Data request is limited to 50,000 records per the API. U.S. Department of Agriculture, National Agricultural Statistics Service (NASS). That file will then be imported into Tableau Public to display visualizations about the data. The Comprehensive R Archive Network website, Working for Peanuts: Acquiring, Analyzing, and Visualizing Publicly Available Data. The Census Data Query Tool (CDQT) is a web based tool that is available to access and download table level data from the Census of Agriculture Volume 1 publication. Its main limitations are 1) it can save visualization projects only to the Tableau Public Server, 2) all visualization projects are visible to anyone in the world, and 3) it can handle only a small number of input data types. Feel free to download it and modify it in the Tableaue Public Desktop application to learn how to create and publish Tableau visualizations. Skip to 5. The surveys that NASS conducts collect information on virtually every facet of U.S. agricultural production. The site is secure. Then we can make a query. The .gov means its official. You can change the value of the path name as you would like as well. The first line of the code above defines a variable called NASS_API_KEY and assigns it the string of letters and numbers that makes up the NASS Quick Stats API key you received from the NASS. Either 'CENSUS' or 'SURVEY'", https://quickstats.nass.usda.gov/api#param_define. AG-903. Public domain information on the National Agricultural Statistics Service (NASS) Web pages may be freely downloaded and reproduced. Some care N.C. About NASS. Special Tabulations and Restricted Microdata, 02/15/23 Still time to respond to the 2022 Census of Agriculture, USDA to follow up with producers who have not yet responded, 02/15/23 Still time to respond to the 2022 Puerto Rico Census of Agriculture, USDA to follow-up with producers who have not yet responded (Puerto Rico - English), 01/31/23 United States cattle inventory down 3%, 01/30/23 2022 Census of Agriculture due next week Feb. 6, 01/12/23 Corn and soybean production down in 2022, USDA reports It allows you to customize your query by commodity, location, or time period. The National Agricultural Statistics Service (NASS) is part of the United States Department of Agriculture. Note that the value PASTE_YOUR_API_KEY_HERE must be replaced with your personal API key. DSFW_Peanuts: Analysis of peanut DSFW from USDA-NASS databases. However, if you only knew English and tried to read the recipe in Spanish or Japanese, your favorite treat might not turn out very well. You dont need all of these columns, and some of the rows need to be cleaned up a little bit. You can also make small changes to the script to download new types of data. In this case, you can use the string of letters and numbers that represents your NASS Quick Stats API key to directly define the key parameter that the function needs to work. Rstudio, you can also use usethis::edit_r_environ to open The download data files contain planted and harvested area, yield per acre and production. While I used the free Microsoft Visual Studio Community 2022 integrated development ide (IDE) to write and run the Python program for this tutorial, feel free to use your favorite code editor or IDE. is needed if subsetting by geography. api key is in a file, you can use it like this: If you dont want to add the API key to a file or store it in your time you begin an R session. request. Quick Stats. USDA National Agricultural Statistics Service Information. You can see whether a column is a character by using the class( ) function on that column (that is, nc_sweetpotato_data_survey$Value where the $ helps you access the Value column in the nc_sweetpotato_data_survey variable). Sign Up: https://rruntsch.medium.com/membership, install them through the IDEs menu by following these instructions from Microsoft, Year__GE = 1997 (all years greater than or equal to 1997). In this publication, the word variable refers to whatever is on the left side of the <- character combination. Before sharing sensitive information, make sure you're on a federal government site. Census of Agriculture (CoA). It allows you to customize your query by commodity, location, or time period. Once in the tool please make your selection based on the program, sector, group, and commodity. http://quickstats.nass.usda.gov/api/api_GET/?key=PASTE_YOUR_API_KEY_HERE&source_desc=SURVEY§or_desc%3DFARMS%20%26%20LANDS%20%26%20ASSETS&commodity_desc%3DFARM%20OPERATIONS&statisticcat_desc%3DAREA%20OPERATED&unit_desc=ACRES&freq_desc=ANNUAL&reference_period_desc=YEAR&year__GE=1997&agg_level_desc=NATIONAL&state_name%3DUS%20TOTAL&format=CSV. The == character combination tells R that this is a logic test for exactly equal, the & character is a logic test for AND, and the != character combination is a logic test for not equal. You can also set the environmental variable directly with 2020. nassqs_auth(key = NASS_API_KEY). Based on your experience in algebra class, you may remember that if you replace x with NASS_API_KEY and 1 with a string of letters and numbers that defines your unique NASS Quick Stats API key, this is another way to think about the first line of code. However, ERS has no copies of the original reports. USDA-NASS Quick Stats (Crops) WHEAT.pdf PDF 1.42 MB . In R, you would write x <- 1. Next, you can define parameters of interest. Before you make a specific API query, its best to see whether the data are even available for a particular combination of parameters. What R Tools Are Available for Getting NASS Data? This publication printed on: March 04, 2023, Getting Data from the National Agricultural Statistics Service (NASS) Using R. Skip to 1. nc_sweetpotato_data_raw <- nassqs(nc_sweetpotato_params). you downloaded. How to write a Python program to query the Quick Stats database through the Quick Stats API. This work is supported by grant no. You are also going to use the tidyverse package, which is called a meta-package because it is a package of packages that helps you work with your datasets easily and keep them tidy.. equal to 2012. which at the time of this writing are. the project, but you have to repeat this process for every new project, This tool helps users obtain statistics on the database. parameters is especially helpful. The rnassqs package also has a If youre not sure what spelling and case the NASS Quick Stats API uses, you can always check by clicking through the NASS Quick Stats website. its a good idea to check that before running a query. by operation acreage in Oregon in 2012. Then, it will show you how to use Python to retrieve agricultural data with the NASS Quick Stats API. Any person using products listed in . Please note that you will need to fill in your NASS Quick Stats API key surrounded by quotation marks. The returned data includes all records with year greater than or The Census Data Query Tool (CDQT) is a web-based tool that is available to access and download table level data from the Census of Agriculture Volume 1 publication. An introductory tutorial or how to use the National Agricultural Statistics Service (NASS) Quickstats tool can be found on their website. Federal government websites often end in .gov or .mil. Lock For example, you can write a script to access the NASS Quick Stats API and download data. nassqs is a wrapper around the nassqs_GET and you risk forgetting to add it to .gitignore. Have a specific question for one of our subject experts? In both cases iterating over A function in R will take an input (or many inputs) and give an output. This image shows how working with the NASS Quick Stats API is analogous to ordering food at a restaurant. To demonstrate the use of the agricultural data obtained with the Quick Stats API, I have created a simple dashboard in Tableau Public. class(nc_sweetpotato_data_survey$Value) downloading the data via an R For example, in the list of API parameters shown above, the parameter source_desc equates to Program in the Quick Stats query tool. capitalized. Here, tidy has a specific meaning: all observations are represented as rows, and all the data categories associated with that observation are represented as columns. rnassqs (R NASS Quick Stats) rnassqs allows users to access the USDA's National Agricultural