Rapid detection of freshness of refrigerated grouper (Epinephelus coioides) ﬁllets by near-infrared spectroscopy and quality index method

Xicai Zhang; Wen bo Huang; Jing Xie

doi:10.6180/jase.202012_23(4).0016

Rapid detection of freshness of refrigerated grouper (Epinephelus coioides) ﬁllets by near-infrared spectroscopy and quality index method

Xicai Zhang ^1,2,3,4,5, Wen bo Huang ^1,2,3,4, and Jing Xie This email address is being protected from spambots. You need JavaScript enabled to view it. ^1,2,3,4

¹College of Food Science Technology, Shanghai Ocean University, Shanghai 201306, China
²Shanghai Engineering Research Center of Aquatic Product Processing and Preservation, Shanghai 201306, China
³Shanghai Professional Technology Service Platform on Cold Chain Equipment Performance and Energy Saving Evaluation, Shanghai 201306, China
⁴National Experimental Teaching Demonstration Center for Food Science and Engineering Shanghai Ocean University, Shanghai 201306, China
⁵Jingchu University of Technology, Jing men, 448000, China

Received: November 5, 2019
Accepted: July 24, 2020
Publication Date: December 1, 2020

Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Download Citation: ||https://doi.org/10.6180/jase.202012_23(4).0016

ABSTRACT

The rapid detection of the freshness of grouper fillets was obtained by establishing a quality index method (QIM) scheme and near-infrared analysis model. Between the QI score and storage time showed a linear relationship (QI = 1.179 × t –1.157, R² = 0.98) which indicates that shelf life of grouper fillets is 12 days under 4 ℃. Partial least squares (PLS) analysis showed the mean squared error between predict days and measure days was almost 1 day (MSE=0.984). Correlation analysis between QI value and freshness indices found that the QI score has a high correlation with total volatile base nitrogen (TVB-N). Partial least squares (PLS), principal component regression (PCR) and multiple linear regression (MLR) methods were used to establish near-infrared spectroscopy (NIRs) prediction models for TVB-N, various spectral pretreatment methods such as the first derivative (1st), vector normalization (SNV), and multi-scatter correction (MSC) have been adopted. The results showed that SNV combined with PLS had the best acceptable fitting accuracy and predictive ability, the coefficients of prediction (Rp) was 0.968 and root mean square error of prediction (RMSEP) was 1.381 for TVB-N. The total results reveal that the feasibility of using NIRS and QIM scheme to detect freshness in grouper fillets.

Keywords: Grouper (Epinephelus coioides); freshness evaluation; rapid detection; quality index method; near-infrared spectroscopy

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