Capsicum from Brazil to India during 1584 (Thamburaj and Singh, 2003). The word. âChilliesâ is ... Bangladesh, Saudi Arabia and Malaysia are the major important markets for Indian chillies. ...... Surya. Local market. 15. Arka Suphal. IIHR, Bangaluru, Karnataka. 16. ...... Kumar K, Baswana K S and Pratap P S. 1999. Effect of ...
“Selection Parameters and Genetic Divergence Analysis in Chilli (Capsicum annuum L. var. acuminatum Fingerh.)” Thesis
Submitted to the VCSG Uttarakhand University of Horticulture and Forestry Bharsar-246123, Pauri Garhwal (Uttarakhand), India
By
Manoj Kumar Bundela IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF
Master of Science Horticulture (Vegetable Science)
September, 2016
CONTENTS
Chapter No.
Title
Page No.
1.
INTRODUCTION
1-3
2.
REVIEW OF LITERATURE
4-25
3.
MATERIALS AND METHODS
26-39
4.
EXPERIMENTAL RESULTS
40-60
5.
DISCUSSION
61-73
6.
SUMMARY AND CONCLUSION
74-79
7.
LITERATURE CITED
80-89
APPENDICES
ABSTRACT
CURRICULUM VITAE
LIST OF TABLES
Table No.
Title
Page No.
3.1
List of Chilli genotypes used in the study
27
3.2
Allotment of treatments in experiment field under RCBD
28
4.1
Performance of Chilli genotypes for Number of branches per plant, Number of primary branches and Plant height (cm)
41
4.2
Performance of Chilli genotypes for Plant stem girth (cm), Days to first flowering and Days to 50% flowering
43
4.3
Performance of Chilli genotypes for Days to first fruit harvesting, Number of fruits per plant and Average fruit weight (g)
44
4.4
Performance of Chilli genotypes for Fruit length (cm), Fruit breadth (cm) and Fruit pericarp thickness (mm)
46
4.5
Performance of Chilli genotypes for Number of seed per fruit and Ascorbic acid content (mg/100g)
48
4.6
Performance of Chilli genotypes for marketable yield for per plant (g), per plot (kg) and per hectare (q)
49
4.7
Estimates of phenotypic and genotypic coefficients of variation, heritability, genetic advance and genetic gain for different traits in Chilli
52
4.8
Phenotypic and genotypic coefficients of correlation among different traits in Chilli
54
4.9
Estimates of direct and indirect effects of different traits on marketable fruit yield per plant in Chilli
56
4.10
Clustering pattern of 25 genotypes of Chilli on the basis of genetic divergence
58
4.11
Average intra and inter cluster distance (D2)
58
4.12
Cluster means for different characters in 25 genotypes of Chilli
59
LIST OF PLATES
Plate No.
Title
Between Pages
1
Best genotypes identified on the basis of overall performance
48-49
2
Best genotypes identified on the basis of overall performance
49-50
ABBREVIATIONS %
Per cent
&
And
°C
Degree centigrade
ARS
Agriculture Research Station (Chilli), Devihosur, Karnataka
CD
Critical difference
Cm
Centimetre
et al.
And others
Fig.
Figure
G
Gram
GBPUAT
Govind Ballabh Pant University of Agriculture and Technology
Ha
Hectare
IARI- RS
Indian Agriculture Research Institute- Research Station, Katrain, Himachal Pradesh
IIHR
Indian Institute of Horticultural Research, Karnataka
IIVR
Indian Institute of Vegetable Research, Varanasi, (UP)
KAU
Kerala Agriculture University, Kerala
Kg
Kilogram
KRCCH
Kittur Rani Channamma College of Horticulture, Arabhavi, Karnataka
LC
Local Collection
mm
Millimetres
NHB
National Horticulture Board
q
Quintal
SEd
Standard error of the difference
UHF
Dr. Yashwant Singh Parmar University of Horticulture and Forestry, Nauni, Solan
VCSGUUHF
Veer Chandra Singh Garhwali Uttrakhand University of Horticulture and Forestry, Bharsar, Uttrakhand
Viz.
videlicet (namely)
Chapter-1
INTRODUCTION
CHAPTER-1 INTRODUCTION Chilli (Capsicum annuum L. var. acuminatum Fingerh.) is an important vegetable cum spice crop valued for its aroma, taste, flavour and pungency. It is grown in all parts of the world. It belongs to the family Solanaceae with the chromosome number 2n = 24 and is native of Tropical America (Raju and Luckose, 1991), while Guatemala is the secondary centre of origin (Salvador, 2002). Cultivation spread from Mediterranean Europe to England by 1548 and central Europe by close of sixteenth century. The Portuguese brought Capsicum from Brazil to India during 1584 (Thamburaj and Singh, 2003). The word “Chillies” is of Mexican origin and is still under use in India (Sunderaraj and Thulasidas, 1976). Chilli performs well in warm humid tropical and sub-tropical regions extending from equator 45o latitude on both southern and northern hemisphere. It can grow well up to an altitude of 2000 m and temperature range of 15-35oC. It thrives well in areas having moderate rainfall within the range of 60-120 cm and can be grown on practically all types of soils except on saline land provided; the soil should be well drained and well aerated. Chilli is the most economic additive to improve food acceptability. It is mainly cultivated for its green fruits and dry chilli as vegetable and spice respectively. The pungency in chilli is due to volatile alkaloid called capsaicin and colouring compound capsanthin is used in pharmaceutical industries. These are the excellent source of natural colors and antioxidant compounds (Howard et al. 2000). Chilli is a rich source of Vitamins C, A, B and minerals (Singh, 2007). It is an important food flavouring ingredient for many vegetarian and non-vegetarian food products. The chilli is used the highly pungent types, with thin and comparatively smooth pericarp in hot sauces and in dry powder, while mild and non- pungent types with thick pericarp are used in the green form for flavouring vegetable dishes and for making pickles. In view of its multifarious uses, the demand for chillies has been increasing worldwide. In India, the area under chilli cultivation is 0.775 million hectares with an annual production of 1.492 million tonnes and productivity of 1.9 MT/ha (Anonymous, 2015). India is the largest exporter of chillies in the world (Anonymous, 2015). Indian chillies are
exported to more than 90 countries in the world. Sri Lanka, USA, UAE, Pakistan, Bangladesh, Saudi Arabia and Malaysia are the major important markets for Indian chillies. Though chilli is being grown in almost all the states of India, Andhra Pradesh is the leading chilli growing state followed by Karnataka and Maharashtra. Andhra Pradesh contributes 28 per cent of area and 62 per cent of production followed by Karnataka with 22.71 per cent of area and 55 per cent of production. The average chilli yield of the country is low (25 t/ha) as compared to USA, Korea and Taiwan which produces 34 t/ha (Anonymous, 2015). High variability present in this crop is still to be fully utilized in crop improvement programmes to develop improved varieties having high yield potential and high adaptability. Genetic variability plays an important role in a crop in selecting the best genotypes for making rapid improvement in yield and other desirable characters as well as to select the potential parent of hybridization programmes. Considering the importance of this crop, there is a need for improvement and to develop varieties suited to specific agro-ecological conditions and also for specific end use. A thorough knowledge regarding the amount of genetic variability existing for various characters is essential for initiating the crop improvement programme. With limited variability much cannot be achieved and the breeder will have to enrich the germplasm or he can resort to create greater variability through hybridization, mutation and polyploidy breeding. The phenotypic expression of the plant characters is mainly controlled by the genetic makeup of the plant and the environment, in which it is growing. Further, the genetic variance of any quantitative trait is composed of additive variance (heritable) and non-additive variance and include dominance and epitasis (non-allelic interaction). Therefore, it becomes necessary to partition the observed phenotypic variability into its heritable and non-heritable components with suitable parameters such as phenotypic and genotypic coefficient of variation, heritability and genetic advance. Further, genetic advance can be used to predict the efficiency of selection. Yield is a complex character controlled by a large number of contributing characters and their interactions. A study of correlation between different quantitative characters provides an idea of association that could be effectively exploited to formulate selection strategies for improving yield components. For any effective selection programme, it would be desirable to consider the relative magnitude of association of
various characters with yield. The path coefficient technique developed by Wright (1921) helps in estimating direct and indirect contribution of various components in building up the total correlation towards yield. On the basis of these studies the quantum importance of individual characters is marked to facilitate the selection programme for better gains. Generally diverse plants are expected to give high hybrid vigour (Harrington, 1940). Hence, it necessitates the study of genetic divergence among the existing varieties and germplasm collection for identification of parents for hybridization programme. The information on genetic divergence of various traits particularly of those that contribute to yield and quality would be of most useful in planning the breeding programme. D2 statistics developed by Mahalanobis (1936) provides a measure of magnitude for divergence between two genotypes under comparison. It considers the variation produced by any character and their consequent effect that it bears on other characters. The technique was first used by Mahalanobis in an anthropometric survey of the united province in India. Therefore, keeping this in view, present investigation was carried out to study the variability, heritability and genetic advance for chilli (Capsicum annuum L. var. acuminatum Fingerh.) with the following objectives, 1) To study the genetic variability in chilli germplasm for growth, earliness, yield and fruit quality characters. 2) To study association among yield and its contributing characters. 3) To study the genetic divergence in the chilli genotypes.
Chapter-2
REVIEW OF LITERATURE
CHAPTER-2 REVIEW OF LITERATURE The genetic improvement of plant characters, both quantitative and qualitative is the main interest of the plant breeder. In order to do this, it is necessary to quantify the genetic variation available for various characters of economic importance and their inter relationship. Hence, for the improvement of chillies, the works so far undergone on these aspects has been reviewed under the following heads: 1. Variability, heritability and genetic advance. 2. Correlation and path analysis. 3. Genetic divergence
2.1. Variability, Heritability and Genetic Advance The determination of genetic variability and its partitioning into various components like genotypic, phenotypic and environmental variability is necessary to have an insight into the genetic nature of yield and its components, which enable the breeders to adopt a suitable strategy and formulate a comprehensive breeding program, required for the crop improvement. The following workers have reported their finding on the above said aspect. Ghaidhyal et al. (1996) evaluated twenty four Capsicum annuum L. cultivars for eight yield related traits and reported high heritability for number and weight of fruits per plant, fruit length and fruit circumference. Rani and Singh (1996) evaluated seventy nine genotypes of chilli for nineteen agronomic traits and reported high genotypic and phenotypic coefficient of variation for fruit yield per plant, mean fruit weight, fruit length, weight of seeds per fruit, 100 seed weight and dry matter production. High heritability estimates coupled with higher genetic advance as percentage of mean were for number and weight of fruits per plant, mean fruit weight and dry matter production. Singh et al. (1998) studied the extent of variability, heritability and genetic advance in thirty genotypes of chilli for seven polygenic traits. The result showed considerable genetic variability for pod yield and other traits. Heritability estimates were high for all the
traits except days to 50% flowering, high heritability linked with moderate genetic advance was observed for pods per plant, pod yield, fresh and dry weight of pods. Munshi and Behera (2000) studied thirty germplasm lines of chillies (C. annuum) study indicated existence of considerable amount of genetic variability for all the characters studied except fruit girth. The number of fruits per plant exhibited highest values of genotypic and phenotypic coefficient of variation (GCV and PCV). High estimates of heritability (broad sense), genotypic coefficient of variation (GCV) and genetic advance was observed for fruit length, number of fruits per plant and yield per plant. These characters can be effectively improved through selection. Rani and Singh (2000) conducted a field experiment at IIHR, Bangalore to evaluate seventy three chilli varieties. They determined fruit length, surface area and stem diameter with their interactions. The result showed that fruit length ranges from 2.99 to 14.73 cm (Avg. 8.35 cm), fruit diameter 0.69 to 2.43 cm (Avg. 1.22 cm), good ranges in these traits exhibited high variability. Mishra et al. (2001) evaluated nine genotypes of chilli for fruit characters for two years. They found PCV had higher value as compared to the GCV indicating the negligible effect of the environment on the fruit characters. They observed highest PCV and GCV for fruits per plant, followed by fruit length, dry weight of single fruit and red chilli yield per plant. Mohammed et al. (2001) studied seventeen genotypes of chilli and they observed that PCV and GCV were highest for fruit length followed by dry fruit yield and number of branches per plant, they also observed that heritability was highest for plant height (98.12%) followed by fruit length (96.74%) and number of fruits per plant (96.18%), whereas number of branches per plant, followed by fruit width and dry fruit yield per plant showed higher genetic advance as percentage of mean. Rathod et al. (2002) evaluated thirteen chilli cultivars for eight yield components and they found high GCV for number of fruits per plant, fresh red chilli yield per plant and for plant height. Sreelathakumary and Rajamony (2002) reported high estimates of heritability and genetic advance for fruit length and number of fruits per plant. These characters could be
effectively improved through selection. This could be treated as an indication of additive gene action and the consequent high expected genetic gain for selection from these characters. The fruit characters like size, length and width has been reported to have high genetic advance. Manju and Sreelathakumary (2002) evaluated thirty-two accessions of hot chilli and revealed that higher phenotypic and genotypic coefficients of variation for fruits per plant yield per plant, seeds per fruit and fruit weight. High estimates of heritability coupled with high genetic advance were also observed for these characters. Kumar et al. (2003) evaluated thirty chilli genotypes for their biochemical component capsaicin, ascorbic acid. Capsaicin content showed a narrow range of variation from 0.33mg/100mg in genotype Rajasthan local to 0.49 mg/100mg in genotype KDCS810, with an overall mean of 0.41 mg/100mg. short fruits which were small and he obtained more capsaicin compared to long fruits. The mean ascorbic acid content was lowest in genotype DCL 344 (78.30mg/100g) and highest in genotype ACS 2000-02 (188mg/100g). The total mean ascorbic acid content was 130.01mg/100g fresh fruit weight. Long fruits contained higher ascorbic acid content than short fruits. Khurana et al. (2003) studied the genetic diversity for growth, yield and quality traits in forty eight Capsicum annuum genotypes. Highly significant variation was observed among the genotypes in terms of fruit yield, fruit length, fruit pericarp thickness, number of fruits per plant, and peel : seed ratio, fruit yield, number of fruits per plant, fruit length, fruit diameter, and number of seeds per fruit had high values of heritability. Gogoi and Gautam (2003) studied fifty two genotypes of chilli and reported higher PCV and GCV for fresh fruit yield per plant and dry fruit yield per plant. They also estimated moderate to high heritability for all characters except the number of primary branches and they found highest genetic advance along with high heritability for fruit drop percent followed by fresh fruit yield per plant, dry fruit yield per plant, number of fruits per plant, leaf area index and fruit length. Gupta (2003) studied the performance of thirty genotypes; he found highest range of variability for fresh weight of shoots per plant and lowest variation for 100 seed weight and
also found high heritability along with high genetic advance for weight of fruits per plant (red ripen) and fruit yield per plant. Verma et al. (2004) evaluated twelve chilli (Capsicum annuum) genotypes to determine the extent of genetic variability, genetic coefficient of variation, heritability, genetic advance as percent of mean and correlation of different characters. Data were recorded for days to 50% germination, days to 50% flowering, days to 50% fruiting, plant height, plant canopy, number of branches per plant, leaf length, leaf width, pod length, pod width and number of fruits per plant. The phenotypic coefficient of variation was higher than the genotypic coefficient of variation in all the characters. Plant canopy, number of fruits per plant, days to 50% fruiting, plant height, days to 50% flowering and pod length showed high heritability. Varkey et al. (2005) assessed the genetic variability and heritability for twelve characters (days to flower, plant height, primary branches per plant, secondary branches per plant, number of fruits per plant, fruit length, fruit girth, number of seeds per fruit, 1000seed weight, fresh fruit yield per plant, dry weight per plant and capsaicin content) in forty five genotypes of chilli (Capsicum annuum). They stated that mean square is due to genotypes were significant for all characters, except days to flower, indicating the existence of variability for number of fruits per plant and fresh fruit yield per plant. High heritability coupled with high genetic advance was recorded for number of fruits per plant, number of seeds per fruit and dry weight per plant. These traits can be exploited in breeding programmes to improve yield in chilli. Pramila (2005) evaluated forty genotypes for quantitative and qualitative traits. The genotype EC 519637, Pant selection 20, EC 519640 and EC 519630 were found promising and produced 345.8, 343.0, 340.4 and 232.1% higher yield over Pant C-1, respectively. High PCV and GCV recorded for 10 red ripe fruit weight, green fruit weight, no. of fruits per plant, seed weight per 100 g, weight of fruits per plant and fruit yield per ha. Heritability was high for all the characters except plant height. High heritability along with high genetic advance were observed for 10 red and green fruit weight, number and weight of fruit per plant, fruit yield and seed weight. Smitha and Basavaraja (2006) evaluated the forty genotypes of chilli and they found higher genotypic and phenotypic coefficient of correlation was observed for fruit per plant,
fruit weight, fruit length, fruit girth and yield. Heritability and genetic advance were also higher for these characters indicating the possibility of selection to these characters. Chatterjee (2006) reported higher PCV and GCV for number of fruits per plant, seed weight, number of seeds per fruit, indicating the higher magnitude of variability. Plant height, spread of plant and fruit diameter exhibited moderate PCV and GCV estimates suggesting the possible role of environment in influencing these characters. Days to 50% flowering and days to maturity recorded low PCV and GCV suggesting limited variability. Krishna et al. (2007) observed high degree of variation for all characters in eighty chilli accessions. The difference between phenotypic coefficient of variation and genotypic coefficient of variation were found to be narrow for most of the traits except primary and secondary branches, tertiary branches, fifty per cent flowering, early and late fruit yield per plant. The high estimates of heritability were found for plant height (93.40%), days to first flowering (83.50%), percent fruit set (70.70%), number of fruits per plant (81.10%), fruit length (92.40%), ten fruit weight (92.40%) and total green fruits per plant (88.40%). Singh et al. (2007) studies presented that the PCV was higher than GCV for most traits. High GCV accompanied by high heritability and genetic gain were recorded for colouring matter, ascorbic acid and dry matter, indicating that these traits could be improved by simple selection. Moderate to high heritability with low GCV and genetic gain were observed for capsaicin content, fruit weight, oleoresin content, fruit width and number of fruits per plant. Shirshat et al. (2007) evaluated the seventy two genotypes of chilli and they the phenotypic coefficient of variation was higher as compared to genotypic coefficient of variation for all characters indicating the influence of environment on these characters. Fruit attributes viz., fruit length, fruit surface area, weight of dry fruit, pericarp weight of fruit, number of seeds per fruit, weight of seeds per fruit, stalk length, ascorbic acid and sugar content showed very narrow differences between phenotypic and genotypic coefficient of variation, which indicated limited influence of environmental factors. Heritability estimates in respect of fruit length, number of seeds per fruit, weight of seeds per fruit, weight of dry fruit, pericarp weight of fruit, ascorbic acid content. Moderate genetic advance was observed for the characters like number of fruits per plant, number of seeds per fruit and sugar content of the fruit. Heritability was high in these characters
except for number of fruits per plant. In case of attributes like fruit length, fruit surface area, weight of dry fruit, pericarp weight of fruit, number of seeds per fruit and weight of seeds per fruit, the genetic advance was low to moderate coupled with high heritability. Yield per plant, the complex trait, which is dependent on several component characters showed moderate heritability with low genetic advance. Tembhurne et al. (2008) conducted a study on eleven elite advanced lines of chilli genotypes and they observed phenotypic and genotypic coefficient of variation were low for days to 50% flowering, plant height, fruit diameter and number of fruits per plant. High genetic advance over mean coupled with higher heritability was observed for number of fruits per plant. Munshi et al. (2010) evaluated thirty diverse chilli genotypes and they observed highest PCV and GCV for number of fruits per plant followed by fruit weight, number of secondary branches and total carotenoids; traits like plant height, number of primary branches, fruit weight and ascorbic acid exhibited nearly equal PCV and GCV values. Very high heritability was associated with ascorbic acid, fruit weight, number of primary branches, TSS, number of secondary branches, plant height, days to flowering, fruit width, fruit length and number of fruits per plant whereas yield per plant and days to first fruit harvest showed moderately high estimates of heritability. Sharma et al. (2010) reported significant differences among the ninety four genotypes for fruit yield per plant, average fruit weight, and number of fruits per plant and took less number of days to 50% flowering. The phenotypic coefficient of variation and genotypic coefficient of variation were high for fruit yield per plant indicating that these traits had wide genetic variability and would respond better to selection. They also reported high heritability and high genetic advance for average fruit weight, fruit yield per plant and fruit diameter indicating the role of additive gene action for the inheritance of these traits. Kumari et al. (2010) reported higher phenotypic and genotypic coefficient of variation (PCV and GCV) and heritability coupled with high genetic advance was observed for number of fruits per plant, fresh fruit yield per plant, seed weight, number of seeds per fruit indicating the higher magnitude of variability for these traits and consequently more scope for their improvement through selection. Plant height, plant spread and fruit diameter
exhibited moderate PCV and GCV estimates suggest the possible role of environment in expression of these characters. Berhanu et al. (2011) reported significant genotypic variability for all the traits studied. In general PCV was higher than that of GCV. Genetic advance that could be expected from selecting the superior 5% of the genotypes as percent of mean varied from 6.2% for days to maturity to 143.22% for fruit weight .They demonstrated the existence of adequate genetic variability, high degree of genetic determination and genetic advance among chilli genotypes for majority of the traits. Chattopadhyay et al. (2011) studied the genetic variability for different traits and reported most of the genotypes possessed the character constellation of C. annuum. Two genotypes, ‘Chaitali Pointed’ and ‘BC CH Sel-4’ were found most promising with respect to green fruit yield (272.79 g, 221.10 g per plant) and dry fruit yield (54.56 g, 44.44 g per plant). Phenotypic and Genotypic Coefficient of Variation values for green fruit weight (119.95%, 111.26%), green fruit girth (89.76%, 48.93%), weight of red ripe fruit (112.02%, 111.93%), weight of dry fruit (111.63%, 110.97%) and number of fruits per plant (86.05%, 85.02%) were recorded to be high. Green fruit yield per plant, ascorbic acid content, and number of fruits per plant also showed very high broad-sense heritability and genetic advance. Data and Das (2013) collected fifty three genotypes of Capsicum annuum L. from different parts of the West Bengal, India and characterized for 23 characters and they found high heritability along with higher genetic advance as percent of mean was found in capsaicin content in fruit, number of fruits per plant, yield per plant and primary branches per plant. Sandeep et al. (2013) recorded highest heritability per cent in broad sense (84.50%) for fruit yield per plant followed by dry fruit yield per hectare (84.49%) and genetic advance were found to be highest for the same characters (58.30 and 58.29 per cent) among ninety chilli genotypes. Syukur and Rosidah (2014) conducted a research on different genotypes of chilli for different quantitative characters and they found high Broad-sense heritability for plant
height, stem diameter, day to flowering and day to harvesting, Whereas these were moderate for fruit length and fruit diameter. Amit et al. (2014) evaluated twenty three genotypes and reported high phenotypic coefficient of variation and genotypic coefficient of variation for number of fruits per plant, fruit weight and dry (red) yield. All the characters showed high heritability estimates. However, number of the fruits per plant, green fruit yield per plant, dry (red) yield per plant, number of seeds per plant and plant height exhibited high genetic advance as percentage of mean indicating additive gene effect. Patel et al. (2015) studied 40 diverse genotypes of chilli and found that high estimates of GCV and PCV were obtained for number of primary and secondary branches per plant, number of fruits per plant, average fruit length (cm), average fruit girth (cm), fruit shape index, average fruit weight (g), green fruit yield per plant (g), chlorophyll content (mg/100g), ascorbic acid content (mg/100g) and capsaicin content (mg/g), while it was low for moisture content (%). The characters like days to flowering (days), plant height (cm), number of primary and secondary branches per plant, number of fruits per plant, average fruit length (cm), average fruit girth (cm), fruit-shape index, average fruit weight (g), green fruit yield per plant (g), chlorophyll content (mg/100g), ascorbic acid content (mg/100g) and capsaicin content (mg/g) exhibited high genetic advance coupled with high heritability. Janaki et al. (2015) studied sixty three genotypes of chilli and found that high magnitude of PCV and GCV for per cent fruit set, number of fruits per plant, fruit diameter, average dry fruit weight, number of seeds per fruit and yield per plant suggesting the existence of wide range of genetic variability in the germplasm for these traits. High heritability coupled with high genetic advance as percent of mean was observed for all the characters except days to 50% flowering, indicating the predominance of additive gene action making the simple selection more effective. Kadwey et al. (2015) studied twenty five diverse chilli (Capsicum annuum L.) genotypes were evaluated in a field study The highest PCV were recorded for number of fruit per plant (42.0), dry fruit yield per plant (30.34), seed yield per plant (28.94), fruit weight of dry chilli (23.38), number of primary branches per plant at 30 DAT (21.88) and fruit width (21.0). While, highest GCV was observed for number of fruit per plant (41.77), dry fruit yield per plant (29.61), seed yield per plant (27.67) and fruit weight of dry chilli
(21.67), The value of heritability was found to be very high for fruit yield per plant (97.91), seed yield per plant (96.82), dry fruit yield per plant (95.24), days to first picking (94.88), fruit length (93.30), fruit weight of green chilli (93.26), fruit yield per plot (92.91), fruit per yield (92.90) and fruit width (92.02). The highest estimates of genetic advance as percentage of mean was recorded for number of fruit per plant (45.59), fruit weight of dry chilli (41.38), fruit width (39.82), dry fruit yield per plant (39.52), seed yield per plant (38.70), fruit weight of green chilli (38.10), fruit yield per plant (37.33) and fruit length (36.78) were observed for all the above characters, imply the potential for crop improvement in chilli through selection. Jogi et al. (2015) estimated high degree of variation for all characters. The difference between phenotypic coefficient of variation and genotypic coefficient of variation were found to be narrow for most of the traits. The high estimates of heritability was found for number of fruits per plant at first picking (98.20%), total number of fruits per plant (94.67%), early yield (94.67%), late yield (95.62%) and total yield (91.37%), fruit length (96.22%), fruit width (96.22%), stalk length (81.04%) and ten fruit weight (96.44%), ascorbic acid (98.30%), chlorophyll-a (95.45%), chlorophyll-b (97.52%) and their total chlorophyll (97.87%).
