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Reference-free spectroscopic determination of fat and protein in milk in the visible and near infrared region below 1000 nm using spatially resolved diffuse reflectance fiber probe. / Bogomolov, Andrey; Belikova, Valeria; Galyanin, Vladislav; Melenteva, Anastasiia; Meyer, Hans.

в: Talanta, Том 167, 15.05.2017, стр. 563-572.

Результаты исследований: Научные публикации в периодических изданияхстатьяРецензирование

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@article{39a6b3e706cc4b9780b8ce2ced8a693b,
title = "Reference-free spectroscopic determination of fat and protein in milk in the visible and near infrared region below 1000 nm using spatially resolved diffuse reflectance fiber probe",
abstract = "New technique of diffuse reflectance spectroscopic analysis of milk fat and total protein content in the visible (Vis) and adjacent near infrared (NIR) region (400–995 nm) has been developed and tested. Sample analysis was performed through a probe having eight 200-µm fiber channels forming a linear array. One of the end fibers was used for the illumination and other seven – for the spectroscopic detection of diffusely reflected light. One of the detection channels was used as a reference to normalize the spectra and to convert them into absorbance-equivalent units. The method has been tested experimentally using a designed sample set prepared from industrial raw milk standards with widely varying fat and protein content. To increase the modelling robustness all milk samples were measured in three different homogenization degrees. Comprehensive data analysis has shown the advantage of combining both spectral and spatial resolution in the same measurement and revealed the most relevant channels and wavelength regions. The modelling accuracy was further improved using joint variable selection and preprocessing optimization method based on the genetic algorithm. The root mean-square errors of different validation methods were below 0.10% for fat and below 0.08% for total protein content. Based on the present experimental data, it was computationally shown that the full-spectrum analysis in this method can be replaced by a sensor measurement at several specific wavelengths, for instance, using light-emitting diodes (LEDs) for illumination. Two optimal sensor configurations have been suggested: with nine LEDs for the analysis of fat and seven – for protein content. Both simulated sensors exhibit nearly the same component determination accuracy as corresponding full-spectrum analysis.",
keywords = "Milk nutrient analysis, Optical sensor, Space-resolved measurement, Three-way PLS regression, Variable selection, Vis/NIR spectroscopy",
author = "Andrey Bogomolov and Valeria Belikova and Vladislav Galyanin and Anastasiia Melenteva and Hans Meyer",
year = "2017",
month = may,
day = "15",
doi = "10.1016/j.talanta.2017.02.047",
language = "English",
volume = "167",
pages = "563--572",
journal = "Talanta",
issn = "0039-9140",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Reference-free spectroscopic determination of fat and protein in milk in the visible and near infrared region below 1000 nm using spatially resolved diffuse reflectance fiber probe

AU - Bogomolov, Andrey

AU - Belikova, Valeria

AU - Galyanin, Vladislav

AU - Melenteva, Anastasiia

AU - Meyer, Hans

PY - 2017/5/15

Y1 - 2017/5/15

N2 - New technique of diffuse reflectance spectroscopic analysis of milk fat and total protein content in the visible (Vis) and adjacent near infrared (NIR) region (400–995 nm) has been developed and tested. Sample analysis was performed through a probe having eight 200-µm fiber channels forming a linear array. One of the end fibers was used for the illumination and other seven – for the spectroscopic detection of diffusely reflected light. One of the detection channels was used as a reference to normalize the spectra and to convert them into absorbance-equivalent units. The method has been tested experimentally using a designed sample set prepared from industrial raw milk standards with widely varying fat and protein content. To increase the modelling robustness all milk samples were measured in three different homogenization degrees. Comprehensive data analysis has shown the advantage of combining both spectral and spatial resolution in the same measurement and revealed the most relevant channels and wavelength regions. The modelling accuracy was further improved using joint variable selection and preprocessing optimization method based on the genetic algorithm. The root mean-square errors of different validation methods were below 0.10% for fat and below 0.08% for total protein content. Based on the present experimental data, it was computationally shown that the full-spectrum analysis in this method can be replaced by a sensor measurement at several specific wavelengths, for instance, using light-emitting diodes (LEDs) for illumination. Two optimal sensor configurations have been suggested: with nine LEDs for the analysis of fat and seven – for protein content. Both simulated sensors exhibit nearly the same component determination accuracy as corresponding full-spectrum analysis.

AB - New technique of diffuse reflectance spectroscopic analysis of milk fat and total protein content in the visible (Vis) and adjacent near infrared (NIR) region (400–995 nm) has been developed and tested. Sample analysis was performed through a probe having eight 200-µm fiber channels forming a linear array. One of the end fibers was used for the illumination and other seven – for the spectroscopic detection of diffusely reflected light. One of the detection channels was used as a reference to normalize the spectra and to convert them into absorbance-equivalent units. The method has been tested experimentally using a designed sample set prepared from industrial raw milk standards with widely varying fat and protein content. To increase the modelling robustness all milk samples were measured in three different homogenization degrees. Comprehensive data analysis has shown the advantage of combining both spectral and spatial resolution in the same measurement and revealed the most relevant channels and wavelength regions. The modelling accuracy was further improved using joint variable selection and preprocessing optimization method based on the genetic algorithm. The root mean-square errors of different validation methods were below 0.10% for fat and below 0.08% for total protein content. Based on the present experimental data, it was computationally shown that the full-spectrum analysis in this method can be replaced by a sensor measurement at several specific wavelengths, for instance, using light-emitting diodes (LEDs) for illumination. Two optimal sensor configurations have been suggested: with nine LEDs for the analysis of fat and seven – for protein content. Both simulated sensors exhibit nearly the same component determination accuracy as corresponding full-spectrum analysis.

KW - Milk nutrient analysis

KW - Optical sensor

KW - Space-resolved measurement

KW - Three-way PLS regression

KW - Variable selection

KW - Vis/NIR spectroscopy

UR - http://www.scopus.com/inward/record.url?scp=85014449938&partnerID=8YFLogxK

U2 - 10.1016/j.talanta.2017.02.047

DO - 10.1016/j.talanta.2017.02.047

M3 - Article

C2 - 28340762

AN - SCOPUS:85014449938

VL - 167

SP - 563

EP - 572

JO - Talanta

JF - Talanta

SN - 0039-9140

ER -

ID: 41677555