In vivo monitoring of dynamic drought responses in tomato using Bioristor to support varietal selection

Extreme weather events, increasing water scarcity, and rising temperatures pose major challenges to agricultural sustainability and global food security. Developing crop varieties with enhanced stress resilience is therefore a priority, yet conventional breeding remains labor-intensive, time-consuming, and costly. Integrating innovative sensing technologies into breeding pipelines offers a promising strategy to improve the efficiency and precision of genotype selection. Here, we present two case studies demonstrating the potential of the Bioristor, an organic electrochemical transistor (OECT)-based in vivo sensor, to support phenotypic selection under drought stress. In the first study, three commercial tomato ( Solanum lycopersicum L.) varieties (Mariner, Faber, and Red Setter) were continuously monitored during drought and recovery. In the second study, the Bioristor was applied to a panel of tomato introgression lines (ILs), enabling continuous, real-time characterization of physiological responses to drought and combined drought–heat stress. Bioristor-derived measurements enabled the robust classification of both commercial varieties and ILs according to their stress tolerance. Novel sensor-derived indices enhanced genotype discrimination by revealing differences in the temporal dynamics of physiological responses, particularly those associated with water and ion transport. Beyond improving phenotypic selection, continuous in vivo monitoring provided new insights into stress onset, acclimation, and recovery, identifying genotype-specific response patterns that are not captured by conventional phenotyping approaches. These findings demonstrate the potential of the Bioristor as a high-resolution functional phenotyping tool for early genotype classification and breeding. By complementing genomic and automated phenotyping platforms with continuous, in vivo physiological information, the Bioristor provides a deeper understanding of plant stress responses and represents a promising technology for developing more resilient crop varieties.