Optimized Chemical Analysis of Cow’s Milk Proteins: Evaluation of New Measuring Devices

Marouane Chrif; Abderrahim El Hourch; Abdellah El Abidi

doi:10.22146/ijc.63900

Optimized Chemical Analysis of Cow’s Milk Proteins: Evaluation of New Measuring Devices

https://doi.org/10.22146/ijc.63900

Marouane Chrif^(1*), Abderrahim El Hourch⁽²⁾, Abdellah El Abidi⁽³⁾

(1) Laboratory of Electrochemistry and Analytical Chemistry, Faculty of Sciences, University Mohammed V, Avenue Ibn Battouta 1014, Rabat, Morocco
(2) Laboratory of Electrochemistry and Analytical Chemistry, Faculty of Sciences, University Mohammed V, Avenue Ibn Battouta 1014, Rabat, Morocco
(3) Laboratory of Physical Chemistry, Department of Hydrology and Toxicology, National Institute of Hygiene, 27 Avenue Ibn Batouta, 10090 Rabat, Morocco
(*) Corresponding Author

Abstract

The demands of quality and choice in the dairy industry require analysis of extended performance. Ancient milk protein measuring devices take a long time and provide slow and inaccurate results. This work is part of the reliable analysis of cow’s milk proteins and defines the laws linking the two parameters, total nitrogen (NT) and protein nitrogen (NP). We are studying to prove a fast and effective method for measuring the non-protein nitrogen (NPN) composition of milk that allows the direct calculation of NP from the NT value, whose objective is to adapt the calibration of the Milko Scan FT2 cow’s milk protein analysis since NPN has a direct impact on protein analysis, payment of milk, and on the manufacture of milk products. The study showed that there is a compatibility between these two parameters and gave an idea of the percentage (5.9%) of NPN in milk. New analytical solutions such as the latest generation of the Kjeldahl K-375/376 and the new Milko Scan FT2 meet these needs. Data processing is done using XLSTAT, which is free statistical analysis software.

Keywords

protein; milk; total nitrogen; non-protein nitrogen; fat

Full Text:

Full Text PDF

References

[1] Yang, Y., Hettinga, K.A., Erasmus, S.W., Pustjens, A.M., and van Ruth, S.M., 2020, Opportunities for fraudsters: When would profitable milk adulterations go unnoticed by common, standardized FTIR measurements?, Food Res. Int., 136, 109543.

[2] Ruska, D., and Jonkus, D., 2014, Crude protein and non-protein nitrogen content in dairy cow milk, Proc. Latv. Univ. Agric., 32 (1), 36–40.

[3] Das, M., Nath, P.C, Sileshi, G.W., Pandey, R., Nath, A.J., and Das, A.K., 2021, Biomass models for estimating carbon storage in Areca palm plantations, Environ. Sustainability Indic., 10, 100115.

[4] Hristov, A.N., Bannink, A., Crompton, L.A., Huhtanen, P., Kreuzer, M., McGee, M., Nozière, P., Reynolds, C.K., Bayat, A.R., Yáñez-Ruiz, D.R., Dijkstra, J., Kebreab, E., Schwarm, A., Shingfield, K.J., and Yu, Z., 2019, Invited review: Nitrogen in ruminant nutrition: A review of measurement techniques, J. Dairy Sci., 102, (7), 5811–5852.

[5] Serra, I., Capusoni, C., Molinari, F., Musso, L., Pellegrino, L., and Compagno, C., 2019, Marine microorganisms for biocatalysis: Selective hydrolysis of nitriles with a salt-resistant strain of Meyerozyma guilliermondii, Mar. Biotechnol., 21 (2), 229–239.

[6] Sraïri, M.T., Chatellier, V., Corniaux, C., Faye, B., Aubron, C., Hostiou, N., and Lortal, S., 2019, Réflexions sur le développement du secteur laitier et sa durabilité dans différentes parties du monde, INRA Prod. Anim., 32 (3), 339–358.

