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Soybean yield maps using regular and optimized sample with different configurations by simulated annealing

By Luciana P. C. Guedes, Paulo J. Ribeiro Junior, Miguel A. Uribe-opazo and Fernanda de Bastiani

Abstract

ABSTRACT This study aimed to compare thematic maps of soybean yield for different sampling grids, using geostatistical methods (semivariance function and kriging). The analysis was performed with soybean yield data in t ha-1 in a commercial area with regular grids with distances between points of 25x25 m, 50x50 m, 75x75 m, 100x100 m, with 549, 188, 66 and 44 sampling points respectively; and data obtained by yield monitors. Optimized sampling schemes were also generated with the algorithm called Simulated Annealing, using maximization of the overall accuracy measure as a criterion for optimization. The results showed that sample size and sample density influenced the description of the spatial distribution of soybean yield. When the sample size was increased, there was an increased efficiency of thematic maps used to describe the spatial variability of soybean yield (higher values of accuracy indices and lower values for the sum of squared estimation error). In addition, more accurate maps were obtained, especially considering the optimized sample configurations with 188 and 549 sample points

Topics: accuracy indices, optimization, sampling grids, spatial variability
Publisher: Associação Brasileira de Engenharia Agrícola
Year: 2016
DOI identifier: 10.1590/1809-4430-eng.agric.v36n1p114-125/2016
OAI identifier: oai:periodicos.ibict.br.EngenhariaAgricola:oai:scielo:S0100-69162016000100114
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