Detection of milk powder in liquid whole milk using hydrolyzed peptide and intact protein mass spectral fingerprints coupled with data fusion technologies

Du, Liuying; Lu, Weiying; Zhang, Yaqiong; Gao, Boyan; Yu, Liangli

doi:10.1002/fsn3.1430

Cited by 13 publications

(5 citation statements)

References 33 publications

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“…Проте при термічній обробці молока, крім зменшення кількості мікроорганізмів, відбуваються фізикохімічні зміни його властивостей: змінюється точка замерзання, густина, відбувається денатурація та агрегація білків, ізомеризація лактози, утворюються продукти реакції Майяра, відбуваються зміни рівноваги мінерального складу молока (Sestan et al, 2016). З питанням сезонності складу молока тісно пов'язане питання виробництва, так званого, відновленого молока, тобто молочного продукту, виготовленого із сухого молока шляхом його розведення водою для отримання заданої кількості сухих речовин (Du et al, 2020). За даними Спілки молочних підприємств України (https://uadairy.com/yak-zminylosya-molochneskotarstvo-ukrayiny-za-ostanni-6-rokiv/) за період 2017-2022 рр.…”

Section: вступunclassified

Monitoring of the main indicators of milk quality of Ukrainian dairy produc-ers

Kvitkovskaya,

Ischenko,

Kochubei-Lytvynenko

et al. 2024

SMLNUVMBF

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The composition and properties of milk are significantly influenced by various factors, such as the breed of cows, stages of lactation, the environment, as well as its temperature treatment. In the research carried out in 2017–2022, ultrasonic analysis of 56 samples of different types of dairy products was carried out: pasteurized and ultra-pasteurized milk of the largest Ukrainian producers of dairy products and milk produced at small enterprises, as well as a dairy product made in laboratory conditions from milk powder (reconstituted milk). The following indicators of milk composition were determined by the method of ultrasonic analysis, such as the content of fat, protein, lactose, solids non fat (SNF), and freezing temperature. The fat content in the samples was in the range of 2.5–3.2 %, the protein content was on average 3.3%, and a clear pattern of increasing the protein content with increasing fat content was observed. The content of SNF was on average 8.4 %, and lactose in the range of 4.5–5.5 g/100 g of milk; in the produced reconstituted milk, the lactose content was somewhat lower and averaged 3.5 %. The freezing temperature of the studied samples ranged from -0.50 ºC (reconstituted milk) to -0.60 ºC (pasteurized and ultra-pasteurized). The method of principal components analysis was used to process the obtained data array. Application of the method of principal components analysis (PCA) made it possible to divide all the studied samples into two groups. The first compact group consists mainly of samples of pasteurized and ultra-pasteurized milk from well-known producers of dairy products. The second diffuse group consists of samples of reconstituted milk, and this group includes several samples of pasteurized milk of a low price category from small producers. The analysis of the eigenvectors and eigenvalues of the PCA indicates that the main factors affecting the grouping of the samples are the content of lactose, protein and the value of the freezing temperature. At the same time, the application of PCA modeling did not reveal any grouping of samples by seasons and years. In the future, based on this method, a discriminatory model can be made, which will allow to quickly detect falsified samples or samples manufactured in violation of technical conditions.

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Section: вступunclassified

Monitoring of the main indicators of milk quality of Ukrainian dairy produc-ers

Kvitkovskaya,

Ischenko,

Kochubei-Lytvynenko

et al. 2024

SMLNUVMBF

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“…With the growing demand for traceability, this analysis could provide an accurate method for milk authentication. Data fusion was used to improve the discrimination ability of PCA to identify milk that has been fortified with milk powder ( 100 ). Electronic tongue and nose were used to distinguish between UHT and pasteurized milk combined with the use of PCA ( 103 ).…”

Section: Applications Of Data Fusion For the Dairy Industrymentioning

confidence: 99%

Spectroscopic technologies and data fusion: Applications for the dairy industry

et al. 2023

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Increasing consumer awareness, scale of manufacture, and demand to ensure safety, quality and sustainability have accelerated the need for rapid, reliable, and accurate analytical techniques for food products. Spectroscopy, coupled with Artificial Intelligence-enabled sensors and chemometric techniques, has led to the fusion of data sources for dairy analytical applications. This article provides an overview of the current spectroscopic technologies used in the dairy industry, with an introduction to data fusion and the associated methodologies used in spectroscopy-based data fusion. The relevance of data fusion in the dairy industry is considered, focusing on its potential to improve predictions for processing traits by chemometric techniques, such as principal component analysis (PCA), partial least squares regression (PLS), and other machine learning algorithms.

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“…To overcome this problem, a protein quantification method based on specific peptides was proposed, usually called targeted proteomics [22]. At present, this technique has been widely used in the detection of common milk proteins in milk [23,24], and it also plays an important role in the identification of milk proteins based on individual amino acid differences [25,26]. Ke et al [27] developed a method to screen and analyze the specific peptides of six milk proteins between goat and cow to quantify the cow proteins adulteration in goat or sheep milk products.…”

Section: Introductionmentioning

confidence: 99%

“…Protein level of β-casein (A) and composition of A1-type and A2-type β-casein (B) in Yak, Pien-niu, and cow milk[24][25][26][27][28][29][30][31][32][33], four samples only contained A2-type β-casein, and one sample only contained A1-type β-casein. The other five samples were found with both A1-type and A2-type β-casein.…”

mentioning

confidence: 99%

Analysis of A1‐type and A2‐type β‐casein in Maiwa Yak and Pien‐niu milk by HPLC‐high‐resolution MS and tandem MS

Chen

Ren

Wang

et al. 2021

J of Separation Science

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In this study, a peptide-based method employing ultra high performance liquid chromatography electrostatic field orbitrap high-resolution mass spectrometry and triple quadrupole mass spectrometry was developed for quantification of A1type and A2-type β-casein in milk from Yak, cows, and their offspring of crosses, Pien-niu. The specific peptides of A1-type and A2-type β-casein were screened and confirmed by protein software after analysis of high-resolution mass spectrometry. The multiple reaction monitoring method was established based on the qualitative results, and isotope-label peptides were used as internal standards.The linear correlation coefficients of this method were >0.99. The relative standard deviations of repeatability test were 0.2-3.6%. The recovery rate ranged from 93.3 to 114.4% with relative standard deviations <6% at three different spiking levels. The method was applied to analyze 45 milk samples from different species.The results showed that β-casein in Yak and Pien-niu milk was about 30% higher than that in cow milk. Furthermore, the β-casein in the Yak milk only contains A2-type β-casein. A1-type and A2-type β-casein coexist in most samples of Pienniu and cow milk, a few samples contain only one type of β-casein. These results provide further understanding in nutritional value of milk from Yak and Pienniu.

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Detection of milk powder in liquid whole milk using hydrolyzed peptide and intact protein mass spectral fingerprints coupled with data fusion technologies

Cited by 13 publications

References 33 publications

Monitoring of the main indicators of milk quality of Ukrainian dairy produc-ers

Monitoring of the main indicators of milk quality of Ukrainian dairy produc-ers

Spectroscopic technologies and data fusion: Applications for the dairy industry

Analysis of A1‐type and A2‐type β‐casein in Maiwa Yak and Pien‐niu milk by HPLC‐high‐resolution MS and tandem MS

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