Maize breeding trial dataset supporting yield increase in multiple managed and non-managed environments with increasing vapor pressure deficit

This dataset provides comprehensive multi-environment trial (MET) results for maize hybrids evaluated under varying vapor pressure deficit (VPD) and water management conditions. Collected over an 11-year period (2009-2019) in Croatia and Turkey, the data include detailed agronomic performance metrics-grain yield, phenological stages, and environmental descriptors-across a range of irrigation regimes and temperature-humidity combinations. The dataset comprises more than 2900 plot-level observations, capturing genetic variance, genotype-by-environment interaction, and yield responses to increasing VPD. These data enable researchers to investigate maize adaptability to emerging hot, managed environments, assess genetic gains over breeding cycles, and explore how transpiration traits influence yield potential. Fully documented environmental indices and methodological details facilitate re-analysis, meta-studies, and integration into broader crop modelling frameworks. Researchers, breeders, and agronomists can use this dataset to inform breeding strategies, optimize management practices, and better understand maize yield stability in the face of climate change.