2.2. Correlation and path analysis The correlation between different quantitative characters provides an idea of association that could be effectively exploited to formulate selection strategies for improving yield components. For any effective selection programme, it would be desirable to consider the relative magnitude of association of various characters with yield. Further, path coefficient technique developed by Wright (1921) helps in estimating direct and indirect contribution of various components in building up the total correlation towards yield. The following researchers have reported their finding for correlations and path coefficient analysis. Dahipale et al. (1991) evaluated cultivar Pusa Jwala of chilli for seven yield components grown under three irrigation schedules and three different nitrogen levels. They found that green fruit yield was positively correlated with fruit diameter, fruit length, plant height, number of branches and dry matter and number of fruits per plant.
Singh et al. (1992) attempted to study six cultivars for fourteen component including yield per hectare and they reported that high yielding genotypes significantly correlated with number of secondary branches, days to 50% flowering, fruit length, fruit weight, number of fruit per plant and dry matter percentage. Khurana et al. (1993) evaluated ten genotypes of Capsicum annuum and they observed that fruit yield was positively and significantly related to mean fruit weight, number of fruit, fruit length, leaf area, leaf weight, number of branches and stem weight had the positive direct effect on yield. Ali (1994) conducted a study on twelve (Capsicum annuum) genotypes and found that yield was significantly correlated with fruit number per plant, seed number per fruit and number of seeds per 25 fruits. He also found that dry fruit weight was significantly correlated with fresh weight, maximum fruit width, 1000 seed weight and weight of pedicel and pericarp. Pawade et al. (1995) studied correlation in chilli cultivar on eight yield components in thirty six local types grown in Nagpur district of Maharashtra. They reported that number of fruits per plant showed the strongest positive correlation with the yield, plant spread, number of branches, plant height, fruit length and 100 seed weight also showed significantly and positive association with yield. The effect was direct for number of fruits per plant and 100 seed weight and indirect for plant spread, plant height, number of branches, fruit length and maturity. Warade et al. (1996) investigated that yield per plant was positively correlated with plant height, plant spread, fruit weight, seed per fruit, days to 50% fruit set, fruit length and fruit girth whereas negatively correlated with days to 50% flowering and maturity. Rani (1996) reported the positive and significant correlation coefficient of fruit yield per plant with number of fruits per plant, plant height, number of primary branches per plant, number of secondary branches per plant, number of fruit per plant with plant height, number of primary and secondary branches, plant height with pedicel length and number of secondary branches per plant, fruit length with pedicel length. Fruit diameter was negatively correlated with fruit length, number of primary branches per plant and pedicel length. 100 seed weight did not show any relationship with any of the character.
Rani (1997) evaluated seventy three diverse chilli genotypes for fruit weight and four other fruit traits at the IIHR, Bangalore, India. Fruit weight showed positive correlation with seed number, seed weight, 1000 seed weight and fruit pericarp weight. Deshmukh et al. (1997) conducted a study on nine genotypes of chilli for eight yield attributing characters at Akola and they observed weight of 50 red ripe fruits had highest direct positive effect on yield, followed by plant diameter and weight of 50 dried fruits. Kumar et al. (1999) studied the genotypic and phenotypic correlation and path coefficient to determine the true component of yield in chilli for seventeen characters in thirty genotypes. They reported that fruit length, fruit diameter, fresh fruit weight. Fruit length and diameter, as well as harvest index, exhibited positive correlation with fruit yield. However path analysis revealed highest direct contribution of fruits per plant towards total yield. It was concluded that number of fruits per plant and fresh and dry weight per fruit were major yield contributing factor in chilli. Rani and Singh (2000) collected the data for twenty different characters from seventy three diverse genotypes of chilli. They reported that stem diameter exhibited maximum direct effect on dry fruit yield followed by root volume, root mass, fruit diameter via stem diameter confirm the importance of stem diameter in influencing the fruit yield. Mishra et al. (2001) attempted to study nine genotypes of chilli for fruit characters. They found that red chilli yield was positively and highly correlated with fruit per plant but negatively correlated with seeds per fruit. Rathod et al. (2002) evaluated thirteen chilli genotype they found that genotypic correlation coefficient was higher than phenotypic correlation coefficient for all the characters. The yield of chilli was positively and significantly associated with the number of fruits per plant, 100 seed weight, seed percentage and harvesting index, 100 seed weight recorded the highest positive direct effects on the net red chilli yield per plant, followed by the seed percentage, days to 50% flowering and number of primary branches per plant. Gogoi and Gautam (2003) evaluated fifty two chilli genotypes for twenty characters and they observed, fresh fruit yield per plant exhibited significant and positive correlation with dry fruit yield, number of fruits per plant, number of flowers per plant, fresh fruit
weight, dry fruit weight, 1000 seed weight, plant height, plant spread, fruit length, number of seeds per fruit and number of primary branches. Khurana et al. (2003) studied the forty eight genotypes of chilli and observed that fruit yield was positively correlated with number of fruits, fruit length and diameter, peel: seed ratio, plant height, leaf area, but was negatively correlated with number of days to flowering, number of days to fruit set. Fruit yield showed a significant phenotypic correlation with number of fruits per plant, fruit length, peel : seed ratio, leaf area and capsaicin content. The number of days to flowering, fruit thickness, wilts and viral incidence had negative direct effects on fruit yield. Path analysis indicates that plant height had an indirect effect on fruit yield through number of fruits, plant height and fruit length. Ajjapplavara et al. (2005) attempted to study thirty six genotypes of chilli for eighteen different quantitative characters, the correlation study indicate that significant and desirable correlation between dry fruit yield per plant with all other characters except number of primary and secondary branches, fruit diameter, fruit volume, powdery mildew disease incidence and leaf curl incidence. Path analysis revealed that importance should be given to fruit weight and fruits per plant. Pramila (2005) evaluated forty genotypes for quantitative and qualitative traits. Correlation study revealed that significant positive correlation were observed for weight of fruits per plant, fruit length, fruit periphery, fruit yield, 10 red and green fruit weight and plant height. Smitha and Basavaraja (2006) reported the correlation study in forty chilli genotypes under rainfed conditions. Correlation study revealed that significant positive correlation of economic traits like fruits per plant, fruit length, and fruit weight with yield was recorded and suggested that selection for these characters would lead to crop improvement. Singh et al. (2007) reported the genetic correlation was higher than the phenotypic correlation. Total yield showed the positive and significant phenotypic and genetic correlation with fruit length, fruit width and fruit per plant.
Krishna et al. (2007) evaluated eighty genotypes of chilli for thirteen important characters. The phenotypic and genotypic association of fruit yield was significantly positive with all the characters except days to first flowering and ten fruit weight. The genotypic and phenotypic path coefficient revealed that total green chilli yield had high direct positive effect from early and late fruit yield. Tembhurne et al. (2008) attempted to study correlation in eleven elite advanced lines of chilli yield was positively associated with most of the traits but its magnitude was high with number of fruits per plant (0.8026) and fruit diameter (0.6401). Kumari et al. (2011) studied on correlation in ninety-four diverse genotypes of paprika (Capsicum annuum) grown at Lam (Andhra Pradesh) indicated that dry fruit yield per plant showed significant and positive association with plant height, plant spread, number of fruits per plant, fruit girth, seeds per fruit and capsanthin content. Chattopadhyay et al. (2011) analyzed thirty-four genotypes were characterized during a period of two year. Study of correlation and path coefficient analysis, the number of fruits per plant, green fruit length for green chilli, weight of dry fruit and the number of fruits per plant for dry chilli were found to the most important selection indices. Diwaker et al. (2012) reported twenty genotypes of chilli and observed that number of branches at 150 days after transplanting, days to anthesis, number of fruits per plant, average fruit weight, Ascorbic acid, capsaicin content and fruit length showed positive correlation with fruit yield per plant. Number fruits per plant exhibited the highest positive direct effect on yield followed by days to anthesis, plant spread (N-S) at 150 days after transplanting, Ascorbic acid content, plant height at 150 days after transplanting and fruit length at genotypic level. Singh and Singh (2012) evaluated fifty germplasm of chilli to assess the genetic variability and association of different traits They found that early fresh fruit yield per plant was positively and significantly correlated with number of fruits per plant, fruit body length, fruit length, fresh fruit yield per plant, number of seeds per fruit, seed weight per fruit and dry fruit yield per plant at both genotypic and phenotypic levels.
Krishnamurthy et al. (2013) recorded phenotypic co-efficient of variation (PCV) and genotypic co-efficient of variation (GCV) were high for red fruit yield plant per plant, green fruit yield per plant, fruits per plant and fruit length. high positive significant correlation of days to 50% flowering and days to first fruit mature suggested that early flowering genotypes would be an appropriate selection criterion to get early marketable (green) fruit yield. The number of fruits per plant had positive correlation with green fruit and red fruit yield per plant at genotypic and phenotypic level. Path analysis helps in partitioning correlation coefficients into direct and indirect effects of component characters in yield. Direct and indirect effects of all the traits on yield were computed at the genotypic level. For path analysis at the genotypic level, green fruit (marketable fresh fruit) yield per plant was taken as dependent variables and all other traits used for correlation were considered as causal variables. Amit et al. (2014) evaluated twenty three genotypes and reported that fruit yield (green and red) per plant was positively and significantly correlated with number of fruits per plant and fruit length. It revealed that the characters viz., plant height, fruit length, number of fruits per plant, fruit weight and fruit yield (green & red) are the most important traits for genetic improvement of chilli. Vikram et al. (2014) observed that green yield per plant showed positive and significant correlation with average green fruit weight, fruit length and fruit breadth at middle while dry fruit yield exhibited the same with fruit length and yield per plant. Path analysis towards dry yield per plant revealed the importance of average dry fruit weight, number of fruits per plant, fruit length and green yield per plant in improvement of dry yield per plant. Patel et al. (2015) studied forty diverse genotypes of chilli and found that green fruit yield per plant had high, significant and positive association with number of fruits per plant, average fruit weight, moisture content and chlorophyll content at both genotypic and phenotypic levels. Path analysis revealed that characters like number of secondary branches per plant, number of fruits per plant and average fruit weight had high and positive direct effects on green fruit yield. Janaki et al. (2016) evaluated sixty three genotypes of chilli (Capsicum annuum L.) and found phenotypic and genotypic association of fruit yield per plant was significant,
positive with plant height, per cent fruit set, number of fruits per plant and number of seeds per fruit whereas only genotypic association of yield per plant was significant, positive with fruit length and significant, negative with fruit diameter. The path analysis revealed that plant height, per cent fruit set, number of fruits per plant, fruit length, average dry fruit weight, number of seeds per fruit had positive direct effect on yield per plant. The direct contribution of number of fruits per plant and average dry fruit weight was high and positive on yield per plant indication that its true relationship with yield and direct selecting based on these traits may be helpful in evolving high yielding varieties of chilli. Aklilu et al. (2016) studied forty nine hot pepper accessions and found genotypic correlation coefficients were higher in magnitude than phenotypic values in most instances in which fruit yield per plant showed high positive significant genotypic correlation value with pericarp thickness (r = 0.91) and number of fruits per plant (r = 0.61). On the other hand, significant negative associations were registered with days to flowering (r = -0.73) and 50% fruiting period (r = -0.75). The phenotypic correlation coefficient of most characters with yield was not significant except for fruit length and number of fruits per plant. The path coefficient analysis indicated that pericarp thickness (mm) (5.5), fruit diameter (mm) (1.4), number of fruits per plant (0.8), number of branches (0.33) and flowering period (0.2) had the highest direct positive effect. However, fruit weight (-2.8 and plant height (-0.4) had a high negative direct effect on yield. The genetic component analysis indicated that phenotypic coefficient of variation (PCV) was higher in magnitude than genotypic coefficient of variation (GCV) for most characters except pericarp thickness and leaf area index. Higher magnitude of GCV was observed in leaf area index (67%) followed by pericarp thickness (34%), number of branches, internodes length (23%) and plant height. Close estimates of GCV and PCV were recorded from fruit and internodes length, pericarp thickness and fruiting period. Very high PCV and very low GCV estimates were obtained from fruit weight and number of fruits, fruit yield, plant height and canopy width. Broad sense heritability was high for fruiting date, fruit length, plant height, internodes length and fruit diameter. However, genetic advance as percent of the mean (GAM) was high to moderate for length and number of internodes, number of branches, fruit diameter and weight, pericarp thickness and leaf area index. Bijalwan and Mishra (2016) studied sixteen genotypes in chilli for fifteen different qualitative and quantitative characters. Correlation coefficients at genotypic and phenotypic
levels indicated that fruit yield per plant was positively and significantly correlated with fruit weight at edible maturity, number of fruits per plant, fruit length, number of branches per plant and ascorbic acid content but negative and significant association was found with days to 50% flowering indicating that early flowering and early picking might be associated with increasing the fruits yield per plant. Path coefficient analysis revealed that the highest positive direct effect on fruit yield per plant was exerted by fruit weight at edible maturity followed by number of fruits per plant and fruit length, while as highest negative direct effect on fruit yield per plant was exerted by number of branches per plant and pedicel length. Hasan et al. (2016) conducted a study with thirty chilli genotypes fruit length, fruit weight, 100 seed weight and fruits per plant showed significant and positive correlation with yield per plant both at genotypic and phenotypic level. Path coefficient analysis revealed that fruits per plant had maximum positive direct effect on yield. Besides fruits per plant; fruit weight, fruit length and number of primary branches/plant also contributed positive direct effect to yield.
2.3. Genetic divergence The magnitude of divergence between two groups under consideration is provided by D² statistic developed by Mahalanobis (1936). It considers the variation produced by a character and their consequent effect that it bears on other characters. The following studies were found in the chilli with the concerned aspect. Sundaram et al. (1980) grouped fifty varieties of chilli were grouped into seven clusters they found no relationship between genetic and geographic diversity in chilli. The relative contribution of characters towards total divergence revealed that the number of branches and number of fruits per plant were the chief contributors towards genetic divergence. Mehra and Peta (1980) grouped twenty seven chilli genotypes into nine clusters based on D2 values. They found maximum contribution (88.03%) of fruits per plant towards the diversity. The plant height contributed very little (0.28%) towards diversity whereas days to first fruit set, days to first fruit harvest, plant height, primary branches per plant and pedicel to fruit ratio were either negligible or nil.
