SPATIAL VARIABILITY OF SOYBEAN / CORN YIELD AND SOIL TEXTURE IN THE GENERATION OF MANAGEMENT ZONES

Authors

  • DÁRIO ALEXANDRE SCHWAMBACH Ex aluno da UFGD
  • JORGE WILSON CORTEZ Universidade Federal da Grande Dourados - UFGDFaculdade de Ciências Agrárias
  • DIANDRA PINTO DELLA FLORA Aluno da UFGD
  • HERMANO JOSÉ RIBEIRO HENRIQUES Aluno da UFGD
  • LUCAS DE OLIVEIRA DONAIRE Ex aluno da UFGD

DOI:

https://doi.org/10.17224/EnergAgric.2021v36n3p335-347

Abstract

The spatial representation of soil texture and crop yield allows the formulation of solid and efficient management strategies. Thus, the objective was to evaluate the spatial variability of soybean / corn yield and soil texture in the generation of management zones. The work was carried out in an area of ​​130 ha with summer soybean and off-season corn succession. A sampling degree was generated, with 64 points in a regular grid and 13 more random points, totaling 77 points, one every 1.7 ha. Soil data collection was performed manually and soybean (2017/2018 and 2018/2019) and corn (2018 and 2019) productivity data were collected from the harvester's productivity monitor. Texture and productivity data were discovered through descriptive statistics and spatialization. The variability of soybean and corn yields was influenced by soil texture and climate. Under water deficit conditions, such as higher corn and soybean yields in regions with more clay, normal soybean yield conditions were higher in regions with more sand. In areas with differing clay content, management zones can be made from this isolated attribute.

Author Biography

JORGE WILSON CORTEZ, Universidade Federal da Grande Dourados - UFGDFaculdade de Ciências Agrárias

Professor Adjunto. Área de Mecanização, Máquinas e Implementos Agrícolas.

Published

2021-09-28

How to Cite

SCHWAMBACH, D. A. ., CORTEZ, J. W., FLORA, D. P. D. ., HENRIQUES, H. J. R. ., & DONAIRE, L. D. O. . (2021). SPATIAL VARIABILITY OF SOYBEAN / CORN YIELD AND SOIL TEXTURE IN THE GENERATION OF MANAGEMENT ZONES. ENERGY IN AGRICULTURE, 36(3), 335–347. https://doi.org/10.17224/EnergAgric.2021v36n3p335-347

Issue

Section

Automation and Optimization of Agricultural Machinery and Equipment

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