Open AccessNon-destructive method for estimating leaf area of Erythroxylum pauferrense (Erythroxylaceae) from linear dimensions of leaf blades
Author(s) -
João Everthon da Silva Ribeiro,
Ester dos Santos Coêlho,
Francisco Romário Andrade Figueiredo,
Marlenildo Ferreira Melo
Publication year - 2020
Publication title -
acta botánica mexicana/acta botánica mexicana
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.255
H-Index - 14
eISSN - 2448-7589
pISSN - 0187-7151
DOI - 10.21829/abm127.2020.1717
Subject(s) - akaike information criterion , mathematics , mean squared error , coefficient of determination , linear regression , statistics , linear model
Background and Aims: Determining the leaf area is essential for studies on growth, propagation, and ecophysiology of forest species. Developing quick, practical, and accurate methods is needed to estimate leaf area without destroying leaves. Therefore, this research aimed to obtain an equation from regression models that meaningfully estimate the leaf area of Erythroxylum pauferrense using linear dimensions of its leaf blades.Methods: For this purpose, 1200 leaves were randomly collected from different plants in the Mata do Pau-Ferro, a state park located in Areia city, Paraíba state, Brazil. Equations were fitted from simple linear, linear without intercept, quadratic, cubic, power, and exponential regression models. Next, the best equation was selected by checking the following assumptions: higher determination coefficient (R²) and Willmott's index (d), lower Akaike information criterion (AIC) and root mean square error (RMSE), as well as the BIAS index closest to zero.Key results: Based on the criteria used, all equations fitted using the product of length by width (L.W) can estimate the leaf area of E. pauferrense.Conclusions: The equation ŷ=0.6740*LW from the linear model without intercept significantly estimates the leaf area of E. pauferrense in a quick and practical way (R²=0.9960; d=0.9953; AIC=1231.61; RMSE=0.4255; BIAS=-0.0130).