Abstract
The objective of this work was to evaluate an estimation system for rice yield in Brazil, based on simple agrometeorological models and on the technological level of production systems. This estimation system incorporates the conceptual basis proposed by Doorenbos & Kassam for potential and attainable yields with empirical adjusts for maximum yield and crop sensitivity to water deficit, considering five categories of rice yield. Rice yield was estimated from 2000/2001 to 2007/2008, and compared to IBGE yield data. Regression analyses between model estimates and data from IBGE surveys resulted in significant coefficients of determination, with less dispersion in the South than in the North and Northeast regions of the country. Index of model efficiency (E1') ranged from 0.01 in the lower yield classes to 0.45 in higher ones, and mean absolute error ranged from 58 to 250 kg ha‑1, respectively.
Highlights
Crop yield forecasting and the knowledge of yield distribution are extremely important for governmental planning
It was composed by two modules: one that estimates crop potential yield or maximum yield; and other that estimates the decrement of potential yield as a function of water deficit
The proposed model was calibrated with basis on rice yield data derived from production and harvested area series surveyed by IBGE, for the growing seasons from 2000/2001 to 2007/2008
Summary
Crop yield forecasting and the knowledge of yield distribution are extremely important for governmental planning This information is essential for public policy formulation, logistic distribution, food security, and for price formation at national and international markets (Figueiredo, 2005). Information on Brazilian total production, cropped area and yield can be obtained from crop surveys conducted by Companhia Nacional de Abastecimento (the national supply company, Conab) and Instituto Brasileiro de Geografia e Estatística (Brazilian Institute of Geography and Statistics, IBGE). These surveys are done for each municipality through interviews with local farmers, agronomists and technicians of cooperatives, agricultural offices and technical assistance agencies.
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