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SNAPMe: A Benchmark Dataset of Food Photos with Food Records for Evaluation of Computer Vision Algorithms in the Context of Dietary Assessment

    We conducted the Surveying Nutrient Assessment with Photographs of Meals (SNAPMe) Study (ClinicalTrials ID: NCT05008653) to develop a benchmark dataset of food photographs paired with traditional food records. The SNAPMe DB includes 1,475 “before” photos of non-packaged foods, 1,436 “after” photos of non-packaged foods, 203 “front” photos of packaged foods, and 196 “ingredient” labels of packaged foods. Each line item of each ASA24 food record is linked to the relevant photo. These data will be transformative for the improvement of artificial intelligence algorithms for the adoption of photo-based dietary assessment in nutrition research.

    Data and code from: Synergistic soil, land use, and climate influences on wind erosion on the Colorado Plateau: Implications for management

      This dataset includes code and data to recreate analysis from the manuscript "Nauman, T.W., Munson, S.M., Dhital, S, Webb, N.P., Duniway, M.C. Synergistic soil, land use, and climate influences on wind erosion on the Colorado Plateau: Implications for managemen". In prep for STOTEN. This includes R statistical code, aeolian monitoring data and associated soil, land use, and climate explanatory data for each site, and a raster map showing areas modeled to have more sediment transport.

      Data and code from: Topographic wetness index as a proxy for soil moisture in a hillslope catena: flow algorithms and map generalization

        This dataset contains all data and code necessary to reproduce the analysis presented in the manuscript: Winzeler, H.E., Owens, P.R., Read Q.D.., Libohova, Z., Ashworth, A., Sauer, T. 2022. 2022. Topographic wetness index as a proxy for soil moisture in a hillslope catena: flow algorithms and map generalization. *Land* 11:2018. DOI: 10.3390/land11112018.

        Evapotranspiration, Irrigation, Dew/frost - Water Balance Data for The Bushland, Texas Sunflower Datasets

          This dataset consist of 15-minute and daily amounts of evapotranspiration (ET), dew/frost fall, precipitation (rain/snow), irrigation, scale counterweight adjustment, and emptying of drainage tanks, all in mm. The values are the result of a rigorous quality control process involving algorithms for detecting dew/frost accumulations, and precipitation (rain and snow). Changes in lysimeter mass due to emptying of drainage tanks, counterweight adjustment, maintenance activity, and harvest are accounted for such that ET values are minimally affected. Data are for sunflower grown at the USDA-ARS Conservation and Production Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU), Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL) in 2009 and 2022. Sunflower was grown for seed on two large, precision weighing lysimeters, each in the center of a 4.44 ha square field.

          TERRA-REF Season 4 and 6 Sorghum phenotypes and agronomic metadata in BrAPI format: ARDN Products

            ARDN (Agricultural Research Data Network) annotations for "TERRA-REF Season 4 and 6 Sorghum phenotypes and agronomic metadata in BrAPI format". The ARDN project ([https://data.nal.usda.gov/ardn](https://data.nal.usda.gov/ardn)) is a network of datasets harmonized and aggregated using the ICASA vocabulary, as recommended by USDA NAL ([https://data.nal.usda.gov/data-dictionary-examples](https://data.nal.usda.gov/data-dictionary-examples)) and described in detail here: [www.tinyurl.com/icasa-mvl](www.tinyurl.com/icasa-mvl) This data represents a small subset of the TERRA-REF release available on Dryad (LeBauer et al 2020), including harvested biomass for each cultivar, plot location, planting date, harvest date, fertilizer application, genotype / accession names and metadata, and additional agronomic management metadata for a population of Sorghum bicolor evaluated over two growing seasons. The data can be accessed through a BrAPI-compliant endpoint at terraref.org/brapi. This dataset is a snapshot of the TERRA-REF BrAPI endpoint contents, representing the minimum data and metadata required to run a crop model.

            TERRA-REF Season 4 and 6 Sorghum phenotypes and agronomic metadata in BrAPI format

              This data represents a small subset of the TERRA-REF release available on Dryad (LeBauer et al 2020), including harvested biomass for each cultivar, plot location, planting date, harvest date, fertilizer application, genotype / accession names and metadata, and additional agronomic management metadata for a population of Sorghum bicolor evaluated over two growing seasons. The data can be accessed through a BrAPI-compliant endpoint at terraref.org/brapi. This dataset is a snapshot of the TERRA-REF BrAPI endpoint contents, representing the minimum data and metadata required to run a crop model.

              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.

                Evapotranspiration, Irrigation, Dew/frost - Water Balance Data for The Bushland, Texas Winter Wheat Datasets

                  This dataset consist of 15-minute and daily amounts of evapotranspiration (ET), dew/frost fall, precipitation (rain/snow), irrigation, scale counterweight adjustment, and emptying of drainage tanks, all in mm. The values are the result of a rigorous quality control process involving algorithms for detecting dew/frost accumulations, and precipitation (rain and snow). Changes in lysimeter mass due to emptying of drainage tanks, counterweight adjustment, maintenance activity, and harvest are accounted for such that ET values are minimally affected. Data are for winter wheat grown at the USDA-ARS Conservation and Production Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU), Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL) in the 1989-1990, 1991-1992, and 1992-1993 seasons. Winter wheat was grown on two large, precision weighing lysimeters, each in the center of a 4.44 ha square field.

                  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.

                    Evapotranspiration, Irrigation, Dew/frost - Water Balance Data for The Bushland, Texas Alfalfa Datasets

                      This dataset consist of 15-minute and daily amounts of evapotranspiration (ET), dew/frost fall, precipitation (rain/snow), irrigation, scale counterweight adjustment, and emptying of drainage tanks, all in mm. The values are the result of a rigorous quality control process involving algorithms for detecting dew/frost accumulations, and precipitation (rain and snow). Changes in lysimeter mass due to emptying of drainage tanks, counterweight adjustment, maintenance activity, and harvest are accounted for such that ET values are minimally affected. Data are for alfalfa grown at the USDA-ARS Conservation and Production Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU), Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL) in 1996 through 1999. Alfalfa was grown on two large, precision weighing lysimeters, each in the center of a 4.44 ha square field.