foodmetaFOOD METAENGINEERINGFOOD METAENGINEERING2949-6497All-Russian Dairy Research Institute10.37442/fme.2025.3.91foodmeta-91Research ArticleОригинальное эмпирическое исследованиеOriginal Empirical ResearchСравнение методов ИК- и Раман-спектроскопии для оценки структурных изменений в молоке при тепловой обработкеComparison of IR and Raman spectroscopy methods for assessing structural changes in milk during heat treatmenthttps://orcid.org/0000-0003-4779-1076БарковскаяИрина АлександровнаBarkovskayaIrina A.

Лаборатория технологий биотрансформации и консервирования 

Младший научный сотрудник

 

Junior Researcher of the Laboratory of Biotransformation and Preservation Technologies

i_barkovskaya@vnimi.orghttps://orcid.org/0000-0002-5875-9875ТуровскаяСветлана НиколаевнаTurovskayaSvetlana N.

Лаборатория технологий биотрансформации и консервирования 

Старший научный сотрудник

 

Senior Researcher of the Laboratory of Biotransformation and Preservation Technologies

s_turovskaya@vnimi.orghttps://orcid.org/0000-0002-9399-0984ИлларионоваЕлена ЕвгеньевнаIllarionovaElena E.

Лаборатория технологий биотрансформации и консервирования 

Научный сотрудник

 

Researcher of the Laboratory of Biotransformation and Preservation Technologies

e_illarionova@vnimi.orghttps://orcid.org/0009-0007-7848-4606ЯрышевВладислав ЮрьевичYaryshevVladislav Yu.

Лаборатория технологий биотрансформации и консервирования 

Младший научный сотрудник

 

Junior Researcher of the Laboratory of Biotransformation and Preservation Technologies

v_yaryshev@vnimi.orghttps://orcid.org/0000-0001-9300-3267БлиадзеВладимир ГеннадьевичBliadzeVladimir G.

Лаборатория технологий биотрансформации и консервирования 

Младший научный сотрудник

Junior Researcher of the Laboratory of Biotransformation and Preservation Technologies

v_bliadze@vnimi.orghttps://orcid.org/0000-0002-0913-5644КондратенкоВладимир ВладимировичKondratenkoVladimir V.

Лаборатория технологий биотрансформации и консервирования 

Заведующий лабораторией

Head of the laboratory of Biotransformation and Preservation Technologies

v_kondratenko@vnimi.orgФГАНУ "ВНИМИ"РоссияAll-Russian Dairy Research InstituteRussian Federation202530092025332138Copyright © Барковская И.А., Туровская С.Н., Илларионова Е.Е., Ярышев В.Ю., Блиадзе В.Г., Кондратенко В.В., 20252025Барковская И.А., Туровская С.Н., Илларионова Е.Е., Ярышев В.Ю., Блиадзе В.Г., Кондратенко В.В.Barkovskaya I.A., Turovskaya S.N., Illarionova E.E., Yaryshev V.Y., Bliadze V.G., Kondratenko V.V.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.fme-journal.org/jour/article/view/91Введение

Введение: Контроль качества молочной продукции требует быстрых, точных и несложных методов анализа. Широкое распространение имеет инфракрасная спектроскопия с использованием в большинстве случаев импортных приборов, что актуализирует задачу разработки российских аналогов и поиск альтернативных методов контроля. Одним их таких методов выступает рамановская спектроскопия, обладающая преимуществами: меньшей чувствительностью к водному фону образцов, высокой информативностью, возможностью перевода спектральных метрик в количественные. В России данный метод практически не применяется для анализа качества молока, что делает актуальным исследования по его адаптации и сравнительной оценке с традиционными подходами.

Цель

Цель: Сопоставление инфракрасной и рамановской спектроскопии в аспекте анализа обезжиренного пастеризованного молока, полученного при разных температурных нагрузках, и определение спектральных диапазонов, наиболее чувствительных к температуре для совершенствования методик контроля качества молочной продукции в российской практике.