Varalakshmi and Haribabu (1991) grouped thirty three chilli genotypes studied were grouped into eleven clusters by out of 10 characters studied, fruits per plant, leaf area index, fruit weight and total yield were reported to be the chief contributors towards genetic divergence. They also found no firm relationship between genetic divergence and geographical distances. Warade et al. (1996) grouped sixty cultivars of chilli obtained from different ecogeographical regions into nine clusters and observed maximum diversity because of maximum cluster distances. The clustering pattern also revealed that geographic diversity did not seem to have direct association with genetic diversity. Mubarak Begum (2002) grouped forty six chilli genotypes into thirteen clusters which showed inter cluster D2 values ranging between 18.91 and 87.12. Three characters namely seed number per fruit, dry fruit yield per plant and numbers of fruits per plant were the chief contributors towards diversity. Maximum diversity revealed by inter- cluster distance revealed between cluster VI and XIII with D2 value 82.21 Prabhudeva (2003) grouped thirty six genotypes into eleven clusters with D2 values ranging 34.02 to 102.13. He concluded that genetic diversity was not an index of geographical diversity as cleared by clustering pattern. In his study, maximum contribution of characters towards diversity was form fruits per plant followed by ten fruit weight and plant height. He observed maximum diversity i.e., inter cluster distance between cluster I and II, suggesting that the genotypes belonging to these clusters form ideal pairs for developing hybrids. Senapati et al. (2003) grouped twenty nine diverse chilli genotypes studied for eleven characters into six clusters. Cluster I was the largest with 13 genotypes, followed by cluster III and IV with 2 genotypes each. They observed maximum genetic distance between cluster II and cluster VI, suggesting wide diversity between these groups, and four characters, viz., fresh fruit weight, fruit girth, fruit length and fruit number per plant were the chief contributors towards genetic divergence. Smitha (2004) grouped forty chilli genotypes into eight clusters based on D2 analysis. Number of fruits per plant, fruit yield per plant, number of primary branches and seeds per fruit were reported as chief contributors towards divergence.
Smitha and Basavaraja (2007) grouped forty genotypes into 8 clusters. The maximum intra and inter cluster distance was observed for the characters, viz., fruits per plant, fruit yield, number of branches, fruit weight and fruit length confirming that existence of ample amount of divergence in genotypes with respect to the traits. Gogate et al. (2007) studied the genetic divergence and magnitude of D2 values for fifty five genotypes and grouped them into 11 clusters. The distribution of different genotypes revealed that cluster I represented maximum number of genotypes followed by cluster IV and cluster III, whereas, minimum single genotype was with each cluster IX, X and XI. Maximum intra cluster distance was observed in cluster VI and minimum in cluster IX, X and XI, and inter cluster distance was maximum between cluster VII and cluster XI, indicating that genetic drift and evaluation in different environment could cause greater diversity than geographic distance. Ajjapplavara (2009) studied the degree of genetic divergence among thirty six chilli genotype on the basis of genetic distance; these genotypes were grouped in to 11 clusters. Cluster-II was largest, consisting of 16 genotypes, while cluster, IV, V, VI, VII, VIII, IX and XI contained single genotype each. There was no parallelism between genetic diversity and geographical distribution. Among the different characters studied fruits per plant, fruit yield per plant, plant height, ten green fruit weight, powdery mildew disease incidence; leaf curl complex incidence contribute significantly for the genetic diversity. The maximum inter cluster distance (125.45) was highest between the II and X. The genotypes phule Sai, LCA-206, Pant C-1, KDC-1, Byadgi dabbi and AD-5 from these clusters may be used as parental donors for future hybridization programme to develop higher fruit yield with resistant to disease pests. Thul et al. (2009) studied the degree of genetic divergence among twenty four chilli accessions and grouped them into 6 clusters. Cluster I was of maximum accessions followed by II, III and IV. The highest intra cluster divergence for cluster I was invariably smaller than the lowest inter cluster divergence between cluster II and cluster III and the inter cluster distance was highest for cluster V, followed by cluster III and lowest was observed for cluster IV. Kumar et al. (2010) conducted the study on genetic diversity with forty five chilli genotypes for various characters revealed substantial differences for all the traits. Based on
D2 values, the genotypes were clustered into eight constellations. Cluster I contained nine genotypes fallowed by cluster-II (four) cluster IV and V (two each). The maximum inter cluster distance (D=12.75) was observed between cluster VI and cluster VIII. The cluster IV recorded maximum intra cluster distance (D=5.91).Intercrossing among the genotypes belonging to cluster III, IV and I was suggested to develop high yielding varieties with other desirable characters or may be used as potential donors for future hybridization programme to develop better chilli variety with good fruit yield. Farhad et al. (2010) evaluated the study on genetic diversity with forty five chilli genotypes and genotypes were fallen into 6 clusters by using cluster analysis. Cluster I and cluster III had maximum number of genotypes and earned the highest cluster mean value for days to 50 per cent flowering and pedicel length and minimum number of genotypes were observed in cluster III. The genotypes from cluster VI produced highest mean for Vitamin-C. Highest inter cluster distance was observed between cluster II and cluster IV, and lowest was observed between cluster I and cluster IV, suggested the close relationship Hasanuzzaman and Golam (2011) conducted the study on genetic diversity with twenty chilli accessions were grouped into six clusters. Cluster I consisted of solitary individual genotype, cluster II and cluster III of three accessions, cluster IV of two genotypes, cluster V of maximum seven genotypes while cluster VI consisted of four genotypes. The highest intra cluster divergence (1.7153) for cluster VI was invariably smaller than the lowest intercluster divergence between cluster III and cluster VI (3.247), thus authenticating the clustering pattern formed in this study. The intra cluster divergence ranged from 0.00 and 0.07288 to 1.7153, whereas the intercluster divergence ranged from 3.247 to 12.677 between clusters III and VI and clusters I and V. Datta and Das (2013) conducted the study on genetic diversity with fifty three genotypes were grouped into 17 clusters and results indicated that Cluster I and Cluster VII comprised with 29 and 9 genotypes respectively. Rest of clusters consisted of one genotype in each case. Variability studies revealed that there was a wide range of variability for all the characters studied. High heritability along with higher genetic advance (as a percentage of mean) was found in capsaicin content in fruit, number of fruits per plant, yield per plant and primary branches per plant. These characters may be considered as reliable selection indices as they are possibly governed by additive gene effect.
Hasan et al. (2014) conducted cluster analysis for grouping of fifty four chilli genotypes into seven clusters. Cluster II had maximum (13) and cluster III had the minimum number (1) of genotypes. The highest inter-cluster distance was observed between cluster I and III, and the lowest between cluster II and VII. The characters yield per plant, canopy breadth, secondary branches per plant, plant height and seeds per fruit contributed most for divergence in the studied genotypes. Considering group distance, mean performance and variability, the inter genotypic crosses between cluster I and cluster III, cluster III and cluster VI, cluster and cluster III and cluster III and cluster VII may be suggested to use for future hybridization program. Vijaya et al. (2014) studied the D2 analysis for the chilli genotypes. Based on the degree of divergence among the genotypes, the twenty four genotypes could be grouped into 11 clusters. The cluster I constituted maximum number of genotypes whereas other ten clusters comprised of 2 genotypes each. The highest inter cluster distance was observed between cluster II and cluster XI, whereas, the distance between cluster IV and V was least. The cluster XI had recorded maximum intra cluster distance followed by cluster I and X, suggested that very high diversity and more number of clusters observed in this study could be due to geographical isolation of the genotypes. Yatung et al. (2014) conducted a study on D2 statistics to estimate the genetic divergence with thirty chilli genotypes and grouped into under six clusters. Cluster III had maximum number of genotypes and exhibited highest intra cluster distance while lowest was observed in cluster II, for the characters like capsaicin and Ascorbic acid content, contributed maximum towards divergence. The highest inter cluster distance was observed between cluster II and cluster IV and lowest was seen in cluster I and cluster IV, so this may be taken into consideration for selection of better parents for an efficient hybridization programme in chilli. Hasan et al. (2015) studied the Genetic diversity of thirteen chilli genotypes based on six characters was estimated using D2 statistics. The results indicated that fruits per plant contributed maximum to the total divergence followed by fruit length and yield per plant. Cluster IV produced highest mean for fruit weight, fruits per plant and yield per plant. Cluster V produced highest mean for fruit length, pedicel length and fruit diameter. Cluster I and III produced maximum lowest mean for almost all characters. Therefore, genotypes
belonging to the cluster IV and V may be used as potential parents for future hybridization programme to develop superior Chilli variety with desired trait. Zehra et al. (2015) study was conducted in sixty four genotypes of chilli (Capsicum annuum L.). Genotypes were grouped into eight clusters as per D2 analysis employing Tocher’s method with maximum number of genotypes in cluster I (37) followed by cluster IV (12), cluster II (6), cluster V (5) and rest of the clusters were mono genotypic. Maximum inter cluster distance was observed between clusters II and VI (19369.21), while maximum intra-cluster distance was observed in cluster IV (4230.34). The per cent contribution towards the total genetic divergence revealed that plant spread (29.76%), seed yield per plant (25.69%), average fruit weight (17.41%), number of fruits per plant (10.22%), days to first flower (4.01%), fruit length (4.76%), number of branches per plant (4.51%) and fruit diameter (2.88%) were the major contributing characters towards total genetic divergence. The crosses between the genotypes from cluster VI with II and VIII and cluster VIII with those of I, III and IV are likely to exhibit high heterosis and produce recombinants with desired traits in segregating generations. Srinivas et al. (2015) study on genetic diversity was conducted with seventy eight chilli (Capsicum frutescence L.) genotypes they were grouped into nine clusters on the basis of relative magnitude of D2 values using Euclidean 2 method. Cluster II accommodated maximum number (24) of genotypes and minimum with cluster III (1 genotype).The inter cluster distances (D values) ranged between 3.90 to12.68. Minimum inter cluster distance was between cluster II and IV (3.90) and maximum inter cluster distance was observed between cluster VII and VIII (12.68). The intra cluster divergence varied from 3.32 to 5.45. Maximum intra cluster distance was achieved in cluster VIII (5.45) and minimum divergence was observed in cluster V (3.32). Cluster III was showed zero intra cluster distance as it contains only one genotype. The maximum relative contribution to the total divergence was made by fruit yield per plant (61.07 %) and cluster VIII and cluster IX may be taken into consideration as better parents for an efficient hybridization programme of chilli. Janaki et al. (2016) conducted a study on D2 statistics to estimate the genetic divergence with sixty-three chilli genotypes and grouped into eight clusters. The maximum contribution towards genetic divergence was by fruit diameter (44.14%) followed by
yellow carotenoids (16.90%), red carotenoids (10.45%), ascorbic acid (10.19%) and capsaicin (9.17%). The mutual relationships between the clusters revealed that inter-cluster distance values were greater than intra-cluster values. Among the clusters, clusters III and V were the largest containing 17 genotypes followed by cluster IV (11) whereas the clusters VI, VII and VIII were mono genotypic (1 genotype). The highest inter cluster distance was observed between clusters IV and VIII (4139.41) whereas the lowest was observed between clusters I and III (117.25). Cluster V (434.43) has exhibited highest intra cluster distance and the lowest was observed in clusters VI, VII and VIII (0.00). D2 cluster analysis revealed wide genetic distance (inter cluster) between the genotypes of cluster IV (LCA-353, LCA716, LCA-756, LCA-724, LCA-714, Pusa Sadabahar, Pant C-1, LCA-758, G-4, LCA-738 and LCA-760) and VIII (Warangal chapatta) and the crossing between genotypes of these two clusters can be exploited for the development of heterotic hybrids in future breeding programmes.
Chapter-3
MATERIAL AND METHODS
CHAPTER-3 MATERIALS AND METHODS
The present investigation entitled “Selection Parameters and Genetic Divergence Analysis in Chilli (Capsicum annuum L. var. acuminatum Fingerh.)” was carried out during Kharif 2015 at Vegetable Research and Demonstration Block of the Department of Vegetable Science, College of Horticulture, VCSG Uttarakhand University of Horticulture and Forestry, Bharsar, Pauri Garhwal, Uttarakhand. The experimental details of materials and methodology adopted during the entire course are given as follows: 3.1
EXPERIMENTAL SITE
3.1.1 Location The present study was carried out at Vegetable Research Farm of the Department of Vegetable Science, College of Horticulture, VCSG Uttarakhand University of Horticulture and Forestry, Bharsar, Pauri Garhwal, Uttarakhand. The experimental site is located at Bharsar, at an altitude of 1950 m above mean sea level lying between latitude 290 30.0560 north and longitude 78.990 east. It falls under the mid- hill zone of Uttarakhand (Bisht and Sharma, 2014). 3.1.2 Climate Climate of the area is generally sub-temperate and sub-humid characterized by cold winters. The important meteorological observations during the period of investigation have been presented in Appendix-I. May and July were the hottest months. The precipitation ranged between 573.5-4278 mm during the crop season, most of which is received during the monsoon season (July-August). Mean temperature during the crop season varied from 18.50C to 28.160C, while the relative humidity varied from 15.00-99.00 per cent. 3.2
EXPERIMENTAL DETAILS
3.2.1 Cultivar Twenty five diverse genotypes of chilli including one check cultivar (Pant C-1) were used for the present investigations. The genotypes along with their sources are presented in Table 3.1.
Table 3.1 List of chilli genotypes to be used in the study Sr. No.
Genotype
1.
LC-1
Jodhpur chilli, Rajasthan
2.
LC-2
Ajmer, Rajasthan
3.
LC-3
Pali, Rajasthan
4.
LC-4
Bharatpur, Rajasthan
5.
LC-5
Pantnagar, Uttarakhand
6.
LC-6
Nainital, Uttarakhand
7.
LC-7
Ranichauri, Uttarakhand
8.
LC-8
Rishikesh, Uttarakhand
9.
LC-9
Srinagar, Uttarakhand
10.
70-F-BR-14
Local market
11.
Paprika
IARI- RS, Katrain
12.
Byadgi dabbi
KRCCH, Arabhavi, Karnataka
13.
Byadgi kaddi
KRCCH, Arabhavi, Karnataka
14.
Surya
Local market
15.
Arka Suphal
IIHR, Bangaluru, Karnataka
16.
Arka Lohit
IIHR, Bangaluru, Karnataka
17.
G-4
IIVR, Varanasi, (UP)
18.
K-1
IIVR, Varanasi, (UP)
19.
DCC-24
ARS (Chilli), Karnataka
20.
DDC-239
ARS (Chilli), Karnataka
21.
DCC-187
ARS (Chilli), Karnataka
22.
DCC-52
ARS (Chilli), Karnataka
23
DCC-27
ARS (Chilli), Karnataka
24.
Long chilli
KAU, Kerala
25.
Pant C-1*
*Check cultivar
Source
G.B.P.U.A.T, Pantnagar, Uttarakhand
Table 3.2 Allotment of treatments in experiment field under RCBD Replication-1
Replication-2
Replication-3
T-4
T-13
T-8
T-11
T-15
T-9
T-8
T-11
T-13
T-12
T-5
T-14
T-13
T-6
T-1
T-25
T-17
T-18
T-10
T-2
T-3
T-1
T-10
T-2
T-7
T-4
T-17
T-23
T-8
T-16
T-17
T-1
T-19
T-19
T-14
T-21
T-18
T-24
T-22
T-5
T-23
T-20
T-20
T-21
T-24
T-16
T-19
T-5
T-22
T-20
T-15
T-9
T-22
T-23
T-14
T-18
T-12
T-2
T-16
T-11
T-15
T-7
T-10
T-3
T-12
T-6
T-6
T-3
T-7
T-24
T-9
T-25
T-21
T-18
T-4
3.2.2 SEED SOWING AND RAISING OF SEEDLINGS IN NURSERY The seed sowing of all the genotypes was carried out on February 20, 2015 in the raised nursery bed. Recommended cultural practices were followed for raising the healthy nursery. 3.2.3 EXPERIMENTAL LAYOUT The experiment was laid out in Randomized Complete Block Design (RCBD) comprising of twenty five genotypes, with three replications of each entry. Transplanting was done on April 25, 2015.in a plot having size 1.35 m x 1.2 m (1.62 m2) at a spacing of 45 cm x 30 cm accommodating 12 plants per plot. The standard cultural practices recommended in the Package of Practices of Vegetable Crops were followed to grow a healthy crop stand. Besides the application of Farm Yard Manure @ 20 t/ha, chemical fertilizers were applied as per the recommendation of package of practices i.e. 120 kg N, 60 kg P2O5 and 50 kg K2O/ha. One third dose of N and full doses of P2O5 and K2O were applied at the time of field preparations. Remaining two-third dose of N was top dressed in equal amounts after 30 and 60 days after transplanting. The remaining intercultural operations were carried out in accordance with the recommended package of practices. 3.3
OBSRVATIONS RECORDED The observations were recorded from five randomly selected plants in each
replication for all characters except for fruit characters for which observations were recorded on ten randomly selected fruits per plot. The characters studied were: 3.3.1 Number of branches per plant Number of branches arising from the main stem above the ground level at harvest was recorded and expressed as numbers. 3.3.2 Number of primary branches The number of primary branches arising from main stem was recorded. 3.3.3 Plant height (cm) Plant height was measured at the end of the crop season i.e., at the start of leaf senescence; from the soil level to the highest tip of the plant and mean height was expressed in centimeters.
3.3.4 Plant stem girth (cm) Stem girth was measured with the help of Digital Vernier Caliper at final harvest. 3.3.5 Days taken for first flowering Days was counted from the date of transplanting to appearance of the first flower in each replicated plot and recorded as number of days taken for first flowering. 3.3.6 Days for 50% flowering Number of days taken from transplanting to the appearance of flowers in 50% of plants in each experimental plot was recorded as days to 50% flowering. 3.3.7 Days to first harvest Total number of days taken from the date of transplanting to fully developed green/coloured stage for picking in each treatment was expressed as days to first fruit harvesting. 3.3.8 Number of fruits per plant The total number of fruits harvested at every picking from randomly selected five plants was taken into consideration to work out as mean number of fruits per plant in each plot. 3.3.9 Average fruit weight (g) The average fruit weight was calculated by dividing the total marketable fruit yield of selected plants with total number of fruits for each treatment and was expressed in grams. 3.3.10 Fruit length (cm) The length of ten randomly selected fruits from each plot was measured with the help of Digital Vernier Caliper and average fruit length was calculated. 3.3.11 Fruit breadth (cm) The fruits used for recording the length was used for breadth measurement and the mean value was worked out. 3.3.12 Fruit pericarp thickness (mm) Pericarp thickness of ten randomly taken fruits of second harvest in each entry was measured after cutting the fruits transversely. Measurement was done with Digital Vernier Caliper in millimeters and mean value was worked out.
3.3.13 Number of seeds per fruit (g) The seeds from the fruits were separated by splitting the fruits and their number was recorded by counting with mean value estimation from seeds of ten separate fruits. 3.3.14 Ascorbic acid content (mg/100g) Ascorbic acid estimated by using 2-6-dichlorophenol indo-phenol visual titration method. The 5 g fruits were crushed and diluted with 50 ml of 3% metaphosphoric acid upto and final volume made to 100 ml. 10 ml of aliquot is titrated against 2,6 dichlorophenol indo phenol dye solution till light pink colour appeared within 10 second of titration. This is expressed in terms of mg/100g by using the following formula: Titre value x Dye factor x Volume made up x 100 Ascorbic acid (mg/100 g) = Aliquot of extract taken for estimation
x
Volume made up taken for estimation
3.3.15 Marketable fruit yield per plant (g), per plot (kg), and per hectare (q) The pickings were made at green stage for recording fruit yield per plant. Fruit yield was recorded at every picking in grams and added up for all the pickings to arrive at the total yield per plant. The total yield per plant was multiplied with total number of plants per plot to obtained yield per plot in kilograms. The total yield per plot was multiplied with total number of plants accommodated per hectare to obtained yield per hectare. 3.4
STATISTICAL ANALYSIS The statistical analysis was carried out for each observed character under the study
using MS-Excel, OPSTAT and SPAR 1.0 packages. The mean values of data were subjected to analysis of variance as described by Gomez and Gomez (1983) for Randomized Block Design (RBD). For estimation of different statistical parameters, following procedure and formulae were adopted:
3.4.1 Analysis of variance Source of
Degree of
Sum of
variance
freedom
squares
Replication (r)
r-1
Sr
Sr/(r-1)
= Mr
Mr/Me
Genotypes (g)
g-1
Sg
Sg/(g-1)
= Mg
Mg/Me
(r-1) (g-1)
Se
Se/(r-1) (g-1) = Me
Error (e)
Mean sum of squares
Variance ratio (V.R.)
