Abstract
A nondestructive method was developed for assessing total viable count (TVC) in pork during refrigerated storage by using hyperspectral imaging technique in this study. The hyperspectral images in the visible/near-infrared (VIS/NIR) region of 400–1100 nm were acquired for fifty pork samples, and their VIS/NIR diffuse reflectance spectra were extracted from the images. The reference values of TVC in pork samples were determined by classical microbiological plating method. Both partial least square regression (PLSR) model and support vector machine regression model (SVR) of TVC were built for comparative analysis to achieve better results. Different transformation methods and filtering methods were applied to improve the models. The results show that both the optimized PLSR model and SVR model can predict the TVC very well, while the SVR model based on second derivation was better, which achieved with RP (correlation coefficient of prediction set) = 0.94 and SEP (standard error of prediction set) = 0.4570 log CFU/g in the prediction set. An image processing algorithm was then developed to transfer the prediction model to every pixel of the image of the entire sample; the visualizing map of TVC would be displayed in real-time during the detection process due to the simplicity of the model. The results demonstrated that hyperspectral imaging is a potential reliable approach for non-destructive and real-time prediction of TVC in pork.
Highlights
As one of the most important animal foods on the dining table, pork is rich in protein, fat, carbohydrate, calcium, iron, phosphorus, and other ingredients
partial least square regression (PLSR) model and Support vector machine regression (SVR) model can predict the total viable count (TVC) very well, while the SVR model based on second derivation was better, which achieved with RP = 0.94 and SEP = 0.4570 log colony-forming units (CFU)/g in the prediction set
The results demonstrated that hyperspectral imaging is a potential reliable approach for non-destructive and real-time prediction of TVC in pork
Summary
As one of the most important animal foods on the dining table, pork is rich in protein, fat, carbohydrate, calcium, iron, phosphorus, and other ingredients. The total viable bacteria count (TVC) is a key indicator to reflect the quality and safety of pork, and meat which TVC exceeds the standard value (6 log CFU/g in China) [1] would greatly endanger consumers’ healthy. The typical detection method of TVC is plate count method (ISO, 2003) [2], which is the national standard method of China, but it is too time-consuming and destructive, with tedious steps and delayed result. Bio-electrochemistry is a method of determining the production or consumption of a microorganism by an electrode, thereby providing a signal for analysis [4]. This method can greatly reduce the time consumption, which is still
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