MENU

Precision pays. Experience leading accuracy in meat analysis

Get precision you can trust with the AOAC-approved FoodScan™ 2 . Discover how scanning a larger sample volume leads to significantly improved repeatability for optimal quality control and exceptional precision in meat production.

In the fast-paced world of meat production, accuracy, efficiency, and quality control are paramount. With the AOAC approved FoodScan™ 2 offering fast and easy analysis of meat products with exceptional accuracy, you get all the information you need to succeed with your process and final product control. In this article, we dive into the advantages driving the industry leading accuracy of FoodScan 2, with a focus on how scanning a larger sample volume can result in significantly improved repeatability.

 

 

Deeper penetration with NIR transmission

Near-Infrared (NIR) technology has been a staple in the food industry for decades. Its ability to rapidly analyze samples has transformed quality control processes. But FoodScan 2 takes NIR to new heights covering a much larger share of the sample than other NIR solutions on the market, offering the best accuracy in meat analysis. So, how is this possible?

 

Unlike other NIR meat analyzers, FoodScan 2 utilizes NIR transmission rather than NIR reflectance.  With NIR reflectance, the light bounces off the surface providing an assessment of the outer layer of the sample. In contrast, NIR transmission provides an assessment of the entire sample with a sample penetration of up to 20 mm.

 

Deeper penetration combined with an increase in sample points means that NIR transmission is less sensitive to inhomogeneous meat samples and requires less homogenization time compared to a NIR reflectance analyzer. Similarly, the FoodScan 2 is less sensitive to surface effects such as fat and moisture, which can skew results. With NIR transmission, FoodScan 2 minimizes these interferences, allowing meat producers to confidently assess quality without worrying about surface variations. 

 

Value graph

 

NIR transmission:

Light passes through 1-2 cm of the sample.
Deep penetration ensures high repeatability and accuracy.
Requires less homogenization.

 

 

NIR reflectance:

Light penetrates the upper few millimeters of the sample.
Requires thorough, time-consuming homogenization to achieve good accuracy. 
Challenged by high fat content samples.

 

 

 

Repeatability and accuracy of FoodScan 2 versus a NIR reflectance solution

In a comparative study conducted by FOSS, the accuracy of NIR transmission and NIR reflectance was investigated. 30 ground meat samples were analyzed using each method respectively. Following NIR analysis, the samples were analysed for total fat by an accredited reference lab.

 

The repeatability is found by repacking the same sample several times and measuring it. The repack error of the NIR reflectance analyzer is higher than the FoodScan 2 analyzer by a factor of more than 5-6. The repack error is an issue that cannot be resolved.

 

 

Sample representation is key

The major difference between the two ways of applying NIR is the sample representation. The FoodScan 2 scans approximately 50% of the sample content while a NIR reflectance analyzer scans the sample surface amounting to approximately 1% of the entire sample. Consequently, the FoodScan 2 NIR transmission method delivers significantly better repeatability and accuracy in meat analysis compared to NIR reflectance solutions.

 

 

 

 

Graph

 

 

The above illustration shows the meat height and the sample volume measured using a FoodScan 2 (transmission) and a NIR reflectance analyser respectively. When a larger volume is scanned with FoodScan 2, the results show a significantly improved repeatability compared to analysis using the NIR reflectance method. 

 

Ultimately, this means that the FoodScan 2 delivers a better accuracy for homogenized ground meat samples.

 

 

The power of Artificial Neural Networks (ANN)

Another powerful driver behind the leading accuracy of FoodScan 2, is the use of ANN. An Artificial Neural Network (ANN) is a ready-to-use calibration model that is based on the neural structure of the human brain, learning from vast datasets, and adapting to variations. 

 

This means that operators can cover a large range of parameters without having to switch between individual analytics packages when testing different products and fat ranges. 

 

ANN calibrations save time and make life easier for the operator.  Real-time predictions and less need to verify calibrations mean that both validation time and the risk of operator error is minimized. When many products and parameters are involved, this aspect can save significant costs compared to using other calibration methods.

 

 

AOAC Approval: A Seal of Excellence

The crowning benefit of FoodScan 2 is the AOAC seal of approval. 

 

The AOAC set rigorous standards for analytical methods, and this acknowledgement ensures that meat producers can trust FoodScan 2 results for regulatory compliance, quality control, and confident decision-making. FoodScan 2 is the only NIR analyser that is AOAC approved for analysis of meat products and is also approved by the Australian Quarantine and inspection Service (AQIS) and Polska Norma in Poland. 

 

Thanks to the power of NIR transmission, ANN calibrations, and AOAC approval, FoodScan 2 offers unprecedented levels of accuracy and efficiency that have earned it a reputation as the industry leading solution for meat analysis in today’s fast-paced world of meat production. 

 

 

 

 

Are you ready to benefit from industry leading accuracy in meat analysis?

Get in touch with our specialists to discuss how the best accuracy in meat analysis can make a difference to your business. Let's talk

FoodScan™ 2 Meat Analyser

FoodScan 2 is the gold standard for fast, accurate and easy analysis of meat and processed meat products. It can be used in all stages of meat production – from checking incoming raw material to final product control.

 

Read more

Stay informed - with insights and news from FOSS

Stay ahead of your competitors! Get fresh knowledge and valuable insights about trends, challenges and opportunities related to analytics in your business, directly in your inbox.

Something went wrong!

Sorry, we were not able to send your form.
back to top icon
The content is hosted on YouTube.com (Third Party). By showing the content you accept the use of Marketing Cookies on Fossanalytics.com. You can change the settings anytime. To learn more, visit our Cookie Policy.