Where, r
=
Number of replications
g
=
Number of genotypes
Sr
=
Sum of squares due to replications
Sg
=
Sum of squares due to genotypes
Se
=
Sum of squares due to error
Mr
=
Mean sum of squares due to replications
Mg
=
Mean sum of squares due to genotypes
Me
=
Mean sum of squares due to error
The calculated F-value was compared with tabulated F-value. When F-test was found significant, critical difference was calculated to find out the superiority of one entry over the others. The standard error and critical differences were calculated as follows: SE (m) ±
=
Me/r
SE (d) ±
=
2 Me/r
CD0.05
=
S.E. (d) x t (0.05) (r-1) (g-1) df
SE (m) ±
=
Standard error of mean
SE (d) ±
=
Standard error of difference
CD0.05
=
Critical difference at 5 per cent level of significance
Where,
All the traits, which differed significantly, were utilized further for estimation of following genetic parameters:
3.7.2
Mean performance and genetic variation
3.7.3
Heritability (in broad sense)
3.7.4
Genetic advance (GA)
3.7.5
Genetic gain (GG)
3.7.6
Correlation coefficients
3.7.7
Path analysis
3.7.8
Genetic divergence (D2 analysis)
3.4.2 Mean performance and genetic variation The Genotypic and Phenotypic Coefficients of variation were calculated as per formulae given by Burton and De-Vane (1953). A) Genotypic Coefficient of variation (GCV)
GCV (%)
Genotypicvariance (Vg)
=
General mean of population ( x )
x 100
B) Phenotypic Coefficient of variation (PCV)
PCV (%)
Phenotypicvariance (Vp)
=
General mean of population ( x )
x 100
3.4.3 Heritability (in broad sense) Heritability in broad sense was calculated by the formula as suggested by Allard (1960). Heritability (%)
=
Vg Vp
x
100
Where, Vg
=
Genotypic variance [Vg = (Mg - Me) / r]
Vp
=
Phenotypic variance [Vg + Ve]
3.4.4 Genetic advance (GA) The expected genetic advance (GA) resulting from selection of five per cent superior individuals was worked out as suggested by Allard (1960). Genetic advance = H x ϭ p x K
Where, K
=
2.06 (Selection differential at 5 per cent selection index)
ϭp
=
Phenotypic standard deviation
H
=
Heritability in broad sense
3.4.5 Genetic gain (GG) Genetic gain expressed as per cent ratio of genetic advance and population mean was calculated by the method given by Johanson et al. (1955). Genetic gain (%)
=
Genetic advance General mean of population ( x )
x 100
For categorizing the magnitude of different parameters, Sharma (1994) suggested the following limits:
PCV and GCV > 30% - High 15-30% - Moderate 80% - High 50-80% - Moderate < 50% - Low
Genetic gain (GG) >50% - High 25-50% - Moderate < 25% - Low
3.4.6 Correlations The genotypic and phenotypic correlations were calculated as per Al-Jibouri et al. (1958) by using analysis of variance and covariance matrix in which total variation has splited into replications, genotypes and errors. All the components of variance were estimated from the analysis of covariance as given below:
3.4.6.1 Analysis of Variance and Covariance Mean sum of Source of
Degree of
variance
freedom
Mean sum of
squares
products X
Y
Replications (r)
r-1
Genotypes (g)
g-1
Mg X
Mg Y
Mg XY = MP1
(r-1) (g-1)
Me X
Me Y
Me XY = MP2
Error (e)
Variance
MP1/MP2
Genotypic, phenotypic and environmental covariances between X and Y characters were worked out as under: Ve XY
=
MP2
Vg XY
=
(MP1-MP2) / r
Vp XY
=
Vg XY + Ve XY
Ve XY
=
Environmental covariance between X and Y
Vg XY
=
Genetic covariance between X and Y
Vp XY
=
Phenotypic covariance between X and Y
Where,
3.8.6.2 Coefficients of correlation a) Genotypic correlation coefficient between X and Y rg =
Vg XY Vg X x Vg Y
Where, Vg XY
=
Genotypic covariance between X and Y
Vg X
=
Genotypic variance of X
Vg Y
=
Genotypic variance of Y
b) Phenotypic correlation coefficient between X and Y rp =
Vp XY Vp X x Vp Y
Where, Vp XY
=
Phenotypic covariance between X and Y
Vp X
=
Phenotypic variance of X
Vp Y
=
Phenotypic variance of Y
Genotypic variance (Vg)
=
(Mg-Me) / r
Phenotypic variance (Vp)
=
(Vg+ve)
The calculated correlation coefficients (r) values were compared with ‘r’ tabulated values as given by Fisher and Yates (1963) at (n-2) degrees of freedom to test their significance, where ‘n’ denotes number of genotypes. If calculated ‘r’ value at 5 per cent level of significance was greater than tabulated value of ‘r’, the correlation was said to be significant. 3.4.7 Path coefficient analysis The genotypic and phenotypic correlation coefficients were used in finding out their direct and indirect contribution towards yield per plot. The direct and indirect paths were obtained by following Dewey and Lu (1959). The path coefficients were obtained by simultaneous selection of the following equations, which express the basic relationship between genotypic correlation ‘r’ and path coefficients (P). r14 : P14 + P24 r12 + P34 r13 r24 : P14 r21 + P24 + P34 r23 r34 : P14 r31 + P24 r32 + P34 Where, r14, r24 and r34 are genotypic correlations of component characters with yield (dependent variable) and r12, r13 and r23 are the genotypic correlations among component characters (independent variables).
The direct effects were calculated by the following set of equations: P14 = C11 r14 + C12 r24 + C13 r34 P24 = C21 r14 + C22 r24 + C23 r34 P34 = C31 r14 + C32 r24 + C33 r34 Where, C11, C22, C23 and C33 are constants derived by using abbreviated Doulittle’s technique as explained by Goulden (1959). r12 P24, r13 P34, r21 P14, r23 P34, r31 P14, r32 P24 are indirect effects. Residual effect The variation in the dependent variable which remained undetermined by including all the variables was assumed to be due to variable (s) not included in the present investigation. The degree of determination of such variable (s) on dependent variable was calculated as follows: 1 = P2x4 + P142 + P242 + P342 + 2P14 r12 P24 + 2P14 r13 P34 + 2P24 r23 P34 3.4.8. Diversity analysis 3.4.8.1 Estimation of genetic divergence The genetic divergence in 25 chilli genotypes was estimated by Mahalanobis D2 (1936) statistics (Generalized distance as suggested by Rao 1952). Transformation of original means of various characters to uncorrelated varieties as carried out by pivotal condensation method as the common dispersion matrix by using computer. This made D2 value as simple sum of squares of differences in transformed values for various characters. The D2 values which determine the statistical distance among various genotypes reflecting their genetic diversity was estimated for each pair of genotypes under study. The calculation of D2 values involved following steps (Murty and Arunachalam, 1966). I.
A set of uncorrelated linear combination (Y,s) was obtained by pivotal condensation of the common dispersion matrix (Rao 1952) of a set of correlated variables (X,s; the common dispersion matrix was arranged with the help of error mean of squares and sum of products).
II.
Using the relationship between Y,s and X,s the mean values of different characters (X1 to Xn) were transformed into the mean values of a set of uncorrelated linear combination (Y1 to Yn).
III.
The D2 values between ith and jth lines for kth character is calculated as under: D2ij = Σkt=1 (Yit - Yjt) i.
The ‘K’ component and D2 for each combination were ranked in descending order of magnitude.
ii.
D-square values over all combinations were obtained.
3.4.8.2 Clustering/Group Constellation Based on D2 values (Mahalanobis, 1936) lines were grouped into a number of clusters. D2 being treated as the square of generalized distance, according to the method described by non-hierarchical Euclidean cluster analysis. Criterion used in clustering by this method is that any line belonging to the same cluster showed, at least on an average, a smaller D2 value than those belonging to two different clusters. The first step of grouping their genotypes into distinct clusters was to arrange them in order of their relative distance from each other. Two populations having the smallest distance from each other were considered first, to which a third population was added having a smallest average D2 value but higher than the previous two. Similarly, the next population was added and the process continued till average D2 value increased considerably with the next addition. At certain stage, when it was felt that after adding a particular population, if there was an abrupt increase in their average value this population was not added in that cluster. Similarly, a second cluster was formed. D2 values of all possible combination of genotypes in one cluster with those in other was computed and its square root was use to represent the statistical distance between two cluster. The cluster mean for each of the characters was calculated by averaging the total mean values of each member belonging to that cluster and inter and intra cluster distances values were also calculated as under: Average intra-cluster distances (D=√D2)
Where, ∑Di2 = Sum of distances between all possible combinations of the populations included in a cluster
n
= Number of populations in a cluster
Average inter-cluster distances (D=√D2)
Where, ∑Dij2 = Sum of distances between all possible combinations of the two cluster ni = Number of populations in ith cluster nj = Number of populations in jth cluster
Chapter-4
EXPERIMENTAL RESULTS
CHAPTER-4 EXPERIMENTAL RESULTS The present investigation entitled “Selection Parameters and Genetic Divergence Analysis in Chilli (Capsicum annuum L. var. acuminatum Fingerh.)” was carried out in twenty five diverse genotypes of chilli including one check cultivar (Pant C-1) collected from different indigenous sources, for yield and yield contributing traits. The experimental results so obtained have been presented under the following subheads: 4.1 Variability Studies 4.1.1 Mean performance of genotypes 4.1.2 Parameters of variability 4.2 Correlation studies 4.2.1 Phenotypic correlations 4.2.2 Genotypic correlations 4.3 Path coefficient analysis 4.4 Genetic divergence studies 4.1 VARIABILITY STUDIES 4.1.1 Mean performance of genotypes The analysis of variance indicated highly significant differences among the genotypes for all the traits studied (Appendix-II), which revealed the existence of good deal of variability in the germplasm. The mean performance of all the genotypes for various traits under study has been described as below: 4.1.1.1 Number of branches per plant The perusal of data presented in table 4.1 revealed significant variations for number of branches (Appendix-II). It ranged from 6.12–12.83. General mean for the character was 10.09. Thirteen genotypes including the check cultivar were found to have more number of branches than population mean. Maximum number of branches was recorded in DCC-27 (12.83) and it was found statistically at par with nine genotypes viz., 70-F-BR-14 (12.60), Long chilli (12.60) and LC-4 (12.59). In the mean while, significantly minimum number of branches was observed in the genotype Paprika (6.12). ) and it was found statistically at par with five genotypes viz., Byadgi kaddi (6.82), Byadgi dabbi (6.59) and DDC-239 (6.9).
Amongst all the genotypes under study, nine genotypes were found to have more than check cultivar Pant C-1 (11.47). Table 4.1 Mean performance of chilli genotypes for different horticultural traits. Sr. No. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25.
Genotype
LC-1 LC-2 LC-3 LC-4 LC-5 LC-6 LC-7 LC-8 LC-9 70-F-BR-14 Paprika Byadgi kaddi Byadgi dabbi Surya Arka Suphal Arka Lohit G-4 K-1 DCC-24 DDC-239 DCC-187 DCC-52 DCC-27 Long chilli Pant C-1* Mean SE(d) CD (0.05) *Check cultivar
Number of branches per plant ±SE(m) 11.65 ± 0.48 11.97 ± 0.58 12.22 ± 0.21 12.59 ± 0.73 9.50 ± 0.58 9.38 ± 0.33 10.91 ± 0.33 9.27 ± 0.60 9.05 ± 0.28 12.60 ± 0.28 6.12 ± 0.11 6.82 ± 0.23 6.59 ± 0.54 7.18 ± 0.21 8.86 ± 0.42 12.03 ± 0.81 9.74 ± 0.61 10.98 ± 0.40 12.27 ± 0.64 6.90 ± 0.314 7.53 ± 0.75 11.20 ± 0.58 12.83 ± 0.41 12.60 ± 0.42 11.47 ± 0.61 10.09 0.71 1.50
Number of primary branches ±SE(m) 3.67 ± 0.29 3.73 ± 0.35 4.07 ± 0.35 5.44 ± 0.58 4.00 ± 0.30 4.67 ± 0.29 5.87 ± 0.17 4.93 ± 0.24 4.13 ± 0.40 6.33 ± 0.29 3.67 ± 0.29 3.87 ± 0.29 4.27 ± 0.52 3.73 ± 0.29 4.53 ± 0.40 6.40 ± 0.61 5.47 ± 0.17 6.93 ± 0.37 7.67 ± 0.37 3.80 ± 0.23 3.47 ± 0.48 6.13 ± 0.17 7.20 ± 0.23 7.27 ± 0.24 6.47 ± 0.17 5.11 0.48 1.01
Plant height (cm) ±SE(m) 81.33 ± 0.59 86.93 ± 1.88 92.93 ± 1.91 82.07 ± 2.05 91.77 ± 2.44 92.47 ± 3.04 96.53 ± 1.56 77.87 ± 2.71 81.17 ± 2.15 86.87 ± 3.48 77.80 ± 2.55 80.73 ± 2.22 82.07 ± 1.53 78.73 ± 2.66 58.93 ± 1.34 62.60 ± 1.84 76.67 ± 3.39 72.47 ± 1.43 73.13 ± 1.64 68.73 ± 2.44 72.33 ± 2.08 83.40 ± 0.64 69.87 ± 1.27 68.93 ± 1.69 85.77 ± 2.27 79.28 2.86 6.06
4.1.1.2 Number of primary branches Significant variations were observed among all the genotypes for number of primary
branches (Appendix-II). Number of primary branches ranged from 3.47–7.67 (Table 4.1). General mean for the character was 5.11. Eleven genotypes including the check cultivar were found to have more number of primary branches than population mean. Maximum number of primary branches was recorded in DCC-24 (7.67) and it was
found statistically at par with three genotype viz., Long chilli (7.27), DCC-27 (7.20) and K1 (6.93). In the mean while, significantly minimum number of primary branches was observed in the genotype DCC-187 (3.47) and it was found statistically at par with nine genotype viz., LC-1 (3.67), Paprika (3.67) and Surya (3.73). Amongst all the genotypes under study, four genotypes were found to have more than check cultivar Pant C-1 (6.47). 4.1.1.3 Plant height (cm) All the genotypes studied indicated significant variations for plant height (Appendix-II). It ranged from 58.93–96.53 cm (Table 4.1). General mean for the character was 79.28 cm. Thirteen genotypes including check cultivar had more plant height than population mean. Significantly maximum plant height was recorded in LC-7 (96.53), and it was found statistically at par with three genotype viz., LC-3 (92.93), LC-6 (92.47) and LC5 (91.77), while minimum was observed in Arka Suphal (58.93) and it was found statistically at par with Arka Lohit (62.60). In overall, six genotypes had more plant height than check cultivar Pant C-1 (85.77). 4.1.1.4 Plant stem girth (cm) The perusal of data presented in table 4.2 revealed significant variations for days plant stem girth (Appendix-II). It ranged from 2.32–3.72 cm. General mean for the character was 2.96 cm. Fourteen genotypes including the check cultivar had higher plant stem girth than population mean. Maximum plant stem girth was recorded in LC-4 (3.72) and it was found statistically at par with three genotype viz., G-4 (3.46), Byadgi dabbi (3.38), and K-1 (3.37). Whereas minimum plant stem girth was observed in DCC-187 (2.32) and it was statistically at par with 5 genotype viz., Arka Suphal (2.41), DDC-239 (2.45) and DCC-27 (2.49). Seven genotypes gave higher plant stem girth than check cultivar Pant C-1 (3.13). 4.1.1.5 Days to first flowering Significant variations were observed among all the genotypes for days to first
flowering (Appendix-II). Days to first flowering ranged from 35.67–44.67 days (Table 4.2). General mean for the character was 39.03 days. Fourteen genotypes including check cultivar were found to have earlier days to first flowering than population mean. Maximum days to first flowering were recorded in DCC-24 (44.67) and it was found statistically at par with LC-7 (44.00) and it was found most significant for the trait under study. In the
mean while, significantly minimum days to first flowering was observed in the genotype LC-1 and Byadgi kaddi (35.67) and it was found statistically at par with eleven genotype viz., Byadgi dabbi (36.00), LC-6 (36.67) and Arka Suphal (37.33). Amongst all the genotypes under study, nine genotypes were found to have earlier than check cultivar Pant C-1 (38.33). Table 4.2 Mean performance of chilli genotypes for different horticultural traits. Genotype Sr. No. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25.
