Food processors chasing zero-defect production now have a new hardware option: KPM Analytics has launched the MCT700 Series, a family of near-infrared (NIR) sensors designed for continuous, non-contact, in-line measurement of moisture, fat/oil, product temperature, and — on the flagship MCT790 model — product color. The sensors install over conveyors, augers, and chutes and are built to handle the demanding environments typical of baked and fried snack lines, cracker and breakfast cereal production, and food ingredient processing.
The Product Family
The series comprises three models differentiated by environmental rating and measurement capability. The MCT790 is the most full-featured, adding color measurement to the standard parameter set and targeting hot, greasy, or wet production environments; it carries an IP69K-rated stainless-steel housing that withstands harsh chemical washdowns, plus an internal fan for thermal management. The MCT750 matches that IP69K rating and adds advanced cooling with a sapphire sensor window, but omits color measurement. The entry-level MCT700 is IP67-rated with a standard Kel-F sensor window for applications where color data is not required. All three models sample at up to 100 readings per second — a speed that allows quality analysis of segmented, discrete products like cookies and crackers moving at production pace.
Process Control Implications
The commercial case for in-line NIR in food manufacturing rests on replacing periodic, manual at-line sampling with continuous automated feedback. Real-time moisture and fat readings tied to automatic equipment adjustments — oven temperature, oil sprayer output — can compress the window between a process deviation and a corrective action from minutes to seconds. That responsiveness directly addresses two persistent cost drivers in snack and cereal production: over-application of costly ingredients like oil and seasoning, and finished-goods rework or destruction when product drifts out of spec.
"Continuous measurement enables rapid response to production issues, which supports the business objectives of increasing productivity and decreasing waste," said Chris Pike, Senior Director of Product Management at KPM Analytics.
For conveyor lines, each MCT700 Series unit can pair with a traversing frame to scan the full belt width. A move-and-park feature lets operators analyze individual product lanes independently — particularly useful on industrial ovens with multiple heating zones, where moisture gradients across the belt are a common quality challenge.
Operational Footprint
KPM Analytics positioned the series for multi-line standardization: all models are fully modular with field-replaceable components and share a common operating interface with prior MCT Series instruments. On-board diagnostics are designed to simplify troubleshooting without requiring instrumentation specialists on-site, a meaningful consideration for processors managing lean maintenance staffing. The sensors are available for order immediately through KPM Analytics.
For foodservice supply-chain operators and contract manufacturers supplying retail and institutional channels, the trend toward in-line quality verification aligns with tightening customer specifications and the increased audit scrutiny that large chain and foodservice distribution customers now routinely apply to supplier facilities. Sensor-generated production data also supports the traceability documentation increasingly required under FSMA and major retailer food-safety programs.
Written by Michael Politz, Author of Guide to Restaurant Success: The Proven Process for Starting Any Restaurant Business From Scratch to Success (ISBN: 978-1-119-66896-1), Founder of Food & Beverage Magazine, the leading online magazine and resource in the industry. Designer of the Bluetooth logo and recognized in Entrepreneur Magazine's "Top 40 Under 40" for founding American Wholesale Floral, Politz is also the Co-founder of the Proof Awards and the CPG Awards and a partner in numerous consumer brands across the food and beverage sector.
