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The bovine milk quality, safety, and security are of great concern mainly due to the dispersion of toxic substances from various anthropogenic activities and poor practices for organophosphates in agriculture use. This study evaluated the potential risk to human health from lead (Pb), cadmium (Cd), and arsenic (As) from the consumption of milk produced in an area of the Central Andes valley near a mini mineral concentrator by estimating the weekly intake (WI), dietary risk quotient (DRC), hazard quotient (THQ), and hazard index (HI) for the Peruvian population aged 2 to 85 years, in three scenarios of milk consumption by age (minimum, average, and maximum). Toxic element quantification was performed by flame atomic absorption spectrometry following standardized procedures. The mean amount ± standard deviation of Pb, Cd, and As in soils was 292±60.90, 3.54±1.58, and 5.60±2.20 mg/kg, the order of importance being Pb>As>Cd. The contents of Pb, Cd, and As in pastures were 23.17±10.02, 0.25±0.57, and 0.06±0.09 mg/kg, being from highest to lowest Pb>Cd>As. The means of Pb, Cd, and As content in 19 milk samples were 0.029±0.022, 0.007±0.006, and 0.010±0.004 mg/kg. Pb and Cd exceeded the maximum permissible limits (MPL), and the As was below the MPL. At all ages and milk consumption levels, the WI for Pb and Cd were below the estimated tolerable intake (TWI). The WI for As in < 19 years was higher than the TWI. The DRC for Pb and Cd at all three milk intake levels and all ages was < 1, and for As, it was > 1 in < 19 years, being the risk group. The TQH and HI for Pb and Cd were also > 1, signifying no health risk, and for As, the values were > 1 in < 11 years. Our results are valuable for preventing adverse health impacts from safe and innocuous milk consumption.

The experiments reported in this research paper aimed to track the microbiological load of milk throughout a low-heat skim milk powder (SMP) manufacturing process, from farm bulk tanks to final powder, during mid- and late-lactation (spring and winter, respectively). In the milk powder processing plant studied, low-heat SMP was produced using only the milk supplied by the farms involved in this study. Samples of milk were collected from farm bulk tanks (mid-lactation: 67 farms; late-lactation: 150 farms), collection tankers (CTs), whole milk silo (WMS), skim milk silo (SMS), cream silo (CS) and final SMP. During mid-lactation, the raw milk produced on-farm and transported by the CTs had better microbiological quality than the late-lactation raw milk (e.g., total bacterial count (TBC): 3.60 ± 0.55 and 4.37 ± 0.62 log 10 cfu/ml, respectively). After pasteurisation, reductions in TBC, psychrotrophic (PBC) and proteolytic (PROT) bacterial counts were of lower magnitude in late-lactation than in mid-lactation milk, while thermoduric (LPC—laboratory pasteurisation count) and thermophilic (THERM) bacterial counts were not reduced in both periods. The microbiological quality of the SMP produced was better when using mid-lactation than late-lactation milk (e.g., TBC: 2.36 ± 0.09 and 3.55 ± 0.13 cfu/g, respectively), as mid-lactation raw milk had better quality than late-lactation milk. The bacterial counts of some CTs and of the WMS samples were higher than the upper confidence limit predicted using the bacterial counts measured in the farm milk samples, indicating that the transport conditions or cleaning protocols could have influenced the microbiological load. Therefore, during the different production seasons, appropriate cow management and hygiene practices (on-farm and within the factory) are necessary to control the numbers of different bacterial groups in milk, as those can influence the effectiveness of thermal treatments and consequently affect final product quality.

Background Intramammary infections negatively affect milk quality, animal welfare and productivity in the dairy industry. Somatic cell count (SCC) is the most used screening tool to detect subclinical mastitis caused by intramammary infections. In dairy goats, SCC is greatly influenced by non-infectious factors, which complicates the interpretation. The aim of this research paper was to determine the association between SCC, intramammary infections and non-infectious factors including parity, season, lactation stage, and milk yield in dairy goats. In this longitudinal study, 451 goats from four Norwegian dairy goat herds were sampled for bacteriology and SCC up to nine times during two lactations. Factors like parity, milk yield, and stage of lactation were retrieved from the Norwegian goat recording system. Results The most prevalent udder pathogen findings were Staphylococcus caprae (6.8%), Staphylococcus warneri (6.3%), and Staphylococcus epidermidis (3.8%), all of which had a mild but significant impact on SCC. Staphylococcus aureus was detected in 3.6% of the udder halves and had a major effect on SCC. Parity, stage of lactation, season, and milk yield significantly influenced SCC. Conclusions This study highlights that intramammary infections caused by Staphylococcus aureus , along with factors such as increasing parity and the seasonal effects of pasturing, significantly influence the SCC. Understanding these key contributors is essential for improving udder health management and improving milk quality in goat milk production.

