seed Treatment and Planting Equipment.” In Proceedings of the 1st Conference on Kenaf for Pulp, 32-3. [19] White, G. A., Adamson, W. C., Whiteley, E. L., and Massey, J. H. 1971. “Emergence of Kenaf Seedlings as Affected by Seed Fungicides.” Agron. J. 63: 484-6. [20] Bañuelos, G. S., Bryla, D. R., and Cook, C. G. 2002. “Vegetative Production of Kenaf and Canola under Irrigation in Central California.” Industrial Crops and Products 15 (3): 237-45. [21] Bednorz, L., and Czarna, A. 2008. “SEM and Stereoscope Microscope Observations on the Seeds of Some Ornithogalum (Hyacinthaceae) Species.” Biologia. 63 (5): 642-6. [22] Korea Food and Drug Administration. 2016. Korea Food Code, 2016: No. 5 Standards and Specifications of Each Food. Korea Food and Drug Administration, Korea, 46-7. [23] Monti, A., and Zatta, A. 2009. “From Growing Kenaf to Its Industrial Use.” In Proceedings of the 1st Workshop on EU Project Crops 2 Industry, 4. [24] Eruola, A., Awomeso, J., Kassim, G. U. H., and Makinde, A. 2014. “An Assessment of Rain Water Supply for Kenaf-Maize Intercrop.” Irrigation & Drainage Systems Engineering 3 (3): 1-7. [25] Kim, J. D., Kwon, C. H., Chae, S. H., Hur, S. N., and Kim, J. G. 2006. “Effect of Priming Materials and Its Concentrations on the Germination of Pasture Seed.” J. Korean Grassl. Sci. 26 (4): 277-84. [26] Ismail, A. I., El-Araby, M. M., Hegazi, A. Z. A., and Moustafa, S. M. A. 2005. “Optimization of Priming Benefits in Tomato (Lycopersicon esculentum M.) and Changes in Some Osmolytes the Hydration Phase.” Asian Journal of Plant Sciences 4: 691-701. [27] Davision, P. A., and Bray, C. M. 1991. “Protein Synthesis during Osmopriming of Leek (Allium porrum L.) Seeds.” Seed Science Research 1: 29-35. [28] Bird, L. S. 1982. “The MAR (Multi-Adversity Resistance) System for Genetic Improvement of Cotton.” Plant Dis. 66: 172-6. [29] Yaldagard, M., Mortazavi, S. A., and Tabatabaie, F. 2008. “Influence of Ultrasonic Stimulation on the Germination of Barley Seed and Its Alpha-Amylase Activity.” African Journal of Biotechnology 7 (14): 2465-71. [30] Li, X. R., Yu, C. Y., and Kim, I. S. 1999. “Effects of Pre-sowing Seed Treatments on Germination and Seedling Emergence of Carrot.” J. Agr. Sci. 10: 10-7. [31] Manzanares, M., Tenorio, J. L., Molina, J. R., and Ayerbe, L. 1991. “Preliminary Estimation of Kenaf Crop Yield in Spain.” In Proceedings of the 5th European Conference on Biomass for Energy and Industry, 22-6. [32] Roberts, E. H. 1986. “Quantifying Seed Deterioration.” In Physiology of Seed Deterioration. Madison, Wisconsin:

Effects of PEG Priming and Fungicide Treatment on Kenaf (Hibiscus cannabinus L.) Seed Germination Crop Science Society of America. [33] Lee, I. S., Song, Y. E., Han, H. A., Song, E. J., Choi, S. R., and Lee, K. K. 2016. “Physicochemical Properties of Oat (Avena sativa L.) Flour according to Various Roasting Conditions.” The Korean Journal of Crop

289

Science 62 (1): 32-9. [34] Serjouie, A., Tan, C. P., Mirhosseini, H., and Man, Y. B. C. 2010. “Effect of Vegetable Based Oil Blends on Physicochemical Properties of Oils during Deep-Fat Frying.” American J. of Food Technology 5 (5): 310-23.

D


DAVID

PUBLISHING

Impact of Irrigation Water Salinity on Germination and Seedling Growth of Egyptian Barley Cultivars Farid Hellal 1, Ahmad Amer 2, Kadria EL Azab2 and Raafat Zewainy1 1. Plant Nutrition Dept., National Research Centre, Dokki, El-Behouth St., Cairo 12622, Egypt 2. Soils, Water and Environ. Res. Institute, Agric. Res. Center (ARC), Giza 12619, Egypt Abstract: The aim of this research was to assess the influence of saline irrigation water which prepared to obtain salt stress of 0.31, 3.21, 5.74, 8.28 and 12.86 dS/m on seed germination, and early seedling growth of 10 cultivars (Giza 123, 124, 125, 126, 127, 129, 130, 134, 135 and 2000) of Egyptian barley grown in clay loam soil. Germination was tested in germination cups filled with clay loam soil moistened with different concentrations of saline water, in the growth chambers condition. Results indicated that, the highest values of germinated seeds were recorded mainly at fresh water (0.31 dS/m) at all germination periods. Also, the maximum values were recorded at investigated barley cultivars Giza 126, 127 and 2000 for three studied periods (3, 5 and 7 d), while Giza 129, 130 and 135 got the same trend where the highest values for germinated seeds attained at the 5 d, 7 d and at 3 d were 9.5 seeds, respectively. Barley cultivar Giza 126 had significantly higher root length (4.07 cm), shoot length (11.75 cm), root fresh weight (48.2 mg), shoot fresh weight (101.1 mg), root dry weight (7.1 mg), shoot dry weight (6.6 mg) and seedling vigor index (13.44). The 6 kDa protein bands had the same increasing after salt stress in cultivars Giza 123, 127, 129, 134 and 135. Barley cultivars in clay soil can be classified into barley cultivars Giza 126, 127 and 2000 as highly tolerance and barley cultivar Giza 129, 123 and 127 as moderately tolerance and the rest is less. Key words: Germination, plant length, barley cultivars, salt stress, clay loam soil.

1. Introduction Crop production in arid and semi-arid regions is restricted by soil salinity and soil moisture deficiencies. Salinity in soil or irrigation water is the major limiting factor for crop growth in many regions of the world [1, 2]. Salt stress at any stage of crop growth can cause an irreversible loss in yield potential in many crops including barley [3, 4]. However, seed germination and seedling establishment are the periods when barley is most sensitive to salinity [5]. Germination and seedling growth are reduced in saline soils with varying responses for species and cultivars. Salinity may also affect the germination of seeds by creating an external osmotic potential that prevents water uptake or due to the toxic effects of Corresponding author: Farid Hellal, professor, research fields: plant nutrition and soil fertility.

Na+ and Cl- on the germinating seed [6]. Seed germination is one of the most fundamental and vital phases in the growth cycle of plants that determine plant establishment and the yield of the crops. Salinity has many-fold effects on the germination process: it alters the imbibitions of water by seeds due to lower osmotic potential of germination media [7], causes toxicity which changes the activity of enzymes of nucleic acid metabolism [8], alters protein metabolism [9] and reduces the utilization of seed reserves [10]. It may also negatively affect the ultra structure of cell, tissue and organs [11]. However, there are various internal (plant) and external (environmental) factors that affect seed germination under saline conditions which includes nature of seed coat, seed dormancy, seed age, seed polymorphism, seedling vigor, temperature, light, water and gasses [12]. Rapid and uniform field emergence is vital for

Impact of Irrigation Water Salinity on Germination and Seedling Growth of Egyptian Barley Cultivars

achieving maximum yield and quality of annual crops [13] such as barley. Under salinity conditions, exogenous application of plant growth regulators (PGRs) may overcome much of the internal PGR deficiency and mitigate salinity-induced inhibitory effects [14]. The present study was, therefore, undertaken in order to compare the effects of iso-osmotic stresses induced by irrigation water salinity on germination components of Egyptian barley cultivars grown in clay loam soil.

2. Materials and Methods This study was carried out as a factorial experiment based on completely randomized design (CRD) with three replicates at the growth chamber of Plant Biotechnology Department, National Research Centre, Egypt. Treatments comprised five salt stress levels and 10 barley cultivars brought from Barley Department, ARC, Egypt. The barley cultivars (Giza 123, 124, 125, 126, 127, 129, 130, 134, 135 and 2000) were subjected to saline water varying in salinity levels. Saline water treatments were: tap fresh water (0.31 dS/m, as control), 3.21, 5.74, 8.28 and 12.86 dS/m. Ten barley seeds were sown in germination cups (5 cm length  10 cm diameter) filled with 200 g clay loam soil moistened with different concentration of saline water, in the growth chambers. Growth chamber conditions were 23 °C day/18 °C night, 16 h/8 h light/dark photoperiod, 60% humidity, photon flux density and 400 μmol/m2s photo synthetically active radiations. Soil moisture content was kept at needs amount of field capacity during the period of the experiment. Germinated seeds were counted every 2 d for 8 d. Seeds were considered germinated when 2 mm of the parties was visible. At this stage, germination component was calculated according to Ref. [15]. Germination percentages (G%) were calculated as total number of germinated seeds by total number of seed used into 100. Germination rate (GR) was

291

calculated as the summation of newly germinated seeds on each day divided by number of days that elapsed since onset of imbibitions with seed numbers adjusted to a base of 100. The seedling vigor index (SVI) was calculated as shoot and root length into germination percentage divided by 100. Root length, shoot length, root fresh weight, shoot fresh weight, root dry weight and shoot dry weight were evaluate. Root: shoot ratio was calculated as root length divided by shoot length into 100. Root and shoot dry weight was obtained after drying at 70 °C for 48 h. Tissue water content (TWC) was calculated as shoot fresh weight minus shoot dry weight divided by shoot fresh weight into 100. 2.1 Protein Extraction The extraction for total soluble protein was done as suggested by Larkindale and Huang [16]. A 0.5 g of leaves was harvested and ground to a fine powder in liquid nitrogen. Ground powder was homogenized in 1.5 mL of cold phosphate buffer (100 mM, pH 7.0) containing 1% polyvinylpyrrolidone (PVP) and 1 mM EDTA and then centrifuged at 4 °C for 15 min at 10,000  g. Protein present in the supernatant was measured by a modification of the Bradford method [17] using crystalline bovine albumin to establish a standard curve. The supernatant was separated and stored at -20 °C till use. 2.2 Poly Acrylamide Gel Electrophoresis of Proteins SDS-PAGE was performed as described by Laemmli [18]. Protein samples were prepared by mixing with equal volume of 2  sample buffer (100 mM Tris-HCl, pH 6.8, 4% SDS, 20% glycerol, 4% -mercapto ethanol, 0.01% bromo phenol blue). Samples boiled for 5 min prior to loading. Electrophoresis was carried out first at 50 V for proper stacking and then at constant voltage of 100 V to resolve the gel. Electrophoresis was carried out using vertical gel electrophoresis apparatus (Bio-Rad) with glass plates 9 cm  10 cm with 1.5 mm spacer. Glass

292


plates, spacers, combs and buffer reservoirs of the gel apparatus were thoroughly cleaned with detergent, rinsed and dried. A monomer solution for the appropriate resolving gel was prepared by combining all reagents, except ammonium per sulfate and TEMED. Then APS and TEMED were gently mixed into monomer solution and the mixture was poured between the gel plates with the help of a pipette up to the mark delimiting the resolving gel. It was immediately over layered with distilled water. Polymerization was achieved in approximately 30 min at room temperature. Gels were either electro blotted onto the nitrocellulose membrane (Hybond-C, Amersham, England) or stained with 0.25% Coomassie Blue R-250. The data were statistically analyzed according to Ref. [19]. The least significant differences (LSD) were used to compare differences among treatment means at 5% level.

3. Results and Discussion The initial soil physical and chemical properties and irrigation water treatments and its properties were shown in Tables 1 and 2. The irrigation water salinity used in the range from fresh water (0.31 dS/m) up to very high salinity (12.86 dS/m). The soil used in the Table 1

3.1 Number of Germinated Seeds Table 3 and Figs. 1 and 2 presented the effect of the investigated barley cultivars and water salinity (0.31, 3.21, 5.74, 8.28 and 12.86 dS/m) on the germinated seeds at different periods (3, 5 and 7 d) length of the root and shoot at the end of the germination test and root/shoot percentage as well as final germination rate and percentage. Regarding to the germinated seeds at different periods (3, 5 and 7 d), data indicated that the highest values were recorded mainly at fresh water (0.31 dS/m) at all periods under examined barley cultivars. Also, the maximum values were recorded at barley cultivars Giza 126, 127 and 2000 for three studied periods, while Giza 129, 130 and 135 got the same trend where the highest values for germinated seeds attained at the 5 d, 7 d and at 3 d were 9.5 seeds, respectively. According to the effect of investigated barley cultivars on the germinated seeds at different periods, data in Table 3 illustrated that after 3 d , Giza 126 got the highest value while after 5 d Giza 127 (9.2), Giza 135 (9.1) and Giza 126 (9.0) recorded the maximum

Irrigation water properties used in the experiment.

Electrical conductivity (dS/m) 0.31 3.21 5.74 8.28 12.86 Table 2

experiment was clay loam in texture, alkaline in reaction, saline (4.5 dS/m) in soil paste and high in calcium carbonate content.

Sodium adsoption ratio (%) 2.46 14.40 17.61 21.09 26.73

Osmotic pressure (bar) -0.11 -1.16 -2.07 -2.98 -4.63

Cations (me/L)

Anions (me/L)

Na

K

Ca

Mg

CO3

HCO3

Cl

SO4

2.44 25.33 44.21 67.05 98.74

0.19 0.23 0.34 0.43 0.54

1.61 4.27 8.58 15.10 19.87

0.35 1.92 4.02 5.12 7.43

0.00 0.00 0.00 0.00 0.00

2.07 3.38 4.73 6.08 16.76

3.42 29.30 53.70 83.10 95.66

0.71 1.30 2.20 3.91 7.23

The physicochemical properties of experimental soil.

Textural class

% Sand

% Silt

% Clay

pH

EC (dS/m) (1:5)

Clay loam Cations (me/L) Na 4.75

44.80

22.40

31.71

K 0.31

Ca 2.11

Mg 2.05

8.3 0.97 Anions (me/L) CO3 HCO3 0 1.34

9.87

Organic matter % 2.16

Cl 4.62

SO4 3.26

CaCO3 %

293


Table 3

Germination rates and plant length as affected by water salinity in clay soil.

Barley cultivars

Giza 123

Giza 124

Giza 125

Giza 126

Giza 127

Giza 129

Giza 130

Giza 134

Giza 135

Water salinity (dS/m) 0.31 3.21 5.74 8.28 12.86 0.31 3.21 5.74 8.28 12.86 0.31 3.21 5.74 8.28 12.86 0.31 3.21 5.74 8.28 12.86 0.31 3.21 5.74 8.28 12.86 0.31 3.21 5.74 8.28 12.86 0.31 3.21 5.74 8.28 12.86 0.31 3.21 5.74 8.28 12.86 0.31 3.21 5.74 8.28 12.86

Number of germinated seeds at 3d 5d 7d 8.0 9.5 9.5 4.7 9.0 9.5 2.0 8.0 9.0 1.7 6.5 9.0 0.7 4.0 7.3 7.5 9.5 10.0 4.5 8.5 10.0 4.0 8.0 9.5 4.0 7.0 9.0 2.0 6.0 7.5 8.0 9.7 10.0 9.5 9.0 9.0 7.0 8.0 7.5 5.0 6.5 6.3 2.0 3.5 4.5 10.0 10.0 10.0 9.5 10.0 9.7 8.0 9.7 9.3 7.0 9.0 9.0 6.5 6.5 8.5 10.0 10.0 10.0 8.5 10.0 10.0 7.5 10.0 9.0 7.3 9.0 7.5 1.5 7.0 7.0 9.5 10.0 10.0 7.5 9.5 10.0 6.5 9.0 9.0 5.0 7.5 8.0 8.0 7.0 9.5 9.0 10.0 10.0 8.5 9.5 9.5 5.0 9.5 9.5 5.5 8.0 9.0 5.5 7.3 8.5 6.5 9.5 9.5 2.5 9.5 9.5 3.5 9.5 9.5 3.5 7.5 8.0 3.0 7.5 7.0 9.5 10.0 10.0 9.0 9.5 10.0 8.0 9.5 9.5 5.5 9.5 8.3 5.0 7.0 7.5

Plant length (cm/plant) Root Shoot 7.83 8.75 7.17 9.60 6.17 7.00 6.17 7.75 5.50 5.90 6.67 9.10 4.83 7.45 6.00 6.50 5.67 5.75 6.50 8.70 7.67 9.25 7.00 8.50 6.17 8.42 5.17 6.75 4.67 4.75 8.83 12.50 8.50 10.10 7.50 8.00 6.13 9.50 4.07 11.75 5.83 12.75 6.17 10.00 5.50 9.30 4.50 9.38 3.07 8.67 8.33 14.30 7.33 13.00 7.83 11.75 6.50 11.67 7.50 10.00 11.00 13.50 10.67 11.80 7.70 9.25 7.33 8.05 5.17 6.85 9.67 13.80 7.67 10.00 7.50 10.75 7.00 9.90 6.33 7.50 6.83 14.50 5.83 12.80 5.50 12.50 4.67 6.85 2.67 6.75

Root:Shoot ratio 89.3 75.2 88.2 79.8 94.8 73.4 65.3 100.4 98.8 74.3 100.8 82.5 72.5 78.0 107.4 72.2 85.4 94.4 64.5 34.7 47.0 61.6 59.6 48.0 36.3 58.6 56.2 66.2 54.8 75.8 81.1 93.9 84.8 91.1 75.4 70.0 76.7 70.2 70.8 90.6 46.8 45.7 44.1 67.9 39.9

Germination rate % 5.92 95.0 4.71 95.0 3.55 90.0 3.14 90.0 2.07 73.3 5.83 100.0 4.63 100.0 4.29 95.0 4.02 90.0 2.94 75.0 6.03 100.0 6.25 90.0 5.00 75.0 3.87 63.3 2.01 45.0 6.76 100.0 6.55 96.7 5.93 93.3 5.42 90.0 4.68 85.0 6.76 100.0 6.26 100.0 5.79 90.0 5.32 75.0 2.90 70.0 6.60 100.0 5.83 100.0 5.25 90.0 4.31 80.0 5.42 95.0 6.43 100.0 6.09 95.0 4.92 95.0 4.72 90.0 4.51 85.0 5.42 95.0 4.09 95.0 4.42 95.0 3.81 80.0 3.50 70.0 6.60 100.0 6.33 100.0 5.92 95.0 4.92 83.3 4.14 75.0

294

Impact of Irrigatiion Water Sallinity on Germ mination and Seedling Gro owth of Egyp ptian Barley Cultivars C

(Table 3 continnued) Num mber of germinaated seeds at 3d 5d 7d 0.31 10.0 10.0 10.0 3.21 7.3 10.0 10.0 5.74 5.5 9.5 Giza 2000 9.5 8.28 1.5 8.7 9.0 12.86 0.5 6.5 8.0 Least significaant difference (LSD) ( (0.05) Barley cultivaars (V) 0.91 0.72 0.53 Salinity levelss (T) 0.64 0.46 0.37 2.03 1.44 (V*T) 1.16

Number of germinated seeds

Barley cultivaars

Water sallinity (dS/m)

33 day d

10.0

60.33 70.22 68.77 58.66 66.88

Germination G rate % 6.76 100.0 5.87 100.0 95.0 5.09 90.0 3.52 80.0 2.61

1.00 0.71 0 2.24 2

17.003 13.663 43.10

1.42 0.57 2.51

5 day

0..65 0..62 1..97

Root:Shoot ratioo

3.72 5.62 10.07

7 day

8.0 6.0 4.0 2.0 0.0 Giza 12 23

Fig. 1

Plant length (ccm/plant) Root R Shhoot 9.33 9 155.50 6.67 6 9..50 5.83 5 8..55 4.83 4 8..25 2.83 2 4..25

Giza 124

G Giza 125

Giza 12 26

Giza 127

G Giza 129

Giza 13 30

Giza 134

G Giza 135 Giza 20 000

Barleey cultivar diffe ferences in germ mination speed d. 3 3 day

Gerrminated seeds

12.0

5 dayy

7 day

10.0 8.0 6.0 4.0 2.0 0.0

0.31 Fig. 2

3.21

5.74

8.28

12.86

Effectt of water salin nity (dS/m) on germinated seeed number.

