Perten Instruments have developed global calibrations for the DA 7250 NIR analyzer for analysis of fat, moisture, protein, collagen, salt and ash in meats and meat products. The calibrations are universal and can be used on a very wide range of samples, from raw meat to in-process products and finished meat products.
The content of fat and other constituents varies significantly in raw meat, depending on the cut and which animal it comes from. Rapid compositional analysis of meat products is thus of great benefit.
- When purchasing and processing meat it's of great benefit to be able to quickly analyze the meat to determine whether it meets specifications, and to segregate by quality for optimal use.
- In many production processes rapid analysis makes it possible to get closer to specifications and reach a more consistent end-product by modifying the exact blend of meats based on fat content.
- And last but not least, rapid verification of finished product compliance with nutritional declarations can avoid costly take-backs and customer claims.
With Near Infrared (NIR) technology it just takes a few seconds to analyze for fat, moisture, protein, collagen, salt and ash, rather than the several hours required for traditional chemical analysis. But using NIR for meat product analysis has often required cumbersome calibration work and the use of different calibrations for each type of meat product. To make it easier to use NIR, Perten set out to develop global and universal calibrations. Several thousands of samples of meat and meat product were collected throughout the world on multiple DA 7250 instruments. The samples covered a very large variation - from raw beef, poultry and pork meat, to in-process products, and finished meat products such as raw ham, frankfurters, salami, cooked ham and meat balls.
Several calibration techniques where evaluated in the calibration development, including Artficial Neural Networks (ANN), and Honigs Regression (HR), a proprietary regression technique developed by Perten Instruments. HR is a self-learning algorithm combining high accuracy with robustness and ability to include great variability in the calibrations. The best accuracy and robustness was achieved using Honigs Regression, providing high accuracy on all kinds of meat products.
Using global combined calibrations models makes the DA 7250 a "plug & play" solution for all kinds of meat products and makes the instrument easy to set up and maintain.
An application note which describes the meat products application in more detail is available for download.
Learn more about the DA 7250.