Navegando por Autor "Guimarães, Larissa Morane Pinto"

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Desenvolvimento de modelos matemáticos para estimativa da área foliar de leguminosas forrageiras
(2020-10-27) Guimarães, Larissa Morane Pinto; Cunha, Márcio Vieira da; http://lattes.cnpq.br/8936474723708253; http://lattes.cnpq.br/4555295690063951
The leaf area is an important characteristic of forage plants. Through it, it is possible to monitor the development of plants and calculate the leaf area index, which has been used as a parameter for the management of forage plants. The objective of this work was to evaluate mathematical models to estimate leaf area of the styling leguminous seabrana (Stylosanthes seabrana BL Maass & 't Mannetje), Leucena (Leucaena leucocephala (Lam.) De Wit.) And Gliricidia (Gliricidia sepium (Jacq.) Kunth ex Walp.) Depending on the length, width and product of the leaf length and width. 200 expanded leaves were collected per legume species. For measurements of leaf dimensions (length and width), a measuring tape graduated in centimeters was used and for the leaf area, the Easy Leaf Area Free application was used for smartphones. Descriptive statistical analysis of the studied variables (leaf area, length and width) was performed and three linear models were tested for each species and for the set of leaves of all species, totaling 12 models, using the leaf area as a dependent variable. The performance of the models was evaluated by RMSE (root mean squared error) and R2. The model with the product of leaf length and width as an independent variable showed the best fit and estimate of the leaf area. Thus, it was possible to estimate the leaf area of forage legumes with greater precision through the product of leaf length and width, in all legumes, notably in Gliricídia. In addition, the best model was obtained by integrating all leaves of the species. The Easy Leaf Area Free smartphone application proved to be efficient and easy to use to estimate the leaf area of the studied legumes.
Relatório de Estágio Supervisionado Obrigatório
(2020-10-29) Guimarães, Larissa Morane Pinto; Lima, Tayara Soares de; http://lattes.cnpq.br/3100045021780173; http://lattes.cnpq.br/4555295690063951