7 datasets found
  1. U

    Estimated annual agricultural pesticide use by major crop or crop group for...

    • data.usgs.gov
    • datasets.ai
    • +2more
    Updated Sep 24, 2021
    + more versions
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    Christine Wieben (2021). Estimated annual agricultural pesticide use by major crop or crop group for states of the conterminous United States, 1992-2019 (including preliminary estimates for 2018-19) [Dataset]. http://doi.org/10.5066/P900FZ6Y
    Explore at:
    Dataset updated
    Sep 24, 2021
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Christine Wieben
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Time period covered
    1992 - 2019
    Area covered
    United States, Contiguous United States
    Description

    This data release provides state-level estimates of annual agricultural use of pesticide compounds by major crop or crop group for states in the conterminous United States, for years 1992-2019, compiled from data used to make county-level estimates by means of methods described in Thelin and Stone (2013) and Baker and Stone (2015). The source of these data is the same as the published county-level pesticide-use estimates for 1992-2009 (Stone, 2013), estimates for 2008-2012 (Baker and Stone, 2015), estimates for 2013-17 (Wieben, 2019), and preliminary estimates for 2018 and 2019 (Wieben, 2021a, Wieben, 2021b, respectively). County-level by-crop estimates are not published because of the increased uncertainty in estimating the geographic distribution of compounds applied to specific crops. High-acreage crops (corn, soybeans, wheat, cotton, rice, and alfalfa) are individually aggregated to state level while low-acreage crops are combined into groups (vegetables and fruit, orchards an ...

  2. TIGER/Line Shapefile, 2022, County, Rice County, KS, Topological Faces...

    • datasets.ai
    • s.cnmilf.com
    • +1more
    55, 57
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    U.S. Census Bureau, Department of Commerce, TIGER/Line Shapefile, 2022, County, Rice County, KS, Topological Faces (Polygons With All Geocodes) [Dataset]. https://datasets.ai/datasets/tiger-line-shapefile-2022-county-rice-county-ks-topological-faces-polygons-with-all-geocodes
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    55, 57Available download formats
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    U.S. Census Bureau, Department of Commerce
    Area covered
    Rice County, Kansas
    Description

    The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

  3. TIGER/Line Shapefile, 2023, County, Rice County, KS, Topological Faces...

    • catalog.data.gov
    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    Updated Aug 9, 2025
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Geospatial Products Branch (Point of Contact) (2025). TIGER/Line Shapefile, 2023, County, Rice County, KS, Topological Faces (Polygons With All Geocodes) [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2023-county-rice-county-ks-topological-faces-polygons-with-all-geocodes
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    Dataset updated
    Aug 9, 2025
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    United States Department of Commercehttp://commerce.gov/
    Area covered
    Rice County
    Description

    The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

  4. TIGER/Line Shapefile, 2020, County, Rice County, MN, Topological Faces...

    • s.cnmilf.com
    • catalog.data.gov
    Updated Jan 28, 2024
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2020, County, Rice County, MN, Topological Faces (Polygons With All Geocodes) [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/tiger-line-shapefile-2020-county-rice-county-mn-topological-faces-polygons-with-all-geocodes
    Explore at:
    Dataset updated
    Jan 28, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    United States Department of Commercehttp://commerce.gov/
    Area covered
    Rice County, Minnesota
    Description

    The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

  5. 🍔 Food Vitamins, Minerals, Macronutrient

    • kaggle.com
    Updated Aug 14, 2023
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    mexwell (2023). 🍔 Food Vitamins, Minerals, Macronutrient [Dataset]. https://www.kaggle.com/datasets/mexwell/food-vitamins-minerals-macronutrient
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 14, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    mexwell
    License

    http://www.gnu.org/licenses/old-licenses/gpl-2.0.en.htmlhttp://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html

    Description

    The following data comes from the United States Department of Agriculture’s Food Composition Database. It contains data for various types of food including the amounts of different vitamins and minerals found in the foods as well as macronutrient percentages. The food covered spans a large variety of foods from butter to Campbell’s soup. Much of the supplementary documenation for each field comes directly from that pages’ Wikipedia article.