Материалы и методы

Материалы и методы: Проводили снятие спектров образцов обезжиренного пастеризованного молока, полученных при нагреве до 70, 80 и 90°С и выдержке 30 секунд. Контроль – молоко, нагретое до 45°С. Использовали российское оборудование: инфракрасный спектрометр Инфраспек-1201 и рамановский спектрометр РС-ИК785. Спектры анализировали методом главных компонент.

Результаты

Результаты: Для инфракрасных спектров образцов зафиксировали изменения в областях амидов I-III (1640-1660 см-1, 1530-1550 см-1 и 1230-1300 см-1 соответственно), лактозы (1040-1150 см-1), липидо-белковых комплексов (2850-2950 см-1) и воды (3200-3400 см-1). Визуальные различия спектральных показателей были минимальны визуально и по показателю поглощения (отн.ед.). Метод главных компонент позволил выявить вклад перечисленных диапазонов волновых чисел в различия образцов. Рамановская спектроскопия зафиксировала ярко выраженные различия в зонах 280-520 см-1, 800-850 см-1, 1450 см-1, 1660 см-1 и 2850-2950 см-1, характеризующих основные компоненты молочной системы. Выявлена четкая тенденция снижения интенсивности характерных полос с повышением температуры обработки. Анализ главных компонент отразил вклад составных частей молока (белки, углеводы и липиды) в различия образцов.

Выводы

Выводы: Полученные данные свидетельствуют о более высокой чувствительности рамановской спектроскопии к выявлению трансформаций составных частей молока при температурном воздействии, в сравнении с инфракрасной спектроскопией. Результаты подтверждают перспективность использования российского рамановского спектрометра для оценки качества молочных продуктов.

Introduction

Introduction: Quality control of dairy products requires fast, accurate, and simple analytical methods. Infrared spectroscopy, often using imported instruments, is widely used, necessitating the development of Russian equivalents and the search for alternative control methods. One such method is Raman spectroscopy, which offers advantages such as lower sensitivity to water contamination in samples, high information yield, and the ability to convert spectral metrics into quantitative data. In Russia, this method is rarely used for milk quality analysis, making research into its adaptation and comparative evaluation with traditional approaches crucial.

Purpose

Purpose: A comparison of infrared and Raman spectroscopy in the analysis of skim pasteurized milk obtained under different temperature loads, and the determination of spectral ranges most sensitive to temperature for improving quality control methods for dairy products in Russian practice.

Materials and Methods

Materials and Methods: Spectra were recorded on samples of skim pasteurized milk heated to 70, 80, and 90°C and held for 30 seconds. Milk heated to 45°C served as a control. Russian equipment was used: an Infraspek-1201 infrared spectrometer and an RS-IK785 Raman spectrometer. The spectra were analyzed using principal component analysis.

Results

Results: For the infrared spectra of the samples, changes were recorded in the regions of amides I-III (1640-1660 cm-1, 1530-1550 cm-1 and 1230-1300 cm-1, respectively), lactose (1040-1150 cm-1), lipid-protein complexes (2850-2950 cm-1) and water (3200-3400 cm-1). Visual differences in the spectral parameters were minimal visually and in terms of absorption (relative units). The principal component analysis allowed us to identify the contribution of the listed wavenumber ranges to the differences between the samples. Raman spectroscopy recorded pronounced differences in the zones of 280-520 cm-1, 800-850 cm-1, 1450 cm-1, 1660 cm-1 and 2850-2950 cm-1, characterizing the main components of the dairy system. A clear trend of decreasing intensity of the characteristic bands with increasing processing temperature was revealed. Principal component analysis revealed the contribution of milk components (proteins, carbohydrates, and lipids) to the differences between the samples.

Conclusion

Conclusion: The obtained data demonstrate the higher sensitivity of Raman spectroscopy in detecting thermally induced transformations of milk components compared to infrared spectroscopy. The results confirm the potential of using the Russian Raman spectrometer for assessing the quality of dairy products.