Background Mastitis is a costly disease affecting dairy ruminants worldwide. Somatic cell count is the most widely used tool for udder health monitoring but is highly influenced by non-infectious factors in goats. The aim of this paper was to define adjusted action thresholds of somatic cell count for the detection of goats with intramammary infections. A secondary aim was to investigate the potential of bulk milk analyses in identifying herds with udder health issues. Nine Norwegian dairy goat herds were visited five times during one lactation. Somatic cell count measurements combined with bacteriological testing were performed both at goat and herd level. Results Staphylococcus (S.) aureus was the udder pathogen with the strongest influence on the somatic cell count and was therefore selected as the focus of udder health control. The period prevalence of S. aureus in the included herds varied from 1 to 40%. The thresholds for identifying goats with S. aureus intramammary infection varied from 500,000 cells/mL in first parity goats in early lactation to 3 million cells/mL in goats of higher parities on pasture. A herd prevalence of S. aureus of more than approximately 10% was associated with significant bulk milk quality challenges. Conclusions The study defined adjusted action thresholds of somatic cell count for the detection of intramammary infections in dairy goats. The somatic cell count levels in goats with S. aureus were in most cases well distinguished from those with no or minor pathogen findings when adjusting according to parity, pasture-status, and lactation stage. The patterns of routinely measured bulk milk parameters, along with analyses of bacteriological composition, provided a rough indication of the herd’s udder health status.

Amiata donkeys are a native breed reared in central Italy. Safeguarding native donkey breeds represents an opportunity for the development of marginal areas, especially given that donkey milk is now appearing on the market due to its potential benefits for human health. To date, only a few studies have focused on the characteristics of the milk fat globules (MFGs) in the donkey species. The aim of this study was to assess the morphometric characteristics of the fat globules, gross composition and fatty acid classes in milk from Amiata donkeys reared according to the typical farming and feeding systems of the area of origin. Individual milk samples, collected from 28 Amiata donkeys between 90 and 150 days of lactation, showed the following average composition (g/100 mL): 9.47 dry matter, 1.63 protein, 0.78 casein, 0.53 fat, 7.12 lactose, and 0.36 ash. The unsaturated:saturated fatty acids ratio in milk was close to 1. The percentage of short chains was 12.29, and the percentage of long chain fatty acids was 47.64. The donkey MFGs showed an average diameter of 1.92 μm, and a number of 2.18*10 9 /mL. Regarding MFG distribution, 70% of the globules donkey of milk are smaller than 2 μm. In conclusion, the gross composition and fatty acids of Amiata donkey milk showed similarities with milk from other Italian donkey breeds, with the exception of the monounsaturated fatty acid values which were slightly higher. Donkey MFGs had a smaller diameter and were fewer than in the ruminant species.

This study examines the contributions of various countries to milk quality research over the past 27 years (1997–2024) using bibliometric analysis of data retrieved from the Scopus database. The study aims to highlight the efforts required by governments to enhance research in this field. The analysis employs bibliometric tools, including VOSviewer, Scimago Graphica, Bibliometrix, and Microsoft Excel, to visualize data and conduct network analysis. The findings indicate a 13% increase in the number of publications related to milk quality. China leads in the number of publications, with 1,178 documents, whereas Italy excels in journal publications, contributing 188 journals and 388 institutions, accounting for 27.80% of the global total. China also dominates research funding, with 159 institutions representing 26.63% of global funding entities. In terms of citation impact, the United States ranks first with 2,953 citations, followed by Italy, China, and Brazil. This study provides valuable insights into dairy cattle research, particularly milk quality, through bibliometric analysis and a scoping review. The findings can assist stakeholders in identifying research trends, gaps, and innovations, thereby informing strategies to enhance milk production, nutritional quality, and sustainable dairy practices.

