Evaluation of the CropSyst Model on Soybean (Glycine max L.) in the Tropics
Abstract
South Sulawesi is one of the soybean producer provinces in Indonesia. As in other tropical areas, South Sulawesi season comprises is dry and rainy seasons, so modeling of crops such as CropSyst can be very helpful in predicting planting time, providing irrigation, and applying the right fertilizer to get maximum soybean productivity. To apply the CropSyst model in the tropics such as South Sulawesi, calibration and validation of several plant parameters are required. Further calibration and validation results need to be tested to see the accuracy of predicting models. The results of soybean evaluation in South Sulawesi showed that RMSE (0.09 and 0.11), MBE (-0.01 and 0.11), MAE (0.08 and 0.11), and d (0.92 and 0.81) had values showing that CropSyst model accurately to predict grain yield of soybean in South Sulawesi.
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Introduction
CropSyst is a friendly crop simulation model used. The CropSyst model is used to look at the effects of climate, soil, and crop management systems on productivity and the environment. CropSyst simulates soil, nitrogen, plant growth and development, crop yields, residual production, soil erosion by water, and salinity [1]. The current developments that are heavily caused by the development of climate change will be a challenge for crop modeling to update the model [2]. Several studies have been done to see the level of accuracy of CropSyst model. Some of these studies suggest that CropSysts can predict convincingly the results of barley and irrigated rescue on plant yields [3], CropSyst models can be used as a means to regulate irrigation water to improve productivity with poor water quality [4], CropSyst model simulation with predictive climate can summarize the predicted outcomes going forward [5], calibration and validation of the CropSyst model for rice can precisely determine irrigation and proper fertilization [6], and evaluation of the CropSyst model on yields for cluster bean in India also shows the proximity between simulation and observation data [7].
South Sulawesi is a province in Indonesia, at 0012' North Latitude - 80 South Latitude and 116048' - 122036' East Longitude. South Sulawesi which has an area of 46,083.94 km2 divided into 21 districts and 3 cities. South Sulawesi is one of the soybean producer provinces in Indonesia, with an average productivity of 1.5 t ha-1 grain yield [8].
Conclusion
The results of the evaluation on the grain yield of soybean show that CropSyst model has a tiny RMSE and MAE value (close to 0), thus accurately to predict the grain yield. While the value of d is close to 1 which means that the model (simulation) accurately predicts the results of field research (observation). Thus it can be concluded that the CropSyst model accurately predicts grain yields in different regions of South Sulawesi, which have a tropical climate. So that, it can be concluded that the CropSyst model can be applied to tropical regions by doing calibration and validation.
References
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