Total and differential bulk cow milk somatic cell counts and their relation with lipolysis

The determination of mastitis severity at 4-level using Milk physical properties: A deep learning approach via MLP and evaluation at different SCC thresholds

Current research aims to generate an alternative model to classical methods in the determination of subclinical mastitis at 4 levels (healthy, suspicious, subclinical, and clinical). For this purpose, multilayer perceptron (MLP) artificial neural networks (ANN) was developed as test model. 5 variables from the physical properties of milk somatic cell count (SCC), electrical conductivity (EC), pH, density, and temperature at fore milking (TFM) were included in the model in the classification of mastitis. Model performance was validated on test data (%25) and compared with the multinomial logistic regression (MNLR). MLP model has shown a satisfactory performance with an accuracy of 95.14% and - 141 of AIC score better than the control model (MNLR) of 80.27% and - 133 AIC despite using higher number of parameters (104). Since the main problem is to diagnose subclinical mastitis, which does not cause any visible symptoms, it was important to distinguish between absolute subclinical (suspicious excluded positives) and absolute healthy (suspicious included positives) ones. Therefore, optimum cut-off threshold was evaluated for these two different scenarios with only variable SCC the gold standard indicator of subclinical mastitis and results were compared in the interpretation of model performance. The results show that the 5-variable MLP model exhibits a high sensitivity of 93.22% (AUC = 0.95 for healthy ones) at low cutoff thresholds as well. New studies should provide a better understanding by evaluating economics, sustainability, animal welfare and health aspects together to determine the optimal threshold value.

Estimating the nonlinear interaction between somatic cell score and differential somatic cell count on milk production by parity using generalized additive models

This observational study aimed to use somatic cell score (SCS) and differential somatic cell count (DSCC), the combