Yield Estimation based on Crop Growth Models and Estimation Evaluation
Paper ID : 1020-NICAME1402
Authors:
Mehrtash Manafifard *
Assistant professor at Arak University of Technology, Arak, Iran
Abstract:
Recently, there has been concern about food security, and a key component is the accurate estimation of major crops. Yield prediction is a crucial task in agricultural monitoring and management, which is beneficial to supply management, predicting humanitarian aid and making decisions on imports and exports. A variety of process-based models have been applied in the literature for yield prediction based on satellite imagery. Moreover, crop yield forecasting depends on many influential factors, including weather, soil, and management practices. Inevitably, the discrepancies between simulated and observed yield exist; since yield estimation models do not take into account all influential factors, such as the effects of pests, diseases and flooding on crop growth. Therefore, model validation is one of the most important tasks in scientific research. In this paper, different Crop Growth Models (CGM) are reviewed. Then, various evaluation measures used for evaluating the results of yield prediction models are discussed.
Keywords:
Yield, Estimation, Evaluation, Satellite, Crop Growth Models.
Status : Paper Accepted (Poster Presentation)