ABSTRACT Chrysanthemum (Dendranthema grandiflora) is the second most produced and commercialized ornamental plant in the world. Measuring leaf area through non-destructive methods is fundamental for studies on its growth and production. The estimation of leaf area by linear dimensions of the leaves can be a strategy for this purpose. The objective of this study was to find allometric equations to estimate the leaf area of chrysanthemum. The linear, linear without intercept, quadratic, cubic, power, and exponential regression models were used for the analysis. The choice of equations was based on the highest coefficients of determination. The non-destructive method using allometric models has accuracy for estimating the leaf area (LA) of chrysanthemum from the product between leaf length (L) and leaf width (W). The LA of chrysanthemum can be estimated using the equation ŷ = 0.6611*LW0.9490 (L - leaf length; W - leaf width). This equation will allow researchers and producers to determine leaf area non-destructively.

RESUMO O crisântemo (Dendranthema grandiflora) é a segunda planta ornamental mais produzida e comercializada no mundo. A medição da área foliar por métodos não destrutivos é fundamental para estudos sobre seu crescimento e produção. A estimativa da área foliar por dimensões lineares das folhas pode ser uma estratégia para este fim. O objetivo deste estudo foi encontrar equações alométricas para estimar a área foliar do crisântemo. Os modelos de regressão linear, linear sem intercepto, quadrático, cúbico, potência e exponencial foram utilizados para a análise. A escolha das equações foi baseada nos maiores coeficientes de determinação. O método não destrutivo por meio de modelos alométricos tem acurácia para estimar a área foliar (AF) do crisântemo a partir do produto entre o comprimento da folha (C) e a largura da folha (L). A AF do crisântemo pode ser estimada pela equação ŷ = 0,6611*CL0,9490 (C - comprimento da folha; L - largura da folha). Essa equação permitirá que pesquisadores e produtores determinem a área foliar de forma não destrutiva.

ABSTRACT The goal of this paper was to apply a method for the delineation of vegetation homogeneous zones (HZs) to map the profitability of cotton ( Gossypium sp.) using NDVI (Normalized Difference Vegetation Index) data from RPA imagery. Two irrigated cotton crops, at the FAU (103 ha) and FRP farms (106 ha), located in the western region of Bahia State, Brazil, were studied. The NDVI images were classified into three HZs: “high”, “medium” and “low” plant vigor; using the k-means clustering method. In each HZ the yield was measured, and the profitability estimated. In FAU we found that the lower the HZ’s NDVI values, the lower its profitability, because there was profit in the “high vigor” HZ, of US$ 829.40 ha-1, and loss in the “low vigor” HZ, of about US$ ‒1.256.09 ha-1 (‒251.44% compared with the “high vigor”). In the FRP plantation, the lower the NDVI values, the lower the loss of the plantation, as there were losses in all HZs: from “high” to “low vigor” HZ, the percentage difference in profitability was ‒343.43%. Thus, the use of a low-cost modified near-infrared Canon S100 on an RPA enabled the mapping of crop profitability, aiding the search for the factors behind yield variability.