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All Journal AGRIVITA, Journal of Agricultural Science
Padjung, Rusnadi
Faculty of Agriculture University of Brawijaya in collaboration with PERAGI
Agriculture, Biological Sciences & Forestry

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Strategy of Soybean Management (Glycine max L.) to Cope with Extreme Climate Using CropSyst© Model Aminah, Aminah; Ala, Ambo; Musa, Yunus; Padjung, Rusnadi; Kaimuddin, Kaimuddin
AGRIVITA, Journal of Agricultural Science Vol 39, No 3 (2017): OCTOBER
Publisher : Faculty of Agriculture University of Brawijaya in collaboration with PERAGI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17503/agrivita.v39i3.1020

Abstract

This research was carried out to verify the CropSyst© plant model from experimental data in a soybean field and to predict planting time along with its potential yield. The researches were divided into two stages. First stage was a calibration for model on field from June to September 2015. Second stage was the application of the model. The required data models included climatic, soil and crop’s genetic data. There were relationship between the obtained data in field and the simulation from CropSyst© model which was indicated by 0.679 of Efficiency Index (EF) value. This meant that the CropSyst© model was well used. In case of Relative Root Mean Square Error (RRMSE), it was shown at 2.68 %. RRMSE value described that there was a 2.68 % error prediction between simulation and actual production. In conclusion, CropSyst© can be used to predict the suitable planting time for soybean and as the result, the suitable planting time for soybean on the dry land is the end of rainy season (2 June 2015). Tanggamus variety is the most resistant variety based on slow planting time, because the decreased percentage of production was lower (8.3 %) than Wilis (26.3 %) and Anjasmoro (43.0 %).
Co-Authors Ambo Ala, Ambo Aminah Aminah Kaimuddin Kaimuddin, Kaimuddin YUNUS MUSA