Sensor Applications

Sensor Applications is sponsored by USDA NIFA. Supports the development and application of sensor technologies in agriculture to enhance productivity, food safety, and environmental monitoring.

Sensor Applications | NIFA The lifecycle of grants and cooperative agreements consists of four phases: Pre-Award, Award, Post-Award, and Close Out. The National Institute of Food and Agriculture is committed to serving its stakeholders, Congress, and the public by using new technologies to advance greater openness.

The Data Gateway enables users to find funding data, metrics, and information about research, education, and Extension projects that have received grant awards from NIFA. This website houses a large volume of supporting materials. In this section, you can search the wide range of documents, videos, and other resources.

Veterinary Services Grant Program Technical Assistance Webinar NIFA staff will hold a Technical Assistance Webinar to discuss the Veterinary Services Grant Program (VSGP) Notice of Funding Opportunity. The National Institute of Food and Agriculture provides leadership and funding for programs that advance agriculture-related sciences. Sensor Technologies are integrated within most programs in NIFA.

Nearly all aspects of production, processing, monitoring, and management in agricultural and food systems (including forestry and natural resources) involve measurement of product/resource attributes (such as quantity, quality, size, condition) or their environment (such as food impurities, or agricultural/forest air, water, and soils). Rural economies and their infrastructures are also affected.

Their biometric activities include inspection, monitoring, tracking, inventory, and valuation. The number of measurement variables—and their measurement frequency and level of detail—demands automated, high-resolution, and rapid technologies. In the interests of efficiency and wise stewardship, increasingly voluminous data are collected that must be further analyzed, interpreted, and applied to support intelligent decision making.

Advances in biometrology and information technologies are required to address our need for timely and reliable information that has temporal and spatial relevance. Food safety and quality represent one of the greatest public issues/concerns nationwide. Safety and quality depend on inspection and monitoring methods that can detect contaminants and discriminate defective (or poor quality) products.

Whereas manual, microscopic, or bio-assay inspections cannot be performed quickly and accurately on 100 percent of any food product, sensor and instrumentation technologies currently under development and testing promise to offer inspection capabilities that are accurate, fast (in real time), and consistent.

These technologies can range from detecting: internal bruising of apples to 10 cells of Listeria (a particularly virulent food pathogen) to insect infestations in a ship's cargo of grain. Environmental quality and resource conservation are other areas where sensor-based monitoring can be helpful.

For example, animal feeding operators can use air quality monitoring around confined animals to keep ammonia or odor emission within acceptable limits. Water monitoring for nitrogen and phosphorus runoff from agricultural lands can help regulate freshwater algae blooms and coastal-zone hypoxia.

An ability to quickly and accurately measure carbon sequestration in soils can facilitate more widespread application of a carbon-credit and trading marketplace. Soil water sensors can be used stand-alone or in synergy with water balance models to provide trusted recommendations on irrigation timing and proper water amounts through field trials with farmer-cooperators.

The key is accurate interpretation of sensor readings and what the models are telling us in terms of crop water use. User-friendly apps can be programmed to provide these recommendations. Adaptive learning can be used to add trust and improve the chances for adoption of irrigation scheduling methods that use these beneficial technologies to conserve water while maintaining crop yield and quality.

Food animal sensors can be used to track movement, detect temperature, predict health status, and predict productivity in live animals. The sensor data can be combined with sophisticated data science analytics such as artificial intelligence (AI) to inform management decisions needed to produce healthier and more productive animals, ultimately increasing sustainability.

These types of measurement activities create special problems, however, because the elements being measured are molecular and they need to be quantified over large land areas. Nevertheless, these applications are scientifically possible; it remains to develop the engineering and technology capability to make them economical and practical.

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