рамановская спектроскопияИК-спектроскопиятермическая обработка молокаспектры молокаRaman spectroscopyIR spectroscopyheat treatment of milkmilk spectraФедерального государственного автономного научного учреждения «Всероссийский научно-исследовательский институт молочной промышленности»ReferencesАбдуллаева, Л. В., Бедретдинова, С. А. (2023). Аналитическая оценка системы подтверждения соответствия молока и молочной продукции обязательным требованиям. Food Metaengineering, 1(4). https://doi.org/10.37442/fme.2023.4.31Abdullaeva, L. V., & Bedretdinova, S. A. (2023). Analytical assessment of conformity system for milk and dairy products. Food Metaengineering, 1(4). (In Russ.) https://doi.org/10.37442/fme.2023.4.31Беляков, М. В., Самарин, Г. Н., Ефременков, И. Ю. (2024). Исследование скисания молока методом рамановского рассеяния. Техника и оборудование для села, (5), 40–44. https://doi.org/10.33267/2072-9642-2024-5-40-44Belyakov, M. V., Samarin, G. N., & Efremenkov, I. Yu. (2024). Study of milk souring by Raman scattering. Engineering for Rural Areas, (5), 40–44. (In Russ.) https://doi.org/10.33267/2072-9642-2024-5-40-44Галстян, А. Г., Петров, А. Н., Юрова, Е. А. и др. (2025). Киберфизические компоненты пищевой метаинженерии. Вестник РАН, (6), 77–84. https://doi.org/10.31857/S0869587325060099Galstyan, A. G., Petrov, A. N., Yurova, E. A., et al. (2025). Cyber-physical components of food meta-engineering. Herald of the Russian Academy of Sciences, (6), 77–84. (In Russ.) https://doi.org/10.31857/S0869587325060099Калугина, Д. Н., Юрова, Е. А. (2022). Обоснование определения индекса азота сывороточного белка для оценки белкового состава молока. Молочная промышленность, (7), 35–37. https://doi.org/10.31515/1019-8946-2022-07-35-37Kalugina, D. N., & Yurova, E. A. (2022). Justification of the whey-proteinКобзева, Т. В., Юрова, Е. А. (2016). Оценка показателей качества и идентификационных характеристик сухого молока. Молочная промышленность, (3), 32–35.nitrogen index for estimation of milk protein composition. Dairy Industry, (7), 35–37. (In Russ.) https://doi.org/10.31515/1019-8946-2022-07-35-37Петров, А. Н., Галстян, А. Г., Радаева, И. А., Туровская, С. Н., Илларионова, Е. Е., Семипятный, В. К. и др. (2017). Показатели качества сгущённого молока: российские и международные приоритеты. Foods and Raw Materials, 5(2), 151–161. https://doi.org/10.21603/2308-4057-2017-2-151-161Kobzeva, T. V., & Yurova, E. A. (2016). Quality and identification characteristics of milk powder. Dairy Industry, (3), 32–35. (In Russ.)Радаева, И. А., Червецов, В. В., Галстян, А. Г., Туровская, С. Н., Илларионова, Е. Е.; Петров, А. Н.(2016). Межгосударственный стандарт на сухое молоко. Молочная промышленность, (3), 36–38.Petrov, A. N., Galstyan, A. G., Radaeva, I. A., et al. (2017). Indicators of quality of canned milk: Russian and international priorities. Foods and Raw Materials, 5(2), 151–161. https://doi.org/10.21603/2308-4057-2017-2-151-161Самарин, Г. Н.; Беляков, М. В. (2024). Оптическая спектральная диагностика казеина. Известия вузов. Пищевая технология, (1), 112–116. https://doi.org/10.26297/0579-3009.2024.1.18Radaeva, I. A., Chervetsov, V. V., Galstyan, A. G., et al. (2016). Interstate standard for milk powder. Dairy Industry, (3), 36–38. (In Russ.)