Temperature fluctuation during cold storage of meat products usually leads to undesirable microbial growths, which affect the overall product quality. In this study, a pushbroom hyperspectral imaging system in the near-infrared (NIR) range (900-1700 nm) as a rapid and non-destructive technique was exploited for determining the total viable count (TVC) and psychrotrophic plate count (PPC) in chilled pork during storage. Fresh pork samples from the longissimus dorsi muscle were obtained directly from a commercial slaughtering plant, and stored in the refrigerated temperatures at 0 degrees C and 4 degrees C for 21 days. Every 48 h, a NIR hyperspectral image in the reflectance mode was acquired directly for each sample. The TVC and PPC were determined simultaneously by classical microbiological plating methods and multivariate statistical models for predicting contamination and spoilage conditions in the samples were then developed. Partial least squares regression (PLS) was applied to fit the spectral information extracted from the samples to the logarithmic values of TVC and PPC. The best regressions were obtained with R-2 of 0.86 and 0.89 for log (NC) and log (PPC), respectively. The most important wavelengths were then selected for regression and for spatial visualization of contamination. Results are encouraging and show the promising potential of hyperspectral technology for detecting bacterial spoilage in pork and tracking the increase of microbial growth of chilled pork during storage at different temperatures. Industrial relevance: A novel method based on hyperspectral imaging technique has been successfully developed for determining the total viable count (TVC) and psychrotrophic plate count (PPC) in chilled pork during storage non-destructively for the meat industry. (C) 2012 Elsevier Ltd. All rights reserved.
机构:
Tshwane Univ Technol, Dept Pharmaceut Sci, Private Bag X680, ZA-0001 Pretoria, South AfricaTshwane Univ Technol, Dept Pharmaceut Sci, Private Bag X680, ZA-0001 Pretoria, South Africa
Sandasi, Maxleene
Chen, Weiyang
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Tshwane Univ Technol, Dept Pharmaceut Sci, Private Bag X680, ZA-0001 Pretoria, South AfricaTshwane Univ Technol, Dept Pharmaceut Sci, Private Bag X680, ZA-0001 Pretoria, South Africa
Chen, Weiyang
Vermaak, Ilze
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Tshwane Univ Technol, Dept Pharmaceut Sci, Private Bag X680, ZA-0001 Pretoria, South Africa
Tshwane Univ Technol, SAMRC Herbal Drugs Res Unit, Private Bag X680, ZA-0001 Pretoria, South AfricaTshwane Univ Technol, Dept Pharmaceut Sci, Private Bag X680, ZA-0001 Pretoria, South Africa
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S China Univ Technol, Coll Light Ind & Food Sci, Guangzhou 510641, Guangdong, Peoples R ChinaS China Univ Technol, Coll Light Ind & Food Sci, Guangzhou 510641, Guangdong, Peoples R China
Liu, Dan
Qu, Jiahuan
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S China Univ Technol, Coll Light Ind & Food Sci, Guangzhou 510641, Guangdong, Peoples R ChinaS China Univ Technol, Coll Light Ind & Food Sci, Guangzhou 510641, Guangdong, Peoples R China
Qu, Jiahuan
Sun, Da-Wen
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S China Univ Technol, Coll Light Ind & Food Sci, Guangzhou 510641, Guangdong, Peoples R China
Natl Univ Ireland Univ Coll Dublin, Agr & Food Sci Ctr, Dublin 4, IrelandS China Univ Technol, Coll Light Ind & Food Sci, Guangzhou 510641, Guangdong, Peoples R China
Sun, Da-Wen
Pu, Hongbin
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S China Univ Technol, Coll Light Ind & Food Sci, Guangzhou 510641, Guangdong, Peoples R ChinaS China Univ Technol, Coll Light Ind & Food Sci, Guangzhou 510641, Guangdong, Peoples R China
Pu, Hongbin
Zeng, Xin-An
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S China Univ Technol, Coll Light Ind & Food Sci, Guangzhou 510641, Guangdong, Peoples R ChinaS China Univ Technol, Coll Light Ind & Food Sci, Guangzhou 510641, Guangdong, Peoples R China