Early prediction of winter cereals yield : A preliminary study based on machine learning technique as a strategic tool for fertilization and field management

Early yield prediction of winter cereals is a very powerful tool assisting in fertilization strategies and optimization. Satellite based vegetation indexes show interesting correlation with yield in winter cereals and is commonly used by technician in fertilization management zone. The aim of this paper is to investigate and develop a tool for quantitative early yield prediction, relying on machine-learning models in order to implement it in a decision support system platform.