Effect of Input Usage on Wheat Yield: An Application of Artificial Neural Networks (ANN)
Publish Year: 1402
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_JASTMO-26-2_001
تاریخ نمایه سازی: 28 اسفند 1402
Abstract:
This study aimed to investigate the effects of inputs such as pesticides, fertilizers, seeds, labor and machine use on wheat yield. The data used in the study were obtained from ۱۷۷ wheat producers in Diyarbakir Province through a questionnaire, and Artificial Neural Networks (ANN) were used in the analysis of the data. According to the results, the average wheat yield is ۵۴۸۲.۰۳ kg ha-۱, and ۲۹۴.۷۵ kg of seeds, ۵۵۰.۷۳ kg of fertilizer, ۳.۵۹ hours of machinery, ۵.۳۷ hours of labor and ۲۶۶۲.۴۳ cc of pesticides were used per hectare for wheat production. According to the results of the ANN analysis, the relative importance of inputs affecting wheat yield was quantified, with the use of pesticides and fertilizer having the most significant impacts. Specifically, the sensitivity coefficients for pesticide use and fertilizer use were found to be ۰.۲۳ and ۰.۱۴, respectively. These coefficients represent the relative change in wheat yield per unit change in the input parameters.
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Authors
M. H. Demirel
Graduate School of Natural and Applied Sciences, Siirt University, Siirt, Turkey.
Z. Sengul
Department of Agricultural Economics, Faculty of Agriculture, Siirt University, Siirt, Turkey.
M. F. Baran
Department of Biosystem Engineering, Faculty of Agriculture, Siirt University, Siirt, Turkey.
O. Gokdogan
Department of Agricultural Machinery and Technologies Engineering, Faculty of Agriculture, Isparta University of Applied Sciences, Isparta, Turkey.
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