LW-NIR hyperspectral imaging for rapid prediction of TVC in chicken flesh

Hui Wang,Zhuangli Kang,Rongguang Zhu,Hanjun Ma,Mingming Zhu,Shengming Zhao,Fusheng Chen,Zhengrong Wang,Hongju He

doi:10.25165/j.ijabe.20191203.4444

Abstract

Total viable count (TVC) is often used as an important indicator for chicken freshness evaluation. In this study, 112 fresh chicken flesh samples were acquired after slaughtered and their hyperspectral images were collected in the LW-NIR (900-1700 nm) range. The full LW-NIR spectra (486 wavebands) within the images were extracted and applied to related to reference TVC values measured in different storage period, using partial least squares regression (PLSR) algorithm, resulting in high correlation coefficients (R) and low root mean square errors (RMSE), for either raw spectra or pretreatment spectra. By using regression coefficients (RC) method, 20, 18, 17 and 20 optimal wavebands were respectively selected from raw spectra, baseline correction (BC) spectra, Savitzky-Golay convolution smoothing (SGCS) spectra and standard normal variate (SNV) spectra and applied for the optimization of original full waveband PLSR model. By comparison, RC-PLSR model based on the SGCS spectra showed a better performance in TVC prediction with RC of 0.98 and RMSEC of 0.35 log10 CFU/g in calibration set, and RP of 0.98 and RMSEP of 0.44 log10 CFU/g in prediction set. At last, by transferring the best RC-PLSR model, the dynamic TVC change during the storage was visualized by color maps to indicate the TVC spoilage degree. The overall study revealed that LW-NIR hyperspectral imaging combined with PLSR could be used to predict the freshness of chicken flesh. Keywords: hyperspectral imaging, chicken, TVC, partial least square regression (PLSR) DOI: 10.25165/j.ijabe.20191203.4444 Citation: H Wang, H J He, H J Ma, F S Chen, Z L Kang, M M Zhu, et al. LW-NIR hyperspectral imaging for rapid prediction of TVC in chicken flesh. Int J Agric & Biol Eng, 2019; 12(3): 180–186.

Highlights

Nowadays, China is the largest country for meat production and consumption, and meat has become one of the must-have foods on the table[1]
Bacteria and the total viable bacteria count (TVC) value always exceeds the standard value of 6 log10 CFU/g in 3-5 d at 4°C storage[5,6], in this situation, the chicken is not safe for consumption as it would greatly endanger consumers’ health
TVC is often used as an indicator for freshness evaluation and is commonly determined by standard plate colony count[7,8], but this method is time-consuming, laborious, destructive and inefficient

Summary

Introduction

China is the largest country for meat production and consumption, and meat has become one of the must-have foods on the table[1]. Hyperspectral imaging technology combining spectroscopy and computer vision technology can simultaneously provide the spatial information and spectral information of the tested samples. It has been widely used for the quality evaluation in meat in terms of chemical quality such as fat, protein, moisture[11,12,13], freshness indexes including total volatile basic nitrogen (TVB-N)[14], thiobarbituric acid reactive substances (TBARS)[15], biogenic amine index (BAI)[16], and physical properties such as color[17], tenderness[18], springness[19] and water-holding capacity[20]

Objectives

Methods

Results

Conclusion