ABSTRACT: Using non-destructive and low-cost methods to determine leaf area has gained important applications. The research objectives were (i) to propose a non-destructive method to estimate the leaf area of castor bean crops and (ii) to build equations that accurately and quickly estimate the leaf area of specie. One thousand healthy and expanded leaves of five castor bean cultivars (New Zealand Purple, Sipeal, Carmencita, Amarelo de Irecê, and IAC-80) were collected, and 200 leaves were collected from each. The maximum length, maximum width, and leaf area were calculated for each leaf. The product between length and width (LW) were calculated. We performed tests with different linear and non-linear regression models between leaf area and linear leaf dimensions of each cultivar. The models used were linear, linear without intercept, and power. The criteria for choosing the best models to estimate the leaf area of castor beans were a higher coefficient of determination, more elevated Pearson’s linear correlation coefficient, lower Akaike information criterion, higher Willmott agreement index, and smallest root mean square error. The equations that presented the best criteria for estimating the leaf area of castor bean cultivars were those that used the product between length and width, compared to equations that used only one leaf dimension. The model ŷ = 0.439 × LW can be used to accurately and quickly estimate the castor bean leaf area through linear measurements of the leaves, using the product between length and width (LW), regardless of the cultivar chosen. ABSTRACT nondestructive non destructive lowcost low cost applications i (i ii (ii specie New Purple Sipeal Carmencita Irecê IAC80 IAC 80 IAC-80 20 (LW nonlinear intercept power determination Pearsons Pearson s criterion index error dimension 0439 0 439 0.43 LW, , chosen IAC8 8 IAC-8 2 043 43 0.4 IAC- 04 4 0.

RESUMO: O uso de métodos não destrutivos e de baixo custo para determinação de área foliar tem ganhado importantes aplicações. Os objetivos da pesquisa foram (i) propor um método não destrutivo para estimar a área foliar da cultura da mamona e (ii) construir equações que estimem com precisão e rapidez a área foliar da espécie. Foram coletadas mil folhas sadias e expandidas de cinco cultivares de mamona (New Zealand Purple, Sipeal, Carmencita, Amarelo de Irecê e IAC-80), sendo coletadas 200 folhas de cada uma. O comprimento máximo, largura máxima e área foliar foram calculados para cada folha. Foi calculado o produto entre comprimento e largura (LW). Foram realizados testes com diferentes modelos de regressão linear e não linear entre área foliar e dimensões lineares das folhas de cada cultivar. Os modelos utilizados foram linear, linear sem intercepto e potência. Os critérios para escolha dos melhores modelos para estimar a área foliar da mamona foram maior coeficiente de determinação, maior coeficiente de correlação linear de Pearson, menor critério de informação de Akaike, maior índice de concordância de Willmott e menor raiz do erro quadrático médio. As equações que apresentaram melhores critérios para estimativa da área foliar das cultivares de mamona foram aquelas que utilizaram o produto entre comprimento e largura, em comparação às equações que utilizaram apenas uma dimensão foliar. O modelo ŷ = 0,439 × LW pode ser utilizado para estimar com precisão e rapidez a área foliar da mamona por meio de medidas lineares das folhas, utilizando o produto entre comprimento e largura (LW), independente da cultivar escolhida. RESUMO aplicações i (i ii (ii espécie New Purple Sipeal Carmencita IAC80, IAC80 IAC 80 , IAC-80) 20 máximo folha LW. . (LW) potência Pearson Akaike médio 0439 0 439 0,43 LW, escolhida IAC8 8 IAC-80 2 (LW 043 43 0,4 IAC-8 04 4 0, IAC-

ABSTRACT 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 (R2), 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 y ^ = 0.875 * LW0.929 was indicated to estimate the peanut leaflet area accurately, regardless of the cultivar.