IJCATR Volume 8 Issue 1

A Hybrid WOFOST and Cropsyst Model for the Prediction of Crop Yield

Achir Jerome Aondongu, Iorshase Agaji, Esiefarienrhe Bukohwo M
10.7753/IJCATR0801.1002
keywords : WOFOST, CROPSYST, Hybrid, yield, crops, model, nutrient, computer

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Food availability is essential for any nation. The availability of food in turn depends on so many factors. In this work a hybrid model for the prediction of crop yield was proposed. This model combines the WOFOST and Cropsyst models and incorporated a crisis situation for prediction of crop yields. Factors used in the proposed model for prediction of crop yields include weather conditions, soil fertility, and crisis data. Crisis determines the availability of land for farming. Benue state of Nigeria was chosen as a study area. This choice is due to the fact that the state is tagged the food basket of Nigeria because of its mass production of many varieties of food crops. The crops covered in the study are maize, rice, tomato, millet, sorghum, beans. The new model was simulated using Visual Basic 2010 and results indicated that the model performed accurate predictions as compared to manual predictions. The system is recommended for use by food security agencies to avert hunger and starvation in future.
@artical{a812019ijcatr08011002,
Title = "A Hybrid WOFOST and Cropsyst Model for the Prediction of Crop Yield",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "8",
Issue ="1",
Pages ="1 - 32",
Year = "2019",
Authors ="Achir Jerome Aondongu, Iorshase Agaji, Esiefarienrhe Bukohwo M"}
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