Simulation and production of soybean plant growth (Glycine max (L) Merrill) using the DSSAT model with different scenarios of water supply and compost

Abstract

Abstract This study aims to study the response of soybean plants to various scenarios of water supply and compost using the DSSAT model. This research was conducted at the Laboratory of Agro-climatology and Statistics, Department of Agronomy, Faculty of Agriculture, Universitas Hasanuddin, Makassar. This research was conducted in February-March 2016. Simulation of the DSSAT model was determined from primary data in the form of plant management data, soil data, and other supporting data, and secondary data in the form of climate data. The results of the study, based on the paired t-test, the DSSAT model for simulating soybean plants can predict each treatment on the parameters of vegetative weight and number of pods. A t-test on leaf root weight showed that the DSSAT model could predict all treatments except in the treatment of watering every ten days and 3.0 tons/ha of compost. Based on the value of MSE, the DSSAT model for simulating soybean plants can predict the yield of each treatment for the parameters of the number of seeds. The average difference between simulation and observation on seed weight of 314.44 kg/ha and simulation results tend to predict below observation in the field.

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