Non-destructive determination of chemical and microbial spoilage indicators of beef for freshness evaluation using front-face synchronous fluorescence spectroscopy

Huan Liu; Zengtao Ji; Xinliang Liu; Ce Shi; Xinting Yang

doi:10.1016/j.foodchem.2020.126628

Non-destructive determination of chemical and microbial spoilage indicators of beef for freshness evaluation using front-face synchronous fluorescence spectroscopy

Food Chem. 2020 Aug 15:321:126628. doi: 10.1016/j.foodchem.2020.126628. Epub 2020 Mar 17.

Authors

Huan Liu¹, Zengtao Ji¹, Xinliang Liu², Ce Shi¹, Xinting Yang³

Affiliations

¹ Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China; National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; National Engineering Laboratory for Agri-product Quality Traceability, Beijing 100097, China.
² Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University, Beijing 100048, China.
³ Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China; National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; National Engineering Laboratory for Agri-product Quality Traceability, Beijing 100097, China. Electronic address: xintingyang@nercita.org.cn.

PMID: 32259731
DOI: 10.1016/j.foodchem.2020.126628

Abstract

We investigated the potential of front-face synchronous fluorescence spectroscopy (△λ = 75 nm) to non-destructively evaluate beef freshness and quality decline during chilled storage. The total volatile basic nitrogen (TVB-N), thiobarbituric acid reactive substances (TBARS) and total viable count (TVC) values were used as standard freshness indicators. The fluorescent substances, including amino acids, collagen and conjugated Schiff bases, were highly correlated with the chemical and microbial deterioration of the beef. Quantitative models for simultaneously predicting the three freshness indicators were built combined with partial least squares (PLS) algorithm and showed good reliability. For TVB-N and TBARS values, R_c² and R_p² were both above 0.900, and for TVC values R_c² and R_p² were 0.912 and 0.871, respectively. The qualitative model established by partial least squares discriminant analysis (PLS-DA) algorithm could accurately classify beef samples as fresh, acceptable or spoiled. The accuracy of the calibration and validation sets were 92.54% and 86.96%, respectively.

Keywords: Beef; Classification; Conjugated Schiff bases; Freshness indicators; Front-face synchronous fluorescence spectroscopy.

MeSH terms

Algorithms
Animals
Calibration
Cattle
Discriminant Analysis
Least-Squares Analysis
Nitrogen / chemistry
Red Meat / analysis*
Red Meat / microbiology
Reproducibility of Results
Spectrometry, Fluorescence
Thiobarbituric Acid Reactive Substances / chemistry

Substances

Thiobarbituric Acid Reactive Substances
Nitrogen