germinated seeds values.. But after 7 d Giza 126, 129, 130 and 20000 have got the highest values (9.3) ( followed by b Giza 1244 (9.2). Reegardless baarley cultivars, waater salinity inhibited the germinated g seeds at different periods wheere increasinng water saliinity associated with decreeasing a number n of the germinated seeds. It is clear the lowest valuess of germinated seeds noticeed at 8.28 dS/m d and 12.86

dS/m m and the higghest values were attained d under freshh watter (0.31 dS/m). d Meannwhile, valu ues of thee germ minated seedds after 3 d w were lower thaan that of 5 d and d 7 d, respectiively. The T rate of decrease d of thhe germinated d seeds afterr the examined periods p was calculated and a could bee writtten as follow ws: 18.8%, 335.2%, 47.4% % and 64.0% % at 3 d, 3.8%, 7.6%, 19.3% and 36.3% after a 5 d andd


1.8%, 7.8%, 16.1% and 23.9% after 7 d. It is worthy to mention that the percentage of the reduction in germinated seeds increased after 3 d than the other two studied periods from 2-6 folds. Higher level of salt stress inhibits the germination of seeds while lower level of salinity induces a state of dormancy [7]. Additionally, increasing salt stress from 8.28 dS/m and 12.86 dS/m increased the time needed for complete germination which affect indirectly on the consequence of different following growth period. 3.2 Root and Shoot Length Regarding to the root and shoot length, data in Table 3 indicated that the highest values were obtained at fresh water under all tested barley cultivars. Same trend was obtained for shoot length except Giza 123 (3.21 dS/m). Also, data observed that the highest values of root and shoot length were recorded at Giza 130 followed by Giza 2000 for root length and for shoot length, Giza 2000 (15.5 cm) and Giza 135 (14.5 cm). With respect to the effect of investigated barley cultivars on the root and shoot length, results pointed out that Giza 129, 130 and 134 were superior for roots and Giza 135, 134 and 126 was the highest for shoot. Also, the lowest values of the root and shoot length were recorded at Giza 135 (5.1 cm) for root length and Giza 124 and Giza 125 (9.5 cm) for shoot. The obtained data revealed that increased salinity in water combined with decreasing in root and shoot length where the highest values scored at fresh water and the lowest ones were recorded at highly water salinity (12.86 dS/m). Water salinity relative to the control (fresh water), data presented in Table 3 showed that the reduction with increasing salinity were 12.4%, 19.9%, 29.3%, 41.3% and 17.1%, 25.8%, 32.4%, 38.4% for root and shoot length, respectively. Root:shoot percentage did not take a clear trend where the highest values attained at Giza 124 (8.28 dS/m), Giza 125 (12.86 dS/m) and Giza 124 (5.74 dS/m) and the lowest values were recorded at Giza 135 in all water salinity, except 12.86

295

dS/m. With respect to the examined barley cultivars effect on the percentage between root and shoot length, data revealed that the superior cultivars could rank as follow in descending order: Giza 130 > Giza 125 > Giza 123 > Giza 124 and the lowest percentage was singled out at Giza 127. According to the effect of water salinity on the root to shoot percentage, results indicated that increased salinity did not give a clear trend; however the highest and lowest percentages were recorded at 8.28 dS/m (71.1%) and 12.86 dS/m (66.2%), respectively. Also, it is worthy to mention that these percentages were increased by 4.1%, 8.7%, 4.8% and -2.6% at water salinity 3.21, 5.74, 8.28 and 12.86 dS/m relative to the control, respectively. Salinity stress adversely affects almost all stages of growth and development, such as germination, growth and vigor of seedling, vegetative growth, flowering and fruit set and ultimately causing diminished economic yield and also quality of products. Seed germination is one of the most important phases in the life cycle of plant and is highly responsive to existing environment [20]. 3.3 Germination Rate and Percentage Data in Table 3 noted that the maximum which obtained at fresh water and examined barley cultivars Giza 126, 127 and 2000 that could be considered the superior ones. Same trend was resulted in case of germination percentage where Giza 127, 125, 135 and 2000 more tolerant for salinity followed by Giza 134. Also, it is clear to point out that high water salinity had a negative effect on the both germination rate and percentage. The lowest values were recorded at water salinity especially 12.86 dS/m and barley cultivars Giza 123, 125 and 2000. Regarding to the effect of examined barley cultivars on the germination rate and percentage, data in Table 3 and Fig. 2 revealed that the highest GR was attained at Giza 126 (5.9), Giza 135 (5.6) and Giza 129 (5.5) and got the highest germination percentage but exceed Giza 2000 [21]. Conducted germination and pot experiments were

296


and 44.9% for germination rate and 1.8%, 7.7%, 16.0% and 23.9% for germination percentage at water salinity 3.21, 5.74, 8.28 and 12.86 dS/m as compared with control (fresh water), respectively (Fig. 4).

conducted to study the influence of irrigation water salinity on yield and chemical composition of wheat in sandy and calcareous soil. Irrigation water salinity levels were 0.43 (control), 4.85, 6.60 and 8.86 dS/m, respectively. Results concluded that, the lower germination percentage and rate and mean daily germination in calcareous soil at any salinity level compared to sandy soil. Water salinity had a negative effect on the germination rate and percentage, where the highest and lowest values were recorded at 0.31 dS/m (fresh water) and 12.86 dS/m, respectively (Fig. 3). Also, it is worthy to state that till 5.24 dS/m, germination rate and percentage are still high which represented that barely cultivars were more tolerant to water salinity. In addition that the percentage of reduction relative to the increase water salinity were 10.3%, 20.5%, 31.8%

3.4 Fresh and Dry Weight Table 4 and Figs. 5 and 6 represented fresh and dry weight and TWC (%) of root and shoot as affected by examined barley cultivars and water salinity. Usually, there is a markedly decrease in the obtained value with increasing salinity among water salinity treatments in each barely cultivars. Also, the highest were recorded at high water salinity. There were two barley cultivars (Giza 134 and Giza 2000) that gained the highest value of fresh weight root and shoot. Whereas, Giza 126 had no plants germinated at 12.86 (dS/m). Similar trend was attained in case of dry Germ % 100 80

6.0

60

4.0 40

2.0

20

0.0

0

Giza 123

Giza 124

Giza 125

Giza 126

Giza 129

Giza 130

Giza 134

Giza 135

Giza 2000

Barley cultivar differences in germination rate and percentage.

Germination rate

120

Germ Rate

7.0

Germ %

100

6.0

80

5.0 4.0

60

3.0

40

2.0

20

1.0

0

0.0

0.31

Fig. 4

Giza 127

3.21

5.74 8.28 Water salinity (dS/m)

Effect of water salinity on germination percentage and rate of barley cultivars.

12.86

Germination %

Fig. 3

Germination %

Germination rate

Germ Rate 8.0

297

Impact of Irrigation Water Salinity on Germination and Seedling Growth of Egyptian Barley Cultivars Table 4 Barley cultivars

Giza 123

Giza 124

Giza 125

Giza 126

Giza 127

Giza 129

Giza 130

Giza 134

Giza 135

Root and shoot weight and tissue water content (TWC) as affected by irrigation water salinity. Fresh weight (mg/plant) Water salinity (dS/m) Root Shoot 0.31 98.1 196.2 3.21 84.2 168.4 5.74 76.1 152.2 8.28 52.2 104.4 12.86 51.7 103.3 0.31 79.7 159.3 3.21 78.8 157.6 5.74 72.0 144.0 8.28 62.7 125.3 12.86 48.7 97.3 0.31 86.7 170.0 3.21 77.0 167.3 5.74 71.8 143.6 8.28 70.8 136.4 12.86 68.2 126.9 0.31 94.1 184.9 3.21 87.9 175.8 5.74 81.4 162.9 8.28 63.2 126.4 12.86 48.2 101.1 0.31 91.1 182.2 3.21 80.0 160.0 5.74 72.2 144.4 8.28 68.8 137.6 12.86 63.6 127.1 0.31 86.2 172.4 3.21 81.1 162.2 5.74 68.6 137.1 8.28 62.2 124.4 12.86 58.8 117.6 0.31 90.0 180.0 3.21 87.3 174.7 5.74 71.1 142.2 8.28 69.8 139.6 12.86 48.3 96.7 0.31 104.9 209.8 3.21 78.9 157.8 5.74 66.1 142.4 8.28 71.2 132.2 12.86 63.4 126.9 0.31 62.4 144.9 3.21 72.4 132.9 5.74 66.4 124.9 8.28 46.0 104.4 12.86 52.2 92.0

Dry weight (mg/plant) Root Shoot 17.3 15.45 12.9 13.19 9.1 8.91 6.4 5.99 6.0 6.35 11.9 11.63 12.1 10.67 8.6 9.54 8.7 8.12 7.3 5.98 18.5 11.56 11.8 12.15 9.8 7.94 8.6 7.82 12.0 7.79 16.6 17.28 19.5 13.76 12.9 10.12 7.7 7.25 7.1 6.5 16.0 14.35 8.4 12.53 8.7 8.45 8.4 7.89 9.5 7.81 15.2 12.59 12.5 10.98 8.2 9.09 7.6 8.06 6.8 7.22 13.5 12.24 13.4 12.68 8.5 7.86 9.7 8.00 7.2 5.94 22.4 19.61 12.1 12.36 9.0 8.85 8.7 7.58 11.2 8.89 11.0 9.86 16.1 9.65 10.5 6.90 5.6 5.99 6.0 5.65

Root 82.39 84.64 88.00 87.82 58.98 85.03 84.64 88.00 86.13 0.00 78.63 84.64 86.36 87.82 27.45 82.39 77.83 84.20 87.82 88.60 82.39 89.48 88.00 87.82 28.34 82.39 84.64 88.00 87.82 58.98 85.03 84.64 58.66 28.71 0.00 78.63 84.64 86.36 87.82 82.36 82.39 77.83 84.20 87.82 88.47

TWC (%) Shoot 92.1 92.2 94.1 94.3 62.6 92.7 93.2 93.4 93.5 0.0 93.2 92.7 94.5 94.3 31.3 90.7 92.2 93.8 94.3 93.6 92.1 92.2 94.1 94.3 31.3 92.7 93.2 93.4 93.5 62.6 93.2 92.7 63.0 31.4 0.0 90.7 92.2 93.8 94.3 93.0 93.2 92.7 94.5 94.3 93.9

Seedling vigor index 15.75 15.93 11.85 12.53 5.24 15.77 12.28 11.88 10.28 11.40 16.92 13.95 10.94 7.55 4.24 21.33 17.98 14.47 14.07 13.44 18.58 16.17 13.32 10.41 8.21 22.63 20.33 17.63 14.53 16.63 24.50 21.34 16.10 13.85 10.21 22.29 16.78 17.34 13.52 9.68 21.33 18.63 17.10 9.60 7.06

298

Impact of Irrigatiion Water Sallinity on Germ mination and Seedling Gro owth of Egyp ptian Barley Cultivars C

(Table 4 continnued) Barley cultivars

Giza 2000

Fresh weighht (mg/plant) W Water salinity (dS/m) Root Shoot 0 0.31 100.8 201.6 3.21 92.1 184.2 5.74 87.0 174.0 8.28 76.9 153.8 12.86 63.0 126.0

180 160 140 120 100 80 60 40 20 0

8.75 8.16 25.81

19.65 16.39 51.84

Root 82.39 89.48 88.00 87.82 85.01

TWC C (%) Shoot 990.7 992.2 993.8 994.3 993.00

1.23 1.15 3.64

11.86 8.69 27.49

12.88 9.46 29.91

1.36 1.07 3.42 14 1

Shoot

Root

Dry weight mg/plant

Fresh weight mg/plant

LSD (0.05 ) Barley cultivaars (V) Salinity levelss (T) (V*T)

Dry weight (mg/plant) Root Shoot 17.7 18.84 9.7 14.43 10.4 10.81 9.4 8.82 9.4 8.82

1.08 0.65 1.39

Shoot

10 1 8 6 4 2 0 Giza Giza Giza Giza Gizaa Giza Giza Gizza Giza Giza 34 135 2000 123 124 125 126 127 129 130 13 Dry we eight

Effectt of water salin nity on fresh and dry weight of barley cultiivars. 200

Root

Shoot

Dry weight (mg/plant)

Fresh weight (mg/plant)

24.83 2 16.17 13.66 11.78 5.67 5

12 1

Giza Giza Giza Giiza Giza Giza Giza Giza Giza Giza 123 124 125 12 26 127 129 13 30 134 135 2000 Fresh weight

Fig. 5

Root

Seedling S vigor index i

150 100 50 0

Roott

Shoot

5.7 74

8.28

15 1 10 1 5 0

0.31 Fig. 6

20 2

3.21 1

5.74

8.28

12.86 6

0.31

3.21

12.86

Effeect of water saalinity (dS/m) on o fresh weightt (A) and dry weight w (B) of barley. b

weight of rooot and shooot, where Gizza 134 and Giza G 2000 were thhe best ones. Regardingg to the exam mined barleyy cultivars efffect on the freshh weight and dry weight of o root and shhoot, data on haand indicatedd that Gizaa 2000 was the superior vaariety whom m scored thee highest value v followed byy Giza 125, 127 1 and 134 in case of fresh f weight of rooot and shoott, respectively. In case off dry weight of rooot, Giza 134 followed by b Giza 125 and Giza 2000 foollowed by Giza G 134 for shoot s dry weight.

Regarding R to the t effect of w water salinity y on the freshh weiight and dryy weight of root and shoot, dataa indiicated that thhere was a m markedly decrrease in freshh weiight and dryy weight oof root and shoot withh incrreasing salinity in water and the reduction underr shoot is more thhan root and the oppositee was true inn casee of dry weigght. It could summarize the t reductionn perccentage resullted from inccreasing wateer salinity ass folllows: 8.3%, 18.0%, 28.0%, 42.1% and 8.9%,, 18.5 5%, 28.7%, 43.7% for ffresh weight of root andd

299


shoot at 3.21, 5.74, 8.28 and 12.86 dS/m as compared with control treatment, respectively. In case of dry weight the percentage of reduction were 19.7%, 40.2%, 49.5%, 52.9% and 14.7%, 38.3%, 43.3%, 55.1% for root and shoot in same sequences. Naseer et al. [22] reported that the germination percentage, root and shoot length and fresh and dry weights were decreased in barley cultivars by increasing of salinity levels. 3.5 Tissue Water Content The TWC in root and shoot of barley cultivars severely was affected by increasing water salinity. These values were little large for Giza 2000 and Giza 127 (3.21 dS/m) followed by water salinity 5.74 dS/m in the same barley of root. But in case of shoot data showed that the highest values were attained in cultivars Giza 125, 127 and 129 with highly water salinity 5.74 dS/m and 8.28 dS/m. The lowest values of TWC recorded at 12.86 dS/m water salinity in all examined barley cultivars. Concerning to the effect of examined barley cultivars on the TWC for root and shoot, data presented in Table 4 and Figs. 7 and 8 illustrated that

was recorded at Giza 124 (14.8%). The differences between the obtained highest relative to the lowest one data found that Giza 129 and Giza 134 increased by about 43% and 40%, respectively. Also, the results of the TWC showed that the effect of water salinity was significantly at 1%. Only fresh water gave the highest value of TWC for root and shoot and water salinity at 12.86 dS/m gave the lowest one. Water salinity had an adverse effect on the TWC. The rates of decrease in percentage in tissue water content were 14%, 17%, 19% and 20% relative to the control (fresh water). 3.6 Seedling Vigor Index The SVI was strongly affected by both examined barley cultivars and water salinity. Data in Table 4 and Figs. 9 and 10 showed that the cultivars Giza 2000, 134 and 126 gained the highest value in descending order 24.8%, 24.7% and 21.5% as compared with control (fresh water). But mostly the lowest values (8.9% (Giza 2000), 12.3% (Giza 124) and 12.6% (Giza 135)) were highly correlated with water salinity. It is well established that salt stress has negative correlation with seed germination and SVI [23]. 100

the best for root and Giza 135, followed by Giza 134

80

and Giza 2000 for shoot were more pronounced effect barley cultivars, while the lowest ones were Giza 130 for root and shoot. In case of the effect of the investigated

water

salinity,

data

cleared

that

Tissue water content %

Giza 2000 followed by Giza 134 and Giza 135 were

Root

60 40 20 0 Giza Giza Giza Giza Giza Giza Giza Giza Giza Giza 123 124 125 126 127 129 130 134 135 2000

progressively decreased in TWC for root and shoot were attained in water salinity 3.21 dS/m and 5.74 dS/m for root and 0.31 dS/m, 92.55% for shoot. Also, it noticed that the change in TWC for root and shoot relative to the increase water salinity were expressed in percentage -2.5%, -2.2%, 0.5%, 47.7% and -0.5%, 1.4%, 4.6%, 49.2%, respectively. With respect to the examined barley cultivars effect on the TWC, the highest number scored at Giza 129 (21.2%) and Giza 134 (20.7%) while the lowest one

Fig. 7 Barley cultivar differences in tissue water content. 100 Root Shoot Tissue water content %

with increasing water salinity. The maximum values

Shoot

80 60 40 20 0

0.31 Fig. 8

3.21

5.74

8.28

12.86

Effect of water salinity on tissue water content.

300


Seedling vigor index

20

positive correlation coefficients between periods of germination and GR with r values 0.963**, 0.855** and 0.742** and with germination percentage 0.571*, 0.802** and 0.998**. Also, markedly positive correlation between SVI from side and fresh weight and dry weight for root and shoot were obtained with r values 0.546*, 0.573*, 0.588* and 0.647**, respectively.

15 10 5 0 Giza Giza Giza Giza Giza Giza Giza Giza Giza Giza 123 124 125 126 127 129 130 134 135 2000

Fig. 9

Barley cultivar differences in seedling vigor index.

Seedling vigor index

25

y = ‐2.7574x + 22.826 R² = 0.9965

20 15 10 5 0 0.31

Fig. 10

3.21

5.74

8.28

12.86

Relation between water salinity and seedling vigor

index.

3.7 Correlation Analysis It is worthy to mention that there were highly

3.8 SDS-PAGE Profile of Saline Irrigation Water of Barley Cultivars in Germination Stage Increased salt concentration caused a significant reduction in the vegetative growth of barley cultivars. Fresh and dry weights of sugar beet decreased significantly with increasing salt concentration in the growth medium. However, significant reduction was observed at high salinity levels. In this experiment the total soluble protein profile shows no significant difference between normal plant and stressed plant (Fig. 11) that may indicate to the positive effect of the clay soil as a reach nutrients soil comparing to sandy soil which was used in the previous salt stress experiment. There was a decrease in the amount of total soluble protein content with the high salinity level (Fig. 11) in cultivar Giza 2000 even if it was showing high percentage of germination and dry matter content. Data

Fig. 11 SDS-PAGE banding patterns showing the total soluble proteins from the leaf tissue of tested nine barley genotypes, Giza 123, 125, 126, 127, 129, 130, 134, 135 and 2000 after 10 d of germination in clay soil watering with saline solution. First lane is protein marker; N: normal condition; T: treated with saline water.


revealed a high intensity of 20 kDa protein band in treated sample with saline water than the control sample especially the cultivars Giza 123, 125, 126, 127, 129 and 130. The 6 kDa protein bands had the same increasing after salt stress in cultivars Giza 123, 127, 129, 134 and 135. The same protein band with 27 kDa was also get accumulated after stress treatment similar to the previous salt stress experiment, which may be related to the oxygen-evolving enhancer protein 2 (OEE2) associated with photo system II complex involved in photosynthesis activity under a biotic stress [24].

[6]

[7]

[8]

[9]

4. Conclusions The ability of barley cultivars Giza 134 and Giza 2000 to grow under the high salinity of irrigation water was greater than the rest of the other cultivars. So, it could be recommended for farmer to be grown under saline irrigation water conditions.

[10]

[11]

Acknowledgments The authors warmly thank the Agricultural Research in the Mediterranean Area 2 (ARIMNet 2) and Academy of Scientific Research and Technology (ASRT) and National Research Centre (NRC), Egypt who have funded this research work.

[12]

[13]

References [1]

[2]

[3] [4]

[5]

Siddiqui, Z. S., Shaukat, S. S., and Zaman, A. U. 2006. “Alleviation of Salinity Induced Dormancy by Growth Regulators in Wheat Seeds.” Turk. J. Bot. 30: 321-30. Kausar, F., Shahbaz, M., and Ashraf, M. 2013. “Protective Role of Foliar Applied Nitric Oxide in Triticum aestivum under Saline Stress.” Turk. J. Bot. 37: 1155-65. Munns, R. 2002. “Comparative Physiology of Salt and Water Stress.” Plant Cell Environ. 25: 239-50. Hameed, M., Nawaz, T., Ashraf, M., Naz, N., Batool, R., Ahmad, M. S. A., and Riaz, A. 2013. “Physioanatomical Adaptations in Response to Salt Stress in Sporobolus arabicus (Poaceae) from the Salt Range, Pakistan.” Turk. J. Bot. 37: 715-24. Emam, Y. 2011. Cereal Production. 4th edition. Shiraz, Iran: Shiraz University Press.

