Evaluation of mathematical equations for estimating leaf area in rapeseed

Abstract

ABSTRACT The aim of this study was to evaluate estimations of leaf area in rapeseed (Brassica napus L.) and the potential for application to different genotypes, environmental conditions and types of crop management. In experiments conducted during 2013, 2014, 2016 and 2017, three genotypes of rapeseed, five doses of nitrogen and three sowing dates were used. Leaves were randomly collected from different plants and positions on the plants. The leaf area (LA), and maximum width (W) and length (L) were determined for each leaf, and the product of L and W (LxW) was calculated. Fifty-six equations for estimating LA in rapeseed, where the independent variables were W, L or LxW, were compiled from the bibliography and evaluated in this work. The evaluation was made using the following statistics: significance of the linear (a) and angular (b) coefficients of the regression around the 1:1 line, concordance index (d), bias index (BIAS), mean absolute error (MAE), mean relative error (MRE), random mean squared error (MSEr) and systematic mean squared error (MSEs). Only 11 equations showed the a and b coefficients as not being different from 0 and 1 respectively. However, only 10 were suitable, as they displayed the lowest values for d, BIAS, MAE and RME, and the MSEs was smaller than the MSEr. The MAE ranged from 5.4 cm2 to 16.2 cm2, well within the error range for generating the equations. LA in rapeseed can be estimated by general biometric equations without considering the specificity of the genotype or the morphological type of the leaf.

Keywords

• Brassica napus
• Colza
• Modelling
• Leaf area index