Non-destructive method for estimating leaf area of Erythroxylum pauferrense (Erythroxylaceae) from linear dimensions of leaf blades

Ribeiro, João Everthon da Silva; Coêlho, Ester dos Santos; Figueiredo, Francisco Romário Andrade; Melo, Marlenildo Ferreira

doi:10.21829/abm127.2020.1717

Cited by 10 publications

(10 citation statements)

References 40 publications

(46 reference statements)

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“…Therefore, the number of leaves ( 200) evaluated in the present study was meaningful for estimating the leaf area of P. colorata using dimensions of its leaf blades. Moreover, high variation in product of length by width and real leaf area was also observed in previous studies (Leite et al 2017;Ribeiro et al 2018a;Ribeiro et al 2020a).…”

Section: Resultssupporting

confidence: 79%

Allometric equations to estimate the leaf area of Psychotria colorata (Willd. Ex Schult.) Müll.Arg.

et al. 2021

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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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Section: Resultssupporting

confidence: 79%

Allometric equations to estimate the leaf area of Psychotria colorata (Willd. Ex Schult.) Müll.Arg.

et al. 2021

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“…The present study showed that the best equations to estimate the LA of peanut cultivars were those that used LW, compared to equations that used only one leaflet dimension (L or W), with the best criteria and adjustments of the models used (Guimarães et al 2019, Macário et al 2020, Goergen et al 2021, except for the exponential model, in which the best equations were those that used L of the leaflets (Ribeiro et al 2020).…”

Section: Discussionmentioning

confidence: 81%

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

et al. 2022

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The determination of leaf area is fundamental for studies related to plant growth and physiology. Thus, non-destructive methods allow an accurate estimate of the leaf area through linear dimensions of the leaves. The research objective was to construct allometric equations to estimate the leaflet area of peanut cultivars. Then, 2,605 leaflets were collected from six peanut cultivars (IAC Caiapó, IAC 8112, Runner IAC 886, BRS Havana, BRS 151 L7, and IAC Tatuí), with more than 400 leaflets sampled for each cultivar. We measured the length, width, product between length and width, and leaflet area. Linear and non-linear models (linear, linear without intercept, power, and exponential) were built, and the best equation was chosen using the statistical criteria: highest coefficient of determination (R 2 ), Pearson's linear correlation coefficient (r), Willmott's agreement index (d), lowest Akaike information criterion (AIC), and root mean square of the error (RMSE). It was found that the models that used the product between length and width were the most suitable for estimating the leaflet area of peanut cultivars. Given the little intraspecific morphological variability, it was possible to group the cultivars, and model ̂= 0.875 * LW 0.929 was indicated to estimate the peanut leaflet area accurately, regardless of the cultivar.

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“…Therefore, the number of leaves (200 leaves) used in this study was adequate to estimate the leaf area of E. velutina through linear dimensions of the central leaflet. Other studies also reported high variation in product of length by width, product of length by length, product of width by width, and real leaf area (RIBEIRO et al, 2020b).…”

Section: Discussionmentioning

confidence: 86%

“…As compared to the equations fitted using length or width, those equations adjusted using the product of length by width (LW) showed the best assumptions for estimating leaf area, thus best fitting the regression models (RIBEIRO et al, 2019b). Except for the equation adjusted using the exponential model, which showed the best indexes when using leaflet width (W) (RIBEIRO et al, 2020b).…”

Section: Discussionmentioning

confidence: 99%

LEAF AREA OF Erythrina velutina Willd. (FABACEAE) THROUGH ALLOMETRIC EQUATIONS

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et al. 2022

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Area foliar de Erythrina velutina Willd. (Fabaceae) a partir de equações alométricas. A estimativa da área foliar é de fundamental importância para avaliar o crescimento, desenvolvimento e propagação das plantas. Este trabalho teve como objetivo ajustar e identificar modelos de regressão para estimar a área foliar de Erythrina velutina a partir das dimensões lineares do folíolo central das folhas. Duzentas folhas simples foram coletadas de árvores matrizes de E. velutina em fragmentos florestais no município de Mossoró, estado do Rio Grande do Norte, Nordeste do Brasil. A equação para estimativa da área foliar de E. velutina foi ajustada a partir de modelos de regressão linear, linear sem intercepto (0,0), quadrático, cúbico, potência e exponencial. As melhores equações foram aquelas com maior coeficiente de determinação (R²), coeficiente de correlação de Pearson (r), índice de Willmott (d) e índice CS (CS), e com o menor critério de informação de Akaike (AIC) erro absoluto médio (MAE) e erro quadrático médio (RMSE), e índice BIAS mais próximo de zero (BIAS). As equações ajustadas pelo produto comprimento pela largura (LW) apresentaram os melhores critérios para estimar a área foliar, portanto, se ajustam melhor aos modelos de regressão utilizados. Portanto, a equação ŷ = 1,4755*LW ajustada usando o modelo linear sem intercepto é a mais adequada para estimar a área foliar de E.

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Non-destructive method for estimating leaf area of Erythroxylum pauferrense (Erythroxylaceae) from linear dimensions of leaf blades

Cited by 10 publications

References 40 publications

Allometric equations to estimate the leaf area of Psychotria colorata (Willd. Ex Schult.) Müll.Arg.

Allometric equations to estimate the leaf area of Psychotria colorata (Willd. Ex Schult.) Müll.Arg.

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

LEAF AREA OF Erythrina velutina Willd. (FABACEAE) THROUGH ALLOMETRIC EQUATIONS

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