Yuxia Fan

Quantitative analysis and detection of adulteration in pork using near-infrared spectroscopy

Authenticity is an important food quality criterion. Rapid methods for confirming authenticity or detecting adulteration are increasingly demanded by food processors and consumers. Near infrared (NIR) spectroscopy has been used to detect economic adulteration in pork . Pork samples were adulterated with liver and chicken in 10% increments. Prediction and quantitative analysis were done using raw data and pretreatment spectra. The optimal prediction result was achieved by partial least aquares(PLS) regression with standard normal variate(SNV) pretreatment for pork adulterated with liver samples, and the correlation coefficient(R value), the root mean square error of calibration(RMSEC) and the root mean square error of prediction (RMSEP) were 0.97706, 0.0673 and 0.0732, respectively. The best model for pork meat adulterated with chicken samples was obtained by PLS with the raw spectra, and the correlation coefficient(R value), RMSEP and RMSEC were 0.98614, 0.0525, and 0.122, respectively. The result shows that NIR technology can be successfully used to detect adulteration in pork meat adulterated with liver and chicken.

Predicting of intramuscular fat (IMF) content in pork using near infrared spectroscopy and multivariate analysis

ABSTRACT The potential of near infrared (NIR) spectroscopy combined with chemometrics methods was studied to rapidly detect intramuscular fat (IMF) content in pork. Near infrared diffuse reflectance spectra were recorded both with an FT-NIR and a USB4000 spectrometer. The data analysis was compared on different sample preparation, spectral range and spectra pretreatment. According to calibration statistics, best calibration for IMF showed R2cal of 0.94, R2val of 0.92, RMSEC of 0.233, RMSEP of 0.462 and RPD of 2.29. The prediction of IMF content for minced samples was more accurate than that for intact samples. The spectra obtained using FT-NIR contained much information correlating to the IMF content than the Vis-NIR spectra of USB4000. The results showed that NIR spectroscopy technique can be used to determine the IMF content in pork as a rapid, convenient, and feasible analysis tool.

On-line determination of pork color and intramuscular fat by computer vision

In this study, the application potential of computer vision in on-line determination of CIE L*a*b* and content of intramuscular fat (IMF) of pork was evaluated. Images of pork chop from 211 pig carcasses were captured while samples were on a conveyor belt at the speed of 0.25 m•s-1 to simulate the on-line environment. CIE L*a*b* and IMF content were measured with colorimeter and chemical extractor as reference. The KSW algorithm combined with region selection was employed in eliminating the surrounding fat of longissimus dorsi muscle (MLD). RGB values of the pork were counted and five methods were applied for transforming RGB values to CIE L*a*b* values. The region growing algorithm with multiple seed points was applied to mask out the IMF pixels within the intensity corrected images. The performances of the proposed algorithms were verified by comparing the measured reference values and the quality characteristics obtained by image processing. MLD region of six samples could not be identified using the KSW algorithm. Intensity nonuniformity of pork surface in the image can be eliminated efficiently, and IMF region of three corrected images failed to be extracted. Given considerable variety of color and complexity of the pork surface, CIE L*, a* and b* color of MLD could be predicted with correlation coefficients of 0.84, 0.54 and 0.47 respectively, and IMF content could be determined with a correlation coefficient more than 0.70. The study demonstrated that it is feasible to evaluate CIE L*a*b* values and IMF content on-line using computer vision.