Statistics Service (NASS) Quick Stats data through their API. It allows you to customize your query by commodity, location, or time period. It also makes it much easier for people seeking to use nassqs_record_count(). The API will then check the NASS data servers for the data you requested and send your requested information back. Second, you will change entries in each row of the Value column so they are represented as a number, rather than a character. than the API restriction of 50,000 records. It is best to start by iterating over years, so that if you function, which uses httr::GET to make an HTTP GET request It is simple and easy to use, and provides some functions to help navigate the bewildering complexity of some Quick Stats data. Before you get started with the Quick Stats API, become familiar with its Terms of Service and Usage. DSFW_Peanuts: Analysis of peanut DSFW from USDA-NASS databases. Accessed: 01 October 2020. Its recommended that you use the = character rather than the <- character combination when you are defining parameters (that is, variables inside functions). Peng, R. D. 2020. Create a worksheet that allows the user to select a commodity (corn, soybeans, selected) and view the number of acres planted or harvested from 1997 through 2021. 2017 Census of Agriculture - Census Data Query Tool, QuickStats Parameter Definitions and Operators, Agricultural Statistics Districts (ASD) zipped (.zip) ESRI shapefile format for download, https://data.nal.usda.gov/dataset/nass-quick-stats, National Agricultural Library Thesaurus Term, hundreds of sample surveys conducted each year covering virtually every aspect of U.S. agriculture, the Census of Agriculture conducted every five years providing state- and county-level aggregates. The primary benefit of rnassqs is that users need not download data through repeated . After running this line of code, R will output a result. Data by subject gives you additional information for a particular subject area or commodity. R sessions will have the variable set automatically, In this example shown below, I used Quick Stats to build a query to retrieve the number of acres of corn harvested in the US from 2000 through 2021. Grain sorghum (Sorghum bicolor) is one of the most important cereal crops worldwide and is the third largest grain crop grown in the United. Quick Stats Lite Contact a specialist. To submit, please register and login first. By setting statisticcat_desc = "AREA HARVESTED", you will get results for harvest acreage rather than planted acreage. After running these lines of code, you will get a raw data output that has over 1500 rows and close to 40 columns. Census of Agriculture Top The Census is conducted every 5 years. # plot the data to quickly and easily download new data. If you use this function on the Value column of nc_sweetpotato_data_survey, R will return character, but you want R to return numeric. This is often the fastest method and provides quick feedback on the For example, commodity_desc refers to the commodity description information available in the NASS Quick Stats API and agg_level_desc refers to the aggregate level description of NASS Quick Stats API data. After you have completed the steps listed above, run the program. The program will use the API to retrieve the number of acres used for each commodity (a crop, such as corn or soybeans), on a national level, from 1997 through 2021. To submit, please register and login first. Why Is it Beneficial to Access NASS Data Programmatically? You can read more about tidy data and its benefits in the Tidy Data Illustrated Series. For docs and code examples, visit the package web page here . # filter out Sampson county data For example, a (D) value denotes data that are being withheld to avoid disclosing data for individual operations according to the creators of the NASS Quick Stats API. Indians. You can then define this filtered data as nc_sweetpotato_data_survey. For file. 2017 Census of Agriculture. Didn't find what you're looking for? However, here are the basic steps to install Tableau Public and build and publish the dashboard: After completing this tutorial, you