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The aim of this study was to obtain a mathematical model for estimating the leaf area index (LAI) of a sunflower crop as a function of accumulated thermal time. Generating the models and testing their coefficients was carried out using data obtained from experiments carried out for different sowing dates in the crop years of 2007/08, 2008/09, 2009/10 and 2010/11 with two sunflower hybrids, Aguará 03 and Hélio 358. Linear leaf dimensions were used for the non-destructive measurement of the leaf area, and thermal time was used to quantify the biological time. With the data for accumulated thermal time (TTa) and LAI known for any one day after emergence, mathematical models were generated for estimating the LAI. The following models were obtained, as they presented the best fit (lowest rootmean- square error, RMSE): gaussian peak, cubic polynomial, sigmoidal and an adjusted compound model, the modified sigmoidal. The modified sigmoidal model had the best fit to the generation data and the highest value for the coefficient of determination (R2). In testing the models, the lowest values for root-mean-square error, and the highest R2 between the observed and estimated values were obtained with the modified sigmoidal model

Estimation of leaf area index in the sunflower as a function of thermal time