RT Journal T1 PRICE ESTIMATION OF SELECTED GRAINS PRODUCTS BASED ON MACHINE LEARNING FOR AGRICULTURAL ECONOMIC DEVELOPMENT IN TÜRKİYE A1 Abdulkadir Keskin A1 Irfan Ersin A1 Abdulkadir Atalan JF Journal of Animal and Plant Sciences JO JAPS SN 1018-7081 VO 34 IS 5 SP 1290 OP 1302 YR 2024 FD 2024/10/22 DO DOI https://doi.org/10.36899/JAPS.2024.5.0811 AB

This study aims to estimate the price fluctuations of essential grain products, namely bread wheat (Triticum aestivum), durum wheat (Triticum durum), barley (Hordeum vulgare), and corn (Zea mays), in Türkiye using machine learning (ML) algorithms. Using data from January 2, 2020, to January 10, 2023, the study employs algorithms such as random forest (RF), neural network (NN), support vector machine (SVM), and linear regression (LR). Independent variables include oil prices, currency exchange rates, and grain production volumes. The random forest (RF) algorithm provided the best results with the highest R² values, while NN and LR showed relatively lower performance. The study highlights the significant impact of production and consumption volumes on grain prices and underscores the importance of ML algorithms in predicting these prices amidst changing conditions. Investments in agricultural technologies should be increased to improve data collection and analysis processes, as this is crucial for preventing price fluctuations in the agricultural sector. 

K1 Agricultural products; grains; durum wheat; bread wheat; corn; barley; machine learning algorithms; price estimation PB Pakistan Agricultural Scientists Forum LK https://thejaps.org.pk/AbstractView.aspx?mid=2023-JAPS-1560