USDA Announces Grant Program for National Animal Identification Trials and Projects

The USDA's Animal and Plant Health Inspection Service announced on Nov. 9 it will award $3 million in cooperative agreements to states and tribes for conducting research to develop or test potential solutions for animal identification and automated data collection in support of the National Animal Identification System (NAIS).

Applicants are encouraged to propose research or field trial projects to:

  • Enhance the effectiveness of collecting animal identification data in typical production, market, and abattoir environments;
  • Establish identity validation when official identification devices are lost, removed, or malfunction;
  • Conduct economic assessments of animal identification systems and technologies in typical production, market, and abattoir environments; and
  • Evaluate emerging animal identification technologies with advanced data collection systems to ascertain the adaptability of the technology for use in NAIS.

Funding application packages are available on the APHIS web site at The deadline for application is Dec. 30. Applications can be submitted electronically to or through Paper applications should be mailed to the Animal and Plant Health Inspection Service, c/o Neil Hammerschmidt, 4700 River Road, Unit 200, Room 4B-07.5, Riverdale, Md. 20737. Any awarded funds will be available for cooperator expenditures incurred within 12 months from the date of signature for the notice of award.

Projects applicable to any livestock or animal industry associated with NAIS are eligible for funding. Collaboration with private companies, producer organizations, colleges and universities, or other research organization is strongly encouraged.

Implementation of NAIS will support state and federal animal disease monitoring and surveillance through the rapid tracing of infected and exposed animals during animal disease outbreaks. Additional benefits of NAIS include enhanced consumer confidence in the health of U.S. livestock and

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