LC-1 LC-2 LC-3 LC-4 LC-5 LC-6 LC-7 LC-8 LC-9 70-F-BR-14 Paprika Byadgi kaddi Byadgi dabbi Surya Arka Suphal Arka Lohit G-4 K-1 DCC-24 DDC-239 DCC-187 DCC-52 DCC-27 Long chilli Pant C-1* Mean SE(d) CD (0.05) *Check cultivar
Plant stem girth (cm) ±SE(m)
Days to first Flowering ±SE(m)
Days to 50% Flowering ±SE(m)
3.11 ± 0.12 3.30 ± 0.14 2.99 ± 0.15 3.72 ± 0.17 2.99 ± 0.11 3.30 ± 0.13 2.86 ± 0.27 3.03 ± 0.18 2.85 ± 0.05 2.87 ± 0.07 3.26 ± 0.12 2.57 ± 0.29 3.38 ± 0.23 3.01 ± 0.12 2.41 ± 0.10 2.47 ± 0.11 3.46 ± 0.24 3.37 ± 0.22 3.04 ± 0.21 2.45 ± 0.16 2.32 ± 0.13 2.76 ± 0.07 2.49± 0.16 2.77± 0.16 3.13± 0.17 2.96 0.18 0.37
35.67 ± 1.20 37.67 ± 0.88 40.33 ± 1.20 39.33 ± 1.45 41.00 ± 1.52 36.67 ± 0.88 44.00 ± 1.15 38.67 ± 0.88 38.00 ± 1.16 41.33 ± 0.88 39.33 ± 0.88 35.67 ± 0.88 36.00 ± 0.58 39.67 ± 1.20 37.33 ± 1.45 38.67 ± 1.20 39.00 ± 1.15 38.67 ± 1.46 44.67 ± 0.88 37.33 ± 0.88 39.67 ± 0.88 38.00 ± 1.16 39.67 ± 0.88 41.00 ± 1.15 38.33 ± 0.88 39.03 1.51 3.18
52.67 ± 1.76 51.00 ± 1.52 52.00 ± 0.57 54.33 ± 2.18 53.33 ± 1.76 52.67 ± 0.88 53.34 ± 0.88 55.00 ± 1.52 54.00 ± 1.52 52.00 ± 1.73 51.34 ± 0.88 47.67 ± 1.45 53.00 ± 1.53 47.67 ± 0.88 56.34 ± 0.88 53.67 ± 1.20 52.33 ± 1.45 54.33 ± 1.77 57.67 ± 1.86 51.33 ± 1.20 59.67 ± 1.45 55.33 ± 1.76 52.00 ± 1.53 54.67 ± 1.21 53.00 ± 1.53 53.21 2.08 4.39
4.1.1.6 Days to 50% flowering The perusal of data presented in table 4.2 revealed significant variations for days to 50% flowering (Appendix-II). It ranged from 47.67–59.67 days. General mean for the
character was 53.21 days. Twelve genotypes including the check cultivar were found to have earlier days to 50% flowering than population mean. Maximum days to 50% flowering were recorded in DCC-187 (59.67) and it was found statistically at par with three genotype viz., DCC-24 (57.67), Arka Suphal (56.34) and DCC-52 (55.33). Significantly minimum days to 50% flowering were observed in the genotype Byadgi kaddi and Surya (47.67) and it was found statistically at par with seven genotype viz., LC-2 (51.00), Paprika (51.34) and DDC-239 (51.33). Amongst all the genotypes under study, eleven genotypes were found to have earlier than check cultivar Pant C-1 (53.00). Table 4.3 Mean performance of chilli genotypes for different horticultural traits. Sr. Genotype Days to first fruit Number of fruit Average fruit weight No. harvest ±SE(m) per plant ±SE(m) (g) ±SE(m) 64.00 ± 1.73 75.47 ± 2.53 3.12 ± 0.13 1. LC-1 65.67 ± 2.03 67.13 ± 3.08 3.45 ± 0.12 2. LC-2 67.67 ± 1.76 89.74 ± 2.28 1.48 ± 0.02 3. LC-3 71.33 ± 1.76 80.66 ± 1.36 2.54 ± 0.02 4. LC-4 69.33 ± 2.33 100.76 ± 2.16 1.38 ± 0.01 5. LC-5 69.67 ± 1.76 92.19 ± 2.12 2.37 ± 0.08 6. LC-6 67.67 ± 1.45 126.07 ± 2.62 1.16 ± 0.05 7. LC-7 69.67 ± 1.45 88.05 ± 2.60 2.75 ± 0.11 8. LC-8 67.00 ± 1.16 85.13 ± 2.59 2.26 ± 0.04 9. LC-9 68.33 ± 1.76 120.6± 1.75 1.38 ± 0.04 10. 70-F-BR-14 67.67 ± 2.60 36.85 ± 3.37 4.66 ± 0.47 11. Paprika 62.33 ± 1.77 56.59 ± 2.21 3.35 ± 0.15 12. Byadgi kaddi 67.33 ± 2.03 105.49 ± 2.55 2.11 ± 0.03 13. Byadgi dabbi 64.33 ± 1.45 109.49 ± 2.21 1.30 ± 0.01 14. Surya 66.67 ± 3.28 110.93 ± 2.03 1.26 ± 0.04 15. Arka Suphal 67.33 ± 2.03 97.15 ± 2.56 1.41 ± 0.01 16. Arka Lohit 64.67 ± 1.86 120.63 ± 2.48 1.39 ± 0.01 17. G-4 70.67 ± 1.45 89.75 ± 2.01 1.35 ± 0.02 18. K-1 73.67 ± 1.45 85.13 ± 2.43 1.30 ± 0.02 19. DCC-24 65.33 ± 1.86 77.84 ± 2.82 1.82 ± 0.09 20. DDC-239 72.67 ± 2.33 65.71 ± 2.29 2.20 ± 0.05 21. DCC-187 74.33 ± 1.76 77.84 ± 2.12 2.12 ± 0.03 22. DCC-52 68.33 ± 0.88 80.75 ± 1.69 2.19 ± 0.03 23. DCC-27 68.33 ± 3.53 105.56 ± 1.83 1.39 ± 0.05 24. Long chilli 72.33 ± 1.85 99.43 ±2.85 1.83 ± 0.07 25. Pant C-1* 68.25 89.77 2.06 Mean 2.78 3.31 0.16 SE(d) 5.88 7.00 0.32 CD (0.05) *Check cultivar
4.1.1.7 Days to first fruit harvesting Among all the genotypes a significant variations were observed for days to first fruit harvesting (Appendix-II). The mean performance of the genotypes ranged from 62.33-74.33 days (Table 4.3). General mean for the character was 68.25 days. Thirteen genotypes took lesser days to first fruit harvesting than the population mean. Minimum days to first fruit harvesting were recorded in the genotype Byadgi kaddi (62.33) and it was found statistically at par with twelve genotype viz., LC-1 (64.00), Surya (64.33) and G-4 (64.67). Whereas the genotype DCC-52 had taken maximum days to first fruit harvesting (74.33) and it was found statistically at par with eight genotype viz., DCC-24 (73.67), DCC-187 (72.67) and LC-4 (71.33). Amongst all the genotypes under study, twenty one genotypes were found earlier than check cultivar Pant C-1 (72.33) for days to first fruit harvesting. 4.1.1.8 Number of fruits per plant The observations recorded for this trait showed significant differences among all the genotypes (Appendix-II). The mean performance of the genotypes ranged from 36.85– 126.07 (Table 4.3). General mean for the character was 89.77. Eleven genotypes including check were recorded higher number of fruits per plant than the population mean. Significantly higher number of fruits per plant were observed in the genotype LC- 7 (126.07), which was found statistically at par with G-4 (120.63) and 70-F-BR-14 (120.6), while minimum number of fruits per plant were recorded in the genotype Paprika (36.85). Amongst all the genotypes under study, eight genotypes were found superior than check cultivar Pant C-1 (99.43) for number of fruits per plant. 4.1.1.9 Average fruit weight (g) The perusal of data presented in table 4.3 revealed significant variations for average fruit weight (Appendix-II). It ranged from 1.16–4.66 g. Population mean for the character observed was 2.06 g. Twelve genotypes produced higher average fruit weight than population mean. Significantly maximum average fruit weight was recorded in the genotype Paprika (4.66), while minimum was observed in LC-7 (1.16) and it was found statistically at par with nine genotypes viz., Arka Suphal (1.26), DCC-24 (1.30) and Long chilli (1.39). In the present studies, twelve genotypes were found superior over check cultivar Pant C-1 (1.83) for the trait under study.
4.1.1.10 Fruit length (cm) The perusal of data presented in table 4.4 revealed significant variations for fruit length (Appendix-II). It ranged from 4.83–13.26 cm. Population mean for the character observed was 9.09 cm. Ten genotypes including check cultivar produced longer fruits than population mean. Significantly maximum fruit length was recorded in the genotype LC-8 (13.26) and it was found statistically at par with LC-1 (13.16) and LC-2 (12.69), while minimum was observed in LC-7 (4.83) and it was found statistically at par with DCC-24 (5.59). In the present studies, fourteen genotypes were found superior over check cultivar Pant C-1 (7.77) for the trait under study. Table 4.4 Mean performance of chilli genotypes for different horticultural traits. Sr. No. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25.
Genotype
LC-1 LC-2 LC-3 LC-4 LC-5 LC-6 LC-7 LC-8 LC-9 70-F-BR-14 Paprika Byadgi kaddi Byadgi dabbi Surya Arka Suphal Arka Lohit G-4 K-1 DCC-24 DDC-239 DCC-187 DCC-52 DCC-27 Long Chilli Pant C-1* Mean SE(d) CD (0.05) *Check cultivar
Fruit length (cm) ±SE(m)
Fruit breath (cm) ±SE(m)
13.16 ± 0.24 12.69 ± 0.26 7.01 ± 0.38 11.05 ± 0.16 7.73 ± 0.24 11.67 ± 0.23 4.83 ± 0.33 13.26 ± 0.18 11.52 ± 0.51 7.93 ± 0.12 12.10 ± 0.43 12.34 ± 0.27 11.67 ± 0.23 6.87 ± 0.20 6.91 ± 0.11 6.74 ± 0.10 7.91 ± 0.65 6.81 ± 0.19 5.59 ± 0.15 7.21 ± 0.13 8.85 ± 0.19 8.53 ± 0.25 9.51 ± 0.13 7.63 ± 0.29 7.77 ± 0.11 9.09 0.38 0.81
1.42 ± 0.02 1.08 ± 0.10 1.22 ± 0.01 1.29 ± 0.12 1.69 ± 0.11 0.94 ± 0.05 1.33 ± 0.05 1.17 ± 0.03 1.57 ± 0.07 0.84 ± 0.05 2.75 ± 0.04 2.04 ± 0.05 1.26 ± 0.07 1.35 ± 0.06 1.35 ± 0.07 1.99 ± 0.11 0.86 ± 0.04 1.43 ± 0.04 1.34 ± 0.08 1.66 ± 0.03 1.96 ± 0.04 1.91 ± 0.04 1.79 ± 0.04 1.59 ± 0.03 1.13 ± 0.06 1.48 0.09 0.19
Fruit pericarp thickness (mm) ±SE(m) 1.40 ± 0.10 1.30 ± 0.01 1.03 ± 0.04 1.54 ± 0.02 0.82 ± 0.01 1.26 ± 0.02 0.56 ± 0.01 1.30 ± 0.12 1.33 ± 0.01 0.73 ± 0.01 2.81 ± 0.02 1.33 ± 0.04 1.32 ± 0.03 1.19 ± 0.05 0.93 ± 0.02 0.79 ± 0.01 0.85 ± 0.03 1.16 ± 0.02 1.10 ± 0.08 1.07 ± 0.05 1.15 ± 0.02 0.92 ± 0.02 1.09 ± 0.01 0.86 ± 0.02 1.14 ± 0.02 1.16 0.06 0.12
4.1.1.11 Fruit breadth (cm) Significant variations for fruit breadth were obtained among all the genotypes studied (Appendix-II). It varied from 0.84–2.75 cm (Table 4.4). General mean for the character was 1.48 cm. Ten genotypes had higher fruit breadth than population mean. Maximum fruit breadth was observed in the genotype Paprika (2.75). Significantly, minimum fruit breadth was recorded in 70-F-BR-14 (0.84) and it was found statistically at par with G-4 (0.86) and LC-6 (0.94). In overall, twenty genotypes were found superior than check cultivar Pant C-1 (1.13) for fruit breadth. 4.1.1.12 Fruit pericarp thickness (mm) All the genotypes studied revealed significant variations for the trait under study (Appendix-II). Pericarp thickness ranged from 0.56–2.81 mm (Table 4.4). General mean for the character was 1.16 mm. Ten genotypes including the higher pericarp thickness than population mean. Maximum pericarp thickness was observed in Paprika (2.81). In the mean while, minimum pericarp thickness was recorded in LC-7 (0.56). Twelve genotypes were found superior over check cultivar Pant C-1 (1.14) for this trait. 4.1.1.13 Number of seed per fruit The observations recorded for this trait showed significant differences among all the genotypes (Appendix-II). The mean performance of the genotypes ranged from 27.70– 108.47 (Table 4.5). General mean for the character was 65.81. Thirteen genotypes have higher number of seed per fruit than the population mean. Significantly higher number of seed per fruit were observed in the genotype LC- 2 (108.47), which was found statistically at par with DCC-187 (106.73), while minimum number of fruits per plant were recorded in the genotype 70-F-BR-14 (27.70). It was found statistically at par with Paprika (32.67). Amongst all the genotypes under study, fourteen genotypes were found superior than check cultivar Pant C-1 (63.80) for number of fruits per plant. 4.1.1.14 Ascorbic acid content (mg/100g) All the genotypes studied revealed significant variations for this character (Appendix-II). It ranged from 63.13–115.10 mg/100g (Table 4.5). General mean for the character was 93.33 mg/100g. Eleven genotypes including the check cultivar recorded higher ascorbic acid content than population mean. Maximum ascorbic acid was observed in the genotype DCC-27 (115.10) and it was found statistically at par with seven genotypes
LC-8 (Rishikesh)
Pant C-1
Surya
LC-6 (Nainital)
LC-2 (Ajmer)
Plate 1: Best genotypes identified on the basis of overall performance
viz., long chilli (112.07), Arka Suphal (111.73) and DCC-24 (106.70). While, significantly minimum ascorbic acid content was recorded in Paprika (63.13) and it was found statistically at par with genotypes Byadgi kaddi (74.73), In the present studies, seven genotypes were found better than check cultivar Pant C-1 (103.20) for ascorbic acid content in the fruits. Table 4.5 Mean performance of chilli genotypes for different horticultural traits. Sr. No. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25.
Genotype
LC-1 LC-2 LC-3 LC-4 LC-5 LC-6 LC-7 LC-8 LC-9 70-F-BR-14 Paprika Byadgi kaddi Byadgi dabbi Surya Arka Suphal Arka Lohit G-4 K-1 DCC-24 DDC-239 DCC-187 DCC-52 DCC-27 Long chilli Pant C-1* Mean SE(d) CD (0.05) *Check cultivar
Number of seed per fruit ±SE(m)
Ascorbic acid Content (mg/100g) ±SE(m)
86.47 ± 4.19 108.47 ± 7.16 64.27 ± 2.13 79.47 ± 4.59 46.40 ± 0.69 42.03 ± 1.86 75.93 ± 1.69 67.13 ± 2.34 72.47 ± 1.05 27.70 ± 2.63 32.27 ± 0.81 58.20 ± 2.11 78.27 ± 1.09 67.27 ± 0.74 38.00 ± 1.47 79.20 ± 1.82 43.40 ± 1.82 74.50 ± 1.07 59.53 ± 0.52 68.27 ± 1.09 106.73 ±3.49 63.20 ± 0.61 84.87 ± 0.87 57.47 ± 0.41 63.80 ± 0.72 65.81 3.23 6.84
94.73 ± 5.11 83.87 ± 2.81 86.30 ± 3.56 85.80 ± 4.05 93.47 ± 2.63 90.77 ± 2.72 86.60 ± 4.04 89.20 ± 4.91 88.80 ± 2.50 88.17 ± 3.78 63.13 ± 3.61 74.73 ± 4.80 88.47 ± 4.96 104.53 ± 3.99 111.73 ± 6.97 103.77 ± 3.32 95.43 ± 5.01 85.17 ± 3.38 106.70 ± 5.89 89.17 ± 3.65 87.90 ± 2.78 104.43 ± 4.06 115.10 ± 5.27 112.07 ± 1.87 103.20 ± 2.93 93.33 5.93 12.54
4.1.1.15 Marketable fruit yield per plant (g) All the genotypes studied revealed significant variations for this character (Appendix-II). It ranged from 110.51–241.99 g (Table 4.6). Population mean for the
character was 170.40 g. Eleven genotypes including check recorded higher marketable fruit yield per plant than the population mean. Maximum marketable fruit yield per plant was recorded in the genotype LC-8 (241.99). Minimum marketable fruit yield per plant was observed in DCC-24 (110.51). Amongst all the genotypes under study, eight genotypes viz., LC-8 (241.99), LC-1 (234.58), LC-2 (230.93), Byadgi dabbi (222.23), LC4 (205.12), LC-6 (217.71), LC-9 (191.80) and Byadgi kaddi (189.47) were found superior over check cultivar Pant C-1 (181.44) for marketable fruit yield per plant. Table 4.6 Mean performance of chilli genotypes for marketable yield. Sr. No. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25.
Genotype
LC-1 LC-2 LC-3 LC-4 LC-5 LC-6 LC-7 LC-8 LC-9 70-F-BR-14 Paprika Byadgi kaddi Byadgi dabbi Surya Arka Suphal Arka Lohit G-4 K-1 DCC-24 DDC-239 DCC-187 DCC-52 DCC-27 Long chilli Pant C-1* Mean SE(d) ± CD (0.05) *Check cultivar
Fruit yield per plant (g) ±SE(m) 234.58 ± 1.83 230.93 ± 3.54 132.03 ± 1.92 205.12 ± 1.98 138.63 ± 1.81 217.71 ± 2.14 146.30 ± 2.55 241.99 ± 1.88 191.80 ± 2.57 166.04 ± 2.98 170.43 ± 1.74 189.47 ± 1.59 222.23 ± 2.43 142.55 ± 2.48 140.06 ± 1.49 136.39 ± 2.70 167.54 ± 1.83 121.23 ± 1.70 110.51 ± 1.88 141.00 ± 2.07 144.60 ± 1.83 163.43 ± 2.27 177.38 ± 1.97 146.69 ± 2.28 181.44 ± 1.79 170.40 3.14 6.63
Fruit yield per plot (Kg) ±SE(m) 2.82 ± 0.02 2.78 ± 0.04 1.59 ± 0.02 2.47 ± 0.02 1.67 ± 0.02 2.62 ± 0.03 1.76 ± 0.04 2.91 ± 0.02 2.30 ± 0.03 2.00 ± 0.04 2.05 ± 0.02 2.28 ± 0.02 2.67 ± 0.03 1.71 ± 0.03 1.69 ± 0.02 1.64 ± 0.03 2.02 ± 0.02 1.46 ± 0.02 1.33 ± 0.02 1.70 ± 0.02 1.74 ± 0.03 1.97 ± 0.03 2.13 ± 0.02 1.76 ± 0.03 2.18 ± 0.02 2.05 0.06 0.11
Fruit yield per ha (q) ±SE(m) 139.25 ± 1.03 137.11 ± 2.17 78.51 ± 1.13 121.80 ± 1.15 82.46 ± 1.14 129.21 ± 1.28 86.74 ± 1.74 143.53 ± 0.99 113.74 ± 1.46 98.59 ± 1.71 101.22 ± 1.14 112.58 ± 0.85 132.01 ± 1.46 84.61 ± 1.43 83.29 ± 1.01 80.98 ± 1.59 99.59 ± 1.15 72.10 ± 0.85 65.68 ± 1.14 84.11 ± 1.46 85.76 ± 1.29 97.11 ± 1.44 105.34 ± 1.15 88.39 ± 2.53 107.81 ± 1.01 101.26 2.78 5.58
LC-1 (Jodhpur chilli)
Byadgi kaddi
Long chilli
LC-4 (Bharatpur)
Arka Lohit
Arka Suphal
Plate 2: Best genotypes identified on the basis of overall performance
4.1.1.16 Marketable fruit yield per plot (kg) Significant variations were observed among all the genotypes for marketable fruit yield per plot (Appendix-II). It varied from 1.33–2.91 kg (Table 4.6). General mean for the character was 2.05 kg. Ten genotypes including check higher marketable fruit yield per plant than the population mean. Maximum marketable fruit yield per plant was recorded in the genotype LC-8 (2.91) and it was found statistically at par LC-1 (2.82) and LC-2 (2.78). Minimum marketable fruit yield per plant was observed in DCC-24 (1.33 kg). Amongst all the genotypes under study eight genotypes viz., LC-8 (2.91), LC-1 (2.82), LC-2 (2.78), Byadgi dabbi (2.67), LC-4 (2.47), LC-6 (2.62), LC-9 (2.30) and Byadgi kaddi (2.28) were found superior over check cultivar Pant C-1 (2.18) for marketable fruit yield per plant. 4.1.1.17 Marketable fruit yield per hectare (q) The perusal of data presented in table 4.6 revealed significant variations for marketable fruit yield per hectare (Appendix-II). It ranged from 65.68–143.53 q and general mean value observed for the trait was 101.26 q. Ten genotypes including check recorded higher marketable fruit yield per hectare than the population mean. Maximum marketable fruit yield per plant was recorded in the genotype LC-8 (143.53) and it was found statistically at par LC-1 (139.25). Minimum marketable fruit yield per plant was observed in DCC-24 (65.68). Amongst all the genotypes under study, eight genotypes viz., LC-1 (139.25), LC-2 (137.11), Byadgi dabbi (132.01), LC-4 (121.80), LC-6 (129.21), LC9 (113.74) and Byadgi kaddi (112.58) were found superior over check cultivar Pant C-1 (107.81) for marketable fruit yield per plant. 4.1.2.1 Parameters of variability 4.1.2.1.1 Coefficients of variability The observed variations in all the genotypes for different traits under study are due to effect of genotype and environment. Environmental variations are not fixable. For determining the magnitude of genotypic and phenotypic variability, the genotypic and phenotypic coefficients of variability were calculated (Table 4.7). For all the characters studied, phenotypic coefficients of variability were higher in magnitude than genotypic coefficients of variability, though difference was very less in majority of cases. Thus, it was showing that these traits are less influenced by environmental factors. Coefficients of variability varied in magnitude from character to character, either low or moderate or high.
Therefore, it indicated that tremendous diversity is available within the available chilli germplasm. The phenotypic coefficients of variability (PCV) were found high for average fruit weight (42.89%), fruit pericarp thickness (36.45%) and number of seeds per fruit (31.42%). Whereas moderate phenotypic coefficients of variability were recorded for fruit breadth (29.93%), fruit length (28.47%), number of primary branches (28.16%), number of fruits per plant (23.63%), number of branches per plant (23.08%) and fruit yield per plant (22.20%), while phenotypic coefficients of variability were recorded low in magnitude for ascorbic acid content (14.43%), plant stem girth (13.80%), plant height (12.49%), days taken for first flowering (6.92%), days for 50% flowering (6.27%) and days to first harvest (6.07%). The genotypic coefficients of variability (GCV) were recorded high for average fruit weight (41.81%), fruit pericarp thickness (35.96%) and number of seeds per fruit (30.84%). Whereas moderate genotypic coefficients of variability were observed for fruit breadth (29.00%), fruit length (28.00%), number of primary branches (25.73%), number of fruits per plant (23.19%), number of branches per plant (21.41%) and fruit yield per plant (22.09%), while genotypic coefficients of variability were recorded low in magnitude for ascorbic acid content (12.16%), plant stem girth (11.72%), plant height (11.68%), days taken for first flowering (5.06%), days for 50% flowering (4.06%) and days to first harvest (3.45%). 4.1.2.1.2 Heritability The estimates of heritability (broad sense) varied from 32.37-98.97% for different traits under study (Table 4.7). It was found high for fruit yield per plant (98.97%), fruit pericarp thickness (97.35%), fruit length (96.71%), number of fruits per plant (96.35%), number of seeds per fruit (96.35%), average fruit weight (95.04%), fruit breadth (93.86%), plant height (87.46%), number of branches per plant (86.05%) and number of primary branches (83.52%), whereas moderate heritability was observed for plant stem girth (72.04%), ascorbic acid content (70.93%) and days taken for first flowering (53.42%), whereas it was recorded low for days for 50% flowering (41.89%) and days to first harvest (32.37%).