Харитонов, В. Д., Юрова, Е. А., Чигасов, А. И. (2012). Спектральный анализ в ближней ИК-области. Молочная промышленность, (2), 55–56.Samarin, G. N., & Belyakov, M. V. (2024). Optical spectral diagnostics of casein. Proceedings of Higher Education Institutions. Food Technology, (1), 112–116. (In Russ.) https://doi.org/10.26297/0579-3009.2024.1.18Хуршудян, С. А., Галстян, А. Г. (2018). Качество пищевых продуктов. Термины, определения и противоречия. Контроль качества продукции, (1), 48–49.Харитонов, В. Д., Юрова, Е. А., Чигасов, А. И. (2012). Спектральный анализ в ближней ИК-области. Молочная промышленность, (2), 55–56.Юрова, Е. А., Фильчакова, С. А. (2021). Разработка методик измерений, обеспечивающих проведение испытаний продукции по всему спектру показателей и идентификационных характеристик продукта. В книге: Идеи академика В. Д. Харитонова в наукоёмких технологиях переработки молока (с. 243–262). Москва: Изд-во.Kharitonov, V. D., Yurova, E. A., & Chigasov, A. I. (2012). NIR spectral analysis. Dairy Industry, (2), 55–56. (In Russ.)Acuña-Nelson, S. M., et al. (2024). Effect of UHT Thermal Treatment on the Secondary Structures of Milk Proteins: Insights From FTIR Analysis and Potential Allergenic Activity. International Journal of Food Science, 2024, 1880779. https://doi.org/10.1155/2024/1880779Khurshudyan, S. A., & Galstyan, A. G. (2018). Quality of food products: terms and contradictions. Product Quality Control, (1), 48–49. (In Russ.)Almeida, M. R., Oliveira, K. D. S., Stephani, R., & de Oliveira, L. F. C. (2011). Fourier-transform Raman analysis of milk powder: A potential method for rapid quality screening. Journal of Raman Spectroscopy, 42(7), 1548–1552. https://doi.org/10.1002/jrs.2893Yurova, E. A., & Filchakova, S. A. (2021). Development of measurement methods… In the book: Ideas of Academician V. D. Kharitonov…(pp. 243–262). Moscow. (In Russ.)Andrade, J., Pereira, C. G., de Almeida Junior, J. C., et al. (2019). FTIR-ATR determination of protein content to evaluate whey protein concentrate adulteration. LWT, 99, 166–172. https://doi.org/10.1016/j.lwt.2018.09.043Acuña-Nelson, S. M., et al. (2024). Effect of UHT Thermal Treatment on the Secondary Structures of Milk Proteins: Insights From FTIR Analysis and Potential Allergenic Activity. International Journal of Food Science, 2024, 1880779. https://doi.org/10.1155/2024/1880779Antunes, C., Bexiga, R., Pinto, C., Roseiro, L. C., & Quaresma, M. A. G. (2023). Cow’s Milk in Human Nutrition and the Emergence of Plant-Based Milk Alternatives. Foods, 12(1), 99. https://doi.org/10.3390/foods12010099Almeida, M. R., Oliveira, K. D. S., Stephani, R., & de Oliveira, L. F. C. (2011). Fourier-transform Raman analysis of milk powder: A potential method for rapid quality screening. Journal of Raman Spectroscopy, 42(7), 1548–1552. https://doi.org/10.1002/jrs.2893Beckett, E. L., Cassettari, T., Starck, C., & Fayet-Moore, F. (2024). Dairy milk: There are alternatives but no equivalents. Food Science & Nutrition, 12(10), 8470–8482. https://doi.org/10.1002/fsn3.4301Andrade, J., Pereira, C. G., de Almeida Junior, J. C., et al. (2019). FTIR-ATR determination of protein content to evaluate whey protein concentrate adulteration. LWT, 99, 166–172. https://doi.org/10.1016/j.lwt.2018.09.043Buckova M, Vaskova H, Bubelova Z. (2016). Raman spectroscopy as a modern tool for lactose determination. Energy, 69(105), 70.Antunes, C., Bexiga, R., Pinto, C., Roseiro, L. C., & Quaresma, M. A. G. (2023). Cow’s Milk in Human Nutrition and the Emergence of Plant-Based Milk