[14]

[15] [16]

[17]

[18]

301

Kaya, M. D., Okcu, G., Atak, M., Cikili, Y., and Kolsarici, O. 2006. “Seed Treatments to Overcome Salt and Drought Stress during Germination in Sunflower (Helianthus annuus L.).” Eur. J. Agro. 24: 291-5. Khan, M. A., and Weber, D. J. 2008. Ecophysiology of High Salinity Tolerant Plants (Tasks for Vegetation Science). 1st edition. Amsterdam: Springer. Gomes-Filho, E., Machado Lima, C. R. F., Costa, J. H., da Silva, A. C., da Guia Silva Lima, M., de Lacerda, C. F., and Prisco, J. T. 2008. “Cowpea Ribonuclease: Properties and Effect of NaCl-Salinity on Its Activation during Seed Germination and Seedling Establishment.” Plant Cell Rep. 27: 147-57. Dantas, B. F., De Sa Ribeiro, L., and Aragao, C. A. 2007. “Germination, Initial Growth and Cotyledon Protein Content of Bean Cultivars under Salinity Stress.” Rev. Bras. de Sementes 29: 106-10. Othman, Y., Al-Karaki, G., Al-Tawaha, A. R., and Al-Horani, A. 2006. “Variation in Germination and Ion Uptake in Barley Genotypes under Salinity Conditions.” World J. Agric. Sci. 2: 11-5. Rasheed, R. 2009. “Salinity and Extreme Temperature Effects on Sprouting Buds of Sugarcane (Saccharum ficinarum L.): Some Histological and Biochemical Studies.” Ph.D. thesis, Dept. of Botany, Univ. of Agriculture, Faisalabad, Pakistan. Wahid, A., Farooq, M., Basra, S. M. A., Rasul, E., and Siddique, K. H. M. 2011. “Germination of Seeds and Propagules under Salt Stress.” In Handbook of Plant and Crop Stress, 3rd edition, edited by Pessarakli, M. Boca Raton: CRC Press, 321-37. Pirasteh-Anosheh, H., Sadeghi, H., and Emam, Y. 2011. “Chemical Priming with Urea and KNO3 Enhances Maize Hybrids (Zea mays L.) Seed Viability under Abiotic Stress.” J. Crop Sci. Biotech. 14: 289-95. Ashraf, M., Athar, H. R., Harris, P. J. C., and Kwon, T. R. 2008. “Some Prospective Strategies for Improving Crop Salt Tolerance.” Adv. Agron. 97: 45-110. International Seed Testing Association (ISTA). 2008. International Rules for Seed Testing. Zurich: ISTA. Larkindale, J., and Huang, B. 2004. “Thermotolerance and Antioxidant Systems in Agrostis stolonifera: Involvement of Salicylic Acid, Abscisic Acid, Calcium, Hydrogen Peroxide, and Ethylene.” J. Plant Physiol. 161: 405-13. Bradford, M. M. 1976. “A Rapid and Sensitive Method for Quantitation or Microgram Quantities of Protein Utilizing the Principle of Protein-Dye Binding.” Anal. Biochem. 72: 248-54. Laemmli, U. K. 1970. “Cleavage of Structural Proteins during the Assembly of the Head of Bacteriophage T4.”

302


Nature 227 (5259): 680-5. [19] Gomez, K. A., and Gomez, A. A. 1984. Statistical Procedures for Agriculture Research. 2nd edition. New York: John Wiley and Sons, 180. [20] Saritha, V., Kuriakose, M., and Prasad, M. N. V. 2007. “Cadmium Stress Affects Seed Germination and Seedling Growth in Sorghum bicolor (L.) Moench by Changing the Activities of Hydrolyzing Enzymes.” J. Plant Growth Regulation 54: 143-56. [21] Ragab, A. A. M., Hellal, F. A., and Abd El-Hady, M. 2008. “Water Salinity Impacts on Some Soil Properties and Nutrients Uptake by Wheat Plants in Sandy and Calcareous Soil.” Australian Journal of Basic and

Applied Sciences 2 (2): 225-33. [22] Naseer, Sh., Nisar, A., and Ashraf, M. 2001. “Effect of Salt Stress on Germination and Seedling Growth of Barley (Hordeum vulgare L.).” Pakistan J. Biol. Sci. 4 (3): 359-60. [23] Rehman, S., Harris, P. J. C., Bourne, W. F., and Wilkin, J. 2000. “The Relationship between Ions, Vigor and Salinity Tolerance of Acacia Seeds.” Plant and Soil 220: 229-33. [24] Kong-Ngern, K., Daduang, S., Wongkham, C. H., Bunnag, S., Kosittrakun, M., and Theerakulpisut, P. 2005. “Protein Profiles in Response to Salt Stress in Leaf Sheaths of Rice Seedlings.” Science Asia 31: 403-8.

D


DAVID

PUBLISHING

Relationships among Bean Yield Traits in Some Cacao (Theobroma cacao L.) Genotypes Adenuga Olalekan Omotayo, Adepoju Abigail Funlayo, Olaniyi Olayinka Olufemi and Balogun Shamsudeen Tomiwa Plant Breeding Section, Cocoa Research Institute of Nigeria, Ibadan 23401, Nigeria Abstract: Cacao (Theobroma cacao L.) produces the cocoa bean, a major foreign exchange earner for most West African countries and many smallholders’ enterprise. Ample production of cacao is however limited by declining yield among other factors. This study aimed at determining the correlations of the phenotypic traits that were related to the yield of the cacao genotypes. Nine new cacao hybrids were produced from some high-yielding parents in the research farm of Cocoa Research Institute of Nigeria, Ibadan and evaluated from 2012 through 2014 in Owena (7°11′ N, 5°1′ E), Ondo state, Nigeria. Analysis of variance, character correlations and path coefficient analysis were used in the analysis of the relationships among the genotypes. Analysis of variance revealed significant (p ≤ 0.05) variations for number of rows, weight of beans per fruit, fresh weight of one bean, weight of one bean after fermentation, pod value, dry bean length, weight of beans (per fruit) after fermentation and pod index. The study concluded that significant genotypic and phenotypic correlations existed among some of the pairs of the fruit and bean characters with one another and with pod index, suggesting that the contribution of these characters is either positive or negative to growth and yield in the cacao genotype, and that fruit and bean traits are determinants of bean yield in cacao. Key words: Bean yield, cacao, correlation, genetic variability, phenotypic traits.

1. Introduction The cacao tree (Theobroma cacao L.) produces cocoa bean, a major foreign exchange earner for most West African countries and many smallholder enterprises. Declining yield is, however, a limiting factor in cacao cropping in Nigeria. The F3 Amazon hybrid, a derivative of the Upper Amazon Forastero material [1], which takes up to four years to flower, is the common variety in farmer plots across Nigeria. The need to obtain early fruiting genotypes with improved yield led to the discovery and release of eight new cacao varieties by the Cocoa Research Institute of Nigeria (CRIN) in 2011 [2]. Variability is the basis for genetic improvement. There is therefore a need for improved genotypes obtained through appropriate breeding procedures to widen the genetic base of cacao genotypes in farmer Corresponding author: Adenuga Olalekan Omotayo, Ph.D., research field: plant breeding.

plots in Nigeria, which is perceived to be narrow due to farmers’ practice of using seed from their own crop for new plantings [3]. This will enable to get the required genetic variability for this crop improvement, namely bean yield. Building on the achievement of CRIN in the release of the new hybrids, some F1 offspring of these newly-released hybrids were found to have fruited early in the Owena sub-station of the institute, with first fruit harvest occurring already during 104-124 weeks of field planting of these F1 offspring. Information has been published on the genetic variability of these F1 offspring [4]. Seventy per cent (70%) of world cocoa beans are produced by small holders in West Africa whose yield has remained low [5]. Cocoa bean yield is influenced by the variety and age of plant [6]. Bean yield in cocoa is also negatively influenced by climatic changes and increased land use for food crops [5]. Correlation is a measure of the degree of relationship between variables [7]. Estimates of

304

Relationships among Bean Yield Traits in Some Cacao (Theobroma cacao L.) Genotypes

genotypic, phenotypic and environmental correlations among characters can provide the basis of planning of more efficient breeding programmes. A plant breeder should know whether the improvement of one character will result in simultaneous change in other characters through estimates of inter-character correlations [7]. Cocoa bean yield has remained low in Nigeria [3] and the yield is believed to be influenced by a number of characters. This study was therefore carried out to determine the correlations between phenotypic traits that were related to the yield of cocoa bean among some Nigerian cacao genotypes.

2. Materials and Methods Nine newly produced early hybrids were planted in July, 2012, at the Owena (7°11′ N, 5°1′ E) sub-station of CRIN, in Ondo state, Nigeria and evaluated through January 2015. Thirty individual seedlings were established per genotype as 10 seedlings per plot in three replications in a randomized complete block design (RCBD). The list of the nine genotypes and their pedigree are shown in Table 1. Five uniformly matured and ripe cocoa pods were harvested per genotype in each replication, giving a total of 15 pods (fruits) per genotype. The fruits were carefully broken to get the beans. The number of rows, number of beans per row and number of beans per pod were counted. Also, the weight of the beans was recorded per fruit, while the weight of one individual bean was recorded as the average of the weight of 10 beans randomly selected per fruit. Beans from each fruit Table 1 S/N 1 2 3 4 5 6 7 8 9

were extracted and fermented in trays. The beans were weighed after fermentation, and the weight recorded per fruit, and per individual bean as the average of 10 fermented beans weighed. The fermented beans were sun-dried, and the pod value recorded as weight of the total dried beans obtained per fruit. The weight of one dried bean was also recorded as the average of the weight of 10 dried bean per fruit. Dried bean length and width were recorded as average of values of 10 dried beans using the vernier calliper. Pod index was inferred from the weight of dried beans from each pod as the number of pods required to produce 1 kg of dry cocoa beans. The studied genotypes were subjected to analysis of variance using SAS package (version 9.2) [8] to assess the variability significance among them, while their means were separated using Duncan’s multiple range test. The phenotypic, genotypic and environmental correlation coefficients were estimated using the formula of Miller et al. [9]:

r ( x, y ) 

Cov( xy) (x) 2 (y ) 2

(1)

where r(x, y) is either genotypic or phenotypic or environmental correlation between variables x and y; Cov(xy) is the covariance of variables x and y; (δx)2 is either the genotypic or phenotypic or environmental variance of variable x; (δy)2 is either the genotypic or phenotypic or environmental variance of variable y. The formula applies equally in the determination of each of genotypic, phenotypic and environmental correlation coefficients.

List of nine cacao genotypes used in the study. Genotype code

Pedigree

AJ AK BJ CJ CK EI FJ GH GJ

(T82/27  T12/11)  (T65/7  T57/22) (T82/27  T12/11)  (T53/5  N38) (P7  T60/887)  (T65/7  T57/22) (T86/2  T9/15)  (T65/7  T57/22) (T86/2  T9/15)  (T53/5  N38) (T86/2  T22/28)  (T65/7  T22/28) (T65/7  T9/15)  (T65/7  T57/22) (P7  PA150)  (T101/15  N38) (P7  PA150)  (T65/7  T57/22)

Weeks to harvest 122 117 124 114 105 117 104 117 114


The significance of the correlation coefficients was tested using the non-directional probability in the software of Lowry [10]. The direct and indirect path coefficients were calculated to reveal the strength of the relationship among pod index and the yield-related characters by solving a series of simultaneous equations as suggested by Dewey and Lu [11].

3. Results and Discussion The mean squares of the characters and the coefficients of variation for 12 characters among the nine cacao genotypes are presented in Table 2. Significant (p ≤ 0.05) genotypic variation existed among the nine hybrids for number of rows, weight of beans per fruit, fresh weight of one bean, weight of one bean after fermentation, pod value, dry bean length and pod index. Highly significant (p ≤ 0.01) genotypic variation also existed for weight of beans (per fruit) after fermentation. The highest coefficient of variation was observed for fruit width (19.94) and pod thickness (19.25). The significant genotypic variations and moderate coefficients of variations of some of the quantitative traits indicate genetic variability of the genotypes. The separation of the means for the 12 characters describing the nine hybrids is presented in Table 3. Hybrid G  H had the largest bean weight per fruit (141.76), while hybrid C  J had the lowest (109.23); hybrid G  H had the heaviest single bean weight (3.91), weight of beans after fermentation (118.56), weight of one bean after fermentation (2.7), one dry bean weight (1.30), dry bean length (23.10) and dry bean width (12.39). Hybrid C  K had the least bean weight after fermentation (85.25) and weight of one bean after fermentation (1.98). Hybrid C  K also had some of the least weight of one bean (2.47), pod value (37.79), one dry bean weight (1.08), dry bean length (21.78) and dry bean width (12.17). Hybrid F  J had the highest pod index (28.59) while hybrid A  J had the least (20.72). Hybrids A  J and G  H had the

305

highest pod values of 48.58 and 47.43, respectively. Selection can therefore be done among the genotypes for the purpose of further improvement. The phenotypic, genotypic and environmental correlation coefficients among the fruit and bean characters of the nine cacao hybrids are presented in Table 4. For selection of genotypes to be successful, the phenotypic expression of their traits must serve as a guide. Moreover, phenotypic correlation is a composite of the genotypic and environmental correlations. The significant phenotypic correlation coefficients are therefore stated thus. Number of rows was negatively significantly (p ≤ 0.01) correlated with beans per row (-0.47), beans weight per row (-0.39), weight of one bean (-0.42), one dry bean weight (-0.58) and dry bean width (-0.57). Number of beans per row was positively significantly (p ≤ 0.01) correlated with beans per fruit (0.77), beans weight per fruit (0.39), pod value (0.56) and one dry bean weight (0.41) but negatively correlated with dry bean length (-0.39) and pod index (-0.71). Number of beans per fruit was positively significantly (p ≤ 0.05) correlated with pod value (0.43) but negatively correlated with weight of one bean (-0.39), dry bean length (-0.48), dry bean width (-0.49) and pod index (-0.56). Beans weight per fruit was positively significantly (p ≤ 0.05) correlated with weight of one bean (0.86), beans weight after fermentation (0.83), one bean weight after fermentation (0.83), pod value (0.87), one dry bean weight (0.86) but negatively correlated with pod index (-0.78). Weight of one bean was positively correlated with beans weight after fermentation (0.73), one bean weight after fermentation (0.74), pod value (0.56), one dry bean weight (0.76), dry bean length (0.66) and dry bean width (0.38) but negatively correlated with pod index (-0.41). Beans weight after fermentation was positively significantly (p ≤ 0.01) correlated with one bean weight after fermentation (0.96), pod value (0.87) and one dry bean weight (0.53) but negatively correlated with pod index (-0.71). One bean weight after fermentation was positively significantly (p ≤ 0.01)

ANOVA (mean squares) of characters of nine cacao hybrids used in the study.

Mean performance of nine cacao hybrids used in the study.

Genotype

Rows

Bns/Row

Bns/Frt

Bns Wgt/Frt Wgt of 1 Bn Bns Wgt 1 Bn Wgt 1 DB Wgt Pd Val (g) DBL (mm) DBW (mm) P. I. (g) (g) Ferm (g) Ferm (g) (g) a a a ab bc ab ab a ab 9.20 44.53 130.47 3.07 115.35 2.76 48.58 1.14 21.68b 12.02ab 20.72c 5.00 AJ 9.33a 44.80a 129.40ab 3.07bc 100.38b-e 2.26bc 45.47ab 1.20ab 22.93a 11.74b 22.08bc 4.80a AK a ab a bc abc de bc ab ab ab ab 9.00 42.00 123.64 3.14 92.52 2.27 41.10 1.14 22.58 12.06 24.87abc 4.80 BJ a ab a bc ab bcd bc ab ab ab a 4.93 8.33 37.67 122.58 3.32 100.97 2.24 41.73 1.11 22.71 12.16 25.18abc CJ ab ab a c bc e c b b b ab 9.13 41.93 109.23 2.47 85.25 1.98 37.79 1.08 21.78 12.17 27.37ab 4.67 CK ab ab a ab ab abc abc ab ab ab a 4.67 8.73 39.93 127.49 3.36 109.14 2.54 43.56 1.14 22.72 12.40 24.42abc EI 8.07b 39.13a 120.52bc 3.22abc 97.35cde 2.37abc 39.02b 1.15ab 23.34a 11.92ab 28.59a 4.93a FJ b a a a a a a a a a a 4.40 9.27 40.20 141.76 3.91 118.56 2.87 47.43 1.30 23.10 12.29 22.09bc GH a ab a bc bc bcd abc ab b ab ab 8.60 41.07 116.47 2.93 103.17 2.40 41.40 1.04 22.38 11.88 26.09abc 4.87 GJ Means with the same letter along the column are not significantly different using Duncan’s multiple range test (DMRT) at 0.05 level of probability. Rows = number of rows per pod; Bns/Row = number of beans per row; Bns/Frt = beans per fruit; Bns Wgt/Frt = weight of beans per fruit; Wgt of 1 Bn = weight of a single bean per fruit; Bns Wgt Ferm = weight of beans per fruit after fermentation; 1 Bn Wgt Ferm = weight of one bean after fermentation; Pd Val = pod value; 1 DB Wgt = weight of one dry bean; DBL = dry bean length; DBW = dry bean width; P. I. = pod index.

Table 3

Source of Bns Wgt of 1 Bns Wgt 1 Bn Wgt 1 DB Wgt df Rows Bns/Row Bns/Frt Pd Val (g) DBL (mm) DBW (mm) P. I. variation Wgt/Frt (g) Bn (g) Ferm (g) Ferm (g) (g) Block 2 0.01 0.19 25.07 10.58 0.16 41.45 0.05 1.90 0.00 0.02 0.09 3.60 Hybrid 8 0.10* 0.60 16.73 256.69* 0.44* 336.81** 0.23* 40.44* 0.02 0.94* 0.13 20.21* Error 16 0.03 0.31 14.83 77.21 0.17 66.74 0.09 15.55 0.01 0.30 0.08 8.01 C.V. (%) 3.77 6.30 9.33 7.05 13.06 7.97 12.34 9.19 9.33 2.43 2.33 11.50 *, ** Significance at p ≤ 0.05 and 0.01, respectively. ANOVA = analysis of variance; Bns/Row = number of beans per row; Bns/Frt = beans per fruit; Bns Wgt/Frt = weight of beans per fruit; Wgt of 1 Bn = weight of a single bean per fruit; Bns Wgt Ferm = weight of beans per fruit after fermentation; 1 Bn Wgt Ferm = weight of one bean after fermentation; Pd Val = pod value, i.e., total weight of dry beans per pod; 1 DB Wgt = weight of one dry bean; DBL = dry bean length; DBW = dry bean width; P. I. = pod index.

Table 2

Bns/Row

Bns/Frt

Bns Wgt/Frt Wgt of 1 Bn

Bns Wgt Ferm -0.21 -0.06 -0.65** 0.20 0.00 0.63** 0.03 0.05 0.03 0.83** 0.81** 0.94** 0.73** 0.79** 0.66** 1 Bn Wgt Ferm

Pd Val

1 DB Wgt

DBL

DBW

Phenotypic, genotypic and environmental correlation coefficients among 12 fruit and beans characters of nine cacao hybrids used in the study. P. I.

Rows

rp -0.47** 0.11 -0.39* -0.42* -0.25 -0.16 -0.58** -0.23 -0.57** 0.15 rg -0.63** -0.29 -0.31 -0.23 -0.04 -0.03 -0.63** -0.44* -0.72** 0.11 re -0.27 0.36 -0.57** -0.77** -0.65** -0.39* -0.63** 0.19 -0.45** 0.24 0.77** 0.39* -0.04 0.21 0.56** 0.41* -0.39* 0.03 -0.71** rp rg 1.33** 0.17 -0.05 0.13 0.41* 0.40* -0.71** -0.24 -0.56** Bns/Row 0.67** 0.74** -0.03 0.32 0.75** 0.43* 0.02 0.24 -0.90** re rp 0.12 -0.39* 0.05 0.43* 0.08 -0.48** -0.49** -0.56** Bns/Frt rg -0.02 0.08 0.94 0.97** 1.84** -2.45** -2.29** -0.96** re 0.24 -0.70** -0.34 0.30 -0.34 0.38* 0.00 -0.52** 0.86** 0.83** 0.87** 0.86** 0.39 0.21 -0.78** rp 1.04** 0.89** 0.87** 1.18** 0.66** -0.15 -0.75** Bns Wgt/Frt rg 0.52** 0.74** 0.88** 0.68** -0.20 0.68** -0.86** re rp 0.74** 0.56** 0.76** 0.66** 0.38* -0.41* Wgt of 1 Bn rg 0.67** 0.65** 0.77** 1.30** 0.31 -0.56** re 0.86** 0.40* 0.81** -0.51** 0.47** -0.18 0.96** 0.87** 0.53** 0.14 0.26 -0.71** rp 1.02** 0.91** 0.52** 0.29 0.04 -0.72** Bns Wgt Ferm rg 0.87** 0.84** 0.74** -0.30 0.70** -0.76** re 0.82** rp 0.58** 0.15 0.28 -0.64** 1 Bn Wgt 0.86** rg 0.31 0.56** -0.01 -0.71** Ferm 0.74** re 0.86** -0.59** 0.58** -0.53** 0.60** -0.03 0.05 -0.96** rp rg 0.62** 0.24 -0.50** -0.97** Pd Val re 0.64** -0.52** 0.63 -0.94** 0.54** 0.17 -0.54** rp 1.67** -0.03 -0.57** rg 1 DB Wgt -0.47** 0.28 -0.55** re rp -0.06 0.16 DBL rg 0.19 0.09 re -0.35 0.29 -0.03 rp 0.44* rg DBW -0.50** re NB: df = 25; *, ** Significance at 0.05 and 0.01, respectively; rp = phenotypic correlation coefficients; rg = genotypic correlation coefficients; re = environmental correlation coefficients. Bns/Row = number of beans per row; Bns/Frt = number of beans per fruit; Bns Wgt/Frt = weight of beans per fruit; Wgt of 1 Bn = weight of a single bean per fruit; Bns Wgt Ferm = weight of beans per fruit after fermentation; 1 Bn Wgt Ferm = weight of one bean after fermentation; Pd Val = pod value, i.e., weight of total dry beans from a pod; 1 DB Wgt = weight of one dry bean; DBL = dry bean length; DBW = dry bean width; P. I. = pod index.

