Near-Infrared Spectroscopy Technology in Food

Chen, Quansheng; Hao, Lin; Zhao, Jiewen

doi:10.1007/978-981-16-3360-7_2

Cited by 2 publications

(2 citation statements)

References 140 publications

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“…Another promising technique is NIR, which has been successful in the quality control of food and drug. As a non-destructive technique, NIR employs measurements of photon energy to obtain qualitative and quantitative information based on the interaction of the sample with NIR radiation [ 20 , 21 ]. It covers the wavelength range of 800–2500 nm and mainly reflects vibration information of hydrogen bonds in a molecular structure, such as carbon–hydrogen (C-H), oxygen–hydrogen (O-H), nitrogen–hydrogen (N-H) [ 22 , 23 ].…”

Section: Introductionmentioning

confidence: 99%

A Synergetic Strategy for Brand Characterization of Colla Corii Asini (Ejiao) by LIBS and NIR Combined with Partial Least Squares Discriminant Analysis

Xia

Che²,

et al. 2023

Molecules

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A synergetic strategy was proposed to address the critical issue in the brand characterization of Colla corii asini (Ejiao, CCA), a precious traditional Chinese medicine (TCM). In all brands of CCA, Dong’e Ejiao (DEEJ) is an intangible cultural heritage resource. Seventy-eight CCA samples (including forty DEEJ samples and thirty-eight samples from other different manufacturers) were detected by laser-induced breakdown spectroscopy (LIBS) and near-infrared spectroscopy (NIR). Partial least squares discriminant analysis (PLS-DA) models were built first considering individual techniques separately, and then fusing LIBS and NIR data at low-level. The statistical parameters including classification accuracy, sensitivity, and specificity were calculated to evaluate the PLS-DA model performance. The results demonstrated that two individual techniques show good classification performance, especially the NIR. The PLS-DA model with single NIR spectra pretreated by the multiplicative scatter correction (MSC) method was preferred as excellent discrimination. Though individual spectroscopic data obtained good classification performance. A data fusion strategy was also attempted to merge atomic and molecular information of CCA. Compared to a single data block, data fusion models with SNV and MSC pretreatment exhibited good predictive power with no misclassification. This study may provide a novel perspective to employ a comprehensive analytical approach to brand discrimination of CCA. The synergetic strategy based on LIBS together with NIR offers atomic and molecular information of CCA, which could be exemplary for future research on the rapid discrimination of TCM.

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Section: Introductionmentioning

confidence: 99%

A Synergetic Strategy for Brand Characterization of Colla Corii Asini (Ejiao) by LIBS and NIR Combined with Partial Least Squares Discriminant Analysis

Xia

Che²,

et al. 2023

Molecules

View full text Add to dashboard Cite

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“…By absorbing electromagnetic waves in the 780–2526 nm range, NIR provides information from molecular vibrations and combined overtones of chemical groups such as C-H, O-H, N-H and S-H, which can be analyzed by chemometrics to relate to target parameters for qualitative and quantitative evaluation [ 26 ], i.e., model establishment between NIR spectra and target parameters. NIR technology has been used for the quality evaluation in various foods in terms of physical, chemical, nutritional, textural and microbial properties, with good or satisfied and even excellent performance, indicating a great potential of NIR in food industrial application [ 27 , 28 ]. However, few studies on NIR technology for the quality evaluation of fruit peels have been reported, especially vitamin C in citrus peels.…”

Section: Introductionmentioning

confidence: 99%

Toward Achieving Rapid Estimation of Vitamin C in Citrus Peels by NIR Spectra Coupled with a Linear Algorithm

Zhang

Lin

et al. 2023

Molecules

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Citrus peels are rich in bioactive compounds such as vitamin C and extraction of vitamin C is a good strategy for citrus peel recycling. It is essential to evaluate the levels of vitamin C in citrus peels before reuse. In this study, a near-infrared (NIR)-based method was proposed to quantify the vitamin C content of citrus peels in a rapid way. The spectra of 249 citrus peels in the 912‒1667 nm range were acquired, preprocessed, and then related to measured vitamin C values using the linear partial least squares (PLS) algorithm, indicating that normalization correction (NC) was more suitable for spectral preprocessing and NC-PLS model built with full NC spectra (375 wavelengths) showed a better performance in predicting vitamin C. To accelerate the predictive process, wavelength selection was conducted, and 15 optimal wavelengths were finally selected from NC spectra using the stepwise regression (SR) method, to predict vitamin C using the multiple linear regression (MLR) algorithm. The results showed that SR-NC-MLR model had the best predictive ability with correlation coefficients (rP) of 0.949 and root mean square error (RMSEP) of 14.814 mg/100 mg in prediction set, comparable to the NC-PLS model in predicting vitamin C. External validation was implemented using 40 independent citrus peels samples to validate the suitability of the SR-NC-MLR model, obtaining a good correlation (R2 = 0.9558) between predicted and measured vitamin C contents. In conclusion, it was reasonable and feasible to achieve the rapid estimation of vitamin C in citrus peels using NIR spectra coupled with MLR algorithm.

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Near-Infrared Spectroscopy Technology in Food

Cited by 2 publications

References 140 publications

A Synergetic Strategy for Brand Characterization of Colla Corii Asini (Ejiao) by LIBS and NIR Combined with Partial Least Squares Discriminant Analysis

A Synergetic Strategy for Brand Characterization of Colla Corii Asini (Ejiao) by LIBS and NIR Combined with Partial Least Squares Discriminant Analysis

Toward Achieving Rapid Estimation of Vitamin C in Citrus Peels by NIR Spectra Coupled with a Linear Algorithm

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