Alternatives. Foods, 12(1), 99. https://doi.org/10.3390/foods12010099Çolak, S. (2025). Simultaneous Raman and FTIR-ATR Spectroscopy Techniques Combined With Chemometrics… Journal of Raman Spectroscopy. https://doi.org/10.1002/jrs.6812Beckett, E. L., Cassettari, T., Starck, C., & Fayet-Moore, F. (2024). Dairy milk: There are alternatives but no equivalents. Food Science & Nutrition, 12(10), 8470–8482. https://doi.org/10.1002/fsn3.4301de Almeida, M. R., de Sá Oliveira, K., Stephani, R., & Cappa de Oliveira, L. F. (2012). Application of FT-Raman Spectroscopy and Chemometric Analysis for Determination of Adulteration in Milk Powder. Analytical Letters, 45(17), 2589–2602. https://doi.org/10.1080/00032719.2012.698672Buckova M, Vaskova H, Bubelova Z. (2016). Raman spectroscopy as a modern tool for lactose determination. Energy, 69(105), 70.Elderderi, S., et al. (2020). ATR-IR spectroscopy for rapid quantification of water content in deep eutectic solvents. Journal of Molecular Liquids, 311, 113361. https://doi.org/10.1016/j.molliq.2020.113361Çolak, S. (2025). Simultaneous Raman and FTIR-ATR Spectroscopy Techniques Combined With Chemometrics… Journal of Raman Spectroscopy. https://doi.org/10.1002/jrs.6812He H, Sun DW, Pu H, Chen L, Lin L. (2019). Applications of Raman spectroscopic techniques for quality and safety evaluation of milk: A review of recent developments. Critical Reviews in Food Science and Nutrition, 59(5), 770-793. https://doi.org/10.1080/10408398.2018.1528436de Almeida, M. R., de Sá Oliveira, K., Stephani, R., & Cappa de Oliveira, L. F. (2012). Application of FT-Raman Spectroscopy and Chemometric Analysis for Determination of Adulteration in Milk Powder. Analytical Letters, 45(17), 2589–2602. https://doi.org/10.1080/00032719.2012.698672He, H., Sun, D.-W., Pu, H., Chen, L., & Lin, L. (2019). Applications of Raman spectroscopic techniques for quality and safety evaluation of milk: A review of recent developments. Critical Reviews in Food Science and Nutrition, 59(5), 770–793. https://doi.org/10.1080/10408398.2018.1528436Elderderi, S., et al. (2020). ATR-IR spectroscopy for rapid quantification of water content in deep eutectic solvents. Journal of Molecular Liquids, 311, 113361. https://doi.org/10.1016/j.molliq.2020.113361Júnior, P. H. R., et al. (2016). FT-Raman and chemometric tools for rapid determination of quality parameters in milk powder: Classification of samples for the presence of lactose and fraud detection by addition of maltodextrin. Food Chemistry, 196, 584–588. https://doi.org/10.1016/j.foodchem.2015.09.055He H, Sun DW, Pu H, Chen L, Lin L. (2019). Applications of Raman spectroscopic techniques for quality and safety evaluation of milk: A review of recent developments. Critical Reviews in Food Science and Nutrition, 59(5), 770-793. https://doi.org/10.1080/10408398.2018.1528436Khan HH, McCarthy U, Esmonde-White K, Casey I, O'Shea N. (2023). Potential of Raman spectroscopy for in-line measurement of raw milk composition. Food Control, 152, 109862. https://doi.org/10.1016/j.foodcont.2023.109862He, H., Sun, D.