Quantifying the radiation–yield relationship of potato beneath tracking agrivoltaic systems

Agrivoltaic (APV) systems enable simultaneous crop and electricity production but create spatially heterogeneous radiation environments that can affect crop productivity. Four potato ( Solanum tuberosum L.) experiments were conducted between 2023 and 2026 beneath a commercial-scale single-axis tracking APV system in central Israel to quantify relationships among cumulative photosynthetically active radiation (PAR), tuber yield, cultivar response, and plant physiology. Seven crop rows positioned beneath and between two photovoltaic arrays experienced reproducible but strongly contrasting radiation environments, ranging from severe shading near the array edges to near-open-field radiation in the central rows. Tuber yield increased with radiation availability, but the magnitude of the response differed among experiments and cultivars. For three cultivars which were represented in all four experiments, a quadratic PAR-only model explained 40.8% of yield variation. Accounting for experiment and cultivar increased R 2 to 0.677, and inclusion of experiment × PAR and cultivar × PAR interactions further increased R 2 to 0.779, demonstrating significant seasonal and genotypic modulation of the radiation response. The relationship between PAR reduction and yield difference relative to an external agronomic reference of 0.9 kg plant -1 was consistently nonlinear but varied in strength among seasons. Analysis of all 28 experiment × row combinations yielded R 2 = 0.674, while leave-one-experiment-out validation yielded R 2 = 0.464, indicating that radiation provides a strong spatial determinant of productivity but does not define a universal yield-response function. Physiological and morphological traits varied across the radiation gradient, indicating plant acclimation to contrasting irradiance environments. The results demonstrate that cumulative seasonal PAR provides a framework for explaining spatial variation in potato productivity beneath tracking APV, while season and genotype determine the magnitude of the response. This multi-season, multi-cultivar analysis extends the nonlinear PAR–productivity framework previously observed in this APV system and provides a quantitative basis for optimizing crop placement, cultivar selection, and photovoltaic-array configuration.