Raw Beef Patty Analysis Using Near-Infrared Hyperspectral Imaging: Identification of Four Patty Categories
Kiah Edwards1, Louwrens C Hoffman2,3, Marena Manley1
1Department of Food Science, Stellenbosch University, Private Bag X1, Matieland, Stellenbosch 7602, South Africa.
Sensors (Basel, Switzerland)
|January 21, 2023
Summary
Near-infrared hyperspectral imaging (NIR-HSI) accurately identifies beef patty types with over 97% accuracy. This rapid, non-destructive method combats processed meat fraud and ensures consumer protection.
Area of Science:
- Food Science
- Analytical Chemistry
- Agricultural Engineering
Background:
- South African regulations mandate strict classification and labeling of raw beef patties to prevent fraud.
- Current authentication methods for processed meat are destructive, time-consuming, labor-intensive, and expensive.
Purpose of the Study:
- To investigate near-infrared hyperspectral imaging (NIR-HSI) as a rapid, non-destructive alternative for authenticating beef patties.
- To assess the capability of NIR-HSI in distinguishing between four distinct categories of beef patties.
Main Methods:
- Acquisition of hyperspectral images using a HySpex SWIR-384 system (952-2517 nm).
- Analysis of spectral data using image analysis, multivariate techniques, and machine learning algorithms.
- Testing on 800 beef patties across four categories: premium, regular, value, and budget.
Main Results:
- NIR-HSI achieved classification accuracies of ≥97% for all four beef patty categories.
- The system demonstrated a high capacity for rapid and reliable identification.
- Successful differentiation between premium, regular, value, and budget beef patties.
Conclusions:
- NIR-HSI is a viable, accurate, and reliable technology for authenticating processed beef patties.
- This method offers a significant improvement over current destructive and time-consuming techniques.
- The study supports enhanced authenticity and fair trade in the processed meat industry, both locally and internationally.
