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

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 periods, 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 R C of 0.98 and RMSEC of 0.35 log 10 CFU/g in calibration set, and R P of 0.98 and RMSEP of 0.44 log 10 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.

Hyperspectral imaging for one-step growth simulation of Brochothrix thermosphacta in chilled beef during storage

“…The data gained by Model II and III may be inaccurate after the bacterial contents reached 8-9 (lg (CFU/g)). Simultaneously, the minimum bacterial loads detected by HSI was 3-4 (lg (CFU/g)), according to the previous reports [53][54][55] .…”

Meat 4.0: Principles and Applications of Industry 4.0 Technologies in the Meat Industry

“…Specifically, this methodology has been widely studied in poultry meat since it is an IR 4.0 tool that permits the elimination of faecal material contaminated carcasses [105], thus preventing the proliferation of bacteria such as Salmonella, Campylobacter, and Escherichia coli. Furthermore, in poultry products, microbial contaminations related to foodborne illnesses (such as Enterobacteriaceae, Salmonella, Campylobacter, Escherichia coli, and Pseudomonas) can be predicted with the use of hyperspectral imaging [106][107][108][109][110][111]. In the case of other meat matrices, hyperspectral images have also been employed in order to predict microbial contamination in real time.…”

Nondestructive determination of IMP content in chilled chicken based on hyperspectral data combined with chemometrics

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