Comparative Analysis of Physiological Indicators Related to Drought Resistance of Tea Plants under Drought and Rehydration Conditions

Backgroud With the ongoing global climate warming, the intensity, frequency, and duration of drought events have significantly increased, making drought become to one of the most severe natural disasters that continuously impact global ecosystems and agricultural production. Frequent drought stress poses a serious threat to the normal growth and economic productivity of tea crops. Therefore, identifying stable and effective morphological, physiological, and oxidative stress-related indicators and establishing a scientifically sound drought resistance evaluation system are of great significance for screening drought-tolerant genotypes and mitigating the impacts of drought stress. Results In this study, three tea cultivars were selected as experimental materials. The dynamic changes in 12 physiological indicators under drought-rehydration stress were systematically analyzed. By integrating multivariate statistical methods including principal component analysis, correlation analysis, and regression analysis key drought resistance indicators were identified. Based on these, a comprehensive evaluation system for tea plant drought resistance was developed. Under drought stress, all three tea cultivars exhibited varying degrees of physiological damage. As the severity of stress increased, visible leaf symptoms progressed from wilting to inward curling, scorching, and even defoliation. Following rehydration, these symptoms showed significant recovery. A comprehensive comparison revealed that cultivar H2 demonstrated superior drought tolerance and better recovery capacity after rehydration compared to the other two cultivars. Seven key indicators electron transport rate (ETR), peroxidase activity (POD), transpiration rate (Tr), potential photochemical efficiency (Fv/Fo), proline content (Pro), soluble sugar content (SS), and photochemical quenching coefficient (qP) were identified as representative markers of tea plant drought resistance. The drought resistance prediction model constructed based on these indicators demonstrated a high goodness of fit (R² = 0.998, P < 0.001) and excellent predictive accuracy. Conclusions This study clarifies the core physiological indicator system for evaluating tea plant drought resistance, providing a solid theoretical foundation and technical support for the rapid screening of drought-resistant genotypes and the implementation of drought-adaptive cultivation strategies.