Monitoring the composition of milk products is an important factor in the management of dairy farms and industry. Information on the quantitative content of milk components is necessary to control milk quality, as well as to optimize dairy cow nutrition and diagnose their clinical condition. The content of fat and protein is considered the main criterion for determining the market value of milk. Increasing the efficiency of dairy production requires the use of inexpensive and compact devices that are capable of performing multicomponent analysis of milk both directly on the farm and in technological lines. We investigated the possibility of fast simultaneous determination of fat and protein content in milk by laser polarimetric scatterometry. The block-diagonal elements of the scattering matrix were measured for a series of commercially produced milk samples with the indicated fat percentage, which were diluted by volume with water. From the measured scattering matrices, the size distributions of fat droplets and casein aggregates were reconstructed. Using the size histograms, the content of fat and protein and protein-to-fat ratio in the studied milk samples are estimated.

This Research Communication addresses the hypothesis that fat, protein, lactose and total solids content can be predicted using daily milk yield (DMY), pH, electrical conductivity (MEC) and refractive index (RI) of milk as predictors. It also addresses the possibility of these measurements being used for on-farm benchmarking activities towards selecting the highest yielding animals and flocks regarding milk quality traits (MQT). A total of 308 purebred Frizarta ewes were used for the study. From each individual ewe, a composite milk sample was collected. pH, MEC and RI of milk were measured and the samples were assayed for fat, protein, lactose and total solids content, using an automatic infrared milk analyser. The predictive value of DMY, pH, MEC and RI of milk on its MQT was assessed using multiple linear regression analysis. Significant regression equations were produced for all of the studied traits. RI and MEC were significant and reliable predictors for all studied MQT, whereas DMY was a significant predictor for most MQT with the exception of protein content. pH was a marginally significant predictor for some of the MQTs at the initial development of the equations but proved unreliable after bootstraping. Using these equations a number of ewes varying from 75 (for fat) to 97 (for protein) out of the 100 highest MQT yielders were correctly predicted, whereas, none of the ewes out of the 100 lowest MQT yielders was mispredicted as a high yielder for protein-, lactose- and total solids- content. Three out of 100 lowest fat-yielders were mispredicted as high fat-yielders. Similar equations can be used for benchmarking activities towards selecting the highest protein-, fat-, lactose- and total solids- yielding animals and flocks in cases where laboratories for MQT analyses are not readily available or the cost of chemical analyses is high. The method can be regarded as a handy tool for the dairy industry to readily assess milk quality at the farm level.

The purpose of the present study was to evaluate the principal component analysis (PCA) to guide technical assistance regarding several dairy farms’ issues, which includes improving microbiological quality and physical-chemical composition of raw refrigerated milk. Data of monthly analysis of fat, protein, lactose, dry defatted stratum, somatic cell count, total bacterial count, milk temperature of 8,101 samples of milk from expansion tanks and production of 78 farms located in the northern region of Minas Gerais, Brazil were processed. Descriptive statistical measures and Pearson correlation coefficient were estimated involving all evaluated traits during the dry and rainy seasons. In addition, multivariate analyses were performed using PCA. The results showed that two farm sites were negatively related to milk quality in both seasons. One farm stood out positively, being able to be used as a herd management model to drive technical assistance actions. Thus, PCA is efficient in simplifying large amounts of data, allowing simpler and faster technical herd management interpretation. 

The study aimed to evaluate the use of the azidiol® preservative for psychrotrophic microorganism count (PMC) in cooled raw milk. Two studies were carried out, one under controlled conditions (experiment 1) and the other under field conditions (experiment 2), in which samples of raw milk were taken with and without the use of the azidiol® preservative and analyzed at predefined times (0, 6, 12 and 24 hours - experiment 1) and at varying times (experiment 2). Analysis of variance and regression analysis using SAS were applied for data statistical analysis. Milk samples without azidiol® showed higher PMC with increasing time between sampling and analysis, while in samples preserved with azidiol®, this count remained constant. Samples of cooled raw milk intended for PMC should be collected in flasks containing the azidiol® preservative.