Modelos matemáticos para a estimativa da área foliar de mandioca

Abstract

The objective of this study was to determine equations that allow estimating the leaf area of cassava genotypes from biometric measurements of the leaves. Leaves of 17 cassava genotypes were collected and the length and width of the central lobe and the real leaf area were measured in each unit. The genotypes were grouped using the UPGMA multivariate analysis method, using the ratio between the length and width of the central lobe (C/L). After grouping, Pearson’s correlation test was performed between the biometric measurements and the real leaf area. Linear and potential equation models were tested for the groups found through cluster analysis. The biometric variables that showed the greatest correlation with the leaf area were the product of the length and width of the lobe and the length of the central lobe. Four different groups were found, in which the linear equation models were best adjusted when using the product between the length and width of the central lobe and the potentials when using the length of the central lobe.