The agriculture sector is facing an enormous task—to increase food production to support the planet’s explosive population growth. At the same time, the industry must address a growing number of food safety challenges associated with pathogenic bacteria like Salmonella and E. coli. These challenges are driving the need for and adoption of innovative solutions at the farm level, including remote sensing and robotics. However, utilizing these new technologies effectively requires the ability to clearly interpret and analyze the vast quantities of data being collected, which comes with its own set of challenges.
AgriNerds, one of 14 startups enabled in FY 2018–19 by technology developed at UC Davis, is helping farmers harness the power of these technologies by providing a data management and visualization tool to integrate and interpret this information in real time. Their Web-based application uses both machine learning and decision sciences to help farmers optimize production yield, food safety and operational efficiency.
The technology is based on the work of Maurice Pitesky from the UC Davis School of Veterinary Medicine-Cooperative Extension and former students Roberto Carrasco, Joseph Gendreau and Tristan Bond.
The team received proof-of-concept funding from the UC Davis Data, Informatics and Application Launch (DIAL™) Grant program from the Office of Research to develop and test the initial versions of the product. The startup is working with several poultry companies to further optimize their custom machine learning algorithms in order to expand operations throughout the agricultural sector.