-W., Pu, H., Chen, L., & Lin, L. (2019). Applications of Raman spectroscopic techniques for quality and safety evaluation of milk: A review of recent developments. Critical Reviews in Food Science and Nutrition, 59(5), 770–793. https://doi.org/10.1080/10408398.2018.1528436Kostovska, R., et al. (2025). Use of Raman spectroscopy as a rapid tool to discriminate milk deriving from different pasture-based diets and breeds in a seasonal, spring-calving dairy production system. Journal of Dairy Science, 108(9), 9205–9221. https://doi.org/10.3168/jds.2025-26489Júnior, P. H. R., et al. (2016). FT-Raman and chemometric tools for rapid determination of quality parameters in milk powder: Classification of samples for the presence of lactose and fraud detection by addition of maltodextrin. Food Chemistry, 196, 584–588. https://doi.org/10.1016/j.foodchem.2015.09.055Łach, K., et al. (2023). Infrared Spectroscopy as a Potential Diagnostic Tool for Medulloblastoma. Molecules, 28(5), 2390. https://doi.org/10.3390/molecules28052390Khan HH, McCarthy U, Esmonde-White K, Casey I, O'Shea N. (2023). Potential of Raman spectroscopy for in-line measurement of raw milk composition. Food Control, 152, 109862. https://doi.org/10.1016/j.foodcont.2023.109862Li M, Chen J, Xu J, Fu S, Gong H. Determination of lactose in milk by Raman spectroscopy. Analytical Letters. 2015;48(8):1333-1340. https://doi.org/10.1080/00032719.2014.979358Kostovska, R., et al. (2025). Use of Raman spectroscopy as a rapid tool to discriminate milk deriving from different pasture-based diets and breeds in a seasonal, spring-calving dairy production system. Journal of Dairy Science, 108(9), 9205–9221. https://doi.org/10.3168/jds.2025-26489Li, M., Chen, J., Xu, J., Fu, S., & Gong, H. (2015). Determination of lactose in milk by Raman spectroscopy. Analytical Letters, 48(8), 1333–1340. https://doi.org/10.1080/00032719.2014.979358Łach, K., et al. (2023). Infrared Spectroscopy as a Potential Diagnostic Tool for Medulloblastoma. Molecules, 28(5), 2390. https://doi.org/10.3390/molecules28052390Markoska, T., Huppertz, T., Grewal, M. K., & Vasiljevic, T. (2019). Structural changes of milk proteins during heating of concentrated skim milk determined using FTIR. International Dairy Journal, 89, 21–30. https://doi.org/10.1016/j.idairyj.2018.08.001Li M, Chen J, Xu J, Fu S, Gong H. Determination of lactose in milk by Raman spectroscopy. Analytical Letters. 2015;48(8):1333-1340. https://doi.org/10.1080/00032719.2014.979358McGoverin, C. M., Clark, A. S. S., Holroyd, S. E., & Gordon, K. C. (2010). Raman spectroscopic quantification of milk powder constituents. Analytica Chimica Acta, 673(1), 26–32. https://doi.org/10.1016/j.aca.2010.05.014Li, M., Chen, J., Xu, J., Fu, S., & Gong, H. (2015). Determination of lactose in milk by Raman spectroscopy. Analytical Letters, 48(8), 1333–1340. https://doi.org/10.1080/00032719.2014.979358Mohammadi, S., Gowen, A., Luo, J., & O’Donnell, C. (2024). Prediction of milk composition using multivariate chemometric modelling of infrared, Raman and fluorescence spectroscopic data: A review. Food Control, 165, 110658. https://doi.org/10.1016/j.foodcont.2024.110658Markoska, T., Huppertz, T., Grewal, M. K., & Vasiljevic, T. (2019). Structural changes of milk proteins during heating of concentrated skim milk determined using FTIR. International Dairy Journal, 89, 21–30. https://doi.org/10.1016/j.idairyj.2018.08.001Moros, J., Garrigues, S., & de la Guardia, M. (2007). Evaluation of nutritional parameters in infant formulas and powdered milk by Raman spectroscopy. Analytica Chimica Acta, 593(1), 30–38. https://doi.org/10.1016/j.aca.2007.04.036McGoverin, C. M., Clark, A. S. S., Holroyd, S. E., & Gordon, K. C. (2010). Raman spectroscopic