Quantitative detection of binary and ternary adulteration of minced beef meat with pork and duck meat by NIR combined with chemometrics. (July 2020)
- Record Type:
- Journal Article
- Title:
- Quantitative detection of binary and ternary adulteration of minced beef meat with pork and duck meat by NIR combined with chemometrics. (July 2020)
- Main Title:
- Quantitative detection of binary and ternary adulteration of minced beef meat with pork and duck meat by NIR combined with chemometrics
- Authors:
- Leng, Tuo
Li, Feng
Xiong, Luoan
Xiong, Qian
Zhu, Mengting
Chen, Yi - Abstract:
- Abstract: This study described a rapid and non-destructive method by near-infrared (NIR) technology (12, 500-5400 cm −1 ) for the detection of pork and duck meat in minced beef. Chemometric techniques were used for adulteration detection and adulterant level prediction. Discriminant Analysis (DA) and Partial Least Squares (PLS) models were optimized by selecting appropriate spectral wavelengths and using different spectral pretreatments. The DA model with selected wavelength and with (none preprocess methods) achieved the best results with classification rates at 100% and 91.5% for binary and ternary system, respectively. The optimal PLS models with full-wavelength for predicting adulterant levels gained correlation coefficient Rp of 95.80% and 95.69%, and the root-mean-square error of prediction (RMSEP) of 7.27 and 9.27 for the binary and tenary samples respectively. The results of this paper allowed that NIR technology is not only suitable for the binary adulteration system of minced beef, but also the ternary system. Highlights: NIR combined with Chemometrics to detect adulteration of beef rapidly. Wavelength selection and data preprocessing were explored for model optimizing. Not only suitable for the binary adulteration system, but also the ternary system. This method is faster and easier than traditional methods.
- Is Part Of:
- Food control. Volume 113(2020)
- Journal:
- Food control
- Issue:
- Volume 113(2020)
- Issue Display:
- Volume 113, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 113
- Issue:
- 2020
- Issue Sort Value:
- 2020-0113-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-07
- Subjects:
- Meat adulteration -- Beef -- Binary -- Ternary -- NIR spectroscopy -- Chemometrics
Food -- Quality -- Periodicals
Food -- Analysis -- Periodicals
Food handling -- Periodicals
Food industry and trade -- Quality control -- Periodicals
Aliments -- Industrie et commerce -- Qualité -- Contrôle -- Périodiques
Aliments -- Qualité -- Périodiques
Aliments -- Analyse -- Périodiques
Hygiène alimentaire -- Périodiques
Food -- Analysis
Food handling
Food -- Quality
Periodicals
Electronic journals
664.07 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09567135 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.foodcont.2020.107203 ↗
- Languages:
- English
- ISSNs:
- 0956-7135
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3977.291500
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
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