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Fast detection and visualization of minced lamb meat adulteration using NIR hyperspectral imaging and multivariate
Mohammed Kamruzzaman1, Da-Wen Sun, Gamal ElMasry
1Food Refrigeration and Computerised Food Technology (FRCFT), School of Biosystems Engineering, University College Dublin, National University of Ireland, Agriculture and Food Science Centre, Belfield, Dublin 4, Ireland.
This study introduces a new near-infrared hyperspectral imaging technique for non-destructively detecting and quantifying pork adulteration in minced lamb. The developed method offers a rapid, low-cost alternative to traditional testing for meat authenticity.
Area of Science:
- Food Science and Technology
- Analytical Chemistry
- Spectroscopy
Background:
- Traditional methods for detecting meat adulteration are often time-consuming and destructive.
- There is a need for rapid, non-destructive techniques to ensure the authenticity of minced lamb meat.
Purpose of the Study:
- To develop and optimize a near-infrared (NIR) hyperspectral imaging technique for detecting and quantifying pork adulteration in minced lamb.
- To establish a rapid, non-destructive analytical method for minced lamb meat quality control.
Main Methods:
- Near-infrared (NIR) hyperspectral imaging was employed to analyze minced lamb samples adulterated with pork.
- Principal Component Analysis (PCA) was used for initial data exploration.
- Partial Least Squares Regression (PLSR) and Multiple Linear Regression (MLR) models were developed to predict adulteration levels.
- Wavelength selection was performed using weighted regression coefficients (Bw).
Main Results:
- A PLSR model achieved a high coefficient of determination (R(2)(cv) = 0.99) and low RMSECV (1.37%) using the full spectral range.
- An MLR model using four selected wavelengths (940, 1067, 1144, 1217 nm) also demonstrated excellent predictive performance (R(2)(cv) = 0.98, RMSECV = 1.45%).
- Prediction maps visualized the spatial distribution of adulteration in the samples.
Conclusions:
- NIR hyperspectral imaging is a viable and effective technique for the rapid, non-destructive detection and quantification of pork adulteration in minced lamb.
- The developed MLR model provides a cost-effective and efficient alternative to traditional analytical methods for ensuring meat authenticity.