quantification of milk powder constituents. Analytica Chimica Acta, 673(1), 26–32. https://doi.org/10.1016/j.aca.2010.05.014Ní Fhuaráin, A. M., O’Donnell, C. P., Luo, J., & Gowen, A. A. (2024). A Review on MIR, NIR, Fluorescence and Raman Spectroscopy Combined with Chemometric Modeling to Predict the Finctional Properties of Raw Bovine Milk. ACS Food Science & Technology, 4(10), 2258–2271. https://doi.org/10.1021/acsfoodscitech.3c00510Mohammadi, S., Gowen, A., Luo, J., & O’Donnell, C. (2024). Prediction of milk composition using multivariate chemometric modelling of infrared, Raman and fluorescence spectroscopic data: A review. Food Control, 165, 110658. https://doi.org/10.1016/j.foodcont.2024.110658Rachah, A., et al. (2021). Exploring Dry-Film FTIR Spectroscopy to Characterize Milk Composition and Subclinical Ketosis throughout a Cow’s Lactation. Foods, 10(9), 2033. https://doi.org/10.3390/foods10092033Moros, J., Garrigues, S., & de la Guardia, M. (2007). Evaluation of nutritional parameters in infant formulas and powdered milk by Raman spectroscopy. Analytica Chimica Acta, 593(1), 30–38. https://doi.org/10.1016/j.aca.2007.04.036Reiner, J., Protte, K., & Hinrichs, J. (2020). Investigation of the applicability of Raman spectroscopy as online process control during consumer milk production. ChemEngineering, 4(3), 45. https://doi.org/10.3390/chemengineering4030045Ní Fhuaráin, A. M., O’Donnell, C. P., Luo, J., & Gowen, A. A. (2024). A Review on MIR, NIR, Fluorescence and Raman Spectroscopy Combined with Chemometric Modeling to Predict the Finctional Properties of Raw Bovine Milk. ACS Food Science & Technology, 4(10), 2258–2271. https://doi.org/10.1021/acsfoodscitech.3c00510Ribeiro, D. C. S. Z., et al. (2023). Determination of the lactose content in low-lactose milk using FTIR and CNN. Heliyon, 9(1), e12898. https://doi.org/10.1016/j.heliyon.2023.e12898Rachah, A., et al. (2021). Exploring Dry-Film FTIR Spectroscopy to Characterize Milk Composition and Subclinical Ketosis throughout a Cow’s Lactation. Foods, 10(9), 2033. https://doi.org/10.3390/foods10092033Schott, J. A., et al. (2021). FTIR investigation of CO₂ sorption in porous ionic liquids. Green Chemical Engineering, 2(4), 392–401. https://doi.org/10.1016/j.gce.2021.10.002Reiner, J., Protte, K., & Hinrichs, J. (2020). Investigation of the applicability of Raman spectroscopy as online process control during consumer milk production. ChemEngineering, 4(3), 45. https://doi.org/10.3390/chemengineering4030045Silva MG, de Paula IL, Stephani R, Edwards HG, de Oliveira LFC. Raman spectroscopy in the quality analysis of dairy products: A literature review. Journal of Raman Spectroscopy. 2021;52(12):2444-2478.Ribeiro, D. C. S. Z., et al. (2023). Determination of the lactose content in low-lactose milk using FTIR and CNN. Heliyon, 9(1), e12898. https://doi.org/10.1016/j.heliyon.2023.e12898Silva, M. G., et al. (2021). Raman spectroscopy in the quality analysis of dairy products: A literature review. Journal of Raman Spectroscopy, 52(12), 2444–2478. https://doi.org/10.1002/jrs.6214Schott, J. A., et al. (2021). FTIR investigation of CO₂ sorption in porous ionic liquids. Green Chemical Engineering, 2(4), 392–401. https://doi.org/10.1016/j.gce.2021.10.002Smith, G. P. S., Gordon, K. C., & Holroyd, S. E. (2013). Raman spectroscopic quantification of calcium carbonate in spiked milk powder samples. Vibrational Spectroscopy, 67, 87–91. https://doi.org/10.1016/j.vibspec.2013.04.005Silva MG, de Paula IL, Stephani R, Edwards HG, de Oliveira LFC. Raman spectroscopy in the quality analysis of dairy products: A literature review. Journal of Raman Spectroscopy. 