Abstract

VASQUEZ ROJAS, Carlos Augusto; SARMIENTO ESTUPINAN, Javier; CONTRERAS CASTRO, Jorge Humberto  and  CANCHILA ASENCIO, Emiro Rafael. Simple Regression Models to Estimate the Leaf Area in Melina Gmelina arborea Roxb. ex Sim. Under the SINPAR Silvopastoral System. Cienc. Tecnol. Agropecuaria [online]. 2023, vol.24, n.2, e2629.  Epub Aug 31, 2023. ISSN 0122-8706.  https://doi.org/10.21930/rcta.vol24_num2_art:2629.

Melina Gmelina arborea Roxb. ex Sim. is considered a potential species to be used in restoration programs and silvopastoral systems for its bromatological characterization, production of green forage and timber properties. However, it is required to establish variables related to the production of foliar biomass, such as the leaf area since it is a dynamic element in plant physiological processes. Therefore, this study aimed to define a simple regression model that estimated the leaf area in this species. A cross-sectional observational correlational study was conducted based on simple random sampling, sample size of 18 trees, cutting of 93 branches and collection of 3368 leaves. In the laboratory, the maximum leaf length and width were measured to establish the leaf area. Descriptive statistics were applied from representative measurements and graphs, as well as inferential statistics supported in the estimation and selection of the simple linearized regression model (linear, quadratic, cubic) and nonlinearized (logarithmic, potential, exponential). For the selection of the proposed model, goodness-of-fit criteria were established: coefficient of determination R., mean square error ECM, p-value of coefficients [(p)βx], normality and homoscedasticity of errors, dispersion of residuals vs adjusted and Akaike AIC. It is concluded that the estimation of the leaf area in melina is related to the variable leaf length and width from the exponential regression models AF=28.0105*e(0.1192*LF) and AF=35.2523*e(0.1421*AnF). In addition, these models have a high degree of reliability for use in predictions of the leaf area in this species.

Keywords : Agroforestry; allometry; dendrometry; photosynthesis; regression analysis.

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