Basil leaf area by allometric relations

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lack of studies about the estimative of basil leaf area, it becomes the objective of this ... leaf area of the basil (Ocimum basilicum L.) grown at field conditions.
  Vol. 8(43), pp. 1275-1283, 17 November, 2014 DOI: 10.5897/JMPR2014.5538 Article Number: AB2CBD348802 ISSN 1996-0875 Copyright © 2014 Author(s) retain the copyright of this article http://www.academicjournals.org/JMPR

Journal of Medicinal Plant Research

Full Length Research Paper

Basil leaf area by allometric relations Jefferson Vieira José*, Rafael Dreux Miranda Fernandes, Patricia Angélica Alves Marques, Ana Luíza Lima Ferreira, João Paulo Francisco and Sérgio Nascimento Duarte Departamento de Engenharia de Biossistemas - Escola Superior de Agricultura Luiz de Queiroz ESALQ-USP, Av. Pádua Dias, 11, CEP 13418-900, Piracicaba, SP, Brazil. Received 20 August, 2014; Accepted 29 October, 2014

The leaf area (LA) is a valuable measure to plant physiological studies; therefore, simple models are necessary to its determination, which may be used in many experimental comparisons. In view of the lack of studies about the estimative of basil leaf area, it becomes the objective of this study to propose models that use non-destructive measures of length (L) and/or width (W) of the leaves, to estimate the leaf area of the basil (Ocimum basilicum L.) grown at field conditions. The measures of leaf area, length and width of the leaves were performed with 600 leaves from digital pictures, including leaves with leaf area from 0.47 to 25.42 cm². The validation of the models was done through the adjusted determination coefficient ( ), the linear correlation coefficient, and the indexes of concordance of Willmott (d) and of performance of Camargo-Sentelhas (c). The models that presented normality and homocedasticity were evaluated through the Bland-Altman plot. The model , that used the ellipse area (CL (π/4)), with

= 0.9943, proved to be the most adequate model to the basil leaf area estimative, with

high precision and accuracy, random pattern of distribution of residuals and easy mensuration. Key words: Ocimum basilicum L., linear dimensions, biometry, Bland-Altman. INTRODUCTION Basil (Ocimum basilicum L.) belongs to the Lamiaceae family. It is an annual or perennial plant, shrubby, with height between 0.30 and 1.00 m, woody or semi hardwood of tender appearance with oval leaves. It is natural from the tropical and subtropical regions of Asia, Africa and Central and South America. Classified as a medicinal, aromatic and seasoning plant with importance in the context of the global economy. Beyond its use for seasoning, the basil is used for obtaining the essential oil

that has as its main component the linalool, important in the pharmaceutical industry (Lorenzi and Matos, 2003; Labra et al., 2004; Blank et al., 2007). Considering the economic importance of the basil cultivation and the lack of information found in the literature, arises the necessity to develop studies regarding the reproduction, growth, development, nutritional requirements, among others. According to Bianco et al. (2002), in most of these studies, the knowledge of the leaf area is

*Corresponding author. E-mail: [email protected]. Tel: +55 19 982743653. Author(s) agree that this article remain permanently open access under the terms of the Creative Commons Attribution License 4.0 International License

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fundamental, being one of the most important parameters in the evaluation of the plant growth. Beyond that, it is one of the variables of highest difficulty of being measured, because it regularly requires expensive equipment or destructive techniques. According to Blanco and Folegatti (2005), the leaf area (LA) is a very important variable to the majority of the agronomic and physiologic studies that involves the plant growth, light interception, photosynthetic efficiency, evapo-transpiration and response to fertilizers and irrigation. Magalhães and Ferri (1979) also emphasizes the importance of the knowledge of the leaf area, because the leaves are responsible by the capitation of the solar energy and biomass production, by photosynthesis. Thus, the production and quality of the vegetables are affected by the photosynthesis and by the transpiration rate that are deeply related to the LA, making this variable an indispensable component in most of the models developed for simulating the carbon and water dynamics in the system (Achten et al., 2010). There are many methods for the measure of the leaf area, the majority with good precision. Marshall (1968) classified them in destructive or non-destructive, direct or indirect. The destructive methods, although being simple and precise, presents the inconvenience of demanding time and not being adequate to measurements to follow plants growth, because they cause the destruction of the vegetable mass (Lu et al., 2004). The indirect methods and/or non-destructive are used when there is no availability of the measuring instruments, or when the destructive method is not practicable (Blanco and Folegatti, 2005). The importance of adopting a nondestructive method is that it allows to follow the growth and leaf expansion of the same plant until the end of the cycle or of the test, beyond being fast and precise. Nondestructive methods of measuring are characterized by establishing relations between the actual leaf area and dimensional parameters of the leaf that presents good