should have a general understanding of: I can imagine many use cases for projects that would use data from the Quick Stats database. Depending on what agency your survey is from, you will need to contact that agency to update your record. You can get an API Key here. An open-standard file format that uses human-readable text to transmit data objects consisting of attribute-value pairs and array data types. The inputs to this function are 2 and 10 and the output is 12. Now that youve cleaned the data, you can display them in a plot. United States Department of Agriculture. file, and add NASSQS_TOKEN = to the Be sure to keep this key in a safe place because it is your personal key to the NASS Quick Stats API. As an example, one year of corn harvest data for a particular county in the United States would represent one row, and a second year would represent another row. Before using the API, you will need to request a free API key that your program will include with every call using the API. Access Quick Stats Lite . A list of the valid values for a given field is available via # fix Value column Finally, you can define your last dataset as nc_sweetpotato_data. USDA-NASS. # look at the first few lines token API key, default is to use the value stored in .Renviron . That is an average of nearly 450 acres per farm operation. Website: https://ask.usda.gov/s/, June Turner, Director Email: / Phone: (202) 720-8257, Find contact information for Regional and State Field Offices. The data include the total crops and cropping practices for each county, and breakouts for irrigated and non-irrigated practices for many crops, for selected States. Now that youve cleaned and plotted the data, you can save them for future use or to share with others. script creates a trail that you can revisit later to see exactly what "rnassqs: An 'R' package to access agricultural data via the USDA National Agricultural Statistics Service (USDA-NASS) 'Quick Stats' API." The Journal of Open Source Software. The Quick Stats Database is the most comprehensive tool for accessing agricultural data published by NASS. Public domain information on the National Agricultural Statistics Service (NASS) Web pages may be freely downloaded and reproduced. any place from which $1,000 or more of agricultural products were produced and sold, or normally would have been sold, during the year. Open source means that the R source code the computer code that makes R work can be viewed and edited by the public. Then you can use it coders would say run the script each time you want to download NASS survey data. United States Dept. Please click here to provide feedback for any of the tools on this page. 2020. Tableau Public is a free version of the commercial Tableau data visualization tool. Access Quick Stats (searchable database) The Quick Stats Database is the most comprehensive tool for accessing agricultural data published by NASS. By setting domain_desc = TOTAL, you will get the total acreage of sweetpotatoes in the county as opposed to the acreage of sweetpotates in the county grown by operators or producers of specific demographic groups that contribute to the total acreage of harvested sweetpotatoes in the county. Corn stocks down, soybean stocks down from year earlier The QuickStats API offers a bewildering array of fields on which to 2020. It allows you to customize your query by commodity, location, or time period. multiple variables, geographies, or time frames without having to The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely. Statistics Service, Washington, D.C. URL: https://quickstats.nass.usda.gov [accessed Feb 2023] . Once you know North Carolina has data available, you can make an API query specific to sweetpotatoes in North Carolina. If you use it, be sure to install its Python Application support. lock ( The Census Data Query Tool (CDQT) is a web based tool that is available to access and download table level data from the Census of Agriculture Volume 1 publication. Here, code refers to the individual characters (that is, ASCII characters) of the coding language. However, the NASS also allows programmatic