Microbiological, chemical, physical, and proteolytic activities of raw milk after thermal processing

Milaneze, Hamara Souza; Silva, L. S; Kottwitz, Luciana Bill Mikito; Zambom, Maximiliane Alavarse; Fonseca, L. R. C.; Guimarães, Ana Tereza Bittencourt; Pozza, M. S. S.

doi:10.1590/1678-4162-9662

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…Increases in MUN concentration might be the result of non-protein nitrogen formed due to milk proteolysis (Milaneze et al, 2018;Santos et al, 2018) and this finding is corroborated with the increased CMP index, which is used as an indicator of illegal cheese whey addition to milk, and may be an indicator of milk proteolysis (Ferron-Baumy et al, 1992;Milaneze et al, 2018;Recio et al, 2000;Villanoeva et al, 2014).…”

Section: Physicochemical and Compositional Parameters Of Uht Milkmentioning

confidence: 93%

Loss of UHT milk quality: changes in compositional and physicochemical parameters triggered by different storage conditions

Santos

Penna²,

Vasconcelos³

et al. 2022

RSD

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The objective of this study was to evaluate some compositional and physicochemical changes that occur during UHT (Ultra-high temperature) milk storage for up to four months. A total of 120 samples of UHT milk were collected from two dairy plants in the state of Minas Gerais, Brazil, and stored under two temperatures (20°C and 30°C) during five periods (0, 30, 60, 90 and 120 days). The experimental design was completely randomized, in a 2x2x5 factorial arrangement, with six replicates per treatment (six batches). Evaluated parameters included fat, total protein, casein, lactose, total solids, solids nonfat (SNF) and milk urea nitrogen (MUN) contents, as well as acidity, density, freezing point and indexes of lipolysis and caseinomacropeptide (CMP). When compared to the Brazilian requirements for UHT milk, the mean values for acidity, fat and SNF contents were in accordance with the standards until the last day of storage. The other parameters are still not covered by the specific UHT milk legislation in Brazil. There was no change of relative density and lactose content also remained constant, except for a decrease at the fourth month. A significant increase, over storage time, in acidity, MUN, lipolysis and CMP indexes occurred. On the other hand, there was a significant decrease in SNF and protein contents. The results showed that there was a gradual loss of quality during UHT milk storage, aggravated by the rise in temperature. These findings demonstrate that UHT milk legislation could be improved by adding parameters such as lipolysis and CMP indexes.

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Section: Physicochemical and Compositional Parameters Of Uht Milkmentioning

confidence: 93%

Loss of UHT milk quality: changes in compositional and physicochemical parameters triggered by different storage conditions

Santos

Penna²,

Vasconcelos³

et al. 2022

RSD

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show abstract

“…Though some other ions identified as peptides were also detected in increasing amounts in the pasteurized milk during cold storage, the levels of these peptides were not stable (relative standard deviation > 20%). The increase in peptides was probably caused by proteolysis due to the action of the plasmin and proteases from somatic cells or the thermoresis-tant proteolytic enzymes produced by psychrotrophic microorganisms (Santos et al, 2003;Milaneze et al, 2018). The proteolytic activity of milk has been found to remain after the pasteurization process (76°C for 30 s) and during cold storage (0.5 and 6°C for 61 d), as shown by the significant decrease of casein as a percentage of true protein (Santos et al, 2003).…”

Section: Milk Compositional Changes During Refrigerated Storagementioning

confidence: 99%

Effects of the vat pasteurization process and refrigerated storage on the bovine milk metabolome

Zhu

Kebede

Chen

et al. 2020

Journal of Dairy Science

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This study is the first to investigate the evolution of cow milk metabolites throughout the vat pasteurization process and storage using untargeted metabolomics based on a multiplatform approach. Nuclear magnetic resonance and ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry were used for fingerprinting water-soluble nutritional compounds, and headspace gas chromatography-mass spectrometry was used to fingerprint the volatile organic compounds. This study demonstrated that vat pasteurization was an efficient and mild means of milk preservation resulting in only minor changes to the metabolites. The pasteurized milk samples exhibited a stable metabolome during the first 8 d of refrigerated storage. However, at the latter stage of storage, the concentrations of pantothenic acid and butyrylcarnitine decreased, whereas some fatty acids, organic acids, α-AA, peptides, and ketones increased. These selected metabolites that changed during milk storage could be used as potential biomarkers to track the storage conditions of pasteurized cow milk.

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Artificial neural networks in the prediction of fraud in integral milk powder by adding whey powder

et al. 2022

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This research was performed to ascertain the most suitable Artificial Neural Network (ANN) model to quantify the degree of fraud in powdered milk through the addition of powdered whey via regular standard physicochemical analyses. In this study, an evaluation was done on 103 samples with different quantities of added whey powder to whole milk powder. Using Fourier Transform Infrared Spectroscopy the fat, cryoscopy, total solids, defatted dry extract, lactose, protein and casein were analyzed. The hyperbolic tangent transformation function was used with 45 topologies, and the Holdback and K-fold validation methods were tested. In the Holdback method, 75% of the database was employed for training, while 25% was used for validation. In the K-fold method, the database was categorized into five equal sized subsets, which alternated between training and validation. Of the two methods, the K-fold method was proven to have superior efficiency. Next, analysis was done on three models of multilayer perceptron networks with feedforward architecture. In Model 1, the input layer contained all the physicochemical analyses conducted, in model 2 the casein analysis was excluded, and in model 3 the routine analyses performed for dairy products was done (fat, defatted dry extract, cryoscopy and total solids). From Model 3 an ANN was derived which could satisfactorily predict fraud calculated from using the routine and standard analyses for dairy products, containing 64 nodes in the hidden layer, with R2 of 0.9935 and RMSE of 0.5779 for training, and R2 of 0.9964 and RMSE of 0.4358 for validation.

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Microbiological, chemical, physical, and proteolytic activities of raw milk after thermal processing

Cited by 3 publications

References 14 publications

Loss of UHT milk quality: changes in compositional and physicochemical parameters triggered by different storage conditions

Loss of UHT milk quality: changes in compositional and physicochemical parameters triggered by different storage conditions

Effects of the vat pasteurization process and refrigerated storage on the bovine milk metabolome

Artificial neural networks in the prediction of fraud in integral milk powder by adding whey powder

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