correlation with the leaf area. These, beyond the fact of not compromising the evaluation of other parameters dependent of the leaf area, reduce the variability associated to sampling procedures, and also allows that the measure be performed many times in different moments in the same individual (Lima and Silva et al., 2004). New instruments, tools and machines, such as handheld laser scanners and optic equipment have been developed to realize the measures of LA. However, these tools are expensive and complex for basics and simple studies (Demirsoy et al., 2005). According to Kandiannan et al. (2009), an approach through modeling is faster, more reliable and involves linear relations between LA and one or more dimensions of the leaf, being an alternative of a precise measure. Modeling is an essential tool to evaluate continuous changes in LA and subsequent crop growth (Bonser and Aarssen, 2009). These relations are empirically determined, establishing the form and the significance between two or more biological variables; the form of this relation is established

through regression analysis (Niklas, 1994). Many authors have used allometric relations for the estimation of the leaf area of plants. Ramos et al. (2008) identified equations to the estimation of leaf area of plants of palm plants using the height, the diameter of the main rod, the length and the thickness of the leaf rachis. Souza et al. (2008) correlated the length and the width of leaves of cowpea with the total leaf area of the plants. Bosco et al. (2012) adjusted equations of linear and quadratic regression for the estimation of leaf area in function of the dimensions of the apple tree leaves and verified that the models that used length and width of the leaves estimated the total leaf area of the plant with accuracy and precision. The mathematical equations for the estimation of the leaf area are developed in search of a method fast and easy to be performed, being an important methodology, by easily adapting itself to the use in the field, and ensuring that the assessments are performed many times throughout the development of the culture. However, the researches developed about the estimative of the LA of basil through allometric relations are nonexistent and there is the need for studies in this scope, facilitating further researches that involve this culture. In this context, the objective of this study was to identify reliable and precise allometric models, using nondestructive measures of length (L) and/or width (W) of the leaf to estimate the actual area of basil leaves (O. basilicum L.) irrigated and rainfed, cultivated at field conditions. MATERIALS AND METHODS The experiment was developed at the Department of Biosystems Engineering (Departamento de Engenharia de Biossistemas) of ESALQ/USP (22° 42’ 30”S, 47° 30’ 00”W, 520 m of altitude) in Piracicaba – SP. The basil (O. basilicum L.) cultivation was performed in three plats, with dimensions of 2 m × 20 m, and the measurements of leaf area (LA) were performed approximately 15 days after the second harvest of the basil. Seedlings propagated by the method of cuttings were used, with the objective of maintaining the genetic characteristics of the mother plant; the spacing between plants was of 0.5 m × 0.5 m, thus each plant occupied an area of 0.25 m². The soil was classified as Rhodic Paleudult (Ultisol) of clayey texture, presenting 50% of clay, 14% of silt and 36% of sand, soil specific mass of 1.45 g cm-3 and particle specific mass of 2.45 g cm-3. The irrigation management was performed with the use of drip irrigation system. There were plants conducted with full irrigation, in other words, the irrigation was performed so that the soil water content returns to the field capacity; and there were plants conducted in rainfed conditions, without irrigation. For the construction of the model, 600 healthy leaves were harvested, being used 100 leaves per plant and three plants per treatment (rainfed and irrigated). The leaves were sampled randomly from different parts of the plants. These plants were removed from the experimental area and, in laboratory, the total number of leaves was accounted (NL), the length (L, in cm) and the width (W, in cm) of the leaves, and calculated the product of these two variables (Arectangle = L W, in cm²), ellipse area (Aellipse = L W (π/4), in cm²) and the leaf area index (IAF). To test the methods of estimative, the actual leaf area (Yi) of the plants and its respective L and W were obtained through the

