Technology firm PerkinElmer introduced the DA 7350 instrument and Process Plus cloud-based software to provide continuous quality control for food and food ingredient manufacturing processes. The new solution is designed to enable food producers to increase efficiency and yield and improve margins by reducing waste, optimizing the use of expensive raw materials and improving product consistency. This innovation is part of PerkinElmer’s portfolio of quality and safety solutions across meat, dairy, seafood, produce, edible oils and cannabis.

Leveraging camera and NIR technology and featuring a smaller, lighter design than previous generation offerings, the PerkinElmer DA 7350 solution measures key production line parameters such as moisture, protein, fat and ash content, in real-time. The Process Plus software continuously feeds this measurement information to factory control systems, control room monitors or any plant-approved, web-enabled device (including mobile phones) so that ongoing manual or automated adjustments can be made to drying, conditioning/hydration or stream blend ratios as needed.

“Consumers demand a certain level of quality and consistency from their favorite food brands and producers want to create products that meet specifications, productivity goals and consumer expectations at the same time,” said Greg Sears, vice president and general manager, Food, PerkinElmer. “Our DA 7350 solution helps food manufacturers get the right information at the right time so they can make necessary course corrections and keep efficiency, quality and cost savings on track.”

For customers with complex, high throughput processing environments, the technology can be applied across multiple production lines to simultaneously, yet independently, measure and control quality parameters across a plant’s production lines. Data from the DA 7350 instrument is also compatible with PerkinElmer’s bench-top DA 7250 NIR analyzer -- bringing together production information gathered in various ways to help provide a more complete picture of the processing environment.