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Data from: High genetic diversity in the landscape suggests frequent seedling recruitment by Euphorbia virgata Waldst. & Kit. (leafy spurge) in the northern U.S.A.

    Site information and field-collected data from a 1-year 100-site survey of leafy spurge (Euphorbia virgata/esula) populations in the northern U.S. Data include: 1) estimates of leafy spurge density and relative prevalence of ramets versus genets; 2) the abundance and composition of Aphthona species complex biological control agents; 3) presence/absence of two additional biological control agents (Oberea erythrocephala and Hyles euphorbiae).

    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 from: Not just crop or forest: building an integrated land cover map for agricultural and natural areas (spatial files)

        To address the need for maps that characterize detailed land cover, including both agricultural and natural habitats, we combined two national datasets of land cover, the Landscape Fire and Resource Management Planning Tools (LANDFIRE) National Vegetation Classification (NVC) and United States Department of Agriculture, National Agricultural Statistics Service (USDA-NASS) Cropland Data Layer (CDL). Our workflow leveraged strengths of the NVC and the CDL to produce annual land-use rasters for 2012-2021.

        Data from: Not just crop or forest: building an integrated land cover map for agricultural and natural areas (tabular files)

          To address the need for maps that characterize detailed land cover, including both agricultural and natural habitats, we combined two national datasets of land cover, the Landscape Fire and Resource Management Planning Tools (LANDFIRE) National Vegetation Classification (NVC) and United States Department of Agriculture, National Agricultural Statistics Service (USDA-NASS) Cropland Data Layer (CDL). Our workflow leveraged strengths of the NVC and the CDL to produce annual land-use rasters for 2012-2021.

          Data from: Effect of Source on Trust of Pulse Nutrition Information and Perceived Likelihood of Following Dietary Guidance

            The purpose of the present study was to examine how information source (control—no source, USDA, fictitious hospital, or fictitious social media) impacts perceptions of diet information. Participants included 943 American adults who were aged 18-74 years and were recruited from across the United States through Amazon Mechanical Turk (MTurk). ANOVA results indicated that the USDA and hospital sources were perceived as more accurate, trustworthy, reliable, and more desirable to learn more from relative to control and social media. There were no differences in likelihood of following guidance depending on source.

            WIC Infant and Toddler Feeding Practices Study-2 (WIC ITFPS-2): Prenatal, Infant Year, Second Year, Third Year, and Fourth Year Datasets

              The WIC Infant and Toddler Feeding Practices Study–2 (WIC ITFPS-2) addresses a series of research questions regarding feeding practices, the effect of WIC services on those practices, and the health and nutrition outcomes of children on WIC. These datasets include data from caregivers and their children during the prenatal period and during the children’s first four years of life (child ages 1 to 48 months).