Rootstock-mediated salinity resilience in cucumber (Cucumis sativus L.): integrating physiological traits, genomic stability and machine learning
Yazarlar (4)
Omer Faruk Coskun
Alim Aydin
Seher Toprak
Doç. Dr. Hakan BAŞAK Kırşehir Ahi Evran Üniversitesi, Türkiye
| Makale Türü |
Özgün Makale
(SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
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| Dergi Adı | BMC PLANT BIOLOGY (Q1) | ||
| Dergi ISSN | 1471-2229 Dergi Bilgileri (2025) | ||
| Makale Dili | İngilizce | Basım Tarihi | 12-2025 |
| Cilt / Sayı / Sayfa | 26 / 1 / – | DOI | 10.1186/s12870-025-07964-y |
| Makale Linki | https://doi.org/10.1186/s12870-025-07964-y | ||
| UAK Araştırma Alanları |
Ziraat, Orman ve Su Ürünleri
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| Özet |
| BackgroundSalt stress is a major abiotic constraint in cucumber (Cucumis sativus L.), reducing biomass, photosynthesis, and genomic stability. Grafting onto salt-tolerant Cucurbita rootstocks is a promising strategy to enhance plant resilience. Recently, machine learning (ML) has provided new opportunities to capture complex trait interactions and identify key predictors of stress tolerance.ResultsWe evaluated two cucumber cultivars (Cagla F1, Minimix F1) grafted onto four interspecific Cucurbita maxima × Cucurbita moschata rootstocks (TZ148, Devrim, Cremna, Kublai) under 0 vs. 100 mM NaCl for 30 days in a soilless fertigation system. Morphological, physiological, and molecular traits were evaluated, including biomass accumulation, chlorophyll content (SPAD) and incident photosynthetically active radiation (PAR), and genomic template stability (GTS) using ISSR markers. Salt stress reduced growth and … |
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BM Sürdürülebilir Kalkınma Amaçları
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| Web of Science | 8 |
| Google Scholar | 15 |