Character

Table 4

Direct and indirect path coefficients between pod index and nine beans characters of the nine cacao hybrids used in the study.

Indirect effects through other plant characters Bns Wgt 1 Bn Wgt Direct effect Bns/Row Bns/Frt Bns Wgt/Frt Wgt of 1 Bn Pd Val 1 DB Wgt DBW Corr with pod index Ferm Ferm Bns/Row -0.4542 -0.2589 0.2054 0.0996 0 0.0668 -0.378 0.2189 -0.0596 -0.56 Bns/Frt -0.1946 -0.6041 -0.0242 -0.1594 -0.0047 0.4831 -0.8943 1.007 -0.5688 -0.96 Bns Wgt/Frt 1.2080 -0.0772 0.0039 -2.0717 -0.0768 0.4575 -0.8021 0.6458 -0.0373 -0.75 Wgt of 1 Bn -1.992 0.0227 -0.0156 1.2563 -0.0749 0.3444 -0.5993 0.4214 0.0770 -0.56 Bns Wgt Ferm -0.0948 0 -0.0097 0.9785 -1.5737 0.5243 -0.8390 0.2846 0.0099 -0.72 1 Bn Wgt Ferm 0.5140 -0.059 -0.1829 1.0751 -1.3347 -0.0967 -0.7929 0.1697 -0.0025 -0.71 Pd Val -0.922 -0.1862 -0.1888 1.0510 -1.2948 -0.0863 0.4420 0.3393 -0.1242 -0.97 1 DB Wgt 0.5473 -0.1817 -0.3581 1.4254 -1.5339 -0.0493 0.1593 -0.5716 -0.0075 -0.57 DBW 0.2484 0.1090 0.4457 -0.1812 -0.6175 -0.0038 -0.0051 0.4610 -0.0164 0.44 Bns/Row = number of beans per row; Bns/Frt = number of beans per fruit; Bns Wgt/Frt = weight of beans per fruit; Wgt of 1 Bn = weight of a single bean per fruit; Bns Wgt Ferm = weight of beans per fruit after fermentation; 1 Bn Wgt Ferm = weight of one bean after fermentation; Pd Val = pod value, i.e., weight of total dry beans from a pod; 1 DB Wgt = weight of one dry bean; DBW = dry bean width; Corr with pod index = correlation with pod index. Residual effect = 0.2139.

Table 5


correlated with pod value (0.82) and one dry bean weight (0.58) but negatively correlated with pod index (-0.64). Pod value was positive significantly (p ≤ 0.05) correlated with one dry bean weight (0.60) but negatively correlated with pod index (-0.96). One dry bean weight was positively significantly (p ≤ 0.05) correlated with dry bean length (0.54) but negatively correlated with pod index (-0.54). Selection of the genotypes based on the relationships of the few pairs of character that exhibited significant phenotypic correlations, but not with corresponding significant genotypic correlation will not be reliable, since the genetic components are obviously not playing significant role in the variability expressed by such character. This applies to the pairs of association between number of rows and each of beans weight per fruit and weight of one bean; bean per row and beans weight per fruit; beans per fruit with weight of one bean; weight of one bean with dry bean weight; and one bean weight after fermentation with one dry bean weight. Selection of the genotypes based only on inter-character associations which are genotypically correlated but not phenotypically correlated may not be of practical value in breeding programme since selection is mostly based on the phenotypes of the characters in consideration and such a selection will be unrepeatable and unreliable [12]. This applies to the many pairs of characters that exhibited this kind of relationship in the study, such as number of rows and dry bean length; beans weight per fruit and dry bean length; one bean weight after fermentation and dry bean length; and pod value and dry bean width. The significant genotypic and phenotypic correlations of some of the pairs of the fruit bean characters with one another and with pod index suggested that these characters contributed either positively or negatively to growth and yield in the cacao genotypes. Such inter-character associations can therefore be used as criteria for selection of the genotypes that particularly exhibit good yield. This

309

relationship applies to number of rows and number of beans per row; number of beans per row and dry bean length; number of beans per fruit and each of pod value and dry bean width; as well as weight of one bean and pod index. The significant environmental correlations among many of the pairs of characters indicated the influence of the environment on which the genotypes were grown in the expression of these traits. From the direct and indirect path coefficients estimating the relationship between pod index and the beans characters (Table 5), number of beans per row, number of beans per fruit, weight of one bean, weight of beans after fermentation, and pod value all had a negative direct effects on pod index. This implies an inverse relationship between each of these traits and pod index, which is very desirable since pod index refers to the number of cocoa pods required to produce 1.0 kg of dry cocoa beans [1], the lower the value (of pod index), the more desirable the genotype. This means that as each of these traits increased in magnitude and reduces the magnitude of pod index, fewer pods are required to give 1 kg of dry cocoa beans, thereby saving the cost of labour and other factors of production. The important negative indirect effects of these plant traits on pod index include their effects through number of beans per fruit, pod value and dry bean width (for number of beans per row); number of beans per row, beans weight per fruit, weight of one bean, weight of beans after fermentation, pod value and dry bean width (for number of beans per fruit); number of beans per fruit, weight of beans after fermentation, and pod value (for weight of one bean); number of beans per fruit, weight of one bean, and pod value (for weight of beans after fermentation); and number of beans per row, number of beans per fruit, weight of one bean, weight of beans after fermentation and dry bean width (for pod value). Hence, number of beans per row, number of beans per fruit, weight of one bean, weight of beans after fermentation, and pod value can be considered along

310


with any or all of each of the other traits that enhance their negative expression in the selection of these cacao genotypes for desirable pod index. The moderate value of the residual factor recorded in the relationship between pod index and the fruit and bean characters indicated a reduction in rounding-off errors.

4. Conclusions Significant genotypic variations exist among the cacao genotypes used in this study as shown by the phenotypic fruit and bean traits that describe them. Therefore, beyond the influence of climate, the fruit and bean traits used in this study are important determinants of yield in cacao. Selection among these genotypes for bean yield improvement can therefore be done with the aid of these traits, considering the negative impact of climate changes of cocoa bean yield.

Recommendations The character association of each of the pairs of number of rows and number of beans per row, number of beans per row and dry bean length, number of beans per fruit and each of pod value and dry bean width, as well as weight of one bean and pod index are recommended as for consideration in the selection of cacao genotypes for improved bean yield. A similar study is also recommended in more multiple cacao agro-ecologies, considering the influence of climate changes on cocoa bean yield.

Acknowledgments The authors acknowledge the invaluable support from the field staff of CRIN in the design of this experiment, the field layout and establishment and data collection, which made the work a success.

References [1]

Wood, G. A., and Lass, R. A. 1985. Cacao. 4th edition. U.K.: Longman publishers, 620. [2] Cocoa Research Institute of Nigeria (CRIN). 2011. New Cocoa Varieties for Nigeria—Attribute and Field Management Requirements. CRIN, 43. [3] Aikpokpodion, P. O. 2007. “Genetic Diversity in Nigerian Cacao (Theobroma cacao L.) Collections as Revealed by Phenotypic and Simple Sequence Repeats Marker.” Ph.D. thesis, University of Ibadan, Nigeria, 131. [4] Adenuga, O. O., Olaniyi, O. O., Adeigbe, O. O., Adepoju, A. F., Dada, K. E., and Mapayi, E. F. 2015. “Phenotypic Description & Discrimination of Some Early-Bearing Cacao (Theobroma cacao L.) Genotypes Using Pod & Bean Traits.” IOSR Journal of Agriculture and Veterinary Science 8 (7): 35-42. [5] Wessel, M., and Quist-Wessel, P. M. F. 2015. “Cocoa Production in West Africa, a Review and Analysis of Recent Developments.” NJAS—Wageningen Journal of Life Sciences 74-75: 1-7. [6] Goenaga, R., Guiltinan, M., Maximova, S., Seguine, E., and Irizarry, H. 2015. “Yield Performance and Bean Quality Traits of Cacao Propagated by Grafting and Somatic Embryo-Derived Cuttings.” Journal of the American Society for Horticultural Science 50 (3): 358-62. [7] Falconer, D. S. 1989. Introduction to Qualitative Genetics. 2nd edition. London: Longman, 340. [8] SAS Institute. 2007. The SAS System for Windows. Release 9.2 SAS Inst Inc, Gary, NC, USA. [9] Miller, P. A., Williams, V. C., Robinson, H. P., and Comestock, R. C. 1958. “Estimates of Genotype and Environmental Variances and Covariances in Upland Cotton and Their Implications in Selection.” Agronomy Journal 50: 126-31. [10] Lowry, R. 2009. “Appendix to Chapter 4: The Significance of a Correlation Coefficient.” Accessed October 9, 2018. http://faculty.vassar.edu/lowry/rdiff.html. [11] Dewey, L. R., and Lu, K. H. 1957. “A Correlation and Path Analysis of Crested Heat Grass Seed Production.” Agronomy Journal 51: 515-8. [12] Ariyo, O. J. 1995. “Genetic Variability, Correlations and Path Coefficient Analysis of Components of Seed Yield in Cowpea (Vigna unguiculata).” Pertanika Journal of Tropical Agricultural Science 18: 61-9.

D


DAVID PUBLISHING

Soil Attributes in Anthropized Hygrophilous Forest in Northern Minas Gerais State, Brazil Maria das Dores Magalhães Veloso1, Luiz Arnaldo Fernandes2, Marly Antonielle de Ávila3, Yule Roberta Ferreira Nunes1 and Leidivan Almeida Frazão2 1. Universidade Estadual de Montes Claros, Montes Claros, Minas Gerais State 39401-089, Brazil 2. Instituto de Ciências Agrárias, Universidade Federal de Minas Gerais, Montes Claros, Minas Gerais State 39404547, Brazil 3. Universidade Federal de Lavras, Lavras, Minas Gerais State 37200-000, Brazil Abstract: The soils of Brazilian Cerrado are characterized with high acidity and low fertility and productivity. However, these attributes are not homogeneously distributed through all phytophysiognomies of this biome, and wetland known as palm swamp or “veredas” are an exception. This study aimed to describe and compare the chemical and physical attributes of soil surface layers at six palm swamps areas under different anthropization processes in the northern region of Minas Gerais state, Brazil. Soil sampling of different hydromorphic soils were collected at 0-20 cm depth layer from 100 m2 plots in the studied areas. The variables were compared using the GLM procedure of ANOVA using Statistica 10 software. Soil chemical attributes and similarities between the six palm swamps areas were compared using the statistical software R. Soil chemical attributes were different and soil physical attributes were similar between the evaluated areas. The similarities among the attributes were classified into three groups according to the anthropic pressures, as well as with the origin of the soil material in the six palm swamps areas evaluated. It could be concluded that soil fertility can be reduced in palm swamps that suffered greater anthropic intervention. The three similarity groups might be associated not only to the anthropic pressures, but also to the raw material of soil at the six palm swamps areas evaluated. Key words: Hydromorphic soils, palm swamps, soil fertility.

1. Introduction Naturally, Cerrado soils have high acidity and low fertility and productivity [1], but these features are not homogenously distributed. Cerrado biome covers approximately 25% of Brazilian surface area and shelters several phytophysiognomies within the biome [1, 2]. Two distinct habitats, akin to differentiated ecosystems, are related through edaphic and topographic factors in addition to fire and anthropization processes [3]. In order to attend the demand for food and fiber, the expansion of agricultural areas and forestry plantations in Brazil during the 1970s, large areas of Cerrado were considered new agricultural lands [2, 4]. Corresponding author: Leidivan Almeida Frazão, professor, research fields: soil science, dynamic of soil organic matter, management of agrosilvopastoral and agroforestry systems.

Among these areas, those located next to bodies of water and seasonally flooded environments became priority areas for monoculture, since water is a facilitating factor for the development of agriculture and livestock. Areas of Cerrado located in wetlands, known as palm swamps or “veredas”, became part of these priority areas, since these environments have fertile soil and large groundwater reservoirs that merge into a central channel [5]. “Vereda”, or hygrophilous forest, is a denomination given to one phytophysiognomy present in the Cerrado, according to Boaventura [6] and Tubelis [7], usually presents peaty and shallow soils, with a sandy surface layer, clayey subsurface layer and high hydric saturation. These environments have low resilience and are sensitive to anthropic pressures, once the changes into surrounding areas can promote a gradual loss of their intrinsic characteristics [8].

312

Soil Attributes in Anthropized Hygrophilous Forest in Northern Minas Gerais State, Brazil

Despite the dominance of Oxisols in Cerrado biome, the main classes of soils in palm swamps are Histosols, Udox and Aquoll [6]. These soils, with low material deposition and high levels of organic material and humidity, are sensitive to anthropic interference. According to Santos and Salcedo [9], lowland soil has higher levels of organic material than upland soil. As these environments are very vulnerable to perturbations, the soil fertility of surface layers can change significantly due to anthropic modifications. The intensive use of soils and the reduction or removal of native vegetation can result in reduction of soil fertility [10, 11]. According to Perin et al. [12], agricultural cultivation reduces the level of soil organic material due to increased decomposition of plant litter. These authors also observed that soil disturbance with conventional tillage leads to decrease in organic material, reducing the soil fertility and contributing to the occurrence of soil erosion. Thus, the aim of this work was to characterize and compare the soil’s chemical and physical attributes in the surface layer of six palm swamps areas under different levels of anthropization in the Pandeiros river basin located at Northern Minas Gerais state, Brazil.

2. Materials and Methods This work was performed in six palm swamps areas located at the municipalities of Bonito de Minas and Januária, in the region of the upper-middle Pandeiros river, a tributary of São Francisco river, in northern of Minas Gerais state, Brazil. The palm swamps areas are denominated as Água Doce (AD) (15°13′18.7″ S, 44°55′21.2″ W), Almescla (AM) (15°21′37.2″ S, 44°54′45.9″ W), São Francisco (SF) (15°23′4.4″ S, 44°50′59.6″ W), Buriti Grosso (BG) (15°26′26.6″ S, 45°3′55″ W), Capivara (CP) (15°16′10.23″ S, 44°51′13.6″ W) and Pindaibal (PI) (15°22′30.2″ S, 45°2′0.17″ W) (Fig. 1). In the AD palm swamp, Histosol was found at the left bank, and Aquoll was observed at the right hand

side bank. In the SF and CP the Aquoll soil was observed, and in the AM, BG, and PI the Histosol was observed. For all evaluated areas, the soil had a sandy texture and flat relief. AD and SF palm swamps are located in areas that contain rocky outcrops. In the six selected areas, AD, AM and SF are visually preserved; at the edges and in the interior, only small areas are occupied by familiar agricultural activities, with no record of large deforestation, fires or the remnants of enterprise. Thus, these palm swamps areas are preserved when compared with the other palm swamps in this study. At the palm swamps BG, CP and PI, the opposite fate is observed, particularly for BG and its surroundings, which suffered a suppression of 99.9% of vegetation when replaced by a monoculture of irrigated rice in the early 1970s [13], with a concomitant opening of drainage ditches to allow the flow of water and maintenance of soil humidity. These impacts were exacerbated by a planted monoculture of eucalyptus that surrounded the palm swamp area. At the end of the 1970s, both the palm swamps and Cerrado were abandoned. As consequence of anthropic impacts suffered over the years, BG was invaded by a single species of Poaceae, rich in biomass, leaving this area vulnerable to constant fires and potential impoverishment of the ecosystem. The palm swamp was gradually but severely degraded, with the disappearance of typical species and the invasion of Cerrado species. As a result, BG palm swamp, which naturally occupied an area of 350 ha, now is restricted to approximately 5% of its original area and no longer shows the characteristics of other palm swamps areas in the region. Water storage happens only at the rainy season, with a flow rate of 207 L/s and a 100% reduction during the dry season [13]. The palm swamps evaluated in this study have shown variation in their conservation condition, mainly in the amount of water and size of vegetation. At AD, water is present year-round, the tree covers


313

Fig. 1 Location of Água Doce (AD), Almescla (AM), São Francisco (SF), Buriti Grosso (BG), Capivara (CP) and Pindaibal (PI) palm swamps areas at the environmental protection area (EPA) of Pandeiros river in Northern Minas Gerais state, Brazil.

dense, with an average height of 25 m, and there are no artificial gutters. There is evidence of cattle and the selective chopping of individual trees. At the AM palm swamp, the occurrence of water is also steady throughout the year and trees are dense and tall (average 30 m), but there is evidence of past fires, ditches and cattle. The palm swamp SF is a private reserve of natural heritage surrounded by fences and protected from anthropic action. In this area, water is present year-round and vegetation at the bottom of the palm swamp reaches an average height of 25 m. At BG palm swamp area, trees are sparse, with an average height of 8 m, and water is present only at the gutter (water channel) during the rainy season. There is evidence of artificial water drainage across the longitudinal direction of the palm swamp as well as evidence of cattle and fire. At CP, the sparse trees

reach an average height of 15 m, there is no gutter for water flow, and water is stored at the soil surface only during the rainy season. In this area, there are artificial drains, agriculture activity, numerous livestock and records of large fires. At PI palm swamp area, the trees are sparse, with an average height of 15 m. The water channel has water all year, but the livestock and small agriculture, as well as fire damage, are present not only at the grassy stratum in the middle of the palm swamp but also at the arboreal stratum deep inside the palm swamp area. The characterization of soil attributes was performed using composed samples, collected from a layer 0-20 cm deep from the interior of 100 m2 areas (10 m  10 m) that had previously been used for arboreal vegetation sampling [8]. After collection, the soil samples were dried in open air, passed through 2

314


mm sieves and analyzed according to the methodology proposed by Embrapa [14]. Ca and Mg content were determined by atomic absorption spectrophotometry. Potassium (K) was determined by flame photometry and phosphorus (P) by colorimetry. The sum of bases (SB), cation exchange capacity at pH 7 (CECpH7), effective cationic exchange capacity (CECe), base saturation (V%) and aluminum (Al) saturation (m%) were calculated. The pH was determined, and the remaining P (Prem) was analyzed using anionic change resin. A determination of soil organic matter (SOM) was performed using humid oxidation with potassium dichromate in a hot sulfurous environment. The excess dichromate was titrated with a standard ferrous ammonium sulfate solution (Mohr’s salt) according to Embrapa [14]. Granulometric analysis to determine the proportion of sand, silt and clay was performed using the pipette method based on Stokes’ law for the sedimentation of particles with a solution of sodium hexametaphosphate, buffered with sodium carbonate,

for the total dispersion of particles. The data analysis of soil attributes was performed using Statistica 10 software [15], with the generalized linear model (GLM) of ANOVA procedure [16, 17]. The soil chemical attributes were interpreted according to Alvarez et al. [18]. To verify similarities between the six palm swamps evaluated areas, sensitivity analysis with R were used [19].

3. Results and Discussion The soil chemical attributes were different among the evaluated areas, but the soil texture was similar (Table 1). Regarding the classification of the soil attributes (Figs. 2a-2m), according to Alvarez et al. [18], the AD palm swamp presented lower rates of pH, Al, H + Al and m (Figs. 2a-2c and 2j) and highest rates of Ca, SB, CECe, CECpH7, V% and SOM (Figs. 2e, 2h, 2i, 2k-2m), compared to the other palm swamps soils studied. The higher soil fertility at AD palm swamp may be attributed to the raw material composed to calcareous rock outcroppings upstream of this area that contribute

Table 1 Soil chemical and physical attributes (mean and standard deviation) at Água Doce (AD), Almescla (AM), Buriti Grosso (BG), Capivara (CP), Pindaibal (PI) and São Francisco (SF) the palm swamps areas located at the environmental protection area (EPA) of Pandeiros river in Northern Minas Gerais state, Brazil.. Palm swamps AD AM BG CP PI SF pH 6.77 ± 0.043 5.33 ± 0.043 4.93 ± 0.043 4.96 ± 0.043 6.27 ± 0.043 5.70 ± 0.043 P 15.92 ± 1.156 2.63 ± 1.162 10.74 ±1.162 37.88 ± 1.162 17.67 ±1.162 6.75 ± 1.162 Prem 33.67 ± 0.695 18.81 ± 0.698 24.52 ± 0.698 14.3 ± 0.698 26.49 ± 0.698 32.51 ± 0.698 K 143.44 ± 7.664 148.99 ± 7.703 19.14 ± 7.703 20.32 ± 7.703 58.06 ± 7.703 69.20 ± 7.703 Ca 14.2 ± 0.293 4.33 ± 0.294 0.57 ± 0.294 0.81 ± 0.294 6.06 ± 0.294 5.24 ± 0.294 Mg 1.82 ± 0.068 1.25 ± 0.068 0.28 ± 0.068 0.41 ± 0.068 2.47 ± 0.068 1.21 ± 0.068 Al 0.01 ± 0.105 0.52 ± 0.105 1.92 ± 0.105 1.27 ± 0.105 0.10 ± 0.105 0.12 ± 0.105 H + Al 1.38 ± 0.334 6.82 ± 0.336 11.5 ± 0.336 9.70 ± 0.336 4.26 ± 0.336 3.48 ± 0.336 SB 16.289 ± 0.343 5.97 ± 0.345 0.9 ± 0.345 1.26 ± 0.345 8.68 ± 0.345 6.63 ± 0.345 CECe 16.29 ± 0.346 6.49 ± 0.348 2.82 ± 0.348 2.53 ± 0.348 8.77 ± 0.348 6.75 ± 0.348 m% 0.03 ± 1.512 13.09 ± 1.520 62.08 ± 1.520 51.18 ± 1.520 1.96 ± 1.520 3.36 ± 1.520 CECpH7 17.67 ± 0.427 12.79 ± 0.429 12.4 ± 0.429 10.96 ± 0.429 12.94 ± 0.429 10.11 ± 0.429 V% 91.49 ± 1.402 45.1 ± 1.409 9.59 ± 1.409 11.96 ± 1.409 67.30 ± 1.409 63.46 ± 1.409 SOM 14.86 ± 0.317 12.2 ± 0.319 11.32 ± 0.319 10.65 ± 0.319 11.42 ± 0.319 9.24 ± 0.319 Sand 85.48 ± 1.13 78.73 ± 1.197 81.33 ± 1.196 76.59 ± 1.197 77.92 ± 1.197 79.39 ± 1.197 Silt 8.54 ± 0.446 11.52 ± 0.448 10.66 ± 0.448 8.75 ± 0.448 11.98 ± 0.448 10.75 ± 0.448 Clay 5.98 ± 0.327 9.76 ± 0.329 6.87 ± 0.329 14.67 ± 0.329 10.10 ± 0.329 9.86 ± 0.329 Prem: remaining P; H + Al: potential acidity; SB: sum of bases; CECe: effective cationic exchange capacity; m%: Al saturation; CECpH7: cation exchange capacity at pH 7; V%: base saturation; SOM: soil organic matter. Attributes

3155

Soil Attribute es in Anthrop pized Hygrophilous Forestt in Northern Minas Gerais s State, Braziil

(a)

pH

(b)

Al 4 3 2 1 0

4 2 0 AD

AM

BG

CP

PI

SF

AD

A AM

(c)

H + Al 4 3 2 1 0

BG

CP

PI

S SF

(d)

P 4 3 2 1 0

AD

AM

BG

CP

PI

SF

AD

A AM

(e)

Ca 4 3 2 1 0

BG

CP

PI

SF

(f)

Mg 4 3 2 1 0

AD

AM

BG

CP

PI

AD

SF

A AM

(g)

K 4 3 2 1 0

BG

CP

PI

SF

(h)

SB 4 3 2 1 0

AD

AM

BG

CP

PI

AD

SF

A AM

(i)

C CECpH7 4 3 2 1 0

BG

CP

PI

SF

(j)

m% 4 3 2 1

AD

AM

BG

CP

PI

SF

0 AD

AM

BG

CP

PI

SF

316

Soil Attribute es in Anthrop pized Hygrophilous Forestt in Northern Minas Gerais s State, Braziil

(k)

CECe 4 3 2 1 0

(l)

V% 4 3 2 1 0

AD

AM

BG

CP

PI

SF

AD

A AM

BG

CP

PI

SF

(m)

SOM 4 3 2 1 0 AD

AM

BG

CP

PI

SF

Fig. 2 Soil attribute a classiification (1: low w; 2: medium; 3: high; 4: veery high) at AD, A AM, BG, C CP, PI and SF palm swampss areas located at EPA of Pan ndeiros river in n Northern Miinas Gerais sta ate, Brazil.

to nutrient rates and acidity neuutralization. This explains thee higher prodduction of aerrial phytomasss at this palm sw wamp area, ass observed byy Nunes et al. [5]. Accordinng to the survvey of regennerating stratta of vegetation published p byy Ávila et al. a [20], the AD palm swam mp showed the highesst richness and abundance compared c to the other stuudied areas. This T higher biom mass producction can be b attributedd to natural soill fertility. In contrast, vegetation may m have contribbuted to highher values of CECe and SOM S in this palm m swamp (Figs. 2k and 2m). Moreoover, areas with higher h soil feertility are thhose that preesent higher denssity, richnesss and abunddance of veggetal species. In contrasst to the palm m swamps off AD and SF,, the remaining palm swam mps did nott contain roocky outcroppings, which cann reduce soil fertility. Beyyond the differentiation of soource materiaal, the lower soil fertility at the remainiing palm sw wamps mayy be attributed to hydric erosion resulting from f deforestationn of the surroounding areass. At BG, CP and PI palm sw wamps, laminnar and grooove erosion were w visible and contributed c significantly to t the removaal of the most feertile soil layyers. In soilss of BG andd CP palm swampps these resullts were confiirmed by low w SB,

Ce and V (%) rates (Figs. 2h, 2k and 2l) that makess CEC estaablishment of large vvegetation difficult d andd con nsequently leaads to a loweer contributio on of residuall veg getation in thee soil [9]. The T attributess related to soil quality arre influencedd by land use annd soil mannagement, mainly m at thee surfface layers [21]. [ Neves [13] reported d that in thee 198 80s, native vegetation v aat BG, PI and a CP wass repllaced by a monocultuure of ricee, and thee surrrounding veggetation wass replaced by y eucalyptuss plan ntations. Nunnes et al. [55] and Ávilaa et al. [20]] observed in phhytosociologiical analysiss at the sixx stud died palm swamps that AD shows the highestt rich hness, abunddance and bbase area, both b in thee arbo oreal strata and a the regenerating stratu um comparedd to BG, B CP and PI P palm swam mps. Therefo ore, reductionn in vegetal v biom mass may be attributed, among a otherr facttors, to excessive land usee, given that in i these areass, the anthropic prrocesses are reflected in the analysiss (Taable 1) and in regional recoords. Erosion E resullting from uuse and han ndling at thee neig ghboring areas certainly contributes negatively n too soill fertility andd vegetation eestablishmentt. The greaterr veg getation obserrved at AM aand SF over BG, CP andd PI palm p swampss probably occcurs due to the adequatee


317

In contrast, according to the soil chemical analysis, AD, AM and SF palm swamps are in good conservation condition (Table 1). These data explain the values acquired through surveys of vegetation made at these six palm swamps areas [5, 20] which showed high values of richness, abundance and base area, among other parameters, both at the arboreal strata and on the regenerating stratum, when compared to the results BG, CP and PI palm swamps areas. Using the similarity or dissimilarity between areas, a dendrogram was constructed from the soil attribute means at the six palm swamps areas, which demonstrates clustering into three different groups. The most impacted palm swamps areas, BG and CP formed a distinct group that distanced itself from the others. PI and SF formed a second group, and AD and AM, the most preserved palm swamps areas, formed the third group (Fig. 3). By comparing the observations of these areas with the results shown here, it may be inferred that the aggregation used to form these groups confirms the current condition of these palm swamps areas. These results are in agreement with those by Araújo et al. [24] in studies made in other palm swamps areas, where similarity was evaluated using soil edaphic characteristics.

land use and soil management in surrounding areas (considered palm swamps recharge areas) as well as their current conservation condition despite long periods of intensive soil use [13]. In the current study, the palm swamp of PI exhibits greater soil fertility recovery (SB, CECe and V (%)) when compared to the BG and CP palm swamps (Figs. 2h, 2i and 2l). These results can be attributed to small portions of these palm swamps are still in good conservation condition; some sampled areas of PI were highly impacted but others are preserved. At the palm swamps of BG and CP, degradation processes are observed across the entire palm swamp. Vegetal community structure is directly related to habitat physical characteristics, and variations at the substrate mainly humidity, fertility and topography influence the distribution of arboreal species [22]. Locations with higher soil nutrient rates shelter vegetation with higher base area, density and species relative dominance [1]. The lower soil fertility caused by erosive processes contributes to a reduced cover of native vegetation, as identified at BG, CP and part of PI palm swamps. The lowering of the water table, aggravated by anthropization in humid areas, provides conditions for the invasion of Cerrado colonizer woody species [23].

200

Escores

150

100

50 AD 0

BG

CP

PI

AM

SF

Fig. 3 Similarity dendrogram constructed from the means of soil attributes, evaluated at AD, AM, SF, BG, CP and PI palm swamps areas located at EPA of Pandeiros river in Northern Minas Gerais state, Brazil.

318


The palm swamps areas of BG and CP are highly degraded, not only in the presence of vegetal species and visual characteristics but also in relation to soil chemical and physical analysis (Table 1). The second group, which shows a close relationship between the palm swamps PI and SF, may have occurred due to sampling at PI. This area contains both highly preserved territory and highly impacted land such as corn, sugar cane and bean plantations throughout the palm swamp. Therefore, the grouping of palm swamps by PI, which is, on average, considered degraded, with SF, a well-preserved palm swamp, may be due to sampled portions that were better preserved than average PI area. In other words, samples from less impacted areas of PI may have had a greater influence on the dendrogram, since SF is better preserved than PI (local observations), which is still dominated by subsistence agriculture over large area after the abandonment of monoculture and shows evidence of degradation. The grouping of AD and AM palm swamps may be justified by their preservation condition, as both are highly developed arboreal strata that are adapted to hydric saturation as provide habitat for the palm trees Mauritia flexuosa L. f. and Mauritiella armata (Mart.) Burret, typical species of these environments. Soil nutrients and organic matter rates are similar in both palm swamps, indicating common conservation conditions.

4. Conclusions Buriti Grosso and Capivara palm swamps areas that suffered higher anthropic interventions showed reduction in soil fertility. The formation of three similarity groups gives evidence that soil fertility at the surface layer in the evaluated palm swamps is a consequence of the soil raw material, land use and soil management that have occurred for decades in the studied region.

Acknowledgments This work is part of the post-doctoral studies of the

first author. The authors express their thanks to FAPEMIG (BIPDT: APQ-00227-16; PPM: APQ-00623-16 and PPP: APQ-00468-15) and CNPq/PELD (CNPq 441440/2016-9).

References [1]

Haridasan, M. 2000. “Mineral Nutrition of Native Plants of Cerrado.” Revista Brasileira de Fisiologia Vegetal 1: 54-64. (in Portuguese) [2] Oliveira, O. S., and Marquis, R. J. 2002. The Cerrados of Brazil: Ecology and Natural History of a Neotropical Savanna. New York: Columbia University Press. [3] Eiten, G. 1972. “The Cerrado Vegetation of Brazil.” The Botanical Review 38 (2): 201-341. [4] Vendrame, P. R. S., Brito, O. R., Guimares, M. F., Martins, D. S., and Becquer, T. 2010. “Fertility and Acidity Status of Latossolos (Oxisols) under Pasture in the Brazilian Cerrado.” Academia Brasileira de Ciências 4: 1085-94. [5] Nunes, Y. R. F., Bahia, T. O., Ávila, M. A., Veloso, M. D. M., and Santos, R. M. 2015. “Floristic and Phytosociology of the Veredas Tree Communities: A Case Study in Northern Minas Gerais, Brazil.” In Phytosociology of Brazil: Methods and Case Studies, edited by Elsenlohr, P. V., Fagg, C. W., Melo, M. M. R. F., Andrade, J. A., and Meira Neto, J. A. A. Viçosa: Editora Viçosa, 264-87. (in Portuguese) [6] Boaventura, R. S. 2007. Veredas: Cradle of Waters. Belo Horizonte: Ecodinâmica. (in Portuguese) [7] Tubelis, D. P. 2009. “Veredas and Their Use by Birds in the Cerrado, South América: A Review.” Biota Neotropica 3: 363-74. [8] Bahia, T. O., Luz, G. R., Veloso, M. D. M., Nunes, Y. R. F., Neves, W. V., Braga, L. L., and Lima, P. C. V. 2009. Veredas in the APA of Rio Pandeiros: Importance, Environmental Impacts and Perspectives. MG. Biota. Belo Horizonte: Insituto Estadual de Florestas, 4-13. (in Portuguese) [9] Santos, A. C., and Salcedo, I. H. 2010. “Fertility in the Várzea and Topo Areas due to the Use of the Soil and the Position of the Relief.” Revista de Biologia e Ciências da Terra 2: 83-90. (in Portuguese) [10] Galvão, S. R. S., Salcedo, I. H., and Santos, A. C. 2005. “Carbon and Nitrogen Fractions as a Function of Texture, Relief and Soil Use in the Agave Microbasin in Vaca Brava (PB).” Revista Brasileira de Ciência do Solo 4: 955-62. (in Portuguese) [11] Carvalho, J. L. N., Cerri, C. E. P., Cerri, C. C., Feigl, B. J., Piccolo, M. C., Godinho, V. P., and Herpin, U. 2007. “Changes of Chemical Properties in an Oxisol after


[12]

[13]

[14]

[15] [16]

[17] [18]

[19]

Clearing of Native Cerrado Vegetation for Agricultural Use in Vilhena, Rondonia State, Brazil.” Soil and Tillage Research 96: 95-102. Perin, E., Ceretta, C. A., and Klamt, E. 2003. “Time of Agricultural Use and Chemical Properties of Two Latosols of the Middle Plateau of Rio Grande do Sul.” Revista Brasileira de Ciência do Solo 27: 665-74. (in Portuguese) Neves, W. V. 2011. “Evaluation of the Flow in Watersheds with Veredas in Different Stages of Conservation in the APA of Rio Pandeiros—MG.” Dissertation, Federal University of Minas Gerais. (in Portuguese) Embrapa. 1997. Manual of Soil Analysis Methods, 2nd editon. National Soil Research Center, Rio de Janeiro, 212. (In Portuguese) Statsoft. 2011. Statistica (data analysis software system). V. 10. www.statsoft.com. Nelder, J. A., and Wedderburn, W. M. 1972. “Generalized Linear Models.” Journal of the Royal Statistical Society 135 (3): 370-84. Zar, J. H. 1996. Biostatistical Analysis. New Jersey: Prentice-Hall, Englewood Cliffs. Alvarez, V. H., Novais, R. F., Barros, N. F., Cantarutti, R. B., and Lopes, A. S. 1999. “Interpretation of Soil Analysis Results.” In Recommendations for the Use of Correctives and Fertilizers in Minas Gerais. Ribeiro, A. C., Guimarães, P. T. G., and Alvarez, V. H. (eds.) Viçosa, 25-32. (in Portuguese) Husson, F., Sebastien, L., Cadoret, M., and Mine, R. S. 2012. “Sensory Data Analysis with R.” R package v. 1.20.

[20]

[21]

[22]

[23]

[24]

319

Accessed October 12, 2017. https://CRAN.R-project.org/ pakage=SensoMineR. Ávila, M. A., Souza, S. R., Veloso, M. D. M., Santos, R. M., Fernandes, L. A., and Nunes, Y. R. F. 2016. “Structure of Natural Regeneration in Relation to Soil Properties and Disturbance in Two Swamp Forests.” Cerne 1: 1-10. Negreiros, D., Fernandes, G. W., Berbara, R. L. L., Rodarte, L. H. O., and Ulhôa, N. P. 2012. “Physicochemical Characterization of Quartzitic Degraded Soils and Adjacent Areas of Rupestrian Fields, Serra do Cipó, MG, Brazil.” Neotropical Biology and Conservation 3: 156-61. Oliveira-Filho, A. T., Vilela, E. A., Carvalho, D. A., and Gavilanes, M. L. 1994. “Effects of Soils and Topography on the Distribution of Tree Species in a Tropical Riverine Forest in South-Eastern Brazil.” Journal of Tropical Ecology 10: 483-508. Meirelles, M. L., Oliveira, R. C., Vivaldi, L. J., Santos, A. R., and Correia, J. R. 2002. “Species of the Herbaceous Stratum and Depth of the Water Table in Humid Areas of the Cerrado.” Research and Development Bulletin. Planaltina: Embrapa Cerrados. Accessed November 15, 2017. https://www.infoteca.cnptia.embrapa.br/bitstream/ doc/548509/1/bolpd25.pdf. (in Portuguese) Araújo, G. M., Barbosa, A. A. A., Arantes, A. A., and Amaral, A. F. 2002. “Floristic Composition of Trails in the City of Uberlândia, MG.” Revista Brasileira de Botânica 4: 475-93. (in Portuguese)


D

DAVID

PUBLISHING

Effect of Browsing on the Growth of Jojoba Seedlings in the Dry-Lands of Kenya Shadrack Kinyua Inoti Egerton University, PO Box 536-20115, Egerton 20115, Kenya Abstract: Jojoba is a desert shrub, introduced in the marginal areas of Kenya during 1980s. Jojoba domestication is being faced by browsing problems due to pastoralism in these areas. Massive browsing of leaves lowers photosynthesis leading to decline in plant functions. An experiment was set up in Maungu, with the aim of determining the effect of browsing on jojoba seedlings. The experimental design was a randomized complete block design with three treatments replicated three times. The treatments consisted of varying levels of browsing as follows: non browsed, 50% browsed and fully browsed. Seedlings were raised for six months before sampling. Variables assessed were: survival, height, root-collar diameter, leaf size, root length and number, internode length, sprout number, root/shoot ratio and total biomass. ANOVA was performed to determine differences among the treatments whilst significant differences among the means were separated using least significant difference (LSD) at p ≤ 0.05. Results showed fully browsed seedlings were significantly lower in height (26.2 cm), internode length (9.7 mm), leaf length (18.3 mm) and width (10.4 mm) and total fresh plant biomass (11.0 g) compared to the non browsed ones which showed 31.1 cm, 23.2, 36.1 and 16.6 mm and 17.8 g, respectively. On the other hand, fully browsed seedlings showed significantly higher root/shoot ratio. Seedling growth was negatively affected by severity of browsing which resulted in stunted growth. The study recommended that browsing of seedlings should be prevented since it hinders plant growth. Key words: Browsing level, growth, jojoba, tree seedling.

1. Introduction Over 80% of Kenya is composed of arid and semi arid lands (ASALs) with only a few crops being grown mainly for subsistence purposes [1]. They experience frequent drought leading to crop failure hence overdependence on food relief [2]. These ASALs are fragile ecosystems with their productivity being threatened by various factors such as overgrazing, deforestation, land degradation and harsh climate [3, 4]. Jojoba domestication is being faced by problems of browsing from both livestock and wildlife which are the major activities in the ASALs. Increasing human population has resulted to migration into fragile marginal lands causing higher livestock stocking triggering severe land degradation [5]. Jojoba (Simmondsia chinensis L. Schn.) is a high Corresponding author: Shadrack Kinyua Inoti, Ph.D., research fields: agroforestry, forest biology and arid land forestry.

value shrub growing in the arid areas [6] and it is a promising cash crop for the arid-lands throughout the world. It grows on coarse, light and medium textured well drained sandy soils with marginal fertility and acidic to alkaline pH of 5-8 [7]. It tolerates low rainfall (220-400 mm/year) and high temperature range (0-54 °C). Jojoba produces nuts with 45%-55% of its weight as oil. It has varied uses ranging from edible oils, lubricants, cosmetics and medicines [8, 9]. Browsing of tree seedlings by wildlife can reduce height growth, stem and foliage density resulting to a more open understory [10]. Recent studies by Foster [11] described that defoliation of trees by herbivores as a biological disturbance that reduces the leaf area and causes the trees to change their growth patterns and produce defense chemicals [12] as a survival strategy. However, faster growing species have significant reduction in carbohydrate concentration due to browsing followed by relatively faster recovery

Effect of Browsing on the Growth of Jojoba Seedlings in the Dry-Lands of Kenya

[13]. Mature jojoba bushes are frequently stunted to a low height of up to 1 m due to the harshness of climate and browsing by wildlife and livestock [14], although they can attain up to 2 m in height. However, during the wet season, other fodder species are available for browsers hence minimal damage occurs in jojoba. The objective of the study was to determine the effect of browsing on the growth of jojoba seedlings in dry-lands.

2. Materials and Methods 2.1 Study Site The trial was set up in Voi, Kenya, where jojoba bushes are established, along longitude 37°40′60″ to 38°35′25″ E and latitude 3°23′60″ to 3°24′26″ S at an altitude of 892 m above the sea level [15]. The area is located in semi arid environment characterized by wooded scattered trees, shrubs and grasses with pastoralism and wildlife as the major activity. A bimodal rainfall distribution of 596 mm annually is received. Temperatures range from 16 °C to 37 °C with an average of 26 °C and moderate high humidity (60%-80%) [16]. However, the area has frequent droughts due to climate change leading to dependence on famine relief food. 2.2 Experimental Design The nursery experiment was laid down in a randomized complete block design with three treatments replicated three times. The treatments consisted of jojoba seedlings at varying levels of browsing as follows: non browsed, 50% browsed and fully browsed. Seedlings were raised for a period of six months from January to June 2013 and treatments were introduced at three months growth. Seedlings were raised in medium sized pots of 12.5 cm width and 20 cm length. The potting media was sand and farmyard manure in the ratio 2:1, respectively. Each replicate consisted of three rows with 10 plants.

321

2.3 Data Collection Six month old jojoba seedlings were sampled after treatment application for a period of three months. Three plants were then sampled per row. Variables assessed were: survival, plant height, root collar diameter, leaf size, root length and number, internode length, number of sprouts, root to shoot ratio and total fresh plant biomass. 2.4 Data Analysis ANOVA was performed using SAS [17] to determine differences among the treatments. The significant differences among the means of variables were separated using least significant difference (LSD) at p ≤ 0.05.

3. Results and Discussion 3.1 Effect of Browsing on Survival and Shoot Growth of Jojoba Seedlings Shoot growth of jojoba seedlings was severely affected by browsing leading to stunted growth. Results of the current study showed that fully browsed seedlings were significantly (p ≤ 0.05) lower in plant height (26.2 cm), internode length (9.7 mm) and total fresh plant biomass (11.0 g) compared to the non browsed ones which showed 31.1 cm, 23.2 mm and 17.8 g, respectively (Table 1). The findings are consistent with earlier studies by Gill and Beardall [10] who reported that browsing of tree seedlings by wildlife tend to limit height growth, reduce stem and foliage density resulting to a more open understory. Mature jojoba bushes are frequently stunted to a height of 60 cm to 90 cm by the harshness of climate and also heavy browsing by wildlife and livestock due to their high palatability and nutritive value [14], although they can attain up to 2 m in height [7]. According to Refs. [8, 10, 18, 19], browsing reduces lower branching and abundance of species but does not affect stem diameter. However, Horsley et al. [20] reported

322

Table 1


Effect of browsing level on survival and shoot growth of jojoba seedlings.

Browsing level

Survival (%)

Plant height (cm)

Non browsed 50% browsed Fully browsed CV LSD

66.7 60.0 63.3 40.8 58.5

31.1a 28.2ab 26.2b 5.9 3.8

Internode length (mm) 23.2a 15.6ab 9.7b 23.1 8.5

Number of sprouts 1.2b 3.7b 12.5a 28.1 3.7

Total fresh plant biomass (g) 17.8a 13.6b 11.0b 9.7 3.1

Means with similar letters in each column are not significantly different using least significant difference (LSD) at p ≤ 0.05.

that browsing resulted to shorter heights and thinner diameters. Similarly, fully browsed seedlings showed 1.6 times lower total fresh plant biomass compared to non browsed seedlings. This shows that the former seedlings depicted stunted shoot growth. This corroborates with findings by Rooney and Waller [21] who reported that defoliation and leaf height reduced relative growth rate over short time periods. Work by Li et al. [22] observed that the leaf edge removal resulted in significantly reducing the total plant and root biomass. Previous results by Ferraro and Oesterheld [23] reported negative effect of defoliation on plant growth and variability in the defoliation responses of different plant components. There was also an intermediate negative effect on total production. However, Roundy et al. [24] reported that moderate browsing pressure resulted in forage yields similar to those of non browsed plants which is contradictory to the present study but they further observed that heavy browsing greatly reduced shrub size and forage yield which agrees with this study. Studies by Ives and Nairn [25] found that partial defoliation reduced initial growth in young tamarack (Larix laricina) trees. Intensity of mammalian browsing may modify the magnitude and the direction of tree diversity effects on tree growth and susceptibility to insect herbivory [26, 27]. Unbrowsed trees experienced lower insect chewing damage in mixed stands whilst browsed trees suffered more insect chewing damage in diverse stands. Low levels of persistent insect damage (< 2%) have been shown to reduce birch growth and fitness

[28]. Thus, the effects of browsing on tree growth may be further compounded by increases in background insect herbivore damage. Growth of moderately browsed trees increased with tree species richness, but growth of severely browsed birch trees was unaffected [27]. As browsing intensity increases, both upright and lateral shoots are usually removed resulting to reduced vertical and horizontal growth [29, 30] and thereby reducing the competitive ability of trees. Similarly, severely browsed trees are more likely to suffer from stem breakage by moose, which reduces tree height and hinders growth [31]. These findings are consistent with the findings of the current study despite the fact that the authors considered mature trees as opposed to seedlings in the present study. However, the number of sprouts was significantly (p ≤ 0.05) higher for fully browsed seedlings compared to the non browsed and partially (50%) browsed seedlings and could be explained by compensatory strategy by the severely browsed seedlings through resprouting. This is in agreement with earlier studies by Roundy and Dobrenz [32] who stated that new twigs were initiated from lateral buds to compensate for the loss of apical buds and twigs from herbivory. Similarly, McNaughton [33] reported that lightly defoliated plants may increase sufficiently in biomass through overcompensation to end up larger in mass than non-defoliated controls. Branches in heavily browsed areas usually take longer to grow if the apical meristem has been removed through browsing [34]. Earlier findings by Ferraro and Oesterheld [23]

323


reported that defoliation intensity had no effect on response to defoliation which is contradictory to the present study. Defoliated larch and pine seedlings showed less biomass and starch component than those not defoliated [35]. However, both species showed overcompensation in total and component biomass in seedlings defoliated by 25% but generally defoliation caused about a 50% decrease in whole-seedling starch concentration. Further studies by Atkinson et al. [13] reported that faster growing species showed significant carbohydrate reduction after browsing but this was followed by fast recovery. Rates of photosynthesis on foliage regrowth increased relative to non-defoliated controls [36]. In addition, plant biomass is not necessarily reduced by the same percentage as leaf area [37]. Heavily browsed trees take less energy into somatic growth but instead divert more energy into forming secondary compounds which might be toxic and hence deter herbivory [38, 39]. High stress levels cause the energy of plants to be focused towards stem development but less branch growth [40]. Studies in Northern Michigan by Rudolph and Autenrieth [41] reported that deer population changes with seasons and their population increases alongside with increase in nutrient availability. Trees invest most of their energy into growing leaves towards the top canopy since this portion receives direct sunlight and these leaves are the most efficient in photosynthesis [42]. Trees above the browsing height are able to obtain sufficient nutrients to increase tree girth regardless of browsing [43]. Table 2

3.2 Effect of Browsing on Root and Foliage Growth of Jojoba Seedlings On the other hand, fully browsed seedlings also showed significantly (p ≤ 0.05) lower growth in leaf length (18.3 mm) and width (10.4 mm) compared to non browsed seedlings which were 36.1 mm and 16.6 mm, respectively (Table 2). Seedling growth was negatively correlated with severity of browsing which resulted in short internodes and small leaf sizes. These findings are in agreement with recent studies by Foster [11] and Gruning et al. [12] who stated that defoliation affects tree performance by reducing leaf area leading to low photosynthetic capacity and nitrogen cycling in the forest ecosystem. Fully browsed seedlings showed significantly higher root to shoot ratio and number of lateral roots, although the latter was not significant, compared to non browsed ones. This shows that root growth in terms of length and also number of lateral roots are least affected by browsing and this leads to a significantly higher root to shoot ratio for the browsed seedlings. The findings of the current study corroborate with earlier studies by Ferraro and Oesterheld [23] who reported that defoliation causes minimum effect on root growth especially root biomass. According to Pinoyfarmer [44], jojoba seedlings can attain root length 10 times the shoot height with a growth rate of 2.5 cm per day making them to possess special deep root system adaptation for arid lands. However, further studies by Li et al. [22] reported that

Effect of browsing level on root and leaf growth of jojoba seedlings.

Browsing level Non browsed 50% browsed Fully browsed CV LSD

Root collar diameter (mm) 5.1b 6.0a 5.1b 5.9 0.7

Root length (cm) Number of roots 32.4 33.2 33.8 9.5 7.1

47.4 59.0 64.2 15.5 20.0

Root to shoot ratio 1.03b 1.03b 1.30a 3.0 0.08

Means with similar letters in each column are not significantly different using LSD at p ≤ 0.05.

Leaf length (mm) Leaf width (mm) 36.1a 26.6ab 18.3b 17.2 10.5

16.6a 12.7ab 10.4b 17.7 5.3

324


removal of leaf edges changed the carbon allocation resulting in reduced root development which further hinder nutrient uptake by plants from the soil leading to stunted growth. More recent research by Foster [11] also stated that evergreen trees are more prone to death after defoliation because most of the food storage is in the foliage while deciduous ones store their carbohydrates in the stem and roots.

4. Conclusions Seedling growth was negatively affected by severity of browsing which resulted in lower plant height, short internodes and small leaf sizes leading to stunted growth.

Recommendations The study recommended that browsing of jojoba seedlings should be prevented through fencing since it severely hinders plant growth which can also further slow down field establishment. Further research needs to be carried out to explore the possibilities of replacing the severely browsed seedlings with newly replanted ones since the former take a long time to recover.

[5] [6]

[7]

[8]

[9]

[10]

[11]

[12]

[13]

Acknowledgments The author wishes to sincerely thank Wildlife works for supporting this research in terms of materials and funding and also Egerton University for giving time off to perform the research.

[14]

References [1] [2]

[3]

[4]

KARI. 2009. Kenya Agricultural Research Institute Strategic Plan 2009-2014. Nairobi, Kenya: KARI, 107. Barrow, E. G. C. 1996. The Drylands of Africa: Local Participation in Tree Management. Nairobi, Kenya: Initiative publishers, 268. Weiss, E. 1986. Plants Tolerant of Arid and Semi Arid Conditions: Their Nomenclature and Potential Uses. Ministry of Agriculture and Livestock Development, Nairobi, Kenya. Dixon, J. A., James, E. D., and Sherman, P. B. 1998. The Economics of Dryland Management. Earth Scans

[15]

[16]

[17]

Publications, HD, London, UK. Rowland, J. R. J. 1993. Dryland Farming in Africa. London: MacMillan Press Ltd, 336. National Academy of Sciences (NAS). 1974. More Water for Arid Lands: Promising Technologies and Research Opportunites. National Academy of Sciences, Washington, DC. USA, 165. Undersander, D. J., Oelke, E. A., Kaminski, A. R., Doll, J. D., Putnam, D. H., Combs, S. M., and Hanson, C. V. 1990. Alternative Field Crop Manual. University of Wisconsin-Madison and Minnesota, St. Paul, USA, 48. Hogan, I., and Bemis, W. P. 1983. “Buffalo Gourd and Jojoba: Potential New Crops for Arid Lands.” Advances in Agronomy 36: 317-49. Amarger, V., and Mercier, L. 1996. “Nuclear Ribosomal DNA Unit Length Variation: A Putative Marker of Genetic Diversity in Jojoba.” International Journal of Plant Science 157 (3): 296-302. Gill, R. M. A., and Beardall, V. 2001. “The Impact of Deer on Woodlands: The Effects of Browsing and Seed Dispersal on Vegetation Structure and Composition.” Forestry 74 (3): 209-18. Foster, J. R. 2017. “Xylem Traits, Leaf Longevity and Growth Phenology Predict Growth and Mortality Response to Defoliation in Northern Temperate Forests.” Tree Physiology 37 (9): 1151-65. Gruning, M. M., Simon, J., Rennenberg, H., and I-M-Arnold, A. 2017. “Defoliating Insect Mass Outbreak Affects Soil N Fluxes and Tree N Nutrition in Scots Pine Forests.” Front Plant Sci. 8: 954. Atkinson, R. R. L., Burrel, M. M., Rose, K. E., Osborne, C. P., and Rees, M. 2014. “The Dynamics of Recovery and Growth: How Defoliation Affects Stored Resources.” Proceedings of the Royal Society B: Biological Sciences 281 (1783). doi: 10.1098/rspb.2013.3355. Nord, E. C., and Kadish, A. 1974. “Simmondsia chinensis (Link) C. K. Schneid. Jojoba.” In Seeds of Woody Plants in the United States, edited by Schopmeyer, C. S. Agriculture Handbook No. 450. Washington, DC: U.S. Department of Agriculture, Forest Service, 774-6. Taita Taveta District Strategic Plan (TTDSP). 2008. “Ministry of State for Development of Northern Kenya and Other Arid Lands.” Accessed October 22, 2018. http://erepository.uonbi.ac.ke/bitstream/handle/11295/613 10/Ednah. Thagana, W. M., Riungu, T. C., and Inoti, S. K. 2003. Report on Jojoba (Simmondsia chinensis) Cultivation in Kenya. KARI, Njoro, 10. Statistical Analytical System (SAS). 1996. SAS/STAT 9.2 User’s Guide. Cary N.C.: SAS Institute Inc. Accessed October 22, 2018.


[18]

[19]

[20]

[21]

[22]

[23]

[24]

[25]

[26]

[27]

[28]

[29]

http://support.sas.com/documentation/cdl/en/statugintrod uction/61750/PDF. Garthe, A., Kissel, L., Machcinski, E., and Lau, P. 2014. “The Impact of Deer Browsing on Tree Growth, Plant Biomass and Biodiversity.” Deep Blue. Accessed July 22, 2017. http://deepblue.lib.umich.edu/handle/2027.42. Anderson, R. C. 1994. “Height of White Flowered Trillium (Trillium grandiflorum) as an Index of Deer Browsing Intensity.” Ecological Applications 4 (1): 104-9. Horsley, S. B., Stout, S. L., and DcCalesta, D. S. 2003. “White Tailed Deer Impact on the Vegetation Dynamics of a Northern Forest.” Ecological Applications 13 (1): 98-118. Rooney, T. P., and Waller, D. M. 2001. “How Experimental Defoliation and Leaf Height Affect Growth and Reproduction in Trillium grandiflorum.” Journal of the Torrey Botanical Society 128 (4): 393-9. Li, W., Luo, J., Tian, X., Peng, C., and Zhou, X. 2012. “Patterns of Defoliation and Their Effect on the Plant Growth and Photosynthetic Characteristics of Ipomoea cairica.” Weed Biology and Management 12 (1): 40-6. Ferraro, D. O., and Oesterheld, M. 2002. “Effect of Defoliation on Grass Growth: A Quantitative Review.” Oikos 98 (1): 125-33. Roundy, B. A., Ruyle, G. B., and Dobrenz, A. K. 1987. “Growth, Nutrient, and Water Status of Jojoba (Simmondsia chinensis) in Relation to Livestock Grazing.” In Proceedings of Symposium on Plant-Herbivore Interactions, edited by Provenza, F. D., Flinders, J. T., and McArthur, E. D. Snowbird, UT. Gen. Tech. Rep. INT-222. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Research Station, 146-53. Ives, W. G. H., and Nairn, L. D. 1966. “Effects of Defoliation on Young Upland Tamarack in Manitoba.” Forestry Chronicle 42: 137-42. Cook-Patton, S. C., Laforgia, M., and Parker, J. D. 2014. “Positive Interactions between Herbivores and Plant Diversity Shape Forest Regeneration.” Proceedings of the Royal Society B 281 (1783). doi: 10.1098/rspb.2014.0261. Muiruri, E. W., Milligan, H. T., Morath, S., and Koricheva, J. 2015. “Moose Browsing Alters Tree Diversity Effects on Birch Growth and Insect Herbivory.” Functional Ecology 29: 724-35. Zvereva, E. L., Zverev, V., and Kozlov, M. V. 2012. “Little Strokes Fell Great Oaks: Minor but Chronic Herbivory Substantially Reduces Birch Growth.” Oikos 121: 2036-43. Den Herder, M., Bergstrom, R., Niemela, P., Danell, K., and Lindgren, M. 2009. “Effects of Natural Winter Browsing and Simulated Summer Browsing by Moose on

[30]

[31]

[32]

[33] [34]

[35]

[36]

[37]

[38]

[39]

[40]

[41]

325

Growth and Shoot Biomass of Birch and Its Associated Invertebrate Fauna.” Annales Zoologici Fennici 46: 63-74. Speed, J., Austrheim, G., and Hester, A. 2013. “Regional-Scale Alteration of Clear-Cut Forest Regeneration Caused by Moose Browsing.” Forest Ecology and Management 289: 289-99. Rea, R. 2011. “Impacts of Moose (Alces alces) Browsing on Paper Birch (Betula papyrifera) Morphology and Potential Timber Quality.” Silva Fennica 45: 227-36. Roundy, B. A., and Dobrenz, A. K. 1989. “Herbivory and Plant Water Status of Jojoba (Simmondsia chinensis (Link) Schn.) in the Sonoran Desert in Arizona.” Journal of Arid Environments 16: 283-91. McNaughton, S. J. 1983. “Compensatory Plant Growth as a Response to Herbivory.” Oikos 40: 329-36. Kribel, J. R., Kolman, K. B., and Ware, S. 2011. “Rapid Change in Sapling and Seedling Layers in an Otherwise Stable Hardwood Forest: An Effect of Deer Browsing.” Castanea 76 (2): 140-8. Vanderklein, D. W., and Reich, P. B. 1999. “The Effect of Defoliation Intensity and History on Photosynthesis, Growth and Carbon Reserves of Two Conifers with Contrasting Leaf Lifespans and Growth Habits.” New Phytol. 144: 121-32. Reich, P. B., Walters, M. B., Krause, S. C., Vanderklein, D. W., Raffa, K. F., and Tabone, T. 1993. “Growth, Nutrition and Gas Exchange of Pinus resinosa Following Artificial Defoliation.” Trees 7: 67-77. Bassman, J., Myers, W., Dickman, D., and Wilson, L. 1982. “Effects of Simulated Insect Damage on Early Growth of Nursery-Grown Hybrid Poplars in Northern Wisconsin.” Canadian Journal of Forest Research 12: 1-9. Swain, T. 1977. “Secondary Compounds as Protective Agents.” Annual Review of Plant Physiology 28 (1): 479-501. Robbins, C. T., Hanley, T. A., Hagerman, A. E., Hjeljord, O., Baker, D. L., Schwartz, C. C., and Mautz, W. W. 1987. “Role of Tannins in Defending Plants against Ruminants: Reduction in Protein Availability.” Ecology 68 (1): 98-107. Stoengart, J., Picdade, M. T. F., Ludwigshausen, S., Horna, V., and Worbes, M. 2002. “Phenology and Stem Growth Periodicity of Tree Species in Amazonian Flood Plain Forests.” Journal of Tropical Ecology 18 (4): 581-97. Rudolph, B., and Autenrieth, A. 2013. “Michigan Deer Hunting Prospects.” Michigan Department of Natural Resources. Accessed September 9, 2017. http://www.michigan.gov/documents/dnr/deer hunting prospects 4358577.pdf.

326


[42] Terjung, W. H., and Louie, S. S. 1973. “Energy Budget and Photosynthesis of Canopy Leaves.” Annals of the Association of American Geographers 63 (1): 109-18. [43] Hartnett, D. C., Ott, J. P., Sebes, K., and Ditlhogo, M. K. 2012. “Coping with Herbivory at the Juvenile Stage: Response to Defoliation and Stem Browsing in the Africa

Savanna Tree Colophospermum mopane.” Journal of Tropical Ecology 28 (2): 161-9. [44] Pinoyfarmer. 2007. “Jojoba: A Promising New Crop for Arid Lands and New Raw Materials for Industry.” Accessed October 22, 2018. http://www.researchgate.net/profile/Arvin-Singh56/post.


