2017
DOI: 10.3390/app7030213
|View full text |Cite
|
Sign up to set email alerts
|

A Nondestructive Real-Time Detection Method of Total Viable Count in Pork by Hyperspectral Imaging Technique

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 (P… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

0
18
0

Year Published

2017
2017
2023
2023

Publication Types

Select...
9
1

Relationship

1
9

Authors

Journals

citations
Cited by 27 publications
(18 citation statements)
references
References 10 publications
0
18
0
Order By: Relevance
“…Peng et al [21] investigated the TVC in beef during every 12 h storage at 8°C by using hyperspectral imaging at 400-1100 nm region, combined with Multiple Linear Regression (MLR) algorithm, and obtained good prediction performance with correlation coefficient (R) of 0.97 and standard error of 0.30 log 10 CFU/g. In the same wavelength region, Zheng et al [22] established a support machine regression (SVR) model to predict the TVC on the pork surface and achieved a better result. Barbin et al [23] investigated the potential of NIR hyperspectral imaging (900-1700 nm) for psychrotrophic plate count (PPC) in chilled pork during 21 days' storage.…”
Section: Introductionmentioning
confidence: 99%
“…Peng et al [21] investigated the TVC in beef during every 12 h storage at 8°C by using hyperspectral imaging at 400-1100 nm region, combined with Multiple Linear Regression (MLR) algorithm, and obtained good prediction performance with correlation coefficient (R) of 0.97 and standard error of 0.30 log 10 CFU/g. In the same wavelength region, Zheng et al [22] established a support machine regression (SVR) model to predict the TVC on the pork surface and achieved a better result. Barbin et al [23] investigated the potential of NIR hyperspectral imaging (900-1700 nm) for psychrotrophic plate count (PPC) in chilled pork during 21 days' storage.…”
Section: Introductionmentioning
confidence: 99%
“…Hyperspectral imaging has been used to detect various compositions of samples as a rapid and nondestructive technique, such as herbal medicine [ 6 , 7 ], food [ 8 , 9 , 10 , 11 ], and agriculture [ 12 , 13 ]. Beyond building detection models, hyperspectral imaging has also been used to obtain prediction visualization images to explore the composition distribution within and among samples [ 14 , 15 , 16 ].…”
Section: Introductionmentioning
confidence: 99%
“…The potential of reflectance spectra for bacterial contamination measurement has also been explored, and satisfactory results were obtained. Zheng et al conducted a study to build a precise and simple model with low cost for TVC of pork [31]. Fifty chilled pork samples were collected and stored in a refrigerator at 4°C.…”
Section: Bacterial Contamination Detection Using Hsimentioning
confidence: 99%