Goal: To develop a data-driven decision making modelling which predict crop yield in the result of increasing productivity, performance and profitability. Note: For the confidential reason, only part of information will be revealed in the repository. For more information, check the link for details.
The predictive model consists of two models: Mechanistic or process-based model and statistical model. The predictive result from the Mechanistic model is feeded as an input parameter in the
statistical model. The Mechanistic model includes three sub-models: basic, model and nitrogen sub-model. An artificial neural network model is used as the statistical model.
Performed modelling and simulation on all of three sub-models. The water sub-model comes from Amir et. al's study.
[1] Amir, J., & Sinclair, T. R. (1991). A model of water limitation on spring wheat growth and yield. Field Crops Research, 28(1-2), 59-69.