The USDA Branded Food Database was integrated as part of FoodData Central on April 2019. For more information on FoodData Central and the USDA Branded Food Database:

Website: https://fdc.nal.usda.gov/ Ag Data Commons link: https://data.nal.usda.gov/dataset/fooddata-central

Several USDA food composition databases, including the Food and Nutrient Database for Dietary Studies (FNDDS), Standard Reference (SR) Legacy, and the USDA Branded Food Products Database, have transitioned to FoodData Central, a new and harmonized USDA food and nutrient data system. FoodData Central also includes expanded nutrient content information as well as links to diverse data sources that offer related agricultural, environmental, food, health, dietary supplement, and other information. The new system is designed to strengthen the capacity for rigorous research and policy applications through its search capabilities, downloadable datasets, and detailed documentation. Application developers can incorporate the information into their applications and web sites through the application programming interface (API) REST access. The constantly changing and expanding food supply is a challenge to those who are interested in using food and nutrient data. Including diverse types of data in one data system gives researchers, policymakers, and other audiences a key resource for addressing vital nutrition and health issues. FoodData Central: Includes five distinct types of data containing information on food and nutrient profiles, each with a unique purpose: Foundation Foods; Experimental Foods; Standard Reference; Food and Nutrient Database for Dietary Studies; USDA Global Branded Food Products Database. Provides a broad snapshot in time of the nutrients and other components found in a wide variety of foods and food products. Presents data that come from a variety of sources and are updated as new information becomes available. Includes values that are derived through a variety of analytic and computational approaches, using state-of-the-art methodologies and transparent presentation. FoodData Central is managed by the Agricultural Research Service and hosted by the National Agricultural Library. Resources in this dataset:Resource Title: Website Pointer for FoodData Central. File Name: Web Page, url: https://fdc.nal.usda.gov/index.html Includes Search, Download data, API Guide, Data Type Documentation, and Help pages.

[Note: Integrated as part of FoodData Central, April 2019.] The USDA Branded Food Products Database is the result of a Public-Private Partnership, whose goal is to enhance public health and the sharing of open data by complementing USDA Food Composition Databases with nutrient composition of branded foods and private label data provided by the food industry. Members of the Public-Private Partnership include: Agricultural Research Service (ARS), USDA (www.ars.usda.gov) Institute for the Advancement of Food and Nutrition Sciences (IAFNS) (www.iafns.org) GS1 US (www.gs1us.org/) 1WorldSync (www.1worldsync.com) Label Insight (www.labelinsight.com) University of Maryland, Joint Institute for Food Safety and Applied Nutrition (jifsan.umd.edu) The BFPDB includes: product name and generic descriptor, serving size in grams or milliliters, nutrients on the Nutrition Facts Panel per serving size and 100 gram-basis, 100 ml-basis, or fluid oz-basis, ingredient list, (never before captured by USDA), and date stamp associated with most current product formulation. All data will be archived, allowing for dietary trends tracking. The BFPDB allows: dietitians to provide specific dietary guidance; researchers to better link dietary intakes to disease measures; and policy makers to develop guidance which promotes public health. New in this August 2018 release are downloadable database files (ASCII .csv and MS Access), Application Programming Interface (API), and Documentation and Download User Guide.

USDA Branded Food Dataset

The USDA Branded Food Dataset is a cleaned and structured dataset created from USDA FoodData Central (FDC) data. This dataset consolidates extensive information on branded food items available in the U.S., providing a valuable resource for nutrition analysis, machine learning, and consumer research.

  Overview

The USDA Branded Food Dataset compiles data on over 456,000 branded food items, including:

Nutrient Profiles: Detailed nutrient content for… See the full description on the dataset page: https://huggingface.co/datasets/jacktol/usda-branded-food-data.

🇺🇸 미국

Context

I needed to record our grocery intake using a standard nomenclature that supports access and tabulation of nutrients consumed. That is, a nomenclature that spans retail grocery using UPC to the identifiers used to access nutrition labels. I wanted to know if our household's intake of nutrients complied with the bounds set forth in the 2015-2020 USDA Dietary Guidelines. And if not, what foods will most efficiently remedy dietary deficiencies/excesses. Professionally, I have been devising countermeasures to fight chronic disease and see food more so than medication as the key.

Content

Downloaded from the USDA FoodData Central database: https://fdc.nal.usda.gov/download-datasets.html, this constellation of tables is centered on the food table. That table identifies foods broadly classed as Standard like what you might find in the periphery of the store, or Branded which typically occupies the center aisles. Each Standard Reference food identifier points to exactly one food label, where each label (in the set of all labels) is a set of entity attribute value (EAV) triples comprised of FoodId NutrientId and Quantity per hectogram (i.e., 100g). Standard Reference and Branded Reference foods each occupy their own tables. Since categories for Standard Reference foods are coded, a table providing their descriptions are also provided. Note that categories for Branded Reference foods are in verbose text.

Layouts

For field definitions and table layouts see: Download_&_API_Field_Descriptions_April_2021.pdf in this distribution.

Derived tables

Syntax for tables derived from USDA FoodData Central: - Filenames are prefixed by user initials 'JCS_' - The remaining portion of the filename is a hyphenated list of its domain names. - FoodId in derived files were zero-left padded for proper collation and joining.

