Estimation of Thunbergia grandiflora leaf area from allometric models

Abstract

Sky vine (Thunbergia grandiflora Roxb) is a vine with important structural components for forest environments. Studies on growth and development are necessary, because of the environmental and economic importance. The leaf area determination is essential for ecophysiological studies to understand the relationship of the plant with the environment. The objective of this work was to estimate an allometric equation to estimate the leaf area of T. grandiflora from linear dimensions. 200 leaves of different shapes and sizes were collected from adult plants and the length (L), width (W), the product between length and width (LW), and real leaf area (LA) were measured. The linear regression, linear without intercept, quadratic, cubic, power, and exponential models were used to estimate the equations. The criteria for determining the best model were higher determination coefficient (R2), Willmott's agreement index (d), lower Akaike information criterion (AIC), the root of the mean error square (RMSE), and BIAS index closer to zero. The leaf area of T. grandiflora can be estimated satisfactorily by the equation ŷ = 0.58*LW.

Allometric models to estimate peanuts leaflets area by non-destructive method

“…Generally, linear models are the most used to estimate the leaf area of agricultural and forest species (Gomes et al 2020, Goergen et al 2021, Hernandéz-Fernandez et al 2021, Mela et al 2022). However, it is assumed that these models are used with losses in precision, which often occurs due to the high values of the intercepts (β0) of the regression line (Santos et al 2021).…”