Adaptive morpho-physiological and biochemical responses of Ghanaian tomato landraces to drought and flood stresses

Tomato ( Solanum lycopersicum L.) production in Ghana is increasingly constrained by recurrent drought and flood events, yet the adaptive capacity of local landraces to these abiotic stresses remains poorly understood. This study evaluated the morphological, physiological, and biochemical responses of eight tomato cultivars, including Ghanaian landraces, using a CRD with four replications per cultivar–treatment combination. The experimental factors were cultivar (eight levels) and watering regimes (three levels: well-watered control, continuous flooding, and severe drought ≤ 10% field capacity). Significant genotype × treatment interactions were observed for all traits, indicating diverse adaptive responses among cultivars. Overall, drought caused stronger growth suppression than flooding. Root length declined up to 2.09-fold under flooding and 1.61-fold under drought, while root volume decreased by 4.6- and 5.0-fold, respectively. Photosynthetic rate was highly sensitive to severe drought, with reductions reaching 13.8-fold in susceptible cultivars. Stress conditions also triggered biochemical adjustments, including 2.7-fold increases in total sugars, 2.3-fold rises in lipid peroxidation, and up to 98.8-fold proline accumulation, alongside intracellular CO 2 increases of up to 61%. Tolerant cultivars such as Local Akoma and Scotia maintained relatively stable growth, higher antioxidant activity, and lower lipid peroxidation under both stresses. In contrast, sensitive cultivars including Local Pectofic L1, Italy 2 Charity, and Pectofic L2 showed marked morphological reductions, impaired photosynthesis, and elevated oxidative damage. Correlation and multivariate analyses indicated that flood tolerance was associated with maintenance of root function and antioxidant protection, whereas drought tolerance relied on osmolyte accumulation and antioxidant activity despite reduced growth. Molecular and OMICS–based approaches are recommended to elucidate the mechanisms underlying the observed changes.