Assessing climate change effects on Turkish tea farming through a dual approach using MMQR and machine learning
Tunahan Haciimamoglu, Gokan Bulbul, Korkmaz Yildirim, Burcu Kartal · 2025
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Description
Tunahan Haciimamoglu and three co-authors study how climate change affects tea yields in Turkiye. Tea is a key crop for the eastern Black Sea region and for rural incomes there. The study covers five tea growing provinces from 2004 to 2022.
Two methods are combined for the first time in this setting, a quantile regression method and machine learning. Both point to the same broad pattern. Higher temperature and rainfall raise yields in the data, while higher humidity lowers them. Farmed area is the strongest factor in the machine learning results, and humidity is the weakest. The authors urge joint farm policies for the five provinces, with a focus on moisture control.
Catalog record
| CREATOR | Tunahan Haciimamoglu, Gokan Bulbul, Korkmaz Yildirim, Burcu Kartal |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 80 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |