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Ag Data Commons migration begins October 18, 2023

The Ag Data Commons is migrating to a new platform – an institutional portal on Figshare. Starting October 18 the current system will be available for search and download only. Submissions will resume after the launch of our portal on Figshare in November. Stay tuned for details!

Data from: Interseeded cover crop mixtures influence soil water storage during the corn phase of corn-soybean-wheat no-till cropping systems

    This study was initiated to evaluate, during the following corn (*Zea mays* L.) phase, the effects of interseeded cover crops on soil temperature, soil water balances, evapotranspiration, infiltration, and yield and water use efficiency of corn. The study was conducted at the USDA Beltsville Agricultural Research Center, Beltsville, MD from 2017 through 2020. The cropping systems under study were primarily sequences of corn-soybean (*Glycine max* L.)-wheat (*Triticum aestivum* L.)-double crop soybean all planted with no-tillage management.

    Data from: Vegetation index-based partitioning of evapotranspiration is deficient in grazed systems

      The dataset includes 30 minutes values of partitioned evaporation (E) and transpiration (T), T:ET ratios, and other ancillary datasets for three ET partitioning methods viz. Flux Variance Similarity (FVS) method, Transpiration Estimation Algorithm (TEA), and Underlying Water Use Efficiency (uWUE) method for the three wheat sites. The dataset also contains remote sensing-derived Enhanced Vegetation Index (EVI) data for each site.

      Data from: Vegetation index-based partitioning of evapotranspiration is deficient in grazed systems

        The dataset includes 30 minutes values of partitioned evaporation (E) and transpiration (T), T:ET ratios, and other ancillary datasets for three ET partitioning methods viz. Flux Variance Similarity (FVS) method, Transpiration Estimation Algorithm (TEA), and Underlying Water Use Efficiency (uWUE) method for the three wheat sites. The dataset also contains remote sensing-derived Enhanced Vegetation Index (EVI) data for each site.

        Data from: Plant strategies for maximizing growth during drought and drought recovery in Solanum melongena L. (eggplant)

          This data represents the collection of physiological and biometric data of above- and below-ground plant traits in four species of Solanum melongena of Philippine origin (PHL 4841, PHL 2778, PHL 2789, and Mara). Half of the plants were subjected to significant water deficit, and half again of those deficit plants were allowed to recover after subsequent watering. This data is suitable to serve as a benchmark for trait values in S. melongena, as well as in studies of trait responses to terminal drought and episodic drought in agricultural settings.