Document Type : Original Article
Authors
1 Shahid madani
2 dd
Abstract
Low-cost and high-precision technology is needed in crop yield forecasting to facilitate agricultural management. In this regard, wheat yields in East and West Azerbaijan provinces were modeled with climate indices (De Martonne index, Koppen 1, Koppen 2, Koppen 3, Angstrom, Selyaninov, Ivanov, Aridity, effective precipitation index and vegetation index). In this type of modeling, the combination of indices was used in the form of two, three and four indices. In order to decide on the appropriate climate index selection in each climate of modeling process, multi-criteria decision making (TOPSIS) was used based on 5 evaluation criteria, and Shannon's entropy was used to determine the weight of the criteria. The average increase in similarity index (SIM) for all indices from East Azerbaijan province to West is equal to 13.2%, which shows the better performance of climate indices in West Azerbaijan compared to East Azerbaijan province. Using a combination of indices is highly accurate under the condition of using an index with a better performance in single-index mode, for example, the rate of SIM increase from single-index to four-index mode in East Azerbaijan province is 20.94. The results of multi-criteria decision-making showed that the indices with Ivanov index in West Azerbaijan province and aridity index in East Azerbaijan province have a high impact on wheat yield. Determining the effective climate index in each region for crop yield forecasting is a powerful tool for decision making in product management and improvement.
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