Soybean yield estimation by an agrometeorological model in a GIS

Authors

  • Luciana Miura Sugawara Berka National Institute for Space Research; Remote Sensing Division
  • Bernardo Friedrich Theodor Rudorff National Institute for Space Research; Remote Sensing Division
  • Yosio Edemir Shimabukuro National Institute for Space Research; Remote Sensing Division

DOI:

https://doi.org/10.1590/S0103-90162003000300003

Keywords:

geographic information system, municipalities, weather, crop

Abstract

Agrometeorological models interfaced with the Geographic Information System - GIS are an alternative to simulate and quantify the effect of weather spatial and temporal variability on crop yield. The objective of this work was to adapt and interface an agrometeorological model with a GIS to estimate soybean [Glycine max (L.) Merr.] yield. Yield estimates were generated for 144 municipalities in the State of Paraná, Brazil, responsible for 90% of the soybean production in the State, from 1996/1997 to 2000/2001. The model uses agronomical parameters and meteorological data to calculate maximum yield which will be penalized under drought stress. Comparative analyses between the yield estimated by the model and that reported by the Paraná State Department of Agriculture (SEAB) were performed using the "t" test for paired observations. For the 1996/1997 year the model overestimated yield by 10.8%, which may be attributed to the occurrence of fungal diseases not considered by the model. For 1997/1998, 1998/1999 and 1999/2000 no differences (P >; 0.05) were found between the yield estimated by the model and SEAB's data. For 2000/2001 the model underestimated yield by 10.5% and the cause for this difference needs further investigation. The model interfaced with a GIS is an useful tool to monitor soybean crop during growing season to estimate crop yield.

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Published

2003-01-01

Issue

Section

Agrometeorology

How to Cite

Soybean yield estimation by an agrometeorological model in a GIS . (2003). Scientia Agricola, 60(3), 433-440. https://doi.org/10.1590/S0103-90162003000300003