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software ImageJ (ImageJ 1.47 v – Wayne Rasband, National Institutes of Health, USA) from digital pictures, correlating the models of linear and non-linear regression between Yi and L, W, Arectangle and Aellipse, and selecting the best fitting model. The model between actual leaf area and the estimated leaf area (

) was validated using 500 new leaves. The statistic criteria for

the model selection were based on the F test, on the Pearson correlation coefficient (r) and on the adjusted determination coefficient (

) closer to one. Also on the root mean square error

(RMSE), on the sum of the squared residuals (SSR) closer to zero and on the indexes of concordance of Willmott (d) and on the indexes of performance of Camargo-Sentelhas (c) closer to one. This last index is calculated by the product between r and d (c = r d), according to Camargo and Sentelhas (1997), being that “r” represents the precision and “d” the accuracy, indicating the performance of the model. In the selected models, both dependent and independent variables were submitted to the formal analysis (graphics) of the residuals and to the Goldfeld-Quandt test to test if the residuals were homoscedastic and also to the test of normality of ShapiroWilk. When not attended, the basic assumptions of normality and homoscedasticity, the variable were submitted to the tests of Bonferroni of outliers and further to the test of Box-Cox to find the most adequate transformation to reach the behavior approximately normal, as suggested by Kandiannan et al. (2009) and Antunes et al. (2008). The

and the Yi were compared by graphic procedures

described with limit of concordance proposed by Bland-Altman (Martin Bland and Altman, 1986). All the statistical analysis were realized by the statistic software R, version 2.2.1 (Venables and Smith, 2005).

RESULTS AND DISCUSSION The descriptive statistic of the variables: number of leaves (NL), leaf area index (LAI), length (L), width (W), rectangle area (Arectangle), ellipse area (Aellipse) and actual leaf area (Yi) are presented in the Table 1. In the irrigated treatment, the values of L of the leaves varied from 1.58 to 10.99 cm, with average of 4.59 cm, on the other hand the value of W of the leaves varied from 0.27 to 4.72 cm, with average of 2.35 cm. The highest value of Yi was registered at the treatment with irrigation (7.07 cm²), while the smallest was recorded at the rainfed treatment (4.98 cm²). The number of leaves was also higher in the irrigated treatment (Table 1). The reduction of the leaf area similarly to the reduction of the number of leaves (approximately 30%) is an indicator that the restriction caused by the hydric deficiency affected both the expansion and the cellular division of the leaves (Pinto, 2006). The wide variability of the leaf sizes observed by the amplitude of L, of W and of Yi, allied to the high magnitude of the coefficient of variation (Table 1), is important to the generation of the models, because it allows the use of the models in small, medium and large leaves. So, this wide set of data of C, L, Aretangle, Aellipse,

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and Yi determined through digital pictures (600 leaves), is adequate to the proposed study according to Cargnelutti et al. (2012). The percentage distribution of Yi of O. basilicum L., in relation to the size group in the irrigated and rainfed treatments, is presented in Table 2. It is observed that 45.77% of the Yi in the irrigated treatment are related to the leaves varying from 5 to 10 cm² and 65.93% of the Yi in the rainfed treatment vary from 0 to 5 cm², indicating that these plants have most of its leaves with a small size. In the irrigated treatment the biggest leaf had Yi of 25.42 cm², however in the rainfed treatment the biggest leaf presented Yi equal to 18.77 cm². In the rainfed treatment, both first size groups (0 to 5 and 5 to 10 cm²) comprehend 89.9% of the number of measured leaves; yet, in the irrigated treatment, these same size groups comprehend only 81.92% of the number of leaves, with a difference of 7.98% between both treatments. Table 3 presents the models for the estimative of LA, the adjusted determination coefficient ( ) and the Pearson correlation coefficient (r), the Willmott index of concordance (d) and the performance index of CamargoSentelhas (c) obtained by the regression between the estimated leaf area and the actual leaf area by the use of the software Image J. As also, the root mean square error (RMSE) and the sum of the squared residuals (SSR) were