2021;52(12):2444-2478.Stani, C., et al. (2020). FTIR investigation of the secondary structure of type I collagen: New insight into the amide III band. Spectrochimica Acta Part A, 229, 118006. https://doi.org/10.1016/j.saa.2019.117653Silva, M. G., et al. (2021). Raman spectroscopy in the quality analysis of dairy products: A literature review. Journal of Raman Spectroscopy, 52(12), 2444–2478. https://doi.org/10.1002/jrs.6214Yan, H., Yu, Z., & Liu, L. (2022). Lactose crystallization and Maillard reaction in simulated milk powder based on the change in water activity. Journal of Food Science, 87(11), 4956–4966. https://doi.org/10.1111/1750-3841.16267Smith, G. P. S., Gordon, K. C., & Holroyd, S. E. (2013). Raman spectroscopic quantification of calcium carbonate in spiked milk powder samples. Vibrational Spectroscopy, 67, 87–91. https://doi.org/10.1016/j.vibspec.2013.04.005Zhang, ZY. (2020). The statistical fusion identification of dairy products based on extracted Raman spectroscopy. RSC Advances, 10(50), 29682-29687. https://doi.org/10.1039/D0RA06318EStani, C., et al. (2020). FTIR investigation of the secondary structure of type I collagen: New insight into the amide III band. Spectrochimica Acta Part A, 229, 118006. https://doi.org/10.1016/j.saa.2019.117653Zhang, Y., Shen, B., Wang, H., & Zhao, Y. (2025). Quantification of cow milk in adulterated goat milk using Raman spectroscopy and machine learning. Microchemical Journal, 215, 114319. https://doi.org/10.1016/j.microc.2025.114319Yan, H., Yu, Z., & Liu, L. (2022). Lactose crystallization and Maillard reaction in simulated milk powder based on the change in water activity. Journal of Food Science, 87(11), 4956–4966. https://doi.org/10.1111/1750-3841.16267Zhang, Z.-Y., Su, J.-S., & Xiong, H.-M. (2025). Technology for the Quantitative Identification of Dairy Products Based on Raman Spectroscopy, Chemometrics, and Machine Learning. Molecules, 30(2), 239. https://doi.org/10.3390/molecules30020239Zhang, ZY. (2020). The statistical fusion identification of dairy products based on extracted Raman spectroscopy. RSC Advances, 10(50), 29682-29687. https://doi.org/10.1039/D0RA06318EZhang, Y., Shen, B., Wang, H., & Zhao, Y. (2025). Quantification of cow milk in adulterated goat milk using Raman spectroscopy and machine learning. Microchemical Journal, 215, 114319. https://doi.org/10.1016/j.microc.2025.114319Zhang, Y., Shen, B., Wang, H., & Zhao, Y. (2025). Quantification of cow milk in adulterated goat milk using Raman spectroscopy and machine learning. Microchemical Journal, 215, 114319. https://doi.org/10.1016/j.microc.2025.114319Zhang, Z.-Y., Su, J.-S., & Xiong, H.-M. (2025). Technology for the Quantitative Identification of Dairy Products Based on Raman Spectroscopy, Chemometrics, and Machine Learning. Molecules, 30(2), 239. https://doi.org/10.3390/molecules30020239Zhang, Z.-Y., Su, J.-S., & Xiong, H.-M. (2025). Technology for the Quantitative Identification of Dairy Products Based on Raman Spectroscopy, Chemometrics, and Machine Learning. Molecules, 30(2), 239. https://doi.org/10.3390/molecules30020239

The authors declare that there are no conflicts of interest present.