An agro-physiological dataset on industrial tomatoes from nine years of field experiments conducted with alternative water-saving strategies in Mediterranean environments

The availability of field experimental data plays a piv- otal role in advancing agricultural research, particularly in the Mediterranean, where farmers face significant chal- lenges due to water scarcity and changing climatic condi- tions. We present a multi-year homogenized dataset of agro- physiological traits collected on industrial tomatoes and fo- cused on the effect of deficit irrigation (DI). The dataset has been compiled over nine years and comprises 100 experi- mental plots, where 32 DI strategies have been tested. Vi- sual observations on tomato phenology and qualitative and quantitative production data have been collected in field and laboratory surveys, complemented with detailed information on pedo-climatic conditions and irrigation scheduling (tim- ing and volume). Researchers can find in this dataset a rich source for calibrating and evaluating agro-physiological mod- els and a reference basis to study the relationships between DI strategies, weather variability, and the performance of tomato growing systems. Agronomists from the public and private sectors can gain domain knowledge to support local farmers with the best DI strategies to achieve high yields while optimizing water use. Moreover, this dataset serves as ground truth for digital decision support systems, which need real-world data to enhance their accuracy in guiding farmers on efficient water use. This data source is intended to become a crucial asset for researchers, agronomists, and decision-makers in the Mediterranean as it bridges the gap between research and practice in an area where farmers are already striving with water scarcity for industrial tomato cultivation.