Comparative Analysis of Geographical Factors Affecting Paddy (Oryza sativa L.) Yields in Türkiye Using Random Forest and ANOVA: The Case of Kırıkkale, Balıkesir, Diyarbakır and Şanlıurfa

Mehmet Özcanlı; Kerim Karadağ

doi:10.24925/turjaf.v14i9.2690-2706.8977

Authors

Mehmet Özcanlı Harran University, Faculty of Science and Letters, Department of Geography, 63200, Şanliurfa, Turkiye https://orcid.org/0000-0003-2228-8298
Kerim Karadağ Harran University, Faculty of Engineering, Department of Electrical and Electronics, 63200, Şanliurfa, Turkiye https://orcid.org/0000-0001-5167-4054

DOI:

https://doi.org/10.24925/turjaf.v14i9.2690-2706.8977

Keywords:

Agricultural Geography, Paddy Yield, Random Forest, ANOVA, Machine Learning

Abstract

Rice (Oryza sativa L.) is a staple food for nearly half of the global population and a strategic crop for Turkey, where inter-provincial yield disparities remain pronounced. This study aims to classify provincial rice yield levels in Turkey for the 2004–2024 period using TurkStat data and to quantify the relative contribution of 14 environmental, edaphic and agronomic parameters driving these differences. Preliminary analyses identified Kırıkkale (21-year mean 908.3 kg/da) as the high-yield province, Balıkesir (747.7 kg/da) as the medium-yield province, and Diyarbakır (448.1 kg/da) and Şanlıurfa (440.5 kg/da) as the low- and lowest-yield provinces, respectively. A 14-parameter dataset compiled from field measurements and published province-level studies was analysed using Principal Component Analysis (PCA), Random Forest (RF) classification and one-way Analysis of Variance (ANOVA).With a 70/30 train/test split, the RF model achieved 93.47% accuracy, 0.9764 ROC-AUC and a mean variance of 0.0145. Gini-based variable importance ranked soil moisture, organic matter, soil pH, rainfall and temperature as the most influential drivers of yield, and ANOVA confirmed statistically significant differences across yield classes for these variables (all p < 0.001). Findings indicate that low yields in south-eastern Anatolia are largely driven by inadequate soil moisture management, low organic matter content, elevated soil pH and summer heat stress, whereas Kırıkkale’s high yields are associated with more balanced soil–water relations. Results provide evidence-based guidance for region-specific rice production policies and data-driven decision support in Türkiye.

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