A non-destructive method for predicting the leaflet area of Cassia fistula L.: An approach to regression models

Abstract

The leaf area is an important parameter for plant growth and development, usually determined by direct and destructive methods. In these methods, high-cost equipment is mainly used, requiring more time and restrictions in the analyses. Therefore, the study sought to construct, through regression models, allometric equations that allow estimating the area of leaflets of Cassia fistula L. by a non-destructive method using the linear dimensions of the leaflets. Six hundred leaflets of different sizes and shapes were randomly collected in adult species matrices. Each leaflet's length, width, and leaf area were measured using digital images. Next, the products were calculated between length and length, width and width, and length and width. Two regression models were used to construct five allometric equations to predict the area of leaflets of C. fistula. All the proposed equations can be used to estimate the leaf area of the species; however, the best equations were constructed using the power and linear without intercept models, being the most indicated to estimate the leaf area of the species, presenting the highest determination coefficients (R² = 0.9949 and 0.9993), Pearson's correlation coefficients (r = 0.9374 and 0.9374), Willmott's agreement index (d = 0.9987 and 0.9986), and lowers Akaike information criterion (AIC = 1071.3 and 1098.2) and normalized root mean square error (NRMSE = 7.2 and 7.1). Thus, the models y^=0.747*LW0.981 and y^=0.696*LW should be applied to estimate the area of leaflets of C. fistula.