feedsensing

Feedsensing refers to the collection, monitoring, and analysis of data related to feed intake, feed quality, and feeding behavior in livestock and, in some contexts, aquaculture. The goal is to support precision feeding by aligning nutrient supply with animal needs, reducing waste, and improving welfare and productivity.

Core components include hardware such as load cells on feeders, RFID tags to identify animals, accelerometers or infrared sensors to capture feeding activity, cameras with computer vision to estimate intake, and spectroscopy or near-infrared sensors to assess feed composition and moisture. Data from these sensors is typically transmitted to farm management software or cloud platforms for processing. Analytics tools may compute metrics such as daily feed intake, feed on offer, feed disappearance, feeding rate, and feed conversion ratio, as well as detecting abnormal feeding patterns that may indicate illness or stress.

Applications include dairy, beef, poultry, and swine operations, where feedsensing supports adaptive feeding strategies, ration optimization, and monitoring of feed efficiency. It can also integrate with automated feeders and precision nutrition systems to adjust rations in real time.

Benefits and challenges: Benefits include reduced feed waste, lower production costs, improved growth performance, and early detection of health issues via changes in feeding behavior. Challenges include capital cost, sensor durability in farm environments, data integration and standardization, and the need for skilled personnel to configure and interpret analytics.