Abstract
<jats:p>Abstract. The relevance of this study is driven by the increasing frequency of extreme temperature events under global climate change and the need to enhance the heat stress tolerance of cultivated strawberry varieties. Elevated temperatures adversely affect the photosynthetic apparatus of plants, leading to reduced productivity and stability of agroecosystems. The problem of objective and reproducible assessment of varietal heat tolerance under controlled conditions remains insufficiently resolved. The aim of this study was to evaluate the effect of heat shock on the parameters of photosynthetic activity of photosystem II in strawberry varieties, to rank them according to their level of tolerance, and to identify the most heat-tolerant genotypes. The research objectives included modeling heat stress, analyzing changes in chlorophyll fluorescence parameters, and quantitatively interpreting the obtained data using neural network-based methods. The study objects were eight strawberry varieties of different ecological and geographical origins. Heat shock was simulated at a temperature of +50 °C for 30 minutes under controlled conditions. The state of the photosynthetic apparatus was assessed using PAM fluorometry based on the maximum and effective quantum yields of photosystem II. Quantitative evaluation of stress-induced inhibition was performed by calculating the area between the fluorescence curves of control and heat-stressed plants using an AI assistant. It was established that heat shock caused a significant decrease in photosynthetic activity in all studied varieties, with the degree of inhibition showing pronounced variety-specific differences. The smallest parameter changes were recorded in the varieties Urozhaynaya CGL and Al’va, whereas the varieties Maryshka, Clery, and Syria exhibited high sensitivity to overheating. The analysis of the dynamics of the effective quantum yield of photosystem II demonstrated higher sensitivity compared to the Fv/Fm parameter. The obtained results confirm the prospects of combining fluorescence-based methods with neural network analysis for screening strawberry genotypes for heat tolerance and may be applied in breeding programs and physiological studies. Key words: garden strawberry, heat shock, chlorophyll fluorescence, PAM fluorometry, heat tolerance, neural network analysis.</jats:p>