The availability of field experimental data plays a pivotal role in advancing agricultural research, particularly in the Mediterranean, where farmers face significant challenges due to water scarcity and changing climatic conditions. We present a multi-year homogenized dataset of agro-physiological traits collected on industrial tomatoes and focused on the effect of deficit irrigation (DI). The dataset has been compiled over nine years and comprises 100 experimental plots, where 32 DI strategies have been tested. Visual 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 (timing and volume). Researchers can find in this dataset a rich source for calibrating and evaluating agro-physiological models 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.
Keywords: Brix; Crop water stress index; Crop yield; Deficit irrigation; Quality; Solanum lycopersicum L..
© 2024 The Authors. Published by Elsevier Inc.