obtained through the validation of the proposed models. The regression models that estimated the leaf area from the L, W, Arectangle and Aellipse were obtained in six estimating models and these models were significant at a P-value (α=0,01) small enough, demonstrating that there is a close correlation between Yi and the linear measures of the leaves. The quality of the regression adjust was verified by the high adjusted determination coefficient; values of varied from 0.973 to 0.835, being that the

smallest value corresponds to the model that used the squared length of the leaf. While the highest value of was obtained when the estimative of the leaf area was based on the data of Arectangle and of Aellipse. These results indicate that at least 83.5% of the observed variations in were explained by the obtained models (Table 3). Based on the values of

(Table 3) and of the

correlation coefficients, it is possible to verify that the most appropriated models for the relations between the linear dimensions and the leaf area of an individual leaf are the ones that include both the dimensions, in other words, length and width. The quadratic models (L² and in comparison to the W²) presented smaller values of linear models. The best result was obtained with the linear models (Arectangle and Aellipse) because these models

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Table 1. Descriptive statistic and average test of the total number of leaves (NL), leaf area index (LAI), length (L) and width (W), rectangle area (Arectangle), ellipse area (Aellipse) and of the actual leaf area obtained by the software ImageJ (Yi).

Minimum Maximum Average Median

Nl 1821 1955 1855±39A 1879

LAI 2.82 4.51 3.88±0.53A 4.33

L (cm) 1.58 10.99 4.59±0.34A 4.23

Irrigated W (cm) Arectangle (cm2) 0.27 1.48 4.72 47.35 2.35±0.28A 11.69 ±0.62A 2.27 9.93

Minimum Maximum Average Median CV (%)

1021 1744 1371±209B 1350 22.42

3.27 4.00 3.74±0.24A 3.97 17.01

0.98 6.93 3.27±0.95B 3.09 36.84

Rainfed 0.42 3.80 1.86±0.33B 1.74 32.33

Parameter

Aellipse (cm2) 1.160 37.19 9.18±0.62A 7.80

Yi (cm2) 1.01 25.42 7.07 ±0.57A 6.21

0.32 20.35 5.17±0.63B 4.24 70.96

0.47 18.77 4.98±0.60B 4.09 61.77

0.41 25.91 6.58±0.63B 5.40 70.96

Averages followed by different letters in the same column differ from one another by the testo f Scott-Knott at the level of 0.05 of probability ± - standard error; CV (%) – Coefficient of variation.

Table 2. Frequence distribution of the leaf area of Ocimum basilicum L., regarding the size groups in the irrigated and rainfed treatments.

Size group (cm²) 0-5 5-10 10-15 15-20 20-25 25-30

Irrigated (%) 36.15 45.77 13.85 4.62 0.77 0.38

Rainfed (%) 65.93 23.97 9.46 0.63 0.00 0.00

Table 3. Equations for the estimative of the leaf area, adjusted determination coefficient (

) and linear correlation

coefficient of Pearson (r), Willmott concordance index (d) and the performance index of Camargo-Sentelhas (c), root mean square error (RMSE) and the sum of the squared residuals (SSR).

Variable

Equation

P-value

L L² W W² Arectangle Aellipse Log (Arectangle) Log (Aellipse)

1.62723* L -2.641* +(2.101* L)+(0.0254* L2) 3.05724* W 0.990-(0.328* W)+(1.174* W²) 0.62987* Arectangle 0.80198* Aellipse 10(0.8205* Arectangle) 10(0.92327* Aellipse)