Akademik Veri Yönetim Sistemi
MAUSAM, cilt.74, sa.3, ss.847-860, 2023 (SCI-Expanded)
Alfalfa is one of the most widely cultivated forage crops in the world. Alfalfa farming is carried out on approximately 35 million ha of land worldwide with an annual production amounting to 255 million tons. The average alfalfa cultivated area is about 637000 ha with a production of 13 million tons and a yield of 2200 kgda1 in Turkey. It is expected that climate change will have significantly different effects on its production and yield in the future. Therefore, the study aimed to predict the effect of climate change on the yield of alfalfa througha selected Artificial Neural Network (ANN) according to RCP4.5 and RCP8.5 climate change scenarios. Therefore, first of all, the best ANN structure among 176 different ANN alternatives consisting of various input parameters, learning rates, decay, and neuron numbers to predict alfalfa yield was selected. The ANN training/test dataset used in the study was composed of the alfalfa cultivation statistics, soil parameters and climatological data. Alfalfa yield for the years 2020-2060 and 2060-2100 in 79 provinces of Turkey is predicted by using the best ANN model, according to climate change projections (HadGEM2-ES RCP4.5 and RCP8.5). The ANN was able to calculate alfalfa yield with a 0.827 coefficient of determination and 0.813 Nash-Sutcliff coefficient. It is understood that the alfalfa can resist climate change and its yield tend to increase or decrease in regions, where there is an increase or decrease in precipitation in the same order as a result of climatic change. It is predicted that the highest yield increase will be noted in Artvin (6%) (a province of the Eastern Anatolia region) and the maximum yield decrease will be noted in Siirt (9%) (a province of the South Eastern Anatolia region). This research may be considered a creative prediction approach for the alfalfa yield estimation.