ABSTRACT Bulk density (BD) is a soil physical property used as a soil quality indicator and variations in this measurement influence soil water content and carbon stock estimates. This study aims to compile a database of samples of bulk density, textural fractions, and organic carbon values, as well as evaluate the accuracy of published pedotransfer functions (PTF) that predict bulk density, and propose a hierarchical PTF to predict the bulk density of Brazilian Soils. The performance of eleven PTFs and the newly proposed PTFs were evaluated and compared using the root mean square error (RMSE) and coefficient of determination (R2) based on a testing soil database collected from the literature. We noticed a slight improvement in accuracy when organic carbon and coarse and fine sand fractions were included as predictors alongside silt and clay. The best results with existing PTFs were obtained by PTF-A in Tomasella and Hodnett (1998) (RMSE = 0.20 g cm–3) and PTF-F in Benites et al. (2007) (RMSE = 0.17 g cm–3). Our proposed PTFs use textural fractions and organic carbon as predictors in a hierarchical form. The proposed PTF-4, which uses fine sand, coarse sand, clay, and organic carbon, presented the lowest value for RMSE (0.14 g cm–3) for BD prediction. (BD estimates values (PTF Soils R2 R (R2 literature clay PTFA A 1998 (1998 020 0 20 0.2 cm–3 cm3 cm 3 PTFF F al 2007 (2007 017 17 0.1 cm–3. . form PTF4, PTF4 4, 4 PTF-4 0.14 014 14 (0.1 prediction (R 199 (199 02 2 0. cm– 200 (200 01 1 PTF- (0. 19 (19 (20 (0 (1 (2 (

Resumo: O objetivo deste trabalho foi desenvolver e avaliar um método para estimar a produtividade de milho com uso de um número mínimo de parâmetros e de informações limitadas sobre o manejo da cultura. O método proposto estima rendimentos potenciais e atingíveis com base no nível tecnológico dos sistemas de produção e em modelos agrometeorológicos relativamente simples. A produtividade de milho foi estimada para as safras de 2000/2001 a 2007/2008, tendo-se considerado vários locais e regiões do Brasil, e comparada aos dados de produção reais de levantamentos oficiais. A produtividade estimada apresentou alta correlação com a observada (0,76≤R2<0,92; p<0,01), com eficiência do modelo (E1’) entre 0,45 e 0,73; erro médio relativo (MRE) entre -0,9 e 2,4%; e erro médio absoluto (MAE) inferior a 70 kg ha-1, de acordo com o nível tecnológico considerado. Com base nestes resultados, este modelo pode ser recomendado para estimativas de produtividade em todo o País, e contribuir para tornar este processo mais preciso e exato.

Abstract: The objective of this work was to develop and evaluate a method for estimating corn yield using a minimum number of parameters and limited information about crop management. The proposed method estimates potential and attainable yields based on the technological level of the production systems and on relatively simple agrometeorological models. Corn yield was estimated for the crop seasons from 2000/2001 to 2007/2008, considering several locations and regions in Brazil, and was compared with the actual yield data from official surveys. There was a high correlation between the estimated and observed yield (0.76≤R2<0.92; p<0.01), with model efficiency (E1’) ranging from 0.45 to 0.73; mean relative error (MRE) between -0.9 and 2.4%; and mean absolute error (MAE) of less than 70 kg ha-1, depending on the technological level adopted. Based on these results, the proposed yield model can be recommended to forecast yields all over the country, contributing to make this process more precise and accurate.

O objetivo deste trabalho foi avaliar um sistema de estimativa de produtividade da cultura do arroz no Brasil, com base em modelos agrometeorológicos simples e no nível tecnológico dos sistemas produtivos. Este sistema de estimativa incorpora as bases conceituais propostas por Doorenbos & Kassam para produtividades potenciais e alcançáveis com ajustes empíricos para produtividade máxima e sensibilidade da cultura à deficiência hídrica, considerando-se cinco classes de produtividade de arroz. A produtividade de arroz foi estimada de 2000/2001 a 2007/2008 e comparada aos dados do IBGE. Análises de regressão entre as estimativas do modelo e dados do IBGE resultaram em coeficientes de determinação significativos, com menor dispersão na região Sul do que nas regiões Norte e Nordeste do país. O índice de eficiência do modelo (E1') variou de 0,01, nas classes de menor produtividade, a 0,45 nas classes de maior produtividade, e o erro médio absoluto variou de 58 a 250 kg ha‑1, respectivamente.

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.