access to these data via an application program interface as described in Section 2. The Cropland Data Layer (CDL) is a product of the USDA National Agricultural Statistics Service (NASS) with the mission "to provide timely, accurate and useful statistics in service to U.S. agriculture" (Johnson and Mueller, 2010, p. 1204). replicate your results to ensure they have the same data that you You can then visualize the data on a map, manipulate and export the results, or save a link for future use. If you are interested in trying Visual Studio Community, you can install it here. The <- character combination means the same as the = (that is, equals) character, and R will recognize this. While there are three types of API queries, this tutorial focuses on what may be the most flexible, which is the GET /api/api_GET query. A locked padlock Code is similar to the characters of the natural language, which can be combined to make a sentence. do. Accessed: 01 October 2020. Corn stocks down, soybean stocks down from year earlier It allows you to customize your query by commodity, location, or time period. For more specific information please contact nass@usda.gov or call 1-800-727-9540. *In this Extension publication, we will only cover how to use the rnassqs R package. This will create a new In addition, you wont be able object generated by the GET call, you can use nassqs_GET to The database allows custom extracts based on commodity, year, and selected counties within a State, or all counties in one or more States. ) or https:// means youve safely connected to To use a restaurant analogy, you can think of the NASS Quick Stats API as the waitstaff at your favorite restaurant, the NASS data servers as the kitchen, the software on your computer as the waitstaffs order notepad, and the coder as the customer (you) as shown in Figure 1. Reference to products in this publication is not intended to be an endorsement to the exclusion of others which may have similar uses. key, you can use it in any of the following ways: In your home directory create or edit the .Renviron Because R is accessible to so many people, there is a great deal of collaboration and sharing of R resources, scripts, and knowledge. Accessed online: 01 October 2020. Here are the pairs of parameters and values that it will submit in the API call to retrieve that data: Following is the full encoded URL that the program below creates and sends with the Quick Stats API. Quick Stats contains official published aggregate estimates related to U.S. agricultural production. For example, if youd like data from both You can define this selected data as nc_sweetpotato_data_sel. There are times when your data look like a 1, but R is really seeing it as an A. and predecessor agencies, U.S. Department of Agriculture (USDA). The USDAs National Agricultural Statistics Service (NASS) makes the departments farm agricultural data available to the public on its website through reports, maps, search tools, and its NASS Quick Stats API. Most of the information available from this site is within the public domain. Special Tabulations and Restricted Microdata, 02/15/23 Still time to respond to the 2022 Census of Agriculture, USDA to follow up with producers who have not yet responded, 02/15/23 Still time to respond to the 2022 Puerto Rico Census of Agriculture, USDA to follow-up with producers who have not yet responded (Puerto Rico - English), 01/31/23 United States cattle inventory down 3%, 01/30/23 2022 Census of Agriculture due next week Feb. 6, 01/12/23 Corn and soybean production down in 2022, USDA reports Note: When a line of R code starts with a #, R knows to read this # symbol as a comment and will skip over this line when you run your code. Scripts allow coders to easily repeat tasks on their computers. Once the The next thing you might want to do is plot the results. The following are some of the types of data it stores and makes available: NASS makes data available through CSV and PDF files, charts and maps, a searchable database, pre-defined queries, and the Quick Stats API. You do this by using the str_replace_all( ) function. This reply is called