AI-Enhanced Projections of Hazelnut Production Under Climate Change: a Regional Analysis from Turkey

Basit Öğe Kaydı
dc.authoridALBAYRAK, AHMET/0000-0002-2166-1102;
dc.contributor.authorAlbayrak, Ahmet
dc.date.accessioned2025-10-11T20:48:46Z
dc.date.available2025-10-11T20:48:46Z
dc.date.issued2025
dc.departmentDüzce Üniversitesien_US
dc.description.abstractHazelnut (Corylus avellana L.) cultivation, a cornerstone of Turkey's fruit production and exports, faces mounting challenges due to climate change. This study analyzes the effects of climatic variables and soil properties on hazelnut yield in two key Turkish regions-Eastern Black Sea and D & uuml;zce-by combining 20 years of agronomic data with machine learning techniques. Yield predictions under different Shared Socioeconomic Pathway (SSP) climate scenarios were generated using Random Forest and Gradient Boosting models, achieving high predictive performance (R-2 > 0.90). Results show that low-emission scenarios (SSP1-1.9) foster favorable growing conditions, while high-emission scenarios (SSP5-8.5) lead to significant yield reductions (up to 17%), mainly due to increased humidity-induced fungal risk and frost events. Soil properties such as organic matter content and water-holding capacity also played critical roles in determining yield variability. The study highlights the potential of AI-driven climate modeling to guide adaptive cultivation practices, such as frost-resistant cultivars and humidity control strategies, ensuring sustainable hazelnut production in the face of future climate uncertainties.en_US
dc.identifier.doi10.1007/s10341-025-01547-9
dc.identifier.issn2948-2623
dc.identifier.issn2948-2631
dc.identifier.issue5en_US
dc.identifier.scopus2-s2.0-105013572592en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1007/s10341-025-01547-9
dc.identifier.urihttps://hdl.handle.net/20.500.12684/22089
dc.identifier.volume67en_US
dc.identifier.wosWOS:001553784200001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorAlbayrak, Ahmet
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofApplied Fruit Scienceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmzKA_WOS_20250911
dc.subjectHazelnut yielden_US
dc.subjectClimate changeen_US
dc.subjectSSP scenariosen_US
dc.subjectMachine learningen_US
dc.subjectRegional agricultureen_US
dc.subjectAgricultural sustainabilityen_US
dc.titleAI-Enhanced Projections of Hazelnut Production Under Climate Change: a Regional Analysis from Turkeyen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu