Detection of adulteration with duck meat in minced lamb meat by using visible near-infrared hyperspectral imaging. (March 2019)

• Record Type: Journal Article
• Authors: Zheng, Xiaochun; Li, Yongyu; Wei, Wensong; Peng, Yankun
• Is Part Of: Meat science. Volume 149(2019)
• Page Start: 55
• Page End: 62
• Publication Date: 2019-03
• Subjects: Hyperspectral imaging -- Adulteration -- Minced lamb meat -- Duck meat -- PLSR; Meat -- Periodicals; Meat industry and trade -- Periodicals; Viande -- Périodiques; Viande -- Industrie -- Périodiques; Meat; Meat industry and trade; Periodicals; 641.36
• DOI: 10.1016/j.meatsci.2018.11.005
• Languages: English
• ISSNs: 0309-1740

Abstract

Abstract: This paper described a rapid and non-destructive method based on visible near-infrared (Vis-NIR) hyperspectral imaging system (400–1000 nm) for detection adulteration with duck meat in minced lamb. The multiple average of the reference spectral and a predicted relative spatial distribution coefficient were applied in this study to reduce the noise of the spectra. The PLSR model with selected wavelengths achieved better results than others with determination of coefficients (R 2 P ) of 0.98, and standard error of prediction (RMSEP) of 2.51%. And the prediction map of the duck minced in lamb meat was generated by applying the prediction model. The results of this study indicate the great potential of the hyperspectral technology applying to rapidly and accurately detect the meat adulteration in minced lamb meat. Highlights: Measured the adulteration of duck in minced lamb by using Visible Near-infrared hyperspectral imaging. Predicted relative spatial distribution coefficient were applied to improve SNR. Different methods are applied and compared to select the optimum wavelengths. Level of duck adulteration in minced lamb was visualized by transferring the optimized model. The coefficient of determination of prediction was above 0.99.