Design and evaluation of a miniature milk quality detection system based on UV/Vis spectroscopy

Yang, Biao; Liang, Wenting; Zhou, Yihang; Zhu, Xinhua

doi:10.1016/j.jfca.2021.104341

Cited by 11 publications

(5 citation statements)

References 32 publications

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“…Compared with the reported results of other techniques for predicting lactose content in cow's milk, the minimum RMSEP (0.29 g kg −1 ) obtained based on VIP-SVR in this study is smaller than the RMSEP (0.90 g kg −1 ) obtained by diffuse reflectance NIR spectroscopy in the wavelength range 851-1649 nm, 36 as well as the RMSEP (1.30 g kg −1 for non-homogeneous cow's milk and 0.90 g kg −1 for high-pressure homogeneous cow's milk) based on UV-visible spectroscopy, 37 and less than the RMSEP (0.88 g kg −1 ) based on Fourier transform mid-infrared spectroscopy. 38 To the best of our knowledge, the RMSEP (0.29 g kg −1 ) obtained in the present study for the prediction of milk's lactose based on the DS combined with the VIP-SVR model is the best prediction available, and the samples do not require additional high-pressure homogenization.…”

Section: Advantages Of Dielectric Spectroscopy For Quantitative Predi...contrasting

confidence: 70%

Hydration dominates dielectric spectroscopy‐based high accuracy quantification of lactose content in cow's milk

et al. 2023

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BACKGROUND Lactose is a critical factor in the quality of milk and dairy products. Achieving high accuracy and rapid detection of lactose content in cow's milk remains a challenge. Dielectric spectroscopy has emerged as a promising tool for detecting food components. We explored the effect of lactose content on the dielectric spectra of cow's milk and we propose a rapid analytical method for the quantitative determination of lactose content in cow's milk with high accuracy based on dielectric spectra. RESULTS We obtained the dielectric spectra of 316 cow's milk samples in the frequency range 20–4500 MHz and noticed a strong negative correlation between the lactose content and the value of the dielectric loss factor (ε″) below 1500 MHz. Lactose does not affect cow's milk dielectric properties by excluded volume effect, but dominates the effect on the dielectric properties of cow's milk by hydration. The support vector regression model based on the variable importance in projection has the best prediction performance for lactose content. Its root‐mean‐square error of prediction set and residual prediction deviation is 0.29 g kg−1 and 6.968, respectively, and its prediction performance is better than that of the currently reported near‐infrared (NIR) method and other methods. CONCLUSION Despite the weak polarity of lactose molecules, its hydration is a significant factor affecting the dielectric properties of milk. The present study provides a basis for high accuracy and rapid quantitative detection of lactose in cow's milk based on dielectric spectra. © 2023 Society of Chemical Industry.

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Section: Advantages Of Dielectric Spectroscopy For Quantitative Predi...contrasting

confidence: 70%

Hydration dominates dielectric spectroscopy‐based high accuracy quantification of lactose content in cow's milk

et al. 2023

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“…Nowadays, a lot of research is being carried out to develop compact milk analyzers based on various physical principles [ 1 , 20 , 21 , 22 , 23 , 24 , 25 , 26 ]. Portable analyzers are designed to analyze milk for fat, protein, lactose, and other bulk components.…”

Section: Introductionmentioning

confidence: 99%

LED-Based Desktop Analyzer for Fat Content Determination in Milk

Surkova,

Shmakova,

Salukova

et al. 2023

Sensors

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In dairy, there is a growing request for laboratory analysis of the main nutrients in milk. High throughput of analysis, low cost, and portability are becoming critical factors to provide the necessary level of control in milk collection, processing, and sale. A portable desktop analyzer, including three light-emitting diodes (LEDs) in the visible light region, has been constructed and tested for the determination of fat content in homogenized and raw cow’s milk. The method is based on the concentration dependencies of light scattering by milk fat globules at three different wavelengths. Univariate and multivariate models were built and compared. The red channel has shown the best performance in prediction. However, the joint use of all three LED signals led to an improvement in the calibration model. The obtained preliminary results have shown that the developed LED-based technique can be sufficiently accurate for the analysis of milk fat content. The ways of its further development and improvement have been discussed.

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“…The visible and short-wave near-infrared (Vis/SW-NIR) region is the most promising for milk analysis [6][7][8][9] because it is possible to create easy-to-use and cost-effective devices that function in this spectral region consisting of light-emitting diodes (LED), optical fibers, 3D-printed parts, and photodetectors [10][11][12][13][14]. The possibility of using the 400-1100 nm region for the determination of fat and protein content has been shown in our previous work [9].…”

Section: Introductionmentioning

confidence: 99%