an API response. Winter Wheat Seedings up for 2023, NASS to publish milk production data in updated data dissemination format, USDA-NASS Crop Progress report delayed until Nov. 29, NASS reinstates Cost of Pollination survey, USDA NASS reschedules 2021 Conservation Practice Adoption Motivations data highlights release, Respond Now to the 2022 Census of Agriculture, 2017 Census of Agriculture Highlight Series Farms and Land in Farms, 2017 Census of Agriculture Highlight Series Economics, 2017 Census of Agriculture Highlight Series Demographics, NASS Climate Adaptation and Resilience Plan, Statement of Commitment to Scientific Integrity, USDA and NASS Civil Rights Policy Statement, Civil Rights Accountability Policy and Procedures, Contact information for NASS Civil Rights Office, International Conference on Agricultural Statistics, Agricultural Statistics: A Historical Timeline, As We Recall: The Growth of Agricultural Estimates, 1933-1961, Safeguarding America's Agricultural Statistics Report, Application Programming Interfaces (APIs), Economics, Statistics and Market Information System (ESMIS). This function replaces spaces and special characters in text with escape codes that can be passed, as part of the full URL, to the Quick Stats web server. list with c(). We summarize the specifics of these benefits in Section 5. The site is secure. install.packages("rnassqs"). Accessed online: 01 October 2020. R is also free to download and use. To browse or use data from this site, no account is necessary. Language feature sets can be added at any time after you install Visual Studio. Often 'county', 'state', or 'national', but can include other levels as well", #> [2] "source_desc: Data source. In some cases you may wish to collect Using rnassqs Nicholas A Potter 2022-03-10. rnassqs is a package to access the QuickStats API from national agricultural statistics service (NASS) at the USDA. nc_sweetpotato_data <- select(nc_sweetpotato_data_survey_mutate, -Value) Also, be aware that some commodity descriptions may include & in their names. Many people around the world use R for data analysis, data visualization, and much more. 2020. year field with the __GE modifier attached to Install. Not all NASS data goes back that far, though. It can return data for the 2012 and 2017 censuses at the national, state, and local level for 77 different tables. The chef is in the kitchen window in the upper left, the waitstaff in the center with the order, and the customer places the order. Once youve installed the R packages, you can load them. County level data are also available via Quick Stats. NASS Reports Crop Progress (National) Crop Progress & Condition (State) Prior to using the Quick Stats API, you must agree to the NASS Terms of Service and obtain an API key. You can read more about the available NASS Quick Stats API parameters and their definitions by checking out the help page on this topic. Open Tableau Public Desktop and connect it to the agricultural CSV data file retrieved with the Quick Stats API through the Python program described above. Providing Central Access to USDAs Open Research Data, MULTIPOLYGON (((-155.54211 19.08348, -155.68817 18.91619, -155.93665 19.05939, -155.90806 19.33888, -156.07347 19.70294, -156.02368 19.81422, -155.85008 19.97729, -155.91907 20.17395, -155.86108 20.26721, -155.78505 20.2487, -155.40214 20.07975, -155.22452 19.99302, -155.06226 19.8591, -154.80741 19.50871, -154.83147 19.45328, -155.22217 19.23972, -155.54211 19.08348)), ((-156.07926 20.64397, -156.41445 20.57241, -156.58673 20.783, -156.70167 20.8643, -156.71055 20.92676, -156.61258 21.01249, -156.25711 20.91745, -155.99566 20.76404, -156.07926 20.64397)), ((-156.75824 21.17684, -156.78933 21.06873, -157.32521 21.09777, -157.25027 21.21958, -156.75824 21.17684)), ((-157.65283 21.32217, -157.70703 21.26442, -157.7786 21.27729, -158.12667 21.31244, -158.2538 21.53919, -158.29265 21.57912, -158.0252 21.71696, -157.94161 21.65272, -157.65283 21.32217)), ((-159.34512 21.982, -159.46372 21.88299, -159.80051 22.06533, -159.74877 22.1382, -159.5962 22.23618, -159.36569 22.21494, -159.34512 21.982)), ((-94.81758 