Table 4.7 Estimates of phenotypic and genotypic coefficients of variation, heritability, genetic advance and genetic gain for different traits in Chilli Sr. No.
Characters
Range
Mean
Coefficients of variability (%) Phenotypic Genotypic
Heritability (%)
Genetic gain (%)
Genetic Advance
1.
Number of branches per plant
6.12–12.83
10.09
23.08
21.41
86.05
40.92
4.13
2.
Number of primary branches
3.47–7.67
5.11
28.16
25.73
83.52
48.45
2.48
3.
Plant height (cm)
58.93–96.53
79.28
12.49
11.68
87.46
22.51
17.84
4.
Plant stem girth (cm)
2.32–3.72
2.96
13.80
11.72
72.04
20.48
0.61
5.
Days taken for first flowering
35.67–44.67
39.03
6.92
5.06
53.42
7.61
2.97
6.
Days for 50% flowering
47.67–59.67
53.21
6.27
4.06
41.89
5.41
2.88
7.
Days to first harvest
62.33–74.33
68.25
6.07
3.45
32.37
4.05
2.76
8.
Number of fruits per plant
36.85–126.07
89.77
23.63
23.19
96.35
46.90
42.10
9.
Average fruit weight (g)
1.16–4.66
2.06
42.89
41.81
95.04
83.98
1.73
10.
Fruit length (cm)
4.83–13.26
9.09
28.47
28.00
96.71
56.72
5.16
11.
Fruit breadth (cm)
0.84–2.75
1.48
29.93
29.00
93.86
57.87
0.86
12.
Fruit pericarp thickness (mm)
0.56–2.81
1.16
36.45
35.96
97.35
73.09
0.85
13.
Number of seeds per fruit
27.70–108.47
65.81
31.42
30.84
96.34
62.36
41.04
14.
Ascorbic acid content (mg/100g)
63.13–115.10
93.33
14.43
12.16
70.93
21.09
19.68
15.
Fruit yield per plant (g)
110.51–241.99
170.40
22.20
22.09
98.97
45.27
77.14
16.
Fruit yield per plot (Kg)
1.33–2.91
2.05
22.17
22.05
98.96
45.19
0.93
17.
Fruit yield per hector (q)
65.68–143.53
101.26
22.12
21.99
98.82
45.03
45.59
4.1.2.1.3 Genetic advance and genetic gain Genetic gain (expressed as per cent of population mean) was low to high in nature and ranged from 4.05-83.98% for different traits under study (Table 4.7). It was found high for average fruit weight (83.98%), fruit pericarp thickness (73.09%), number of seeds per fruit (62.36%), fruit breadth (57.87%) and fruit length (56.72%), whereas moderate heritability was observed for number of primary branches (48.45%), number of fruits per plant (46.90%), fruit yield per plant (45.27%) and number of branches per plant (40.92%), whereas it was recorded low for plant height (22.51%), ascorbic acid content (21.09%), plant stem girth (20.48%), days taken for first flowering (7.61%), days for 50% flowering (5.41%) and days to first harvest (4.05%). 4.2 Correlation studies The correlation coefficients among the different characters were worked out at phenotypic and genotypic levels (Table 4.8). In general, the genotypic correlation coefficients were higher in magnitude than phenotypic correlation coefficients. The phenotypic correlation coefficients among different characters showed that marketable yield per plant had significantly positive association with fruit length (0.882), average fruit weight (0.624), plant stem girth (0.360), fruit pericarp thickness (0.348), number of primary branches (0.316), plant height (0.294), fruit breadth (0.235), number of fruits per plant (0.227), while significantly negative correlations were observed with days taken for first flowering (-0.491) and ascorbic acid content (-0.249), respectively. The genotypic correlation coefficients among different characters showed that marketable yield per plant had significantly positive association with fruit length (0.898), average fruit weight (0.641), plant stem girth (0.419), fruit pericarp thickness (0.356), number of primary branches (0.349), plant height (0.322), number of fruits per plant (0.236), fruit breadth (0.240) and number of seeds per fruit (0.226).While significantly negative correlations were observed with days taken for first flowering (-0.667), days to first harvest (-0.287), days for 50% flowering (-0.269) and ascorbic acid content (-0.297), respectively, Beside this, fruit length resulted in positive and significant association with average fruit weight (0.826 and 0.852), fruit pericarp thickness (0.600 and 0.625), plant stem girth (0.281 and 0.320) and it revealed significantly negative correlation with days taken to first
Table 4.8 Phenotypic and genotypic coefficients of correlation among different traits in chilli Traits P 1 G P 2 G P 3 G P 4 G P 5 G P 6 G P 7 G P 8 G P 9 G P 10 G P 11 G P 12 G P 13 G P 14 G P 15 G
1 1.00 1.00
2 -0.304** -0.354** 1.00 1.00
3 0.166 0.175 0.090 0.105 1.00 1.00
4 0.111 0.122 0.435** -0.079 0.826** 0.852** 1.00 1.00
5 0.084 0.175 -0.051 -0.079 -0.524** -0.743** -0.381** -0.535** 1.00 1.00
6 -0.236* -0.347** 0.019 -0.007 -0.152 -0.281* -0.235* -0.297** 0.211 0.412** 1.00 1.00
7 0.064 0.053 -0.010 0.038 -0.194 -0.302** -0.162 -0.237* 0.177 0.681** 0.356** 1.228** 1.00 1.00
8 0.402** 0.508** -0.383** -0.433** 0.281* 0.320** 0.200 0.220 -0.033 -0.030 -0.097 -0.223 0.040 0.127 1.00 1.00
9 -0.023 -0.013 0.469** 0.504** 0.600** 0.625** 0.819** 0.848** -0.234* -0.351** -0.165 -0.222 -0.050 -0.097 0.313** 0.383** 1.00 1.00
10 -0.057 -0.051 0.053 0.051 0.173 0.184 0.120 0.140 -0.109 -0.154 0.130 0.199 0.037 0.060 -0.084 -0.084 -0.067 -0.061 1.00 1.00
11 -0.198 -0.242* -0.163 -0.165 -0.443** -0.500** -0.445** -0.489** 0.392** 0.584** 0.213 0.409** 0.290* 0.727** 0.000 0.005 -0.372** -0.416** -0.105 -0.128 1.00 1.00
12 -0.364** -0.463** -0.232* -0.225* -0.397** -0.498** -0.539** -0.667** 0.167 0.195 0.196 0.384** 0.132 0.314** -0.251* -0.416** -0.512** -0.632** 0.011 0.047 0.473** 0.589** 1.00 1.00
13 0.089 0.106 0.648** 0.679** -0.557** -0.576** -0.823** -0.830** 0.265* 0.394** 0.069 0.046 -0.018 -0.056 0.030 0.064 -0.730** -0.750** -0.251* -0.269* 0.344** 0.379** 0.434** 0.517** 1.00 1.00
14 0.104 0.095 -0.353** 0.105 -0.237* -0.261* -0.300** -0.331** 0.293** 0.484** 0.157 0.306** 0.236* 0.459** 0.098 0.135 -0.414** -0.442** 0.145 0.151 0.614** 0.720** 0.383** 0.483** 0.269* 0.277* 1.00 1.00
15 0.294** 0.322** 0.235* 0.240* 0.882** 0.898** 0.624** 0.641** -0.491** -0.667** -0.177 -0.269* -0.162 -0.287* 0.360** 0.419** 0.348** 0.356** 0.222 0.226* 0.316** 0.349** -0.249* -0.297** 0.227* 0.236* -0.062 -0.078 1.00 1.00
*Significant at 5% level of significance **Significant at 1% level of significance Where, 1= Plant height (cm), 2= Fruit breadth (cm), 3= Fruit length (cm), 4= Average fruit weight 5= Days taken for first flowering, 6= Days for 50 per cent flowering, 7= Days to first harvest, 8= Plant stem girth (cm), 9= Fruit pericarp thickness (mm), 10= Number of seeds per fruit, 11= Number of primary branches, 12= Ascorbic acid content (mg/100g), 13= Number of fruits per plant, 14= Number of branches per plant and 15= Marketable fruit yield per plant (g)
flowering (-0.524 and -0.743), number of primary branches (-0.443 and -0.500), ascorbic acid content (-0.397 and -0.498) and number of branches per plant (-0.237 and -0.261), respectively. Significantly positive correlation of average fruit weight was found with fruit pericarp thickness (0.819 and 0.848), while significant negative association of this trait was found with days taken to first flowering (-0.381 and -0.535), days for 50% flowering (0.235 and -0.297) and ascorbic acid content (-0.539 and -0.667). In the mean while plant height resulted in positive and significant association with plant stem girth (0.402 and 0.508), while significant negative association of this trait was found with ascorbic acid content (-0.364 and -0.463), fruit breadth (-0.304 and -0.354) and days for 50% flowering (-0.236 and -0.347), respectively. In the meanwhile, plant stem girth was significantly and positively correlated with fruit pericarp thickness (0.313 and 0.383), while significant negative correlation of this trait was found with ascorbic acid content (-0.251 and -0.416). Fruit breadth showed significantly positive correlation with number of fruit per plant (0.648 and 0.679) and fruit pericarp thickness (0.469 and 0.504), while negative association of this trait was observed with plant stem girth (-0.383 and -0.433) and ascorbic acid content (-0.232 and -0.225). Number of primary branches revealed significantly positive correlation with ascorbic acid content (0.473 and 0.589), number of fruit per plant (0.344 and 0.379) and number of branches per plant (0.614 and 0.720). In the mean while ascorbic acid content resulted in positive and significant association with number of fruit per plant (0.434 and 0.517) and number of branches per plant (0.383 and 0.483). Number of fruit per plant showed significantly positive correlation with number of branches per plant (0.269 and 0.277). 4.3 Path coefficient analysis Path coefficient analysis depicts the effects of different independent characters individually and in combination with other characters on the expression of different Characters on marketable fruit yield per plant. The data on path coefficient analysis at genotypic level showing the direct and indirect effects of significant characters over marketable fruit yield per plant have been represented in Table 4.9. The data revealed that average fruit weight (0.409) has maximum positive direct effect on marketable fruit yield per plant followed by fruit length (0.328), fruit pericarp thickness (0.196), number of fruits per plant (0.152), fruit breadth (0.111), number of seeds per fruit (0.049), days taken for first flowering (0.048), number of primary branches (0.039), plant height (0.032) and days.
Table 4.9 Estimates of direct and indirect effects of different traits on marketable fruit yield per plant in chilli. Traits
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
1
0.032
0.039
0.057
0.050
0.008
0.003
0.001
0.029
0.002
-0.003
-0.010
-0.072
0.016
-0.012
0.322**
2
-0.011
0.111
0.034
0.186
-0.004
0.000
0.001
-0.025
-0.085
0.002
-0.007
-0.035
-0.103
0.047
0.240*
3
0.006
-0.012
0.328
0.348
-0.036
0.002
-0.005
0.018
-0.105
0.009
-0.020
-0.077
-0.088
0.032
0.898**
4
0.004
-0.051
0.279
0.409
-0.026
0.002
-0.004
0.012
-0.143
0.007
-0.019
-0.103
-0.126
0.041
0.641**
5
0.006
0.009
-0.244
-0.219
0.048
-0.003
0.012
-0.002
0.059
-0.008
0.023
0.030
0.060
-0.060
-0.667**
6
-0.011
0.001
-0.092
-0.121
0.020
-0.008
0.022
-0.013
0.038
0.010
0.016
0.059
0.007
-0.038
-0.269*
7
0.002
-0.004
-0.099
-0.097
0.033
-0.010
0.018
0.007
0.016
0.003
0.029
0.049
-0.009
-0.057
-0.287*
8
0.016
0.048
0.105
0.090
-0.001
0.002
0.002
-0.057
-0.065
-0.004
0.000
-0.064
0.010
-0.017
0.419**
9
0.000
-0.056
0.205
0.347
-0.017
0.002
-0.002
0.022
0.169
-0.003
-0.016
-0.098
-0.114
0.055
0.356**
10
-0.002
-0.006
0.060
0.057
-0.007
-0.002
0.001
-0.005
0.010
0.049
-0.005
0.007
-0.041
-0.019
0.226*
11
-0.008
0.018
-0.164
0.200
0.028
-0.003
0.013
0.000
0.070
-0.006
0.039
0.091
0.058
-0.089
0.349**
12
-0.015
0.025
-0.163
-0.273
0.009
-0.003
0.006
-0.024
0.107
0.002
0.023
-0.155
0.079
-0.060
-0.297**
13
0.003
0.075
-0.189
0.340
0.019
0.000
-0.001
0.004
0.127
-0.013
0.015
0.080
0.152
-0.034
0.236*
14
0.003
0.042
-0.086
-0.135
0.023
-0.002
0.008
0.008
0.075
0.007
0.028
0.075
0.042
-0.124
-0.078
Where, 1= Plant height (cm), 2= Fruit breadth (cm), 3= Fruit length (cm), 4= Average fruit weight 5= Days taken for first flowering, 6= Days for 50% flowering, 7= Days to first harvest, 8= Plant stem girth (cm), 9= Fruit pericarp thickness (mm), 10= Number of seeds per fruit, 11= Number of primary branches, 12= Ascorbic acid content (mg/100g), 13= Number of fruits per plant, 14= Number of branches per plant and 15=Genotypic correlation coefficient for marketable fruit yield per plant (g) Residual effect: 0.00298 Diagonal figures represent the direct effect
to first fruit harvesting (0.018). While, negative direct effect of ascorbic acid content (0.155), number of branches per plant (-0.124), plant stem girth (-0.057) and days for 50% flowering (-0.008) was observed on marketable fruit yield per plant. Maximum positive indirect effects of average fruit weight (0.348) via fruit length, Fruit pericarp thickness (0.347) via average fruit weight, Average fruit weight (0.340) via number of fruits per plant, Fruit length (0.279) via average fruit weight, Fruit length (0.205) via fruit pericarp thickness, Average fruit weight (0.200) via number of primary branches, Fruit pericarp thickness (0.127) via number of fruits per plant, Fruit pericarp thickness (0.107) via ascorbic acid content, Fruit length (0.105) via plant stem girth, Fruit breadth (0.075) via number of fruits per plant and Fruit breadth (0.059) via fruit pericarp thickness was observed on marketable fruit yield per plant. In the mean while, maximum negative indirect effects of average fruit weight (-0.273) via ascorbic acid content, Fruit length (-0.244) via days taken for first flowering, Average fruit weight (-0.219) via days taken for first flowering, Fruit length (-0.163) via Ascorbic acid content, Average fruit weight (-0.135) via number of branches per plant, Average fruit weight (-0.121) via days taken for 50% flowering, Number of fruits per plant (-0.114) via fruit pericarp thickness and average fruit weight (-0.121) via days taken to first harvest was recorded on marketable fruit yield per plant. At genotypic level residual effect was found to be 0.00298. 4.4 Genetic divergence studies On the basis of performance of various traits, the clustering pattern of twenty five diverse genotypes of chilli has been presented in the table 4.10. On the basis of Mahalanobis D2 (1936) statistics, all the genotypes were grouped into 7 clusters. Maximum number of genotypes were accommodated in the cluster-I (7) followed by cluster-II (5), cluster-VI (5), cluster-III (3), cluster-V (2), cluster-VII (2) and cluster-IV (1). Averages inter and intra cluster divergence (D2) values have been presented in the table 4.11. The diagonal figures in the table represent the intra cluster distances. The intra cluster distance was found maximum in cluster VII (2.768) and minimum in cluster IV (0.001). Whereas, highest inter cluster distance (6.978) was recorded between cluster I and VII and lowest (2.828) was observed between cluster V and VI.
Table 4.10 Clustering pattern of twenty five genotypes of chilli on the basis of genetic divergence. Clusters
No of genotypes
Genotypes along with their sources Arka Lohit (IIHR, Karnataka), K-1 (IIVR, Varanasi, UP), DCC-24
I
7
(ARS, Chilli, Karnataka), DCC-52 (Karnataka), DCC-27 (Karnataka), Long chilli (Kerala), Pant C-1 (Pantnagar, Uttarakhand) LC-3(Pali, Rajasthan), LC-5 (Pantnagar, Uttarakhand), LC-7
II
5
(Ranichauri, Uttarakhand), 70-F-BR-14 (Local market), G-4 (IIVR, Varanasi, UP) Surya (Local market), Arka Suphal (IIHR, Karnataka), DDC-239
III
3
IV
1
DCC-187 (ARS,Chilli, Karnataka)
V
2
LC-1 (Jodhpur chilli, Rajasthan), LC-2 (Ajmer, Rajasthan)
(ARS,Chilli, Karnataka)
LC-4 (Bharatpur, Rajasthan), LC-6 (Nainital, Uttarakhand), LC-8 VI
5
(Rishikesh, Uttarakhand), LC-9 (Srinagar, Uttarakhand), Byadgi dabbi (KRCCH, Arabhavi, Karnataka)
VII
2
Paprika (IARI- RS, Katrain), Byadgi kaddi (KRCCH, Arabhavi, Karnataka)
Table 4.11 Average intra and inter cluster distance (D2) Clusters
I
I
2.517
II
3.280
2.222
III
3.753
3.663
2.340
IV
4.965
6.155
5.262
0.001
V
5.885
5.672
5.825
6.735
1.117
VI
4.413
4.123
4.657
5.730
2.828
1.949
VII
6.978
6.794
5.831
6.898
5.698
5.248
II
III
IV
V
VI
VII
2.768
The cluster means for various horticultural and quality traits have been presented in the table 4.11. The number of branches per plant was maximum in cluster I (11.91) followed by cluster II (11.00), cluster V (10.15), cluster VI (9.38) cluster III (7.65), cluster IV (7.53), and cluster VII (6.12). Whereas maximum number of primary branches have
Table 4.12 Cluster means for different trait in twenty five genotypes of chilli. Sr.
Clusters
Traits
No.
I
II
III
IV
V
V1
VII
1.
Number of branches per plant
11.91
11.00
7.65
7.53
10.15
9.38
6.12
2.
Number of primary branches
6.87
5.15
4.02
3.47
3.76
4.69
3.67
3.
Plant height (cm)
73.74
88.95
68.80
72.33
83.00
83.13
77.80
4.
Plant stem girth (cm)
2.86
3.03
2.62
2.32
2.99
3.26
3.26
5.
Days taken for first flowering
39.86
41.13
38.11
39.67
36.33
37.73
39.33
6.
Days for 50 per cent flowering
54.38
52.60
51.78
59.67
50.44
53.80
51.33
7.
Days to first harvest
70.71
67.53
65.44
72.67
64.00
69.00
67.67
8.
Number of fruits per plant
90.71
111.56
99.42
65.71
66.40
90.30
36.85
9.
Average fruit weight (g)
1.76
1.36
1.46
2.20
3.31
2.41
4.56
10.
Fruit length (cm)
7.51
7.08
7.00
8.85
12.73
11.83
12.10
11.
Fruit breadth (cm)
1.60
1.18
1.45
1.96
1.51
1.25
2.75
12.
Fruit pericarp thickness (mm)
1.01
0.80
1.06
1.15
1.34
1.35
2.81
13.
Number of seeds per fruit
68.94
51.54
57.84
106.73
84.38
67.87
32.27
14.
Ascorbic acid content (mg/100g)
104.35
89.99
101.81
87.90
84.44
88.61
63.13
15.
