Application of Hyperspectral imaging to predict the pH, intramuscular fatty acid content and composition of lamb M . longissimus lumborum at 24 h post mortem

Combination of spectra and image information of hyperspectral imaging data for fast prediction of lipid oxidation attributes in pork meat

“…Hyperspectral imaging (HSI) is another relatively novel and dominant analytical tool that combines information of image and spectroscopy into one system to predict and visualize quality attributes associated with food products. HSI has been used extensively for food quality and safety analysis including the prediction and visualization of deteriorating indexes of chicken and sausage (Siripatrawan, ; Xiong et al, ), tenderness, color, and pH (Craigie et al, ; Liu, Pu, Sun, Wang, & Zeng, ; Wu, Sun, & He, ), as well as microbiological attributes (He & Sun, ; Huang, Zhao, et al, ; Siripatrawan & Makino, ). Previous studies demonstrated the feasibility of using HSI to accurately predict TBARS content in meat and fish (Aheto et al, ; Cheng, Sun, Pu, Wang, & Chen, ; Kamani, Safari, Mortazavi, Mehraban Sang Atash, & Azghadi, ; Wu, Song, Qiu, & He, ).…”

Hyperspectral Imaging in Tandem with R Statistics and Image Processing for Detection and Visualization of pH in Japanese Big Sausages Under Different Storage Conditions

“…As aforementioned, PLSR can establish a mathematical relationship between a set of independent variables and a set of dependent variables, describing any latent relationship among the spectral variables. Although there are several modelling methods, such as LS‐SVM, BPANN, MLR, using for HSI data analysis, PLSR is comprehensively and effectively applied to handle multicollinear data (Craigie and other ). Kamruzzaman and others () elaborated that achieved encouraging outcomes with both PLSR and LS‐SVM ( R p 2 : 0.95 and 0.97, respectively) when predicting moisture of beef, lamb and pork, though LS‐SVM had slightly better performance.…”

“…Additionally, it can efficiently detect products’ adulteration. Plenty of studies have addressed the application of HSI to detect pH of chicken (Jia and others ), beef (Nubiato and others ; Crichton and others ), lamb (Craigie and others ), and pork (Liu and others ), however, pH prediction in cooked sausages using hyperspectral imaging with the range of 380 to 1000 nm has not been exploited yet. Unlike the aforementioned whole pieces of meat, sausages experienced mincing, mixture and stuffing operation, they are more readily spoiled during handling and so pH is an important parameter to evaluate the safety of the sausages.…”

Chemometrics and hyperspectral imaging applied to assessment of chemical, textural and structural characteristics of meat

“…of each pixel at each band of the hyperspectral data. (Craigie et al, 2017). Ten different methods were evaluated including: Partial least squares regression (PLSR) with latent variables selection based on the adjusted wold's R criterion with thresholds on unity (AW) and 0.99 (AW0.99) (Li et al, 2002), Gaussian process regression (GPR) (Chen, Morris, et al, 2007;Gibson et al, 2012;Verrelst et al, 2013), Support…”