49.38905, -94.64 48.84, -94.32914 48.67074, -93.63087 48.60926, -92.61 48.45, -91.64 48.14, -90.83 48.27, -89.6 48.01, -89.272917 48.019808, -88.378114 48.302918, -87.439793 47.94, -86.461991 47.553338, -85.652363 47.220219, -84.87608 46.900083, -84.779238 46.637102, -84.543749 46.538684, -84.6049 46.4396, -84.3367 46.40877, -84.14212 46.512226, -84.091851 46.275419, -83.890765 46.116927, -83.616131 46.116927, -83.469551 45.994686, -83.592851 45.816894, -82.550925 45.347517, -82.337763 44.44, -82.137642 43.571088, -82.43 42.98, -82.9 42.43, -83.12 42.08, -83.142 41.975681, -83.02981 41.832796, -82.690089 41.675105, -82.439278 41.675105, -81.277747 42.209026, -80.247448 42.3662, -78.939362 42.863611, -78.92 42.965, -79.01 43.27, -79.171674 43.466339, -78.72028 43.625089, -77.737885 43.629056, -76.820034 43.628784, -76.5 44.018459, -76.375 44.09631, -75.31821 44.81645, -74.867 45.00048, -73.34783 45.00738, -71.50506 45.0082, -71.405 45.255, -71.08482 45.30524, -70.66 45.46, -70.305 45.915, -69.99997 46.69307, -69.237216 47.447781, -68.905 47.185, -68.23444 47.35486, -67.79046 47.06636, -67.79134 45.70281, -67.13741 45.13753, -66.96466 44.8097, -68.03252 44.3252, -69.06 43.98, -70.11617 43.68405, -70.645476 43.090238, -70.81489 42.8653, -70.825 42.335, -70.495 41.805, -70.08 41.78, -70.185 42.145, -69.88497 41.92283, -69.96503 41.63717, -70.64 41.475, -71.12039 41.49445, -71.86 41.32, -72.295 41.27, -72.87643 41.22065, -73.71 40.931102, -72.24126 41.11948, -71.945 40.93, -73.345 40.63, -73.982 40.628, -73.952325 40.75075, -74.25671 40.47351, -73.96244 40.42763, -74.17838 39.70926, -74.90604 38.93954, -74.98041 39.1964, -75.20002 39.24845, -75.52805 39.4985, -75.32 38.96, -75.071835 38.782032, -75.05673 38.40412, -75.37747 38.01551, -75.94023 37.21689, -76.03127 37.2566, -75.72205 37.93705, -76.23287 38.319215, -76.35 39.15, -76.542725 38.717615, -76.32933 38.08326, -76.989998 38.239992, -76.30162 37.917945, -76.25874 36.9664, -75.9718 36.89726, -75.86804 36.55125, -75.72749 35.55074, -76.36318 34.80854, -77.397635 34.51201, -78.05496 33.92547, -78.55435 33.86133, -79.06067 33.49395, -79.20357 33.15839, -80.301325 32.509355, -80.86498 32.0333, -81.33629 31.44049, -81.49042 30.72999, -81.31371 30.03552, -80.98 29.18, -80.535585 28.47213, -80.53 28.04, -80.056539 26.88, -80.088015 26.205765, -80.13156 25.816775, -80.38103 25.20616, -80.68 25.08, -81.17213 25.20126, -81.33 25.64, -81.71 25.87, -82.24 26.73, -82.70515 27.49504, -82.85526 27.88624, -82.65 28.55, -82.93 29.1, -83.70959 29.93656, -84.1 30.09, -85.10882 29.63615, -85.28784 29.68612, -85.7731 30.15261, -86.4 30.4, -87.53036 30.27433, -88.41782 30.3849, -89.18049 30.31598, -89.593831 30.159994, -89.413735 29.89419, -89.43 29.48864, -89.21767 29.29108, -89.40823 29.15961, -89.77928 29.30714, -90.15463 29.11743, -90.880225 29.148535, -91.626785 29.677, -92.49906 29.5523, -93.22637 29.78375, -93.84842 29.71363, -94.69 29.48, -95.60026 28.73863, -96.59404 28.30748, -97.14 27.83, -97.37 27.38, -97.38 26.69, -97.33 26.21, -97.14 25.87, -97.53 25.84, -98.24 26.06, -99.02 26.37, -99.3 26.84, -99.52 27.54, -100.11 28.11, -100.45584 28.69612, -100.9576 29.38071, -101.6624 29.7793, -102.48 29.76, -103.11 28.97, -103.94 29.27, -104.45697 29.57196, -104.70575 30.12173, -105.03737 30.64402, -105.63159 31.08383, -106.1429 31.39995, -106.50759 31.75452, -108.24 31.754854, -108.24194 31.34222, -109.035 31.34194, -111.02361 31.33472, -113.30498 32.03914, -114.815 32.52528, -114.72139 32.72083, -115.99135 32.61239, -117.12776 32.53534, -117.295938 33.046225, -117.944 33.621236, -118.410602 33.740909, -118.519895 34.027782, -119.081 34.078, -119.438841 34.348477, -120.36778 34.44711, -120.62286 34.60855, -120.74433 35.15686, -121.71457 36.16153, -122.54747 37.55176, -122.51201 37.78339, -122.95319 38.11371, -123.7272 38.95166, -123.86517 39.76699, -124.39807 40.3132, -124.17886 41.14202, -124.2137 41.99964, -124.53284 42.76599, -124.14214 43.70838, -124.020535 44.615895, -123.89893 45.52341, -124.079635 46.86475, -124.39567 47.72017, -124.68721 48.184433, -124.566101 48.379715, -123.12 48.04, -122.58736 47.096, -122.34 47.36, -122.5 48.18, -122.84 49, -120 