[7] Kim, H., Kang, S., Jung, B.M., Yi, H., Jung, J.A., and Chang, N., 2017, Breast milk fatty acid composition and fatty acid intake of lactating mothers in South Korea, Br. J. Nutr., 117 (4), 556–561.

[8] Li, S., Ye, A., and Singh, H., 2019, Seasonal variations in composition, properties, and heat-induced changes in bovine milk in a seasonal calving system, J. Dairy Sci., 102 (9), 7747–7759.

[9] Srisaikham, S., Jaijapo, W., Lounglawan, P., and Suksombat, W., 2018, Effect of feeding fermented fresh cassava pulp on lactoperoxidase activity and performance of Holstein Friesian crossbred lactating dairy cows, PIM 1^st International Conference 2018, Amphoe Pak Kret, Thailand, 21 June 2018, 1–38.

[10] Souhassou, S., Bassbasi, M., Hirri, A., Kzaiber, F., and Oussama, A., 2018, Evaluation of Milkoscan FT2 milk analyzer for determining the freezing point of cow milk under different analytical conditions, Int. J. Chem. Mater. Environ. Res., 5 (2), 165–172.

[11] Baum, A., Dominiak, M., Vidal-Melgosa, S., Willats, W.G.T., Søndergaard, K.M., Hansen, P.W., Meyer, A.S., and Mikkelsen, J.D., 2017, Prediction of Pectin Yield and Quality by FTIR and Carbohydrate Microarray Analysis, Food Bioprocess Technol., 10 (1), 143–154.

[12] Løkke, M.M., Engelbrecht, R., and Wiking, L., 2016, Covariance structures of fat and protein influence the estimation of IgG in bovine colostrum, J. Dairy Res., 83 (1), 58–66.

[13] Stocco, G., Cipolat-Gotet, C., Bonfatti, V., Schiavon, S., Bittante, G., and Cecchinato, A., 2016, Short communication: Variations in major mineral contents of Mediterranean buffalo milk and application of Fourier-transform infrared spectroscopy for their prediction, J. Dairy Sci., 99 (11), 8680–8686.

[14] Kharitonov, V., Sherstneva, N., Kharitonov, D., Yurova, E., and Kurchenko, V., 2019, Changes in physico-chemical properties of milk under ultraviolet radiation, Foods Raw Mater., 7 (1), 161–167.

[15] Nguyen, Q.T., Fouchereau, R., Frénod, E., Gerard, C., and Sincholle, V., 2020, Comparison of forecast models of production of dairy cows combining animal and diet parameters, Comput. Electron. Agric., 170, 105258.

[16] Hurtado-Lugo, N., Rincon, A., and Ceron-Muñoz, M., 2020, Physicochemical and statistical analysis of a dairy production, J. Phys.: Conf. Ser., 1587, 012026.

[17] Franzoi, M., Niero, G., Penasa, M., and De Marchi, M., 2019, Development of infrared prediction models for diffusible and micellar minerals in bovine milk, Animals, 9 (7), 430.

[18] Chrif, M., El Hourch, A., Chouni, S., Aitbenyouf, S., and El Abidi, A., 2018, The variation of the non-protein nitrogen content by region and season and their impact on the analysis of milk proteins in Morocco, J. Mater. Environ. Sci., 9 (3), 811–816.

[19] Roveglia, C., Niero, G., Penasa, M., Finocchiaro, R., Marusi, M., Lopez-Villalobos, N., and Cassandro, M., 2019, Phenotypic analysis of milk composition, milk urea nitrogen and somatic cell score of Italian Jersey cattle breed, Ital. J. Anim. Sci., 18 (1), 405–409.

[20] Chrif, M., El Hourch, A., Chouni, S., Bouyahya, A., and El Abidi, A., 2019, Changes of Physicochemical composition of Moroccan bovine’s milk along the years, Mediterr. J. Chem., 8 (6), 470–475.

DOI: https://doi.org/10.22146/ijc.63900