Domains for derived tables from which individual column values are drawn: - SRCat: Standard Reference food category, zero-left padded to two places. - Applicable: A Boolean {YES,NO} indicating whether a standard reference food category applies to the current study. - CatDesc: The description of that food category. - FoodId: A unique and unchanging food identifier, zero-left padded to seven places. - Description: Text describing each Standard Reference food item. - FoodName: Text describing each Branded Reference food item. - BRCat: Branded Reference category expressed as verbose text. - UPC: Uniform Product Code that identifies a branded food item regardless of revision date. - BrandOwner: Corporate entity that owns that brand of foods. - SvgSizeHgs: Serving size of a branded food item in hectograms. - DateAvail: Revision date for a UPC's metadata or nutrition label. - VerCnt: Number of revisions that a food identified by its UPC code underwent. - NutrientId: Uniquely identifies a nutrient as a 4-digit number with cross-references stored in nutrient.csv - Per100g: Quantity of a nutrient per hectogram as a float but stored as plain text.

Acknowledgements

To my Chair, Prof. Taghi M. Khoshgoftaar, PhD.

Inspiration

Given a list of foods and when and how much of each were consumed: - aggregate quantities of each nutrient consumed, - norming the quantities of nutrients consumed to average daily calorie burn, and - comparing each nutrient consumed to the target range for that nutrient.

Nutrient-wise deficiencies and excesses relative to target ranges are fed to a recommender that identifies: - what foods most efficiently by weight remedies these deficiencies and excesses - while being foods most likely to be consumed.

Rankings presented by the recommender during one period are evaluated by foods consumed in the following period. What ranking is the most 'compact'? That is, what ranking has the most of its foods consumed among its top k foods?

Background: Increasing evidence suggests that ultra-processed foods (UPFs) lead to elevated risk of obesity-related conditions, but UPF measurement has been criticized for its subjectivity and lack of clarity on biological mechanism. Sensory-related industrial additives (SRIAs) are a defining feature of UPFs and may encourage overconsumption by enhancing the sensory quality of foods. However, practical challenges have prevented systematic incorporation of SRIAs into UPF measurement.Objective: The objectives of this work were to describe a new, open-source ingredient list search method and to apply this method to describe the presence of SRIAs in US packaged foods.Methods: We developed computer coding to search for 64 common SRIAs related to sweetness, flavor, appearance, and texture in 241,688 foods in the US Branded Food Products Database (BFPD). The BFPD includes manufacturer-provided ingredient lists for ~300,000 branded and private label food items. We determined the total number of SRIAs (0–64) and the number of different types of SRIAs (sweetness, flavor, appearance, texture, 0–4) in each food, then calculated the percent of all foods with SRIAs. This was done for all foods, and by food group for 224,098 items with food group data.Results: Most (64.9%) foods in the BFPD contained at least one SRIA, and more than a third had at least three. Sweets (89.5%), beverages (84.9%), and ready-to-eat (RTE) foods (82.0%) were the most likely to contain SRIAs. With respect to SRIA types, 25.7% of all food items had at least three of the four types of SRIAs examined, with texture-related additives being the most common. Among sweets, 20% had all four types of SRIAs.Discussion: This work confirms the high prevalence of SRIAs in US packaged foods. They are ubiquitous in sweets, beverages, and RTE foods, but also present in substantial proportions of other food groups. Quantifying the presence of SRIAs in ingredient lists offers a novel way to identify UPFs for research; to distinguish more vs. less ultra-processed foods; and to test whether UPFs increase risk for obesity-related conditions through additives that enhance the product's sensory qualities.

Fitness Nutrition Dataset

A processed and cleaned nutritional dataset optimized for fitness and health applications, derived from the USDA Food Data Central database.

  Dataset Description

This dataset contains nutritional information for branded food products with UPC codes, making it ideal for fitness apps, nutrition tracking, and health research. Each row represents a unique food product with comprehensive macronutrient and micronutrient data. Dataset Statistics:

📊 1… See the full description on the dataset page: https://huggingface.co/datasets/trentmkelly/US-food-nutrient-data.

Entities that store products that have been locally and/or regionally sourced.

This list is a sub-category of the All Warehouses list: Facilities and companies that store food products and/or distribute food products from warehouse locations to retail locations. This list includes food warehouses and distributors with facility locations in Maryland.

Please note: this list was compiled through many different sources and verified through online research. Some entities were excluded as they were captured in other data sets (food pantries, club warehouses, etc.), were unverifiable, or found to have little to no food available.

For ease of locating Food Distribution Warehouse Facilities with specific characteristics, separate layers of data are available on the map in each category of facility. These layers are not mutually exclusive, i.e. an individual Distribution/Warehouse Facility can be included in multiple categories.

Additional categorization can be found in the complete dataset available for downloading:

Third Party Distributor: Entities that purchase groceries and products from manufacturers, processors or other distributors and resell these products to retailers, institutions and other businesses. May also be called third party wholesalers. They tend to have a variety of brands for a variety of products.

Name brand/Self Distributing: Merchant wholesale operations maintained by grocery manufacturers or processors to market their own products.

Logistic Services: Entities that market their services, rather than products, within the supply chain including transportation, warehousing, and technology/software support.

On Farm Storage: Farms that have received an “on-farm processing license”, which allows farms who raise animals for meat or dairy to have their raw products processed at an official processing plant and brought back to the farm for storage and sale. Farms with this license may sell their product from the farm or to retail and institutions within the state.

Data compiled and categorized by CLF staff.

Data source: Charles County Health Department, Environmental Health Services, Licenses to Operate a Food Establishment in Charles County; Maryland Department of Health and Mental Hygiene, Center for Food Processing; Maryland Department of Agriculture, Food Quality Assurance Program, Registered Egg Distributors/Packers; Maryland Department of Health and Mental Hygiene, Division of Milk Control, Milk and Frozen Desserts Processors and Transportation Companies; Online research; Prince George’s County Health Department, Food Service Facility Permits, Warehouse/Processing Plants; USDA Food Safety and Inspection Service, Meat, Poultry and Egg Product Inspection Directory; USDA Center for Food Safety and Applied Nutrition, Interstate Milk Shippers List

Date: 2015