Context:

“The Universal Product Code (UPC) is a barcode symbology that is widely used in the United States, Canada, United Kingdom, Australia, New Zealand, in Europe and other countries for tracking trade items in stores.

“UPC (technically refers to UPC-A) consists of 12 numeric digits, that are uniquely assigned to each trade item. Along with the related EAN barcode, the UPC is the barcode mainly used for scanning of trade items at the point of sale, per GS1 specifications.[1] UPC data structures are a component of GTINs and follow the global GS1 specification, which is based on international standards. But some retailers (clothing, furniture) do not use the GS1 system (rather other barcode symbologies or article number systems). On the other hand, some retailers use the EAN/UPC barcode symbology, but without using a GTIN (for products, brands, sold at such retailers only).”

-- Tate. (n.d.). In Wikipedia. Retrieved August 18, 2017, from https://en.wikipedia.org/wiki/Plagiarism. Text reproduced here under a CC-BY-SA 3.0 license.

Content:

This dataset contains just over 1 million UPC codes and the names of the products associated with them.

Acknowledgements:

While UPC’s themselves are not copyrightable, the brand names and trademarks in this dataset remain the property of their respective owners.

Inspiration:

• Can you use this dataset to generate new product names?
• Can you use this in conjunction with other datasets to disambiguate products?

The National Health Related Items Code (NHRIC) is a system for identification and numbering of marketed device packages that is compatible with other numbering systems such as the National Drug Code (NDC) or Universal Product Code (UPC). Those manufacturers who desire to use the NHRIC number for unique product identification may apply to FDA for a labeler code. This database contains NHRIC data retrieved from records that date back 20 years.

This dataset represents the list of CA WIC authorized food items identified by food category and subcategory. Each item is uniquely identified by a Universal Product Code (UPC) or Price Look-Up code (PLU) for WIC electronic benefit transfer (EBT). The WIC Authorized vendors use the CA Authorized Product List (APL) to transact WIC food items at cash registers. The APL plays a crucial role in supporting WIC EBT purchases. WIC EBT requires vendor systems to maintain the APL to match the scanned food items' UPCs to ensure they are on the APL. The food items identified by UPC and PLU can be found in the data files below. When you download the files, Excel may prompt you to automatically format the data. If prompted, you may want to hit ‘Don’t Convert’ so that Excel leaves the data as is without any formatting or data conversions.

The Women, Infants and Children (WIC) Program is a federally-funded health and nutrition program that provides assistance to pregnant women, new mothers, infants, and children under age five. WIC helps California families by providing food benefits to individual participants based on their nutritional need and risk assessment. The food benefits can be used to purchase healthy supplemental foods from approximately 3,800 WIC authorized vendor stores throughout the State. WIC also provides nutritional education, breastfeeding support, healthcare referrals, and other community services. Participants must meet income guidelines and other criteria. Currently, 84 WIC agencies provide services monthly to approximately one million participants at several hundred sites in local communities throughout the State.

rCRUX generated reference database using NCBI nt blast database and an additional custom blast database comprised of all Actinopterygii mitogenomes. Both blast databases were downloaded in December 2022.

Primer Name: MiFish Universal Gene: 12S Length of Target: 163–185 get_seeds_local() minimum length: 170 get_seeds_local() maximum length: 250 blast_seeds() minimum length: 140 blast_seeds() maximum length: 250 max_to_blast: 1000 Forward Sequence (5'-3'): GTGTCGGTAAAACTCGTGCCAGC Reverse Sequence (5'-3'): CATAGTGGGGTATCTAATCCCAGTTTG Reference: Miya, M., Sato, Y., Fukunaga, T., Sado, T., Poulsen, J. Y., Sato, K., ... & Kondoh, M. (2015). MiFish, a set of universal PCR primers for metabarcoding environmental DNA from fishes: detection of more than 230 subtropical marine species. Royal Society open science, 2(7), 150088. https://doi.org/10.1098/rsos.150088

We chose default rCRUX parameters for get_blast_seeds() of percent coverage of 70, percent identity of 70, evalue 3e+7, and max number of blast alignments = '100000000' and for blast_seeds() of coverage of 70, percent identity of 70, evalue 3e+7, rank of genus, and max number of blast alignments = '10000000'.

Explore the historical Whois records related to upc-barcode.com (Domain). Get insights into ownership history and changes over time.

The Drug Listing Act of 1972 requires registered drug establishments to provide the Food and Drug Administration (FDA) with a current list of all drugs manufactured, prepared, propagated, compounded, or processed by it for commercial distribution. (See Section 510 of the Federal Food, Drug, and Cosmetic Act (Act) (21 U.S.C. � 360)). Drug products are identified and reported using a unique, three-segment number, called the National Drug Code (NDC), which serves as a universal product identifier for drugs. FDA publishes the listed NDC numbers and the information submitted as part of the listing information in the NDC Directory which is updated daily.

Taxonomic identification of biological specimens based on DNA sequence information (a.k.a. DNA barcoding) is becoming increasingly common in biodiversity science. Although several methods have been proposed, many of them are not universally applicable due to the need for prerequisite phylogenetic/machine-learning analyses, the need for huge computational resources, or the lack of a firm theoretical background. Here, we propose two new computational methods of DNA barcoding and show a benchmark for bacterial/archeal 16S, animal COX1, fungal internal transcribed spacer, and three plant chloroplast (rbcL, matK, and trnH-psbA) barcode loci that can be used to compare the performance of existing and new methods. The benchmark was performed under two alternative situations: query sequences were available in the corresponding reference sequence databases in one, but were not available in the other. In the former situation, the commonly used “1-nearest-neighbor” (1-NN) method, which assigns the taxonomic information of the most similar sequences in a reference database (i.e., BLAST-top-hit reference sequence) to a query, displays the highest rate and highest precision of successful taxonomic identification. However, in the latter situation, the 1-NN method produced extremely high rates of misidentification for all the barcode loci examined. In contrast, one of our new methods, the query-centric auto-k-nearest-neighbor (QCauto) method, consistently produced low rates of misidentification for all the loci examined in both situations. These results indicate that the 1-NN method is most suitable if the reference sequences of all potentially observable species are available in databases; otherwise, the QCauto method returns the most reliable identification results. The benchmark results also indicated that the taxon coverage of reference sequences is far from complete for genus or species level identification in all the barcode loci examined. Therefore, we need to accelerate the registration of reference barcode sequences to apply high-throughput DNA barcoding to genus or species level identification in biodiversity research.