Prediction of Aerobic Plate Count on Beef Surface Using Fluorescence Fingerprint

Yoshimura, Masashi; Sugiyama, Junichi; Tsuta, Mizuki; Fujita, Kaori; Shibata, Mario; Kokawa, Mito; Oshita, Seiichi; Oto, N.

doi:10.1007/s11947-013-1167-8

Cited by 31 publications

(6 citation statements)

References 29 publications

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“…The FFs were preprocessed following the procedure of Yoshimura et al (2014). First, data whose excitation wavelength was longer than that of the emission wavelength was removed, since fluorescence is defined as light emission with longer wavelengths than the excitation light.…”

Section: Pls Model For Prediction Of Maturation Indices Three Partialmentioning

confidence: 99%

Measuring Cheese Maturation with the Fluorescence Fingerprint

Kokawa

Ikegami

Chiba

et al. 2015

FSTR

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Section: Pls Model For Prediction Of Maturation Indices Three Partialmentioning

confidence: 99%

Measuring Cheese Maturation with the Fluorescence Fingerprint

Kokawa

Ikegami

Chiba

et al. 2015

FSTR

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“…Furthermore, the regions where the regression coefficient of the PLSR model was relatively higher were consistent with those of the FF peaks of 5 intrinsic fluorophores of tryptophan, NADPH, vitamin A, porphyrins, and flavins. It was suggested that changes in the autofluorescence of these intrinsic fluorophores because of the metabolism of bacterial flora on meat were reflected in the PLSR model for predicting APC from the FF dataset (Yoshimura and others ). Therefore, FF spectroscopy coupled with multivariate analysis was considered to be applicable to the nondestructive determination of APC on the surface of lean beef.…”

Section: Applications Of Spectroscopic Techniquesmentioning

confidence: 99%

Recent Applications of Spectroscopic and Hyperspectral Imaging Techniques with Chemometric Analysis for Rapid Inspection of Microbial Spoilage in Muscle Foods

Cheng

Sun

2015

Comp Rev Food Sci Food Safe

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Muscle food is one of the most perishable food products because of its vulnerability to microbial spoilage, which can result in critical food safety problems. Traditional techniques for detection and evaluation of microbial spoilage in muscle foods are tedious, laborious, destructive, and time-consuming. In recent years, spectroscopic and imaging technologies have shown great potentials for the assessment of food quality and safety due to their nondestructive, noninvasive, cost-effective, and rapid responsive nature. This review focuses on the applications of several valuable spectroscopic techniques including visible and near-infrared spectroscopy, Fourier transform infrared spectroscopy, fluorescence spectroscopy, Raman spectroscopy, and hyperspectral imaging for the rapid and nondestructive detection of microbial spoilage in common muscle foods such as meat, poultry, fish, and related products. Combined with chemometric analysis, such as spectral preprocessing and modeling methods, these potential technologies have been successfully developed for the determination of total viable count, aerobic plate count, Enterobacteriaceae, Pseudomonas, Escherichia coli, and lactic acid bacteria loads in muscle foods. Moreover, the advantages and disadvantages of these techniques are discussed and some perspectives about future trends are also presented.

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“…Chemometric, multivariate, and multiway data analysis of the EEM can resolve the complex signal from an intact food sample into its principal emission components; properly validated, such signals can shed information on specific food quality and safety characteristics [44,45]. For example, changes in tryptophan and NADPH fluorescence can signal microbial growth and spoilage of food products [46,47]. In a similar manner, hyperspectral imaging integrates multispectral analysis of intrinsic fluorophores with imaging techniques providing spatial and spectral data on food samples [45,48 ,49] giving results that can be translated sensitively in real time into food safety and food quality measurements.…”

Section: Autofluorescence and Hyperspectral Imagingmentioning

confidence: 99%