SOYBEAN APSIM MODEL SOFTWARE
SOYBEAN APSIM MODEL SIMULATOR

The predicted variability of crop yield was also due to the variation of weather during soybean growing season and amount of irrigation and N used during wheat growing season. The discrepancy observed between the observed and predicted yield in the control under soybean was due to the P limiting condition of the treatment rather than the model. For other treatments, model prediction was satisfactory in most of the cases in simulating water and organic carbon, grain yield and N uptake by both the crops.

SOYBEAN APSIM MODEL SOFTWARE

The model predicted successfully grain yield and N uptake under FYM treatments in soybean and wheat. APSIM: a novel software system for model development 267 in concept to the soybean model of Sinclair (1986). The model was parameterized by specifying the N mineralized from the manure in the laboratory incubation. For organic treatments, we simulated N management using the FYM as the source of plant available N under field condition. Three nutrient treatments, viz., control (no nutrient), inorganic (recommended rate) and FYM (8В tВ ha в€’1 to soybean and 16В tВ ha в€’1 to wheat) were used to validate the APSIM model.

SOYBEAN APSIM MODEL SIMULATOR

The data on water use, N uptake, grain yield and soil organic C from an ongoing long-term experiment was used for validation purpose. The crop modeling was carried out by using the Agricultural Production Systems Simulator (APSIM) and the Decision Support System for Agrotechnology Transfer (DSSAT) crop simulation models (CSMs), which were tested on the cross-sectional data of 217 farm households collected from the seven strata in the study area. Genetic coefficient generated from this study was used for subsequent model validation. Independent data set was used to parameterize soybean cultivar (JS 335) and wheat cultivar (Sujata) to be used for APSIM simulation. To achieve this, the APSIM model was parameterized and validated for soybean and wheat crop of subtropical central India. In this connection, the crop growth simulation models are handy in identifying the constraints to yield and recommending appropriate management practices to optimize the productivity of soybeanвЂ“wheat system.

The reduction in grain yield was mainly attributed to a suboptimal supply of nutrients to both the crops, use of poor quality farmyard manures and erratic distribution of rainfall during soybean's growing season and unavailability of irrigation water during wheat season. In recent years, nutrient management of soybeanвЂ“wheat systems in central India has become a cause for concern because of stagnation of grain yields of soybean and wheat. This data set contains output data from simulations with the model APSIM-UGOE for soybean as part of AgMIPs Global Gridded Crop Model Intercomparison (GGCMI) phase II output data set.

Soybean apsim model