    Data Dictionary

    KeyList of...CommentExample Value
    CategoryStringThe general category of food that this item belongs to."Milk"
    DescriptionStringA full description of this food item, including its category and some sub categories."Milk, human"
    Nutrient Data Bank NumberIntegerA unique ID for this food item.11000000
    Data.Alpha CaroteneIntegerAlpha Carotene is a form of carotene with a Beta-ionone ring at one end and an Alpha-ionone ring at the opposite end. It is the second most common form of carotene. Alpha Carotene is common in yellow-orange and dark-green vegetables. Measured in micrograms (mcg).0
    Data.Beta CaroteneIntegerAn organic, strongly colored red-orange pigment abundant in plants and fruits. Measured in micrograms (mcg).7
    Data.Beta CryptoxanthinIntegerCryptoxanthin is a natural carotenoid pigment. It has been isolated from a variety of sources including the petals and flowers of plants in the genus Physalis, orange rind, papaya, egg yolk, butter, apples, and bovine blood serum. In the human body, cryptoxanthin is converted to vitamin A (retinol) and is, therefore, considered a provitamin A. As with other carotenoids, cryptoxanthin is an antioxidant and may help prevent free radical damage to cells and DNA, as well as stimulate the repair of oxidative damage to DNA. Measured in micrograms (mcg).0
    Data.CarbohydrateFloatIn food science and in many informal contexts, the term carbohydrate often means any food that is particularly rich in the complex carbohydrate starch (such as cereals, bread and pasta) or simple carbohydrates, such as sugar (found in candy, jams, and desserts). Carbohydrates are found in wide variety of foods. The important sources are cereals (wheat, maize, rice), potatoes, sugarcane, fruits, table sugar(sucrose), bread, milk, etc. Starch and sugar are the important carbohydrates in our diet. Starch is abundant in potatoes, maize, rice and other cereals. Sugar appears in our diet mainly as sucrose(table sugar) which is added to drinks and many prepared foods such as jam, biscuits and cakes. Glucose and fructose are found naturally in many fruits and some vegetables. Glycogen is carbohydrate found in the liver and muscles (as animal source). Cellulose in the cell wall of all plant tissue is a carbohydrate. It is important in our diet as fibre which helps to maintain a healthy digestive system. Measured in grams (g) by difference.6.89
    Data.CholesterolIntegerAn organic molecule that is a sterol (or modified steroid), a type of lipid molecule, and is biosynthesized by all animal cells, because it is an essential structural component of all animal cell membranes; essential to maintain both membrane structural integrity and fluidity. Cholesterol enables animal cells to dispense with a cell wall (to protect membrane integrity and cell viability), thereby allowing animal cells to change shape and animals to move (unlike bacteria and plant cells, which are restricted by their cell walls). Since all animal cells manufacture cholesterol, all animal-based foods contain cholesterol in varying amounts. Measured in milligrams (mg).14
    Data.CholineFloatA water-soluble vitamin. Humans make choline in the liver. Whether dietary or supplemental choline is beneficial or harmful to humans is undefined. Measured in milligrams (mg).16.0
    Data.FiberFloatDietary fiber or roughage is the indigestible portion of food derived from plants. It has two main components: soluble fiber and insoluble fiber. Measured in grams (g).0.0
    Data.Lutein and ZeaxanthinIntegerL...

  6. TIGER/Line Shapefile, 2022, County, Rice County, MN, Topological Faces...

    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    Updated Jan 27, 2024
    Share
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2022, County, Rice County, MN, Topological Faces (Polygons With All Geocodes) [Dataset]. https://res1catalogd-o-tdatad-o-tgov.vcapture.xyz/dataset/tiger-line-shapefile-2022-county-rice-county-mn-topological-faces-polygons-with-all-geocodes
    Explore at:
    Dataset updated
    Jan 27, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    United States Department of Commercehttp://commerce.gov/
    Area covered
    Rice County, Minnesota
    Description

    The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

  7. TIGER/Line Shapefile, 2020, County, Rice County, KS, Topological Faces...

    • catalog.data.gov
    Updated Jan 28, 2024
    Share
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    TwitterTwitter
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    Click to copy link
    Link copied
    Close
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    U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch (Point of Contact) (2024). TIGER/Line Shapefile, 2020, County, Rice County, KS, Topological Faces (Polygons With All Geocodes) [Dataset]. https://catalog.data.gov/dataset/tiger-line-shapefile-2020-county-rice-county-ks-topological-faces-polygons-with-all-geocodes
    Explore at:
    Dataset updated
    Jan 28, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    United States Department of Commercehttp://commerce.gov/
    Area covered
    Rice County
    Description

    The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.

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Christine Wieben (2021). Estimated annual agricultural pesticide use by major crop or crop group for states of the conterminous United States, 1992-2019 (including preliminary estimates for 2018-19) [Dataset]. http://doi.org/10.5066/P900FZ6Y

Estimated annual agricultural pesticide use by major crop or crop group for states of the conterminous United States, 1992-2019 (including preliminary estimates for 2018-19)

Explore at:
16 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Sep 24, 2021
Dataset provided by
United States Geological Surveyhttp://www.usgs.gov/
Authors
Christine Wieben
License

U.S. Government Workshttps://www.usa.gov/government-works
License information was derived automatically

Time period covered
1992 - 2019
Area covered
United States, Contiguous United States
Description

This data release provides state-level estimates of annual agricultural use of pesticide compounds by major crop or crop group for states in the conterminous United States, for years 1992-2019, compiled from data used to make county-level estimates by means of methods described in Thelin and Stone (2013) and Baker and Stone (2015). The source of these data is the same as the published county-level pesticide-use estimates for 1992-2009 (Stone, 2013), estimates for 2008-2012 (Baker and Stone, 2015), estimates for 2013-17 (Wieben, 2019), and preliminary estimates for 2018 and 2019 (Wieben, 2021a, Wieben, 2021b, respectively). County-level by-crop estimates are not published because of the increased uncertainty in estimating the geographic distribution of compounds applied to specific crops. High-acreage crops (corn, soybeans, wheat, cotton, rice, and alfalfa) are individually aggregated to state level while low-acreage crops are combined into groups (vegetables and fruit, orchards an ...

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