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Allometric equations to estimate the leaf area of Psychotria colorata (Willd. Ex Schult.) Müll.Arg.
Ribeiro, João Everthon da Silva; Figueiredo, Francisco Romário Andrade; Coêlho, Ester dos Santos; Melo, Marlenildo Ferreira.
  • Ribeiro, João Everthon da Silva; Private Pratice. Mari. BR
  • Figueiredo, Francisco Romário Andrade; Federal Rural University of the Semi-Arid. Mossoró. BR
  • Coêlho, Ester dos Santos; Federal Rural University of the Semi-Arid. Mossoró. BR
  • Melo, Marlenildo Ferreira; Federal Rural University of the Semi-Arid. Mossoró. BR
Biosci. j. (Online) ; 37: e37076, Jan.-Dec. 2021. ilus, tab, graf
Artículo en Inglés | LILACS | ID: biblio-1359210
ABSTRACT
Estimating leaf area using non-destructive methods from regression equations has become a more efficient, quick, and accurate way. Thus, this study aimed to propose an equation that significantly estimates the leaf area of Psychotria colorata (Rubiaceae) through linear leaf dimensions. For this purpose, 200 leaves of different shapes were collected, and length (L), width (W), product of length by width (L.W), and real leaf area (LA) of each leaf blade were determined. Then, equations were adjusted for predicting leaf area using simple linear, linear (0.0), quadratic, cubic, power, and exponential regression models. The proposed equation was selected according to the coefficient of determination (R²), Willmott's agreement index (d), Akaike's information criterion (AIC), mean absolute error (MAE), mean squared error (RMSE) and BIAS index. It was noted that the equations adjusted using L.W met the best criteria for estimating leaf area, but the equation LA = 0.59 * L.W from linear regression without intercept was the most suitable. This equation predicts that 59% of leaf area is explained by L.W. Concluding, the leaf area of P. colorata can be estimated using an allometric equation that uses linear leaf blade dimensions.
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Texto completo: Disponible Índice: LILACS (Américas) Asunto principal: Hojas de la Planta / Psychotria Idioma: Inglés Revista: Biosci. j. (Online) Asunto de la revista: Agricultura / Disciplinas das Ciˆncias Biol¢gicas / Pesquisa Interdisciplinar Año: 2021 Tipo del documento: Artículo País de afiliación: Brasil Institución/País de afiliación: Federal Rural University of the Semi-Arid/BR / Private Pratice/BR

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Texto completo: Disponible Índice: LILACS (Américas) Asunto principal: Hojas de la Planta / Psychotria Idioma: Inglés Revista: Biosci. j. (Online) Asunto de la revista: Agricultura / Disciplinas das Ciˆncias Biol¢gicas / Pesquisa Interdisciplinar Año: 2021 Tipo del documento: Artículo País de afiliación: Brasil Institución/País de afiliación: Federal Rural University of the Semi-Arid/BR / Private Pratice/BR