Non-destructive prediction of thiobarbituricacid reactive substances (TBARS) value for freshness evaluation of chicken meat using hyperspectral imaging

Xiong, Zhenjie; Sun, Da‐Wen; Pu, Hongbin; Xie, Anjian; Han, Zhong; Luo, Man

doi:10.1016/j.foodchem.2015.01.116

Cited by 204 publications

(69 citation statements)

References 66 publications

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“…These changes were possibly attributed to the variations of physical properties and chemical components of pork muscle induced by microbial spoilage and enzyme activities during cold storage. This phenomenon was in agreement with that observed by Xiong, Sun, Pu, Xie, Han and Luo (2015), who applied HSI in monitoring the lipid oxidation in chicken meat. From the above analysis it can be noted that the most obvious difference among the mean reflectance spectra obtained at different storage time was the magnitude, and the changes of the shape were complicated.…”

Section: Reference Hplc Analysissupporting

confidence: 93%

Integration of spectral and textural data for enhancing hyperspectral prediction of K value in pork meat

Cheng

Sun

et al. 2016

LWT - Food Science and Technology

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100

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Section: Reference Hplc Analysissupporting

confidence: 93%

Integration of spectral and textural data for enhancing hyperspectral prediction of K value in pork meat

Cheng

Sun

et al. 2016

LWT - Food Science and Technology

Self Cite

100

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“…So, selection of optimal wavenumbers is significant for building a simplified model [20, 25]. Interval partial least squares (iPLS) regression is a wavenumber selection method proposed by Norgaard [20], which can extract the spectral wavenumbers highly related to the chemical structure, thus achieving the objective to improve the stability of the prediction model and increase the interpretability of the relationship between the spectral response and chemical structure [20].…”

Section: Methodsmentioning

confidence: 99%

Optical Determination of Lead Chrome Green in Green Tea by Fourier Transform Infrared (FT-IR) Transmission Spectroscopy

Liu

Zhang

et al. 2017

PLoS ONE

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The potential of Fourier transform infrared (FT-IR) transmission spectroscopy for determination of lead chrome green in green tea was investigated based on chemometric methods. Firstly, the qualitative analysis of lead chrome green in tea was performed based on partial least squares discriminant analysis (PLS-DA), and the correct rate of classification was 100%. And then, a hybrid method of interval partial least squares (iPLS) regression and successive projections algorithm (SPA) was proposed to select characteristic wavenumbers for the quantitative analysis of lead chrome green in green tea, and 19 wavenumbers were obtained finally. Among these wavenumbers, 1384 (C = C), 1456, 1438, 1419(C = N), and 1506 (CNH) cm-1 were the characteristic wavenumbers of lead chrome green. Then, these 19 wavenumbers were used to build determination models. The best model was achieved by least squares support vector machine (LS-SVM)algorithm with high coefficient of determination and low root-mean square error of prediction set (R2p = 0.864 and RMSEP = 0.291). All these results indicated the feasibility of IR spectra for detecting lead chrome green in green tea.

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“…Wu et al, [41] have applied Partial least squares regression (PLSR) to create a prediction model in pork meat exposed to freeze-thawed processes with correlation coefficient of prediction of 0.81 and root mean square error of 0.33. A comparable analytical procedure has been applied by Xionq et al, [42] with regression coefficients in prediction (Rp) of 0.944 and root mean squared errors estimated by prediction (RMSEP) of 0.081. Li et al [17] have examined meat pork quality to distinguish normal from pale, soft and exudative meat (PSE).…”

Section: Application Of Nir Spectroscopy Andmentioning

confidence: 99%

Аdvanced computer-based approaches for food quality evaluation: updated review

Veleva¹

2017

TJS

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From the point of view of their usage biological resources must be managed in a sustainable manner in order to uphold the social, economic and environmental functions and to contribute to the peoples' livelihoods. Within the food production and processing industry requirements are focused on improvement of quality control of technologies by incorporating them into precise, computer-based, low-cost methods. The present work is a review of different approaches and tools for computer aided methods for food quality evaluation. Powerful techniques based on Near Infrared Spectroscopy and Aquaphotomics are presented.

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Non-destructive prediction of thiobarbituricacid reactive substances (TBARS) value for freshness evaluation of chicken meat using hyperspectral imaging

Cited by 204 publications

References 66 publications

Integration of spectral and textural data for enhancing hyperspectral prediction of K value in pork meat

Integration of spectral and textural data for enhancing hyperspectral prediction of K value in pork meat

Optical Determination of Lead Chrome Green in Green Tea by Fourier Transform Infrared (FT-IR) Transmission Spectroscopy

Аdvanced computer-based approaches for food quality evaluation: updated review

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