Yield per plant
148.15
150.11
141.20
144.60
218.33
215.77
170.43
been recorded in cluster I (6.87) followed by cluster II (5.15), cluster VI (4.69), cluster III (4.02) cluster VII (3.67), cluster V (3.76) and cluster IV (3.47). Maximum plant height has been recorded in cluster II (88.95) followed by cluster VI (83.13), cluster V (83.00), cluster VII (77.80), cluster I (73.74), cluster IV (72.33) and cluster III (68.80). Maximum plant stem girths have been recorded in cluster VI and VII (3.26) followed by cluster II (3.03), cluster V (2.99), cluster I (2.86), cluster III (2.62) and cluster IV (2.32). Minimum days taken for first flowering have been recorded in cluster V (36.33) followed by cluster VI (37.73), cluster III (38.11), cluster VII (39.33), cluster IV (39.67), cluster I (39.86) and cluster II (41.13). While days for 50% flowering was minimum in cluster V (50.44) followed by cluster VII (51.33), cluster III (51.78), cluster II (52.60), cluster VI (53.80), cluster I (54.38) and cluster IV (59.67). Similarly days to first harvest was also minimum in cluster V (64.00) followed by cluster VII (67.00), cluster III (65.44), cluster II (67.53), cluster VI (69.00), cluster I (70.71) and cluster IV (72.67).
For number of fruits per plant cluster II (111.56) exhibited
maximum number followed by cluster III (99.42), cluster I (90.71), cluster VI (90.30), cluster V (66.40), cluster IV (65.71) and cluster VII (36.85). Average fruit weight was recorded maximum in the cluster VII (4.56) followed by cluster V (3.31), cluster VI (2.41), cluster IV (2.20), cluster I (1.76), cluster III (1.46) and cluster II (1.36). Maximum fruit lengths have been recorded in cluster V (12.73) followed by cluster VII (12.10), cluster VI (11.83), cluster IV (8.85), cluster I (7.51), cluster II (7.08) and cluster III (7.00). While fruit breadth was highest in cluster VII (2.75) followed by cluster IV (1.96), cluster I (1.60), cluster V (1.51), cluster III (1.45), cluster VI (1.25) and cluster II (1.18).
Pericarp thickness was recorded
maximum in the cluster VII (2.81) followed by cluster VI (1.35), cluster V (1.34), cluster IV (1.15), cluster III (1.06), cluster I (1.01) and cluster II (0.80). While number of seeds per fruit was maximum in cluster IV (106.73) followed by cluster V (84.38), cluster I (68.94), cluster VI (67.87) cluster III (57.84), cluster II (51.54) and cluster VII (32.27). The highest ascorbic acid content was recorded in cluster I (104.35) followed by cluster III (101.81), cluster II (89.90), cluster V (84.44), cluster VI (88.61), cluster IV (87.90) and cluster VII (63.13). Maximum fruit yield per plant have been recorded in cluster V (218.33) followed by cluster VI (215.77), cluster VII (170.43), cluster II (150.11), cluster I (148.15), cluster IV (144.60) and cluster III (141.20).
Chapter-5
DISCUSSION
CHAPTER-5 DISCUSSION Chilli (Capsicum annuum L. var. acuminatum Fingerh.) commonly known as hot Pepper is one of the most popular and highly remunerative vegetable crop grown in India. It is most remunerative cash crop of mid hills of Uttarakhand being grown as an warm season vegetable for fresh market and supply the produce to the plains of Northern India. Despite of its economic importance, growers are not in a position to produce good quality chilli with high productivity due to various biotic and abiotic stresses. The chief immediate and long term objective of plant breeding remains increasing the productivity or yield to the required land. In recent years quality has become even more important than yield potential, especially to meet quality specification of international trade and for industrial use. The plant breeders have to identify source of favorable genes incorporate them into breeding population/lines and selection should be made for a combination of desirable traits that might result in the isolation of productive genotypes. The scope of improvement of any crop depends upon the magnitude of genetic variability present in the available germplasm. Greater the variability in available germplasm better would be the chances of selecting superior genotypes (Simmonds, 1962). The studies on the extent of variability available in the germplasm offer a better opportunity to judge the scope for the selection of desirable genotypes. Variability parameters are important assets to the breeders especially in a crop like chilli, where improvement for quantitative and qualitative characters is required continuously. Proper screening and evaluation of germplasm lines would provide an estimate of their potential value as suitable genotypes for utilization in varietal development. The information on nature and magnitude of variability, heritability, genetic advance and genetic gain for various characters in respect of germplasm available is required for maximizing the correlated response to selection to examine the genetic variability, to select superior germplasm for yield and related characters. To incorporate desirable yield and quality traits in a variety/hybrid, there is a need to know the inter-relationship and identification of important attributes through correlation and path analysis, which is used to design suitable plant type with improved characters and for multiple trait
selection. However, if selection is not responsive further, genetic divergence helps in selecting superior parents for hybridization programme resulting in better hybrids and desirable recombinants and segregates. Therefore, the present investigation was carried out on twenty five diverse genotypes of chilli to study genetic variability, correlation, path analysis and genetic divergence for different horticultural and quality traits. These traits have been discussed here under in the light of available literature: 5.1 VARIABILITY STUDIES 5.1.1 Mean performance of genotypes The analysis of variance indicated highly significant differences among the genotypes for all the traits studied viz., number of branches per plant, number of primary branches, plant height (cm), days to first flowering, days to 50% flowering, plant stem girth (cm), days to first fruit harvesting, number of fruits per plant, average fruit weight (g), fruit length (cm), fruit breadth (cm), pericarp thickness (mm), number of seed per fruit, ascorbic acid content (mg/100g), marketable fruit yield per plant (g), per plot (kg) and per hectare (q), which revealed the existence of good deal of variability in the germplasm. The experimental results have been discussed under the following headings: 5.1.1.1 Number of branches per plant The observations recorded for this trait showed significant differences among all the genotypes ranged from 6.12–12.83. A significant maximum number of branches was recorded in DCC-27 (12.83). Amongst all the genotypes under study, nine genotypes were found to have more than check cultivar Pant C-1 (11.47). Tremendous variations regarding number of branches in chilli have also been agreed by Shirshat et al. (2007), Sreelathakumary and Rajamony (2002) and Amit et al. (2014). 5.1.1.2 Number of primary branches Significant variations were observed among all the genotypes for number of primary branches ranged from 3.47–7.67. Maximum number of primary branches was recorded in DCC-24 (7.67). Amongst all the genotypes under study, four genotypes were found to have more than check cultivar Pant C-1 (6.47). Tremendous variations regarding number of primary branches in chilli have also been reported earlier by Manju and Sreelathakumary (2002), Nandadevi (1999), Madankumar (2008) and Patel et al. (2015).
5.1.1.3 Plant height (cm) Plant height was found considered as an important yield contributing trait, because it leads to more number of branches and ultimately result in increased productivity. All the genotypes studied indicated significant variations for plant height (58.93–96.53 cm). Significantly maximum plant height was recorded in the genotype LC-7 (96.53). In overall, six genotypes had more plant height than check cultivar Pant C-1 (85.77). Similar variations for plant height in different genotypes of chilli had also been reported by earlier workers like Smitha (2004), Smitha and Basavaraja (2006), Madankumar (2008), Amit et al. (2014) and Vijaya et al. (2014). 5.1.1.4 Plant stem girth (cm) Significant differences were observed among all the genotypes for plant stem girth ranged from 2.32–3.72 cm. Maximum plant stem girth was recorded in LC-4 (3.72 cm), followed by G-4 (3.46), Byadgi dabbi (3.38) and K-1 (3.37). Seven genotypes gave higher plant stem girth than check cultivar Pant C-1 (3.13). Variations for number of fruits per plant were also reported earlier by Verkey et al. (2005) and Krishna et al. (2007) 5.1.1.5 Days to first flowering Earliness was one of the most important factors which decide how early the fruits reach the market and how best they appeal to the eyes of the customers. Significant variations were observed among all the genotypes for days to first flowering. Days to first flowering ranged from 35.67–44.67 days. Minimum days to first flowering was observed in the genotype LC-1 and Byadgi kaddi (35.67) followed by Byadgi dabbi (36.00). Amongst all the genotypes under study, nine genotypes were found earlier than check cultivar Pant C-1 (38.33). Similar results are also in agreement with Krishna et al. (2007) and Patel et al. (2015). 5.1.1.6 Days to 50% flowering Earliness was one of the most important factors which decide how early the fruits reach the market and how best they appeal to the eyes of the customers, significant variations were observed among all the genotypes for days to 50% flowering. Days to 50% flowering ranged from 47.67–59.67 days. Significantly minimum days to 50% flowering were observed in genotype Surya (47.67). Amongst all the genotypes under
study, eleven genotypes were found earlier than check cultivar Pant C-1 (53.00). Similar results had also in harmony with Krishna et al. (2007) and Vijaya et al. (2014). 5.1.1.7 Days to first fruit harvesting Earliness was one of the most important factors which decide how early the fruits reach the market and how best they appeal to the eyes of the customers. Significant variations were observed among all the genotypes for days to first fruit harvesting (62.33–74.33 days). Minimum days to first fruit harvesting (62.33) were recorded in the genotype Byadgi kaddi followed by LC-1 (64.00), Surya (64.33) and G4 (64.67). Amongst all the genotypes under study, twenty one genotypes were found earlier than check cultivar Pant C-1 (72.33) for days to first fruit harvesting. Similar results had also been reported earlier by Munshi and Behera (2000), Sharma et al. (2010) and Diwakar et al. (2012) for days to first fruit harvesting in chilli. 5.1.1.8 Number of fruits per plant Number of fruits per plant is a major yield contributing character. The observations recorded for this trait showed significant differences among all the genotypes (36.85–126.07. Significantly higher number of fruits per plant was observed in the genotype LC-7 (126.07) followed by G-4 (120.63) and 70-F-BR-14 (120.6), amongst all the genotypes under study, eight genotypes were found superior than check cultivar Pant C-1 (99.43) for number of fruits per plant. Wide variations for number of fruits per plant were also in harmony with earlier Shirshat et al. (2007), Datta and Das (2013), Vijaya et al. (2014) and Amit et al. (2014) in Chilli. 4.1.1.9 Average fruit weight (g) Fruit weight has direct effect on yield and this is a character which appeals to the consumers. Wide variations were recorded among all the genotypes for average fruit weight (1.16–4.66 g). Maximum average fruit weight was recorded in Paprika (4.66) followed by LC-2 (3.45). In the present studies, twelve genotypes exhibited higher average fruit weight than check cultivar Pant C-1 (1.83). Tremendous variations for average fruit weight were also reported earlier by Munshi and Behera (2000), Diwakar et al. (2012) and Amit et al. (2014).
5.1.1.10 Fruit length (cm) Fruit length was an important parameter, which directly contributes to the fruit weight, thereby affecting the total yield. All the genotypes studied indicated significant variations for fruit length (4.83–13.26 cm). Maximum fruit length was recorded in the genotype LC-8 (13.26) followed by LC-1 (13.16 cm) and LC-2 (12.69). Fourteen genotypes had greater fruit lengths than check cultivar Pant C-1 (7.77). The results of present studies are in line with Rani and Singh (2000), Munshi and Behera (2000), Kumari et al. (2010), Diwakar et al. (2012), Patel et al. (2015) and Vijaya et al. (2014) for the trait under study. 5.1.1.11 Fruit breadth (cm) Fruit breadth had also direct effect on fruit weight, and ultimately on total yield significant variations for fruit breadth was obtained among the entire genotypes under studied (0.84–2.75 cm). Maximum fruit breadth was observed in the genotype Paprika (2.75). In overall, twenty genotypes were found superior than check cultivar Pant C-1 (1.13) for fruit breadth. Similar variations for fruit breadth in different genotypes of chilli had also been reported by earlier workers like. Rani and Singh (2000), Smitha and Basavaraja (2006), Krishna et al. (2007) and Amit et al. (2014). 5.1.1.12 Pericarp thickness (mm) Pericarp thickness has been globally identified as an important component of keeping quality and whole fruit firmness in chilli. All the genotypes studied revealed significant variations for the trait under study (0.56–2.81 mm). In the present studies, maximum pericarp thickness was observed in Paprika (2.81) followed by LC-4 (1.54), LC-1 (1.40) and LC-9 (1.33). Twelve genotypes were found superior over check cultivar Pant C-1 (1.14) for this trait. These findings are in line with Munshi and Behera (2000) and Aklilu et al. (2016) 5.1.1.13 Number of seed per fruit The observations recorded for this trait showed significant differences among all the genotypes ranged from 27.70–108.47. A significantly higher number of seed per fruit was observed in the genotype LC- 2 (108.47) followed by DCC-187 (106.73), amongst all the genotypes under study, fourteen genotypes were found superior than check cultivar Pant C-1 (63.80) for number of fruits per plant. Variations for fruits per plant
were also in agreement with Warade et al. (1996), Verkey et al. (2005), Shirshat et al. (2007), Madankumar (2008) and Kumari et al. (2010). 5.1.1.14 Ascorbic acid content (mg/100g) Ascorbic acid is the major component of the nutritional quality in chilli. In the present studies, Ascorbic acid content ranged from 63.13–115.10 mg/100g. Maximum ascorbic acid was observed in the genotype DCC-27 (115.10) followed by Long chilli (112.07) and Arka Suphal (111.73). In the present studies, seven genotypes viz., DCC27 (115.10), Long chilli (112.07), Arka Suphal (111.73), DCC-24 (106.70), DCC-52 (104.43) and Surya (104.53) were found better than check cultivar Pant C-1 (103.20) for ascorbic acid content in the fruits. The results of present findings for ascorbic acid content in chilli fruits are in line with variations for plant height in different genotypes of chilli had also been reported by earlier workers like Manju and Sreelathakumary (2002), Kumar et al. (2003) and Datta and Das (2013). 5.1.1.15 Marketable fruit yield per plant (g), per plot (kg) and per hectare (q) The main focus of cultivating a crop is to have the maximum yield per unit area for better returns. Moreover, high fruit yield is the ultimate goal of any breeding program; hence, it requires the highest consideration. All the genotypes studied revealed significant variations for marketable fruit yield per plant, per plot and per hectare (110.51–241.99 g, 1.33–2.91 kg and 65.68–143.53 q, respectively). Maximum marketable fruit yield was recorded in the genotype LC-8 (241.99 g, 2.91 kg and 143.53 q), respectively) followed by LC-1 (234.58 g, 2.82 kg and 139.25 q, respectively), LC-2 (230.93 g, 2.78 kg and 137.11 q, respectively) and Byadgi dabbi (222.23 g, 2.67 kg and 132.01 q, respectively). In the present studied, eight genotypes viz., LC-1, LC-2, LC-4, LC-6, LC-8, LC-9, Byadgi kaddi and Byadgi dabbi recorded higher marketable fruit yield than check cultivar Pant C-1 (181.44 g, 2.18 kg and 107.81 q). Tremendous variations regarding yield parameter in chilli have also been reported earlier by Verkey et al. (2005), Singh et al. (2004), Sreelathakumary and Rajamony (2002) and Datta and Das (2013). 5.1.2
Parameters of variation
5.1.2.1 Coefficients of variation The estimates of phenotypic and genotypic coefficients of variation gave a clear picture of amount of variations present in the available germplasm. For all the characters
studied, phenotypic coefficients of variation were higher in magnitude than genotypic coefficients of variation, though difference was very less in majority the cases. It was showing that these traits are less influenced by environmental factors. Coefficients of variation varied in magnitude from character to character (either low or moderate or high). Therefore, it indicated that there was a great diversity in the experimental material used. The phenotypic coefficients of variability (PCV) were found high for average fruit weight, fruit pericarp thickness and number of seeds per fruit. Earlier workers like Verkey et al. (2005), Kadwey et al. (2015) and Janaki et al. (2015) had also reported high phenotypic coefficients of variation for these traits. Moderate phenotypic coefficients of variation were recorded for fruit breadth, fruit length, number of primary branches, number of fruits per plant, number of branches per plant and fruit yield per plant. Similar finding were also reported by Manju and Sreelathakumary (2002), Prabhudeva (2003), Tembhurne et al. (2008), Krishnamurthy et al. (2013) and Patel et al. (2015). In the mean while, phenotypic coefficients of variation were recorded low in magnitude for ascorbic acid content, plant stem girth, plant height, days taken for first flowering, days for 50% flowering and days taken to first harvest. Diwakar et al. (2012), Datta and Das (2013) and Amit et al. (2014) had also reported similar results for phenotypic coefficients of variation in chilli. The genotypic coefficients of variation (GCV) were recorded high average fruit weight, fruit pericarp thickness and number of seeds per fruit. Whereas moderate genotypic coefficients of variation were observed for fruit breadth, fruit length, number of primary branches, number of branches per plant, number of fruits per plant, fruit yield per plant and number of fruits per plant. while genotypic coefficients of variation were recorded low in magnitude for ascorbic acid content, plant stem girth, plant height, days taken for first flowering, days for 50% flowering and days taken to first harvest. Earlier workers like Verkey et al. (2005), Datta and Das (2013), Patel et al. (2015), Kadwey et al. (2015) and Janaki et al. (2015) had also reported similar genotypic coefficients of variation trends for different traits under study. 5.1.2.2 Heritability The genotypic coefficient of variation does not offer full scope to estimate the variations that are heritable and therefore, estimation of heritability becomes necessary.
Burton and De-Vane (1953) has suggested that genetic coefficient of variation along with heritability estimates would give a reliable indication of expected amount of improvement through selection. The estimates of heritability (broad sense) varied from 32.37–98.97% for different characters under study. It was found high for the characters viz., fruit yield per plant, fruit pericarp thickness, number of seeds per fruit, average fruit weight, fruit length, number of fruits per plant, plant height, number of branches per plant, fruit breadth and number of primary branches. High heritability for above studied traits was also reported earlier by Diwakar et al. (2012), Patel et al. (2015), Amit et al. (2014) and Kadwey et al. (2015). Moderate heritability was observed for plant stem girth, days taken for first flowering and ascorbic acid content. Similar results had also been reported earlier by Verkey et al. (2005), Smitha and Basavaraja (2006) and Datta and Das (2013). Whereas it was recorded low for days to first harvest and days for 50% flowering. Similar results had also been reported earlier by Mubarak Begum (2002), Krishna et al. (2007), Shirshat et al. (2007) and Sharma et al. (2010). 5.1.2.3 Genetic advance and genetic gain Genetic gain (expressed as per cent of population mean) was low to high in nature and ranged from 4.05–83.98% for different characters under study. It was found high for the characters viz., average fruit weight, fruit pericarp thickness, fruit breadth, number of seeds per fruit and fruit length. Sreelathakumary and Rajamony (2002), Smitha and Basavaraja (2006), Patel et al. (2015), Janaki et al. (2015) and Kadwey et al. (2015) had also reported high genetic gain for above traits under study. Moderate genetic gain was observed for number of primary branches, number of fruits per plant, fruit yield per plant and number of branches per plant. These results of present findings are in agreement with Diwakar et al. (2012), Krishnamurthy et al. (2013) and Amit et al. (2014). Whereas it was recorded low for plant height, ascorbic acid content, plant stem girth, days taken for first flowering, days to first harvest and days for 50% flowering. Mubarak Begum (2002), Prabhudeva (2003), Farhad et al. (2010), Tembhurne et al. (2008), Sharma et al. (2010) and Vijaya et al. (2014) High heritability estimates coupled with high genetic gain were observed fruit pericarp thickness, average fruit weight, fruit breadth, number of seeds per fruit and fruit length which indicated that these characters are under additive gene effects and these
characters are more reliable for effective selection (Panse, 1957). Similar results were also reported by Manju and Sreelathakumary (2002), Gogoi and Gautam (2003), Smitha and Basavaraja (2006), Sharma et al. (2010), Patel et al. (2015), Amit et al. (2014) and Janaki et al. (2015) for these traits under study. High heritability coupled with moderate genetic gain observed number of fruits per plant, number of branches per plant, number of primary branches and fruit yield per plant indicated that these characters are under non-additive gene effects and selection for these characters will be less effective. Such traits are more under the influence of environment and do not respond to selection. Similar results for different traits under study were also reported by Diwakar et al. (2012) and Krishnamurthy et al. (2013). 5.2
Correlation studies Knowledge of degree of association of yield with its components is of great
importance, because yield is not an independent character, but it is the resultant of the interactions of a number of component characters among themselves as well as with the environment in which the plant grow. Further each character is likely to be modified by action of genes present in the genotypes of plant and also by the environment and it becomes difficult to evaluate this complex character directly. Therefore, correlation study of yield with its component traits has been executed, to find out the yield contributing traits. The correlation coefficients among the different characters were worked out at phenotypic and genotypic levels. In general, the genotypic correlation coefficients were higher in magnitude than phenotypic correlation coefficients. The phenotypic correlation coefficients among different characters showed that marketable yield per plant had positive and significant association with fruit length, plant stem girth, fruit pericarp thickness, average fruit weight, number of fruits per plant, number of primary branches, fruit breadth and plant height, while significantly negative correlations were observed with days taken for first flowering and ascorbic acid content, respectively. The genotypic correlation coefficients among different characters showed that marketable yield per plant had positive and significant association with fruit length, plant stem girth, fruit pericarp thickness, average fruit weight, number of fruits per plant, plant height, fruit breadth, days for 50% flowering, number of primary branches and number of seeds per fruit, while significantly
negative correlations were observed with days taken for first flowering, days to first harvest, days for 50% flowering and ascorbic acid content, respectively. Beside this, fruit length resulted in positive and significant association with average fruit weight, Fruit pericarp thickness, Plant stem girth and it revealed significantly negative correlation with days taken to first flowering, number of primary branches, ascorbic acid content and number of branches per plant, respectively. Significantly positive correlation of average fruit weight was found with fruit pericarp thickness, while significant negative association of this trait was found with days taken to first flowering, days for 50% flowering and ascorbic acid content. In the mean while plant height resulted in positive and significant association with plant stem girth, while significant negative association of this trait was found with ascorbic acid content, fruit breadth and days for 50% flowering, respectively. In the meanwhile, plant stem girth was significantly and positively correlated with fruit pericarp thickness, while significant negative correlation of this trait was found with ascorbic acid content. Fruit breadth showed significantly positive correlation with number of fruit per plant and fruit pericarp thickness, while negative association of this trait was observed with plant stem girth and ascorbic acid content. Number of primary branches revealed significantly positive correlation with ascorbic acid content, number of fruit per plant and number of branches per plant. In the mean while ascorbic acid content resulted in positive and significant association with number of fruit per plant and number of branches per plant. Number of fruit per plant showed significantly positive correlation with number of branches per plant. Similar correlation of yield with various horticultural and quality traits have also been reported earlier by several workers viz., Khurana et al. (1993), Pawade et al. (1995), Rani (1996), Kumar et al. (1999), Gogoi and Gautam (2003), Khurana et al. (2003), Ajjapplavara et al. (2005), Pramila (2005), Smitha and Basavaraja (2006), Singh et al. (2007), Kumari et al. (2011), Diwaker et al. (2012), Singh and Singh (2012), Krishnamurthy et al. (2013), Vikram et al. (2014), Hasan et al. (2016), Aklilu et al. (2016) and Janaki et al. (2016). 5.3.
