A central hub for digital tools that improve dairy processing and products
Digital tools, including data analysis and prediction tools, are increasingly applied across the food industry to drive innovation and continuous improvement in areas ranging from product development to process optimization and food safety and sustainability. The US dairy industry currently lacks a unified platform to drive the development and implementation of digital tools and risks a further innovation deficit unless efforts are implemented to drive digital innovation in the dairy industry. Digital innovation needs are substantial and range from the development and validation of appropriate models to digital dairy workforce training and development of a digital innovation ecosystem. While this area requires substantial investments, smaller focused projects are needed and have the potential to serve as nucleation points for larger initiatives and investments. In this platform, we provide access to existing digital tools for various dairy products.
Extend fluid milk shelf-life
The goal of this collection of models is to 1) predict microbial spoilage in fluid milk due to raw milk contamination by psychrotolerant spore-formers and post-pasteurization contamination (PPC) by Gram-negative bacteria, 2) identify key quality management practices that influence contamination of fluid milk, and 3) optimize benefit-cost ratio for the existing intervention strategies.
Prevent late-blowing defects (LBD) in cheese
The goal of this model is to 1) predict the occurrence of LBD in Gouda cheese by stimulating the growth of Clostridium tyrobutyricum over cheese aging, 2) evaluate various intervention strategies to prevent LBD, and 3) identify the key knowledge gap in understanding LBD.
Inhibit mold and yeast spoilage in yogurt
The goal of this collection of models is to 1) predict the mold and yeast growth in yogurt, 2) identify various key factors that can facilitate the spoilage, and 3) evaluate different biopreservatives to prevent yogurt spoilage.