Issue 18, 2015

Hyperspectral imaging in tandem with multivariate analysis and image processing for non-invasive detection and visualization of pork adulteration in minced beef

Abstract

Pork adulteration in minced beef was detected for the first time using a hyperspectral imaging (HIS) technique. Minced beef samples were adulterated with minced pork in the range of 2–50% (w/w) at approximately 2% intervals. Images were acquired using a visible near-infrared hyperspectral imaging (VNIR-HSI) system and their spectral data were extracted. Several data pre-treatments and different linear multivariate analyses, namely partial least squares regression (PLSR), principal component regression (PCR), and multiple linear regression (MLR), were investigated to determine the predictive ability of VNIR-HSI in detecting pork meat adulteration in minced beef. PLSR had a better performance than PCR for predicting pork adulteration in minced beef. Only four wavelengths centered at 430, 605, 665, and 705 nm were selected as the important wavelengths to build the MLR model for visualizing the distribution of adulteration. The results confirm that HSI can be used to provide a rapid, low cost, and nondestructive testing technique for detection of adulteration in minced meat.

Graphical abstract: Hyperspectral imaging in tandem with multivariate analysis and image processing for non-invasive detection and visualization of pork adulteration in minced beef

Article information

Article type
Paper
Submitted
25 jun. 2015
Accepted
17 jul. 2015
First published
22 jul. 2015

Anal. Methods, 2015,7, 7496-7502

Author version available

Hyperspectral imaging in tandem with multivariate analysis and image processing for non-invasive detection and visualization of pork adulteration in minced beef

M. Kamruzzaman, Y. Makino and S. Oshita, Anal. Methods, 2015, 7, 7496 DOI: 10.1039/C5AY01617G

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