Path coefficient analysis Although correlation studies are helpful in determining the components of yield
but it does not provide a clear picture of nature made by number of independent traits. Path coefficient analysis devised by Dewey and Lu (1959), however, provides a realistic basis for allocation of appropriate weight age to various attributes while
designing a pragmatic programme for the improvement of yield. Path coefficient analysis depicts the effects of different independent characters individually and in combination with other characters on the expression of different characters on marketable fruit yield per plant. The path coefficient analysis at genotypic level revealed that marketable yield per plant has maximum positive direct effect on that average fruit weight has maximum positive direct effect on marketable fruit yield per plant followed by fruit length, fruit pericarp thickness, number of fruits per plant, fruit breadth, number of seeds per fruit, days taken for first flowering, number of primary branches, plant height and days to first fruit harvesting. While, negative direct effect of ascorbic acid content, number of branches per plant, plant stem girth and days for 50% flowering was observed on marketable fruit yield per plant. Maximum positive indirect effects of average fruit weight via fruit length, Fruit pericarp thickness via average fruit weight, Average fruit weight via number of fruits per plant, Fruit length via average fruit weight, Fruit length via fruit pericarp thickness, Average fruit weight via number of primary branches, Fruit pericarp thickness via number of fruits per plant, Fruit pericarp thickness via ascorbic acid content, Fruit length via plant stem girth, Fruit breadth via number of fruits per plant and Fruit breadth via fruit pericarp thickness was observed on marketable fruit yield per plant. In the mean while, maximum negative indirect effects of average fruit weight via ascorbic acid content, Fruit length via days taken for first flowering, Average fruit weight via days taken for first flowering, Fruit length via Ascorbic acid content, Average fruit weight via number of branches per plant, Average fruit weight via days taken for 50% flowering, Number of fruits per plant via fruit pericarp thickness and average fruit weight via days taken to first harvest was recorded on marketable fruit yield per plant. At genotypic level residual effect was found to be 0.00298. At genotypic level residual effect was found to be 0.00298. Rani (1996), Kumar et al. (1999), Rathod et al. (2002), Khurana et al. (2003), Ajjapplavara et al. (2005), Chattopadhyay et al. (2011), Diwaker et al. (2012), Patel et al. (2015), Bijalwan and Mishra (2016), Hasan et al. (2016) and Janaki et al. (2016) had reported similar direct and indirect effects of various horticultural and quality traits on yield in chilli
5.4
Genetic divergence studies The analysis of variance revealed highly significant differences among the
genotypes for all the characters studied, indicating the existence of wide genetic divergence among them. On the basis of performance of various traits, all the genotypes were grouped into different clusters. Information on genetic diversity was also used to identify the promising diverse genotypes, which may be used in further breeding programmes. Genotypes from same centre of origin were placed in separate clusters, indicating wide genetic diversity among them. This may be due to frequent exchange of germplasm between different geographical regions. In the present studies, the genetic divergence observed among twenty five diverse genotypes of chilli showed low quantum of divergence. On the basis of performance of various traits, all the genotypes were grouped into 7 clusters. Maximum number of genotypes were accommodated in the cluster-I (7) followed by cluster-II and cluster-VI (5), cluster-III (3), cluster-V and cluster-VII (2) and IV (1). The resultant seven clusters showed genetic diversity. The intra cluster distance was found maximum in cluster VII (2.768). Whereas, highest inter cluster distance (6.978) was recorded between cluster I and VII. Theoretically, crossing of genotypes belonging to same cluster will not expect to yield superior hybrids or segregants. Whereas, highest inter cluster distance was recorded between cluster I and VII. Such diverse genotypes characterized by maximum inter cluster distance will differ in phenotypic performance and therefore, chances to obtain favorable transgressive segregates are more on the basis of results obtained. The existence of diversity among the genotypes was also assessed by the considerable amount of variation in cluster means for different characters. Cluster-V exhibited most desirable means for fruit length, days to first flowering, days taken for 50% flowering, days to first harvest, yield per plant whereas cluster-VII was found superior for average fruit weight, fruit breadth, fruit pericarp thickness, plant stem girth while cluster-I exhibited higher means for number of primary branches, ascorbic acid content and number of branches per plant, while cluster-II was found superior for plant height, number of fruits per plant and cluster-IV was found superior for number of seeds per fruit. Crossing between the genotypes of two clusters appeared to be most promising to combine the desirable characters. In the present investigations, cluster V and VII were found more divergent and there will be more chances of getting better segregants in F2 and subsequent
generations from the crossing genotypes from cluster V and VII. Earlier workers like Prabhudeva (2003), Senapati et al. (2003), Smitha (2004), Gogate et al. (2007), Ajjapplavara (2009), Thul et al. (2009), Kumar et al. (2010), Farhad et al. (2010), Hasanuzzaman and Golam (2011), Datta and Das (2013), Hasan et al. (2014), Vijaya et al. (2014), Yatung et al. (2014), Hasan et al. (2015) and Zehra et al. (2015) have also indicated the significance of genetic divergence in chilli.
Chapter-6
SUMMARY AND CONCLUSION
CHAPTER-6 SUMMARY AND CONCLUSION The present investigations entitled “Selection Parameters and Genetic Divergence Analysis in Chilli (Capsicum annuum L. var. acuminatum Fingerh.)” were carried out in diverse group of twenty five genotypes of chilli, indigenous collections along with one check cultivar (Pant C-1) to ascertain nature and magnitude of variability, correlation, path coefficient analysis and genetic divergence. The experiment was laid out in Randomized Complete Block Design with three replications of each genotype at Vegetable Research and Demonstration Block of VCSG Uttarakhand University of Horticulture and Forestry, Bharsar, Pauri Garhwal, Uttarakhand during Kharif 2015. The observations were recorded for number of branches per plant, number of primary branches, plant height (cm), days to first flowering, days to 50% flowering, plant stem girth (cm), days to first fruit harvesting, number of fruits per plant, average fruit weight (g), fruit length (cm), fruit breadth (cm), pericarp thickness (mm), number of seed per fruit, ascorbic acid content (mg/100g), marketable fruit yield per plant (g), per plot (kg) and per hectare (q), The results obtained from present investigations have been summarized as below: 6.1
Variability Studies
6.1.1
Mean performance The analysis of variance showed highly significant variations among the
genotypes for all the horticultural traits under study, which revealed the existence of good deal of variability in the germplasm. Number of branches per plant was recorded significantly maximum in DCC-27 (12.83) Moreover, nine genotypes viz., 70-F-BR-14 (12.60), Long chilli (12.60), LC-4 (12.59), DCC-24 (12.27), LC-3 (12.22), Arka Lohit (12.03), LC-2 (11.97) and LC-1 (11.65) were found to have higher number of branches than check cultivar Pant C-1 (11.47). Number of primary branches was recorded significantly maximum in the genotype DCC-24 (7.67). Besides this, four genotypes viz., Long chilli (7.27), DCC-27 (7.20), K-1 (6.93) and Arka Lohit (6.40) had more primary branches than check cultivar Pant C-1 (6.47).
Significantly highest plant height (cm) was recorded in LC-7 (96.53), followed by LC-3 (92.93), LC-6 (92.47) and LC-5 (91.77) besides this, six genotypes had more plant height than check cultivar Pant C-1 (85.77). Maximum stem girth (cm) was recorded in LC-4 (3.72) followed by G-4 (3.46), Byadgi dabbi (3.38) and K-1 (3.37). Seven genotypes recorded higher stem girth than checks cultivar Pant C-1 (3.13). Among all the genotypes, LC-1 and Byadgi kaddi was found earliest days to first flowering (35.67 days) followed by Byadgi dabbi (36.00) and LC-6 (36.67) Besides this, nine genotypes matured earlier than check cultivar Pant C-1 (38.33 days). Among all the genotypes, Surya and Byadgi kaddi was found earliest in days to 50% flowering (47.67 days) followed by LC-2 (51.00), Paprika (51.34) and DDC239 (51.33). Besides this, eleven genotypes matured earlier than check cultivar Pant C-1 (53.00). Among all the genotypes, Byadgi kaddi was found earliest in maturity (62.33 days) followed by LC-1 (64.00), Surya (64.33) and G-4 (64.67). Besides this, twenty one genotypes matured earlier than check cultivar Pant C-1 (72.33). Significantly higher numbers of fruits per plant were recorded in the genotype LC7 (126.07), followed by G-4 (120.63) and 70-F-BR-14 (120.60). Amongst all the genotypes under study, eight genotypes were found superior than check cultivar Pant C-1 (99.43) Maximum average fruit weight (g) was recorded in Paprika (4.66) followed by LC2 (3.45). Twelve genotypes recorded higher average fruit weight than checks cultivar Pant C-1 (1.83). Highest fruit length (cm) was recorded in genotype LC-8 (13.26) followed by LC-1 (13.16) and LC-2 (12.69). Fourteen genotypes had greater fruit lengths than check cultivar Pant C-1 (7.77).
Significantly maximum fruit breadth (cm) was observed in Paprika (2.75) followed by Byadgi kaddi (2.04), Arka Lohit (1.99) and DCC-187 (1.96) and twenty genotypes were found superior than check cultivar Pant C-1 (1.13). Pericarp thickness was recorded maximum in Paprika (2.81 mm), followed by LC-4 (1.54) and LC-1 (1.40). Besides this, twelve genotypes were found superior over check cultivar Pant C-1 (1.14). Highest numbers of seed per fruit were observed in LC- 2 (108.47), followed by DCC-187 (106.73) and LC-1 (86.47). In overall, fourteen genotypes were found to have more number of seed per fruit than Pant C-1 (63.80). Ascorbic acid content (mg/100 g) was observed maximum in DCC-27 (115.10) followed by long chilli (112.07), Arka Suphal (111.73) and DCC-24 (106.70). Seven genotypes had higher ascorbic acid than the check cultivar Pant C-1 (103.20) Maximum marketable fruit yield per plant (g), per plot (kg) and per hectare (q) was recorded in the genotype LC-8 (241.99 g, 2.91 kg and 143.53 q, respectively) followed by LC-1 (234.58 g, 2.82 kg and 139.25 q, respectively), LC-2 (230.93 g, 2.78 kg and 137.01 q, respectively) and Byadgi dabbi (222.23 g, 2.67 kg and 132.01 q, respectively). In overall, eight genotypes viz. LC-8 (241.99 g, 2.91 kg and 143.53 q), LC-1 (234.58 g, 2.82 kg and 139.25 q, respectively), LC-2 (230.93 g, 2.78 kg and 137.11 q, respectively), Byadgi dabbi (222.23 g, 2.67 kg and 132.01 q, respectively), LC-4 (205.12 g, 2.47 kg and 121.80 q, respectively), LC-6 (217.71 g, (2.62 kg) and 129.21 q, respectively), LC-9 (191.80 g, 2.30 kg and 113.74 q, respectively) Byadgi kaddi (189.47 g, 2.28 kg and 112.58 q, respectively), recorded higher marketable fruit yield than check cultivar Pant C-1 (181.44g, 2.18kg, 107.81q). 6.1.2
Coefficients of variability For all the characters studied, phenotypic coefficients of variation were higher
in magnitude than genotypic coefficients of variation, though difference was very less in majority of cases. The phenotypic coefficients of variation and genotypic coefficients of variation were recorded high for average fruit weight, fruit pericarp thickness and number of seeds per fruit. The estimates of heritability (broad sense) were found high for fruit yield per plant, fruit pericarp thickness, number of seeds per fruit,
average fruit weight, fruit length, number of fruits per plant, plant height, number of branches per plant, fruit breadth and number of primary branches thereby suggesting that straight selection for these traits may bring worthwhile improvement in identifying superior genotypes in chilli. Besides this, high heritability estimates coupled with high genetic gain were observed average fruit weight, fruit pericarp thickness, fruit breadth, number of seeds per fruit and fruit length which indicated that these characters are under additive gene effects and these characters are more reliable for effective selection. 6.2
Correlation studies The phenotypic and genotypic correlation coefficients among different
characters showed that marketable yield per plant had positive and significant association with fruit length, plant stem girth, average fruit weight, fruit pericarp thickness, number of fruits per plant, fruit breadth, number of primary branches, plant height, days for 50% flowering and number of seeds per fruit. Beside this, fruit length resulted in positive and significant association with average fruit weight, fruit pericarp thickness, plant stem girth significantly positive correlation of average fruit weight was found with fruit pericarp thickness. In the mean while plant height resulted in positive and significant association with plant stem girth In the meanwhile, plant stem girth was significantly and positively correlated with fruit pericarp thickness, number of seeds per fruit showed significantly positive correlation with number of branches per plant. Fruit breadth showed significantly positive correlation with number of fruit per plant and fruit pericarp thickness. Hence, there is ample scope for yield improvement in chilli through selection for these traits. 6.3
Path coefficient analysis
The path coefficient analysis revealed that maximum positive direct effect towards fruit yield per plant was contributed by average fruit weight has maximum positive direct effect on marketable fruit yield per plant followed by fruit length, fruit pericarp thickness, number of fruits per plant, fruit breadth, number of seeds per fruit, days taken for first flowering, plant height and days to first fruit harvesting, indicating direct selection for these trait as a criteria for improvement in chilli. In the mean while, Maximum positive indirect effects of average fruit weight via fruit length, Fruit pericarp thickness via average fruit weight, Average fruit weight via number of fruits per plant, Fruit length via average fruit weight, Fruit length via fruit pericarp thickness,
Average fruit weight via number of primary branches, Fruit pericarp thickness via number of fruits per plant, Fruit pericarp thickness via ascorbic acid content, Fruit length via plant stem girth, Fruit breadth via number of fruits per plant and Fruit breadth via fruit pericarp thickness was observed on marketable fruit yield per plant. There by indicating the importance of yield contributing traits for yield improvement in chilli through indirect selection. 6.4
Genetic divergence studies For those traits, where selection is not responsive and non-additive gene effects
are playing major role in the expressions, hybridization between diverse parents on the basis of their mean performance to get superior hybrids or transgressive segregants or partitioning of additive genetic variation and non-additive genetic variation in segregating generations will be useful. Studies on genetic divergence will be helpful in identification of better parents. Here in this case, genetic divergence studies grouped twenty five genotypes into seven clusters. The hybridization between genotypes of cluster V and cluster VII can be utilized for getting superior recombinants or transgressive segregants in segregating population because these clusters were found most divergent.
Conclusion From the present investigation, it can be concluded that eight genotypes viz., LC-8, LC-1, LC-2, LC-4, LC-6, LC-9, Byadgi dabbi and Byadgi kaddi recorded higher fruit yield and also performed better for other horticultural traits than check cultivar Pant C-1. These genotypes need further testing to be released as a substitute of already existing chilli varieties or they can be involved in further breeding programme for development of superior varieties or hybrids for yield and quality improvement in chilli. High heritability estimates coupled with high genetic gain were observed for average fruit weight, fruit pericarp thickness, fruit breadth, number of seeds per fruit and fruit length. Hence selection can prove effective for improvement in yield. Besides this, high heritability coupled with moderate genetic gain was observed for number of fruits per plant, number of branches per plant, number of primary branches and fruit yield per plant. Therefore, these characters also show some scope for improvement through selection.
The correlation studies revealed that marketable yield per plant had positive and significant association with fruit length, plant stem girth, average fruit weight, fruit pericarp thickness, number of fruits per plant, fruit breadth, number of primary branches, plant height, days for 50% flowering and number of seeds per fruit. Hence, there traits should be taken into consideration, while making the selection for yield improvement in chilli. The path coefficient analysis revealed that maximum positive direct effect towards fruit length, fruit pericarp thickness, number of fruits per plant, fruit breadth, number of seeds per fruit, days taken for first flowering, number of primary branches, plant height and days to first fruit harvesting. Maximum positive indirect effects of average fruit weight via fruit length, Fruit pericarp thickness via average fruit weight, Average fruit weight via number of fruits per plant, Fruit length via average fruit weight, Fruit length via fruit pericarp thickness, Fruit pericarp thickness via number of fruits per plant was observed on marketable fruit yield per plant. There by indicating the importance of these traits for yield improvement in chilli through direct or indirect selection. For the traits, where selection is not effective, genetic divergence can play an important role on further partitioning of variability. In the present investigation, the cluster V and cluster VII were found more divergent and there will be more chances of getting better segregants in F2 generations from the crossing of genotypes from cluster V and cluster VII. Therefore, hybridization between the genotypes of these groups can be very effective for further improvement in chilli.
Chapter-7 LITERATURE CITED
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ABSTRACT
APPENDICES
APPENDIX - I Agro-meteorological data April to September, 2015
Figure1: Graphical representation of the monthly data pertaining to average temperature, relative humidity and rainfall.
APPENDIX – II ANALYSIS OF VARIANCE FOR DIFFERENT CHARACTERS UNDER STUDY
Source of variation
Degree of freedom
Mean sum of squares
Replication
2
X1 0.20
X2 0.86
X3 51.48
X4 0.90
X5 8.49
X6 2.33
X7 14.97
X8 31.27
Treatment
24
14.76**
5.53**
269.67**
0.41**
15.08**
20.47**
28.29**
1316.95**
Error
48
0.76
0.34
12.30
0.05
3.40
6.47
11.61
16.43
Source of variation
Degree of freedom
Replication
2
X9 0.02
X10 0.35
X11 0.03
X12 0.00
X13 65.13
X14 5.59
X15 3.77
X16 16.78
Treatment
24
2.27**
19.66**
0.56**
0.53**
1251.59**
438.82**
4264.77**
1417.03**
Error
48
0.04
0.22
0.01
0.01
15.67
52.75
14.75
11.51
Mean sum of squares
X1. Number of branches per plant X4. Plant stem girth (cm) X7. Days to first harvest X10. Fruit length (cm) X13. Number of seed per fruit X16. Fruit yield per hectare (q)
X2. Number primary branches X5. Days to first flowering X8. Number of fruit per fruit X11. Fruit breath (cm) X14. Ascorbic acid content (mg/100g)
X3. Plant height (cm) X6. Days to 50% flowering X9. Average fruit weight (g) X12. Fruit pericarp thickness (mm) X15. Fruit yield per plant (g)