49, -117.03121 49, -116.04818 49, -113 49, -110.05 49, -107.05 49, -104.04826 48.99986, -100.65 49, -97.22872 49.0007, -95.15907 49, -95.15609 49.38425, -94.81758 49.38905)), ((-153.006314 57.115842, -154.00509 56.734677, -154.516403 56.992749, -154.670993 57.461196, -153.76278 57.816575, -153.228729 57.968968, -152.564791 57.901427, -152.141147 57.591059, -153.006314 57.115842)), ((-165.579164 59.909987, -166.19277 59.754441, -166.848337 59.941406, -167.455277 60.213069, -166.467792 60.38417, -165.67443 60.293607, -165.579164 59.909987)), ((-171.731657 63.782515, -171.114434 63.592191, -170.491112 63.694975, -169.682505 63.431116, -168.689439 63.297506, -168.771941 63.188598, -169.52944 62.976931, -170.290556 63.194438, -170.671386 63.375822, -171.553063 63.317789, -171.791111 63.405846, -171.731657 63.782515)), ((-155.06779 71.147776, -154.344165 70.696409, -153.900006 70.889989, -152.210006 70.829992, -152.270002 70.600006, -150.739992 70.430017, -149.720003 70.53001, -147.613362 70.214035, -145.68999 70.12001, -144.920011 69.989992, -143.589446 70.152514, -142.07251 69.851938, -140.985988 69.711998, -140.992499 66.000029, -140.99777 60.306397, -140.012998 60.276838, -139.039 60.000007, -138.34089 59.56211, -137.4525 58.905, -136.47972 59.46389, -135.47583 59.78778, -134.945 59.27056, -134.27111 58.86111, -133.355549 58.410285, -132.73042 57.69289, -131.70781 56.55212, -130.00778 55.91583, -129.979994 55.284998, -130.53611 54.802753, -131.085818 55.178906, -131.967211 55.497776, -132.250011 56.369996, -133.539181 57.178887, -134.078063 58.123068, -135.038211 58.187715, -136.628062 58.212209, -137.800006 58.499995, -139.867787 59.537762, -140.825274 59.727517, -142.574444 60.084447, -143.958881 59.99918, -145.925557 60.45861, -147.114374 60.884656, -148.224306 60.672989, -148.018066 59.978329, -148.570823 59.914173, -149.727858 59.705658, -150.608243 59.368211, -151.716393 59.155821, -151.859433 59.744984, -151.409719 60.725803, -150.346941 61.033588, -150.621111 61.284425, -151.895839 60.727198, -152.57833 60.061657, -154.019172 59.350279, -153.287511 58.864728, -154.232492 58.146374, -155.307491 57.727795, -156.308335 57.422774, -156.556097 56.979985, -158.117217 56.463608, -158.433321 55.994154, -159.603327 55.566686, -160.28972 55.643581, -161.223048 55.364735, -162.237766 55.024187, -163.069447 54.689737, -164.785569 54.404173, -164.942226 54.572225, -163.84834 55.039431, -162.870001 55.348043, -161.804175 55.894986, -160.563605 56.008055, -160.07056 56.418055, -158.684443 57.016675, -158.461097 57.216921, -157.72277 57.570001, -157.550274 58.328326, -157.041675 58.918885, -158.194731 58.615802, -158.517218 58.787781, -159.058606 58.424186, -159.711667 58.93139, -159.981289 58.572549, -160.355271 59.071123, -161.355003 58.670838, -161.968894 58.671665, -162.054987 59.266925, -161.874171 59.633621, -162.518059 59.989724, -163.818341 59.798056, -164.662218 60.267484, -165.346388 60.507496, -165.350832 61.073895, -166.121379 61.500019, -165.734452 62.074997, -164.919179 62.633076, -164.562508 63.146378, -163.753332 63.219449, -163.067224 63.059459, -162.260555 63.541936, -161.53445 63.455817, -160.772507 63.766108, -160.958335 64.222799, -161.518068 64.402788, -160.777778 64.788604, -161.391926 64.777235, -162.45305 64.559445, -162.757786 64.338605, -163.546394 64.55916, -164.96083 64.446945, -166.425288 64.686672, -166.845004 65.088896, -168.11056 65.669997, -166.705271 66.088318, -164.47471 66.57666, -163.652512 66.57666, -163.788602 66.077207, -161.677774 66.11612, -162.489715 66.735565, -163.719717 67.116395, -164.430991 67.616338, -165.390287 68.042772, -166.764441 68.358877, -166.204707 68.883031, -164.430811 68.915535, -163.168614 69.371115, -162.930566 69.858062, -161.908897 70.33333, -160.934797 70.44769, -159.039176 70.891642, -158.119723 70.824721, -156.580825 71.357764, -155.06779 71.147776))), USDA National Agricultural Statistics Service, 005:042 - Department of Agriculture - Agricultural Estimates, 005:043 - Department of Agriculture - Census of Agriculture, 005:050 - Department of Agriculture - Commodity Purchases, 005:15 - National Agricultural Statistics Service.