D

DAVID

PUBLISHING

Fortification of Pasta Using Different Plant Sources R. Saraswathi and R. Sahul Hameed Department of Home Science, the Gandhigram Rural Institute (Deemed to be University), Dindigul 624 302, India Abstract: Nowadays food industries are focused on two major factors for health and convenience during the development of breakfast food and variety of snack products, because consumers have sparked the development of convenient and nutritious food products. Pasta is one of the easiest and most versatile food products consumed today. Pasta usually made from durum semolina which is hard grain wheat flour that is high in protein but lack of other nutrients such as vitamins, minerals and fibre. Recently, pasta products has developed into improve the nutritional quality by the addition of other ingredients like pulses, vegetable and fruit extracts which is help to get the nutritional well being of the consumers. One of the solutions for this is the incorporation of millet flour, pulse flour and plantain flour which were addition or replacement of durum wheat semolina to formulate healthy pasta. Hence the objective of study was aimed to develop multigrain nutrient dense pasta products prepared from composite mixture such as durum semolina, millets (barnyard millet (Echinochloa utilis), kodo millet (Paspalum setaceum) and little millet (Panicum sumatrense), pulses (peas (Pisum sativum L.) and lentil (Lens culinaris)) and vegetable (plantain flours (Musa paradisiaca)) at different proportions. It contains durum semolina flour, millet and pulse blend flour (millet flour blends (flours of barnyard millet, kodo millet, little millet mixed at ratio 1:1:1) and pulse flour blends (flours of peas and lentil mixed at ratio 1:1) both millet and pulse blends were mixed at ratio 1:1) and plantain flour. All the three flours samples were mixed at 70:15:15 percent for formulae 1, 55:30:15 percent for formulae 2 and 40:45:15 percent for formulae 3. Durum semolina (100%) was used as control. For 15% of plantain flour addition to millet pulse blend flour increase the nutritional content of flour due to which is more fiber content. Then composite mixture of formulae and control were analyzed the nutritional properties of such as moisture (%), energy (kcal), carbohydrate (g), protein (g), fat (g), crude fibre (g), ash (%) and minerals content were evaluated by standard procedures. Further pasta developed from composite mixtures of formulae and assessed its shelf life were also evaluated. The results showed that the composite flours of moisture content (7.8% to 8.2%), energy (363.3 kcal to 365.6 kcal), carbohydrate (78.4 g to 81.3 g), protein (9.4 g to 11.7 g), fat (0.1 g to 0.3 g), ash (0.72% to 1.38%) and crude fiber content (7.88 g to 14.06 g). These findings revealed that composite flour formulae of protein, ash, crude fiber content and calcium, iron, copper, zinc content were higher than control. While manganese content of all composite mixture and formulae 2 of calcium content was also lower than control. Therefore, three composite mixtures of formulae could be used to produce good quality of pasta products. Among the composite mixture, formulae1 was high score (8.81) in overall acceptability. During storage period, composite mixture of all formulae nutrients content and also sensory parameters were slightly decreased. Even though, multigrain food products that provide to improve good health and other beneficial effect but also have good taste, extended shelf life and appealing colour and are also economically feasible for all grades of population. Key words: Composite flour, millet pulse blend flour, nutritional properties, pasta sensory attribute and shelf life.

1. Introduction Wide spread of malnutrition and associated health problems around the world has put up pressure on food industries to develop food products with high nutritional properties, health benefits and novelty to consumers. Dietary based approaches should be taken into consideration while addressing deep-rooted Corresponding author: R. Saraswathi, Ph.D. student, research field: food processing.

problems like malnutrition and nutritional insecurity. Pasta is one of the versatile food products liked by the consumers of all age groups, because of its convenience in preparation and serving it. Pasta products, traditionally manufactured from durum wheat semolina, known to be the best raw material suitable for pasta production. Pasta contains 74%-77% of carbohydrates and 11%-15% of proteins [1]. Although pasta plays an integral role in regular diet, but poor nutritional value (lack of vitamins, minerals and

328

Fortification of Pasta Using Different Plant Sources

fibre) of these products may lead into nutritional deficiencies on daily consumption. Researchers have been studying the possibility of improving the nutritional quality of pasta products by adding other ingredients like vegetable and fruit extracts and claiming that it may help in attaining nutritional well-being of the consumers which is a sustainable force for health and development and maximization of human genetic potential [2]. This provides an opportunity for the use of non-traditional raw materials to increase the nutritional quality of pasta. Among these non-traditional raw materials as millet, legumes represent an interesting source of proteins, fibres, vitamins and minerals [3]. Though millets have high nutritious than other cereals, even millet utilization is not considerably flourished, their utilization can be increased by a way that directs to blend them with wheat flour [4]. Millet contains nearly 15% of protein, high amounts of fiber, B-complex vitamins including niacin, thiamin and riboflavin, folic acid, the essential amino acid as methionine, lecithin and some vitamin E. Furthermore, millets are rich source of minerals such as iron, magnesium, calcium, phosphorous, manganese and potassium. The seeds are also rich in phytochemicals, including phytic acid, believed to lower cholesterol and phytate, which is associated with reduced cancer. Millet is more than just an interesting alternative to the more common grains [5]. Additionally they also have nutraceutical properties and provide health benefits like tumor incidence reduction, cardiovascular disease, low blood pressure, cholesterol problem, fat absorption rate, heart disease, gastric problems and also gastro-intestinal bulk supply [6, 7]. Some studies were carried out that persons who consumed millet diet were found to have considerably decreased blood glucose levels [8]. Research says that millet crop proteins have high amounts of amino acids in comparison to other cereals but has less lysine and threonine content whereas methionine is relatively in higher amounts [2, 9]. Adding exogenous ingredients

rich in protein is an ideal way to get higher biological value and a better amino acid pattern. Legumes are important crops because of their nutritional quality. Pulses are rich in amino acid like lysine [10]. While pulses are deficient in methionine, but cereals are rich in methionine and deficient in lysine [11]. So when pulses are combined with cereals (a source of the amino acid like methionine), it provides the balanced protein necessary for growth [12]. Therefore, addition of pulses flour to cereal based products could be a good option to overcome the world protein calorie malnutrition problem, because pulses contain approximately three times more proteins than cereals [13]. In addition to that pulses are rich in complex carbohydrates, vitamins and minerals [14]. Consequently, legumes and cereals are nutritionally complementary food [15]. Addition with plantain (Musa paradisiaca) constitutes a rich energy source with carbohydrate content of 32% and also rich in vitamins A, B1, B2, B3, B6, C, dietary fibre, iron, potassium, calcium, magnesium and sulfur [16]. Recent developments in pasta products include attempts to improve the nutritional properties of pasta by the addition of supplements from various natural sources. Plantain can be very cheap to buy and important food for low income families. Therefore new economical strategy is to increase the consumptions of plantain into flour. The production of plantain flour incorporate into various innovative products such as weaning and extruded food products, it is means of value added foods and it’s extend the shelf life of derived foods. Hence the plantain (unripe banana) flour is used for the food industry, mainly in bakery products, dietary products and infant foods [17]. For that reason addition of 15% plantain flour to composite flour, the product can be claimed to be functional pasta products due to the fiber and resistant starch content of the final product. Therefore the objective of the study was aimed to determine the nutritional properties of control and composite mixture such as


329

durum semolina, millets (barnyard millet (Echinochloa utilis), kodo millet (Paspalum setaceum) and little millet (Panicum sumatrense)), pulses (peas (Pisum sativum L.) and lentil (Lens culinaris)) and vegetable (plantain flours (Musa paradisiaca)) at different proportions. Durum semolina (100%) was used as control. Then formulated nutrient dense pasta products prepared from composite mixtures and studied shelf life of pasta products were evaluated by standard procedures. Thus whole grain food is good but multigrain blends helps to maximize their nutritional, functional and sensory properties. This could be utilized for the development of composite blends from locally produced millet, pulses and plantain at small scale industry level as value-added products.

(40 µm). Then, the flours were stored in air tight

2. Materials and Methods

which were subsequently defingered (each plantain

2.1 Raw Materials

fingers were washed, peeled, cut into three or four

Durum wheat semolina (Triticum turgidum L. var. durum), plantain (Musa paradisiaca) were purchased from local market, Mysore, Karnataka, India and millets such as kodo millet (Paspalum setaceum), barnyard millet (Echinochloa utilis) and little millet (Panicum sumatrense) and pulses such as peas (dry) (Pisum sativum L.) and lentil (Lens culinaris) were purchased from Bombay Traders, Madurai, Tamil Nadu, India. The experiments were conducted in Food Lab, Central Food Technology Research Institute (CFTRI), Mysore, Karnataka, India. Chemicals used for the experiments were of analytical grade.

pieces which were blanched for 5 min. Then they

2.2 Preparation of Raw Materials Durum wheat semolina, millets (kodo millet, barnyard millet and little millet) and pulses (peas and lentil) were cleaned by manual winnowing and passed on to laboratory hammer mill to produce flours. The flours were sieved using 80 mm BS sieve (TP series, 38 µm-125 mm and Test sieve) and packed in high-density polyethylene (HDPE) bags

containers at refrigeration temperature (4 C) until further use. 2.2.1 Preparation of Millets Flour Blend Millet flour blend was prepared by mixing kodo millet, barnyard millet and little millet flours at equal proportions (ratio 1:1:1, respectively). 2.2.2 Preparation of Pulses Flour Blend Pulse flour blend was prepared by mixing the pea and lentil flours at ratio 1:1. 2.2.3 Preparation of Millet and Pulses Flour Blend Millet and pulses flour blend was prepared by admixing millet flour blend and pulse flour blend at ratio 1:1. 2.2.4 Preparation of Plantain Flour Plantain heads were separated from bunches from hand into a bowl containing water). The

were sliced into uniform thickness. Sliced plantain pieces were dipped into 0.2% potassium meta bisulphite (KMS) solution for 10 min to prevent enzymatic browning reactions and retain its colour. Plantain slices were dehydrated in a cabinet air drier at 65 °C for 8 h. The dried chips were milled using a hammer mill, sieved the powders (300-400 μm) and packed in HDPE bags (40 µm) until it is needed for product development. 2.3 Preparation of Composite Mixture of Formulae Composite flour prepared by mixing durum wheat semolina, millet & pulse flour blend and plantain flour at ratio 70:15:15, respectively, for formulae 1, ratio 55:30:15 followed for formulae 2 and ratio 40:45:15 for formulae 3 and durum wheat semolina were used as control (Table 1). 2.4 Nutritional Properties of Composite Mixture of Flour Nutritional properties of composite mixture of flour

330

Table 1


Ingredients used for preparation of composite mixture of formulae.

Samples Control Formulae 1 Formulae 2 Formulae 3

Durum wheat semolina (%) 100 70 55 40

Millet & pulses flour blend (%) 15 30 45

such as moisture, fat, protein, ash, carbohydrate, energy and crude fiber were determined by following the standard procedure as described by Ref. [18]. 2.4.1 Estimation of Moisture Content Moisture content of the flour samples was determined by hot air oven (Toplab, Tl-Oven, 2008, Toplab India) for drying method. Two grams of well mixed flour sample was taken in a clean, dried and pre weighed Petri dish. It was then placed in an oven at 130 °C for 1 h. The samples were cooled in a desiccator (Hamco, Chemical Laboratory, 1969, Hindustan Apparatus Mfg. Company) and weighed. The percentage of moisture was calculated as follows: Moisture content (%) =

W1 – W2 Sample weight (W)

× 100

(1)

where W1 = weight of sample before oven drying; W2 = weight of sample after oven drying. 2.4.2 Estimation of Fat Content The fat content of the flour samples were determined using solvent extraction method in a Soxhlet apparatus. Two grams of moisture free flour samples was accurately weighed and wrapped in a filter paper. Then it was placed in a Soxhlet reflux flask (Soxhlet Extraction Apparatus, 2007, Standard Steel) which is connected to a condenser (HL-A1245, 1963, H.L. Scientific Industries) on the upper side and 200 mL of petroleum ether was added to the Soxhlet reflux flask. The ether was brought to its boiling point, the vapor condensed into the reflux flask immersing the samples completely for extraction to take place. On filling up the reflux flask siphons with condense solvent, it over flows along with oil extracted back to the boiling solvent in the flask. The process of boiling, condensation and reflux was allowed to go on for 4-5

Plantain flour (%) 15 15 15

h. The oil extract in the flux was dried in the oven at 60 °C for 1 h then allowed to cool in a dessicator (Hamco, Chemical Laboratory, 1969, Hindustan Apparatus Mfg. Company) and weighed until constant weight was obtained. Percentage of fat in the sample was calculated as follows: Crude fat (%) =

W2 – W1 Weight of sample (W)

× 100

(2)

where W1 = weight of empty flask; W2 = weight of flask with oil. 2.4.3 Estimation of Protein Content Crude protein of the sample flours was determined using the Kjeldahl method. For digestion, 1 g of dry sample was dropped into the 100 mL Kjeldahl digestion flask. Then 2-3 g of copper sulfate and sodium sulfate (digestion mixture) and 20 mL of concentrated sulphuric acid (H2SO4) were added to the sample. The flask was heated in electrical heater for 2-3 h until a clear solution was obtained and left for another 30 min. The flask was removed and allowed to cool. For distillation, 4% boric acid and 40% NaOH were used. The distillation apparatus was set and rinsed for 10 min after boiling. A 10 mL of the digested sample was then placed in the distillation apparatus and 20 mL of 40% NaOH were added and the distillation was continued for 10-15 min. The sample is automatically distilled after the addition of concentrated alkali solution (NaOH 40%) to make the medium alkaline. Ten milliliters of 4% boric acid was pipetted out into conical flask; further sample was diluted with 75 mL of distilled water during distillation. The diluted sample was received in 10 mL of 4% boric acid contained in 100 mL conical flask attached to the receiving end. The steam exit (ammonia evolved) of the distillatory was closed and the change of colour of

331


boric acid solution to green was timed. The distillation was continued until the volume in the flask was 50 mL then the flask was removed from the distillatory. Then three drops of methyl red and Brome cresol green in alcohol indicator was added to the flask. The trapped ammonia (distillate) was then titrated against 0.1 N hydrochloric acid (HCl) until the red color was obtained. The percentage of protein was calculated: TF  N (HCl)  14  100 Nitrogen content of = (3) sample (%) 1000  weight of sample Crude protein content (%) = nitrogen content (%) × conversion

(4) where TF = reading of titration; 14 = equivalent weight of nitrogen; N = normality; 5.7 = protein factor. 2.4.4 Estimation of Ash Content The ash content of composite flour sample was determined by using muffle furnace (230 V, 50 Hz, Single Phase 2008, M. G. Furnaces (India)). Silica crucibles were dried and cooled in desiccators before weighing. Two grams of the sample flours were weighed into the crucible and recorded the weight. The crucible containing the samples was charred over a slow burning flame and then kept into the muffle furnace and maintained the temperature of 600 °C for 3 h or till the appearance of a gray-white ash. The muffle furnace was then allowed to cool; the crucibles were then brought out and then transferred to a desiccator (Glass, 150-300 mm, 2010, S.K. Appliances) to cool. The percentage of ash was calculated as follows: factor (5.7)

Ash content (%) =

W2 – W1 Weight of sample

× 100

(5)

where W1 = weight of empty crucible; W2 = weight of the crucible with ash. 2.4.5 Estimation of Carbohydrate Content According to Ref. [19], the carbohydrate content of the composite flour samples were calculated by using the following formula and the values were expressed in g/100 g. Carbohydrate by difference = 100 – [moisture (%) + protein (g %) + crude fat (%) + ash (%)]

(6)

2.4.6 Estimation of Energy Value Calculated the energy value of the composite flour using conversion factor viz., 1 g of carbohydrate = 4 kcal, 1 g of protein = 4 kcal and 1 g of fat = 9 kcal. The sum of carbohydrate, fat and protein content of flours were summed to calculate energy value (kcal) [20]. 2.4.7 Estimation of Crude Fiber Content According to Ref. [21], 1 g of fat free and moisture free sample was added with 200 mL of H2SO4 and boiled for 30 min with bumping chips. Filter through muslin and wash with boiling water until washing are no longer acidic. Boil with 200 mL NaOH solution for 30 min. Filter through muslin cloth again and wash with 25 mL of boiling 1.25% H2SO4, three 50 mL portion of water and 25 mL alcohol. Remove the residue and transfer to ashing dish (Pre weighed dish W1). Dry the residue for 2 h at 130 ± 2 °C. Cool the dish in a desiccator and weigh (W2). Ignite for 30 min at 600 ± 15 °C. Cool the dish in desiccators and reweigh (W3). Calculate crude fiber of flour samples as follows: Crude fiber (%) =

(W2 – W1 ) – (W3 – W1) Weight of sample

× 100

(7)

2.4.8 Minerals Analysis The estimation of mineral content of samples was described by Mahajan and Chauhan [22]. About 1 g sample was shaken with 10 mL of 0.03 M HCl for 3 h at 37 °C and then filtered. The clear extract obtained was oven-dried at 100 °C and then the sample was acid-digested with diacid mixture (HNO3:HClO4, 5:1, v/v) at 180 °C for 2 h. The amount of extractable minerals such as Ca, Fe, Cu, Zn and Mn was determined using atomic absorption spectrophotometer (A Analyst 100, Agilent, Norvalk, C.T., USA) in acetylene air flame at wavelengths: 422, 248, 325, 214 and 279.5 nm, respectively. Each sample was analysed thrice and the mean data are reported herein. 2.5 Preparation of Pasta Pasta was prepared by composite flour such as

332


durum semolina flour, millet pulses blend flour and plantain flour in different proportions at 70:15:15, 55:30:15, 40:45:15 for formulae 1, formulae 2 and formulae 3, respectively, were used to develop pasta products. Durum semolina (100%) was used as control. Each blend (300 g) separately mixed with water added slowly within 45-60 s at slow speed in a Hobart mixer equipped with a special mixing paddle. After all water was added (to achieve the desired level of hydration at 32% moisture) the sample was mixed at low speed (speed position 1 of the mixer) for 4 min to reach uniform mix. The wetted dough was placed in the mixing chamber of the extruder and extruded into pasta using demaco semi commercial laboratory extruder (P3 model, Le monferrina, Masoero Arturo and C.S.N.C, Italy). Pasta was extruded using the round die (No. 62) and cut to short pieces of approximately 2 cm in length through blade, then pasta was dried in cabinet air drier (drying cabinet, 1988, Reliance Instruments Corporation) at 65 °C for 3-4 h. Further samples were cooled, sealed in HDPE bags (40 µm) and stored at room temperature [23].

HDPE packs (200 gauges) and stored at ambient temperature for shelf life study. Subsequent quality analysis was as follows: pasta products were evaluated for moisture, ash and sensory analysis, at 0 d, after 30 d, after 60 d, after 90 d and after 120 d. The intent of the study was to determine how well the pasta products in moisture, ash content and in overall acceptability of pasta and usage though a controlled 120 d storage.

2.6 Sensory Evaluation of Pasta Products

3. Results and Discussion

Evaluation of the pasta quality characteristics was carried out room temperature for 1 h. Sensory evaluation was performed by 10 trained panelists who were graduate students at the Department of Home Science, Fatima Arts and Science College, Madurai, Tamil Nadu, India. Pasta products were randomly assigned to each panelist. The panelists were asked to evaluate pasta for appearance, texture, color, taste, flavor and overall acceptability. A nine point hedonic scale was used where 9 = like extremely and 1 = dislike extremely.

3.1 Nutrient Content of Composite Flours

2.7 Shelf Life Studies of Pasta The pasta samples from composite mixture of formulae and control were subjected for assessing the storage stability. Prepared products were packed in

2.8 Statistical Analysis Nutritional properties of composite flours were analysed and experiments were conducted in triplicates. Data was analyzed with the help of factorial design. Mean and standard deviations were reported. Analysis of variance (ANOVA) was performed and the results were separated using Duncan’s multiple range test, which was used to know the significant differences. The relationship between the parameters was examined by Pearson’s product moment correlation also done. Significance was accepted at probability p < 0.05 using the statistical software of INSTAT (Graphpad), USA.

Nutrient content of composite flours were presented in Table 2 and Fig. 1. It showed that moisture content of control and composite flour sample were ranged from 7.8% to 8.2%. The results showed that moisture content of composite formulae were lower than control and no significant (p > 0.05) difference was observed between formulae 3 to control. The energy value of control and composite flour ranges from 363.3 kcal to 365.6 kcal, composite mixture of energy value was equal to control. Further the carbohydrate content was 80.9%, 81.3%, 79.3% and 78.4% for control, composite flour formulae 1, formulae 2 and formulae 3, respectively. The carbohydrate content of composite flour formulae decreased than control except formulae 1. Furthermore

Fortific cation of Pas sta Using Diffferent Plant Sources S

Table 2

3333

Nuttrient content of o composite fllour formulae..

Durum wheaat flour substitu uted with composite flour Nutrients conttent/100 F value p value Contrrol g of sample F Formulae 1 Formulae 2 Formuulae 3 * ** * ns Moisture (%) 8.2 ± 0.05 7 ± 0.07 7.9 7.8 ± 0.1 8.1 ± 0.09 77.74 0.0095 0 Energy (kcal) 364.55 ± 0.2 3 365.6 ± 0.1** 364.9 ± 0.5 5** 363.3 ± 0.2** 3391.9 0.0001 0 Carbohydrate (g) 80.9 ± 0.07 8 81.3 ± 0.1** 79.31 ± 0.3 3** 78.4 ± 0.2** 5541.04 0.0001 0 Protein (g) 9.9 ± 0.2 9 9.41 ± 0.1* 11.24 ± 0.2 2** 11.7 ± 0.1** 881.96 0.0001 0 * 0 ± 0.01** 0.3 0.3 ± 0.01** 0.3 ± 0.01** 1146.83 0.0001 0 Fat (g) 0.1 ± 0.01 1 ± 0.01** 1.29 ± 0.01** 1.38 ± 0.02** 11,485.1 0.0001 0 Ash (g) 0.72 ± 0.02 0 0.9999 1.0000 0.9999 R2 value Mean ± standaard deviation was w reported; coontrol denotes 0% 0 composite flour f substitutioon; **1% levell of significancee; *5% level off significance; ns: n not significaant.

Composite flour

Nu utritional pro operties of co omposite flou urs 400 300 200 100 0

control Formulae 1 Formulae 2 Formulae 3

Nutrient co ompositions Fig. 1

Nutriient compositioon of compositte formulae.

among the flour samplles, formulaae 1 had higher carbohydratee content (811.3 g) than otther flour sam mple which may due to increase in the concentrationn of durum semoolina in the composite flour fl formulaee. A significant difference d bettween controol and compoosite formulae off carbohydratte content waas observed (p < 0.05). Amonng the compoosite mixturee, formulae 3 had the highestt protein content c whicch was 11..7%, followed byy formulae 2 (11.2%), formulae 1 (9..4%) and controol (9.9%). The findinggs suggest that composite mixtures m form mulae was higher h in prootein content thaan control due to incrreased levell of substitution of composite mixture to wheat flour and the differencces were signnificant (p < 0.05) to conntrol. Fat content of compositee mixtures off all formulae had 0.3% whichh was noted as a higher (0.33%) than conntrol (0.1%) and it was signifficant (p < 0.05). Ash conntent of formulae was 1.38%, 1.29% and 1% % for formullae 3, formulae 2 and formulaae 1 which was higher than

con ntrol (0.72%)). The resultss indicate thaat increasingg the concentration of composite mixture of o flour leadss to increase i the ash content and the diffeerences weree sign nificant (p < 0.05) to coontrol. Accorrding to Ref.. [24], Hayma repported that thhe moisture content c of alll flou ur samples raanges from 110.3% to 11.5% which iss acceptable for effective flour storage. Accordingly, A , Olaadunmoye et al. [25] exppressed that durum d wheatt sem molina proteinn content hadd 12.3%, 0.8% % ash contentt, carb bohydrate 700.9%, fat conttent 4% and energy e 372.44 kcaal. Nutrient profile p as comparable to control wass observed in com mposite flourr formulae off protein, fatt and d ash contennt were incrreased by in ncreasing thee con ncentration off millet and puulse flour bleends. Correlation C a analysis revealed that the t nutrientss con ntent of com mposite flour formulae 1,, formulae 2 and d formulae 3 showed positive linear relationshipp (perrfect uphill) with controol. Here it was presentedd on Fig. F 2.

334


350

300

Form ulae 1

250

200

150

100

50

0 0

50

100

150

200

250

300

350

200

250

300

350

200

250

300

350

control

350

300

Formulae2

250

200

150

100

50

0 0

50

100

150 control

350

300

Form ulae 3

250

200

150

100

50

0 0

50

100

150 control

Fig. 2

Coefficient correlation of composite flour with control.


3.2 The Mineral Content of Flour Samples The mineral content of flour samples were tabulated in Table 3 and Fig. 3. The calcium content of composite mixture was 2.13, 1.87 and 2.06 mg for formulae 1, formulae 2 and formulae 3, respectively and control had 2.05 mg. The result showed that calcium content of composite flour was higher than control except formulae 2. While manganese contains 0.36, 0.32 and 0.31 mg for formulae 1, formulae 2 and formulae 3, respectively and control had 0.45 mg, from the result it could be observed that manganese content of control had higher than composite flour. Further iron content of control had 0.54 mg, formulae 1 had 0.63 mg, formulae 2 had 0.7 mg and formulae 3 had 0.82 mg, which was higher than other flour samples. Though copper content of control had 0.06 mg and composite mixture of formulae 1 had 0.98 mg and formulae 2 and 3 had 1.15 mg. At the same time zinc content of control had 0.28 mg, and composite Table 3

mixture of formulae 1 had 0.34 mg, formulae 2 had 0.42 mg and formulae 3 had 0.5 mg. The result revealed that iron, copper, zinc content of composite flour formulae increased than control flour due to increased level of composite flour mixture formulae substitution with wheat flour. These results revealed that composite flour may provide sufficient amounts of minerals to meet the human mineral requirement (recommended dietary allowance (RDA)). For this reason, ratios of the mineral constituents are important for good nutrition. 3.3 Crude Fiber Content of Flour Samples The crude fiber content of control had 7.88 g, composite mixture of formulae 1 fiber content had 9.89 g, formulae 2 had 11.43 g, and formulae 3 had 14.06 g. From the Table 4 and Fig. 4, it can be observed that composite mixture formulae of fiber content was higher than control because composite flour has a mixture of millets, legumes and plantain so

Minerals content of composite flour formulae.

Nutrients content/100 Control g of sample Calcium (mg) Manganese (mg) Iron (mg) Copper (mg) Zinc (mg)

Formulae 1 (15%) 2.13 ± 0.03 0.36 ± 0.02 0.63 ± 0.03 0.98 ± 0.01 0.34 ± 0.01

2.05 ± 0.2 0.45 ± 0.01 0.54 ± 0.01 0.06 ± 0.03 0.28 ± 0.01

Durum wheat flour substituted with composite flour Formulae 2 (30%) Formulae 3 (45%) 1.87 ± 0.07 2.06 ± 0.07 0.32 ± 0.02 0.31 ± 0.05 0.7 ± 0.03 0.82 ± 0.02 1.15 ± 0.04 1.15 ± 0.04 0.42 ± 0.01 0.5 ± 0.03

Mean ± standard deviation were reported; control denotes 0% composite flour substitution.

Minerals content of composite flour Composite flour

2.5 2

Control

1.5 1

Formulae 1

0.5 Formulae 2

0

Formulae 3

Minerals contents

Fig. 3

Minerals content of composite flour formulae.

335

336

Table 4

Fortific cation of Pas sta Using Diffferent Plant Sources S

Fibre content of composite c flourr formulae.

Durum wheat semolina substtitution with coomposite flour

Crude fibre (g)

Control

7.88 ± 0.4

Formulae 1

9.89 ± 0.07

Formulae 2

11.43 ± 0.1

Formulae 3

14.06 ± 0.3

Mean ± standaard deviation were w reported; coontrol denotes 0% 0 composite flour f substitutioon.

Cru ude fibre (g) content of coomposite flourr

grams

15 10 5 0 Co ontrol

Form mulae 1

Formulae 2

Formu ulae 3

co omposite flou ur Fig. 4

Fibree content of com mposite flour formulae f

it was morre nutrient content. c Furrther among the composite mixture m form mulae 3 had the higher fiber f content thaan other sam mples due to t the increased substitution level of compposite mixturre to wheat flour. S 3.4 Sensory Characteristtics of Pasta Samples e waas carried out as per nine point p Sensory evaluation hedonic scalle (Table 5 annd Fig. 5). The T values aree the means of 100 readings. Among A the coomposite mixxture of pasta, foormulae 1 (88.81) had thee highest overall acceptabilityy, followed by formulaae 2 (8.76) and formulae 3 (8.5). All theese three com mposite mixttures of pasta werre acceptabiliity score relaative to controol of pasta score. 3.5 Storage Studies of Paasta Samples m of preedicting the shelf s One of the principal methods life of pastta products is to monittor the level of moisture conntent, ash conntent and sennsory attributees of overall acceeptability of products p durring food storage were presennted in Tablle 6 and Figg. 6. The reesult

showed that at 0 day, the mooisture conteent of controll had d 7.13% afterr 120 d, whicch was increeased slightlyy by 7.33%, 7 follow wed by compposite mixturee of formulaee 1 moisture m content increasee from 6.11% % to 9.66%,, form mulae 2 moisture contentt increase fro om 5.65% too 8.33 3% and form mulae 3 moistuure content in ncrease from m 4.81% to 9.16% %. The resuult found th hat moisturee con ntent was higgh at 120 d aas compared with w 0 d. Ass sam me as the assh content oof control haad 0.73% att initially, it wass decreased as 0.59% after a 120 d,, wheereas compossite mixture oof formulae 1 had 1.04% % at initially, i it was w decreasedd as 0.84% after 120 d,, folllowed by form mulae 2 had 1.27% at iniitially, it wass decreased as 1.007% after 1220 d, and forrmulae 3 hadd 1.38 8% at initiallyy, it was decrreased as 1.12% after 1200 d. From F the result observed that during storage timee the composite mixture m of fo formulae 3 pasta p had thee moiisture contennt was incrreased rapid dly and ashh con ntent was decreased rapiddly at 120 d. d The pastaa products shelf life l studies oof moisture content, ashh con ntent and overrall acceptabillity of pasta products were


Table 5

337

Sensory evaluation (nine-point scale) of pasta developed using composite flour formulae.

Sensory attributes

Control

Colour & appearance Texture Flavour Taste Overall acceptability

9 8.5 8 9 9

Durum wheat flour substituted with composite flour Formulae 1 (15%) Formulae 2 (30%) Formulae 3 (45%) 8 7.5 7.5 7.72 7.2 7.2 7.4 7 7.2 8.86 8.13 7.86 8.81 8.76 8.5

Mean scores (nine-point scale) of sensory attributes for pasta.

Fig. 5 Table 6

Control

Formulae 1 (70:15:15)

Formulae 2 (55:30:15)

Formulae 3 (40:45:15)

Pasta products made from composite formulae. Effect of on storage studies of pasta developed using composite flour.

Composite flour Control Formulae 1 (15%) Formulae 2 (30%) Formulae 3 (45%)

Moisture content of uncooked pasta 0d 120 d 7.1 ± 0.08 7.3 ± 0.2 6.1 ± 0.13 9.6 ± 0.2 5.6 ± 0.05 8.3 ± 0.2 4.8 ± 0.03 9.1 ± 0.2

Ash content of uncooked pasta 0d 120 d 0.7 ± 0.01 0.5 ± 0 1 ± 0.01 0.8 ± 0.06 1.2 ± 0.05 1 ± 0.01 1.3 ± 0.04 1.1 ± 0.09

Over all acceptability of cooked pasta 0d 120 d 7.4 ± 0.08 6.7 ± 0.03 7.4 ± 0.05 7.1 ± 0.01 6.8 ± 0.04 6.2 ± 0.05 6.5 ± 0.02 6 ± 0.02

Mean ± standard deviation were reported; control denotes 0% composite flour substitution.

displayed in Fig. 5. The pasta products were evaluated for sensory qualities for colour, flavour, texture, taste, overall acceptability by panel members at room temperature. Each member independently examined the pasta products and assigned the score on hedonic

scale for its acceptability. A score of nine meant very good and a score of one indicated poor quality. After 120 d, all the parameters of the sensory evaluation indicated that there is decrease in the scores of pasta products prepared from composite mixture of

338


Shelf life of pasta from composite flour formulae 12

composite flour

10 8

Control

6

Formulae 1 (15%)

4

Formulae 2 (30%) Formulae 3 (45%)

2 0 0 day

120 days

0 day

Moisture content of uncooked pasta

120 days

Ash content of uncooked pasta

0 day

120 days

Over all acceptability of cooked pasta

Shelf life of pasta products

Fig. 6

Storage studies of composite flour formulae.

formulas and control. It is also interesting to note that the drop in the scores of sensory evaluation was higher in composite mixture of formulae 1 (7.1) had overall acceptability compared to the other samples. Deteriorative changes in read to eat extruded snack during storage and exposure to atmosphere are loss of flavour, development of rancidity and softening of texture [12, 26]. Coulibaly et al. [19] reported that the stability of the food during storage is important; some deterioration in cereal-legume blends during storage is mostly caused by fat oxidation due to deterioration in taste, flavor, odor, color, texture and appearance, and a decrease in the nutritional value of the foods.

4. Conclusions The most serious nutritional problem of the world is protein calorie malnutrition (PCM), especially in the developing countries. The lower income group of the population is particularly vulnerable, because of its low purchasing power of this group. Attention, therefore, must be focused on the cheap, but nutritious plant protein sources, such as cereals, pulses and vegetable. It is advisable to enhance the protein content of easily available and accessible plant protein

sources (especially legumes) to improve the nutritional status of the low-income groups of the population. Among the cereal grains, millet has more healthy benefits and better nutritious than other major cereals such as rice and wheat. Hence millet is called as miracle grain. Although addition with 15% of plantain flour incorporated to blend of millets, pulses flour to obtain nutritious composite flour which is more fiber and resistant starch content. The present work revealed that pasta could be made using multi grain and plantain flour for the nutritional improvements to get high quality food products. Hence formulated the composite mixture of formulae such as durum semolina, millet, pulse blend flour and plantain flours in different ratios such as 70:15:15, 55:30:15 and 40:45:15 showed higher nutritive value especially protein, crude fiber, carbohydrate, ash and mineral contents. All the three composite mixtures of formulae could be used to produce pasta products of good quality. Among the composite mixtures, formulae1 had high score in overall acceptability. During storage period, composite mixture of formulae nutrients content and also sensory parameters were slightly decreased. Product shelf life is important for


quality and economic reasons. During storage period of food, the stability of the food has been deteriorated due to oxidation, hydrolysis and thermal decomposition by chemical reactions occur in food which are affect the sensory and nutritional quality of food. Although, in post-harvest technology, the value addition technology has given the opportunities to prepare and enhanced the process products which are accepted by both urban and rural consumers. Hence the multigrain food products provide the good health, appealing color, good taste and other beneficial effect like extended shelf life. So these foods are also economically feasible for all grades of population.

[7]

[8]

[9]

[10]

Acknowledgments The authors are thankful to University Grants Commission (UGC) for providing financial support to complete this project as UGC-JRF. Authors would like to express their gratitude to the director, Central Food Technological Research Institute (CFTRI), Mysore for permitting them to use their infrastructure facilities available in the Department of Flour Milling, Bakery and Confectionery Technology.

[11]

[12]

[13]

References [1]

[2]

[3]

[4]

[5]

[6]

Bashir, K., Aeri, V., and Masoodi, L. 2012. “Physio-Chemical and Sensory Characteristics of Pasta Fortified with Chickpea Flour and Defatted Soy Flour.” IOSR Journal of Environmental Science, Toxicology and Food Technology (IOSR-JESTFT) 1 (5): 34-9. Singh, P., and Raghuvanshi, R. S. 2012. “Finger Millet for Food and Nutritional Security.” African Journal of Food Science 6 (4): 77-84. Del Nobile, M. A., Baiano, A., Conte, A., and Mocci, G. 2005. “Influence of Protein Content on Spaghetti Cooking Quality.” Journal of Cereal Science 41: 347-56. Singh, P., Singh, G., Srivastava, S., and Agarwal, P. 2005. “Physico-Chemical Characteristics of Wheat Flour and Millet Flour Blends.” Journal of Food Science and Technology 42 (4): 340-3. Changmei, S., and Dorothy, J. 2014. “Millet the Frugal Grain.” International Journal of Scientific Research and Reviews (IJSRR) 3 (4): 75-90. Truswell, A. S. 2002. “Cereal Grain and Coronary Heart Disease.” European Journal of Clinical Nutrition 56 (1): 1-4.

[14]

[15] [16]

[17]

[18]

[19]

339

Gupta, N., Srivastava, A. K., and Pandey, V. N. 2012. “Biodiversity and Nutraceutical Quality of Some Indian Millets.” Proceedings of the National Academy of Sciences, India Section B: Biological Sciences 82 (2): 265-73. Platel, K., Eipeson, S. W., and Srinivasan, R. 2010. “Bio Accessible Mineral Content of Malted Finger Millet (Eleusine coracana), Wheat (Triticum aestivum), and Barley (Hordeum vulgare).” Agricultural and Food Chemistry 58: 8100-3. Mal, B., Padulosi, S., and Ravi, S. B. eds. 2010. Minor Millets in South Asia: Learnings from IFAD-NUS Project in India and Nepal. Maccarese, Rome, Italy: Bioversity International and Chennai, India, Swaminathan, M. S. Research Foundation, 1283-5. Borsuk, Y., Arntfield, S., Lukow, O., Swallowc, K., and Malcolmsond, L. 2012. “Incorporation of Pulse Flours of Different Particle Size in Relation to Pita Bread Quality.” J. Sci. Food Agric. 92: 2055-61. doi: 10.1002/jsfa.5581. Amjad, I., Khalil, I. A., and Shah, H. 2003. “Nutritional Yield and Amino Acid Profile of Rice Protein as Influenced by Nitrogen Fertilizer.” Sarhad Journal of Agriculture 19: 127-34. Sharma, S., Bajwa, U. H., and Nagi, H. P. S. 1999. “Rheological and Baking Properties of Cowpea and Wheat Flour Blends.” Journal Science Food Agriculture 79: 657-62. Hefnawy, T. M. H., El-Shourbagy, G. A., and Ramadan, M. F. 2012. “Impact of Adding Chickpea (Cicer arietinum L.) Flour to Wheat Flour on the Rheological Properties of Toast Bread.” International Food Research Journal 19 (2): 521-5. Wang, N., Hatcher, D. W., Tyler, R. T., Toews, R., and Gawalko, E. J. 2010. “Effect of Cooking on the Composition of Beans (Phaseolus vulgaris L.) and Chickpeas (Cicer arietinum L.).” Food Research International 43: 589-94. Duranti, M. 2006. “Grain Legume Proteins and Nutraceutical Properties.” Fitoterapia 77 (2): 67-82. Amankwah, E. A., Ayin, I., Dzisi, K., and Barimah, J. 2011. “Nutritional Content and Functional Properties of French Horn, False Horn and FHIA-21.” American Journal of Food Technology 6 (4): 322-8. Fasolin, L. H. 2007. “Biscoitos Produzidos Com Farinhade Banana: Avaliações Química, Física e Sensorial.” Ciência e Tecnologia de Alimentos, Campinas 7 (3): 524-9. AACC. 2000. Approved Methods of the American Association of Cereal Chemists. 10th edition. St. Paul: American Association of Cereal Chemists, Inc. Coulibaly, A., Kouakou, B., and Chen, J. 2012. “Extruded Adult Breakfast Based on Millet and Soybean:

340

[20]

[21]

[22]

[23]

Fortification of Pasta Using Different Plant Sources Nutritional and Functional Qualities, Source of Low Glycemic Food.” J. Nutr. Food Sci. 2 (7): 151. doi: 10.4172/2155-9600.1000151. Mullan, W. M. A. 2006. “Labelling-Determination of the Energy Content of Food.” Accessed July 25, 2018. https://www.dairyscience.info/index.php/packaging/119-l abelling-determination-of-the-energy-content-of-food.ht ml. Yadilal, G., Manisha, M., Pavani, E., Navya, M., Alekhya, C., Chandini, H., and Madhu, C. 2017. “Estimation of Crude Fibre Content in Spices and Fruits.” Indo American Journal of Pharmaceutical Sciences 4 (10): 3864-8. Mahajan, S., and Chauhan, B. M. 1988. “A Research Note Effect of Natural Fermentation on the Extractability of Minerals from Pearl Millet Flour.” Journal of Food Science 53:1576-7. Krishnan, J., Menon, R., Padmaja, G., Sajeev, M. S., and

Moorthy, S. N. 2012. “Evaluation of Nutritional and Physico-mechanical Characteristics of Dietary Fiber-Enriched Sweet Potato Pasta.” European Food Research and Technology 234: 467-76. [24] Hayma, J. 2003. The Storage of Tropical Agricultural Products. Wageningen, Netherlands: Agromisa Foundation, 84. [25] Oladunmoye, O. O., Aworh, O. C., Maziya-Dixon, B., Erukainure, O. L., and Elemo, G. N. 2014. “Chemical and Functional Properties of Cassava Starch, Durum Wheat Semolina Flour, and Their Blends.” Food Science & Nutrition 2 (2): 132-8. [26] Gulla, S., and Waghray, K. 2012. “Blending of Oils: A Case Study on Storage Stability and Sensory Characteristics of Ready to Eat Extruded Snack.” Journal of Nutrition, Dietetics and Food Science 2 (1): 1-12.