ArticleBMC plant biology2025
Rootstock-mediated salinity resilience in cucumber (Cucumis sativus L.): integrating physiological traits, genomic stability and machine learning.
Article in BMC plant biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Interactive effects of selenium and fertigation regimes on strawberry performance and biofortification under salinity stress.Scientific reports · 2026Article
- Integrated WGCNA and TO-GCN analysis reveals pathways and genes underlying salt tolerance in Sesbania cannabina.BMC plant biology · 2026Article
- Genome-wide identification of the SnRK gene family in willow and expression analysis under abiotic stress.BMC plant biology · 2026Article
- Integrating hyperspectral reflectance and machine learning for rapid diagnosis of nutrient deficiencies in greenhouse chrysanthemum leaves.BMC plant biology · 2026Article
- Integrating Taguchi design and machine learning models for trait stability and predicting forage quality in naturally occurring grass pea (Lathyrus spp.).BMC plant biology · 2026Article
- Influence of rootstock-scion combinations on morpho-physiological responses, yield, and fruit quality of tomato under hydroponic salinity stress.BMC plant biology · 2026Article
- Mitigation of salinity stress in tomato using green-synthesized silver nanoparticles derived from Teucrium stocksianum.BMC plant biology · 2026Article
- A novel approach for disease and pests detection in potato production system based on deep learning.Scientific reports · 2026Article
- Chrysanthemum miR166 functions as a positive regulator in the salt stress response of Arabidopsis thaliana.BMC plant biology · 2026Article
- Integrative cross-platform transcriptomic analysis coupled with machine learning identifies candidate biomarkers of abiotic stress resilience in Arabidopsis thaliana.BMC plant biology · 2026Article
- Assessment of waterlogging tolerance in tea genotypes through morpho-physiological and biochemical profiling.PloS one · 2026Article
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4 authors.
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Abstract
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 biomass (leaf FW - 56%, root DW - 74%) and lowered SPAD and relative water content (RWC); grafting-especially with TZ148 (and to a lesser extent Kublai)-mitigated these losses by maintaining chlorophyll content (SPAD) and biomass under salinity. Grafted combinations, especially TZ148/Cagla, maintained higher stability (GTS: 88%, GC: 0.07), confirming the protective role of grafting. ML approaches, including Principal Component Analysis (PCA) and Random Forest (RF), clearly separated control vs. salinity and, while grafting types showed only partial separation, RF consistently ranked root/stem fresh weight, SPAD, leaf area, and fruit weight as top predictors.
conclusionGrafting significantly improved cucumber tolerance to salinity by sustaining biomass, photosynthetic capacity proxies (SPAD), and genomic integrity. ML-based analyses added predictive power and biological interpretation, confirming grafting with appropriate rootstocks as a sustainable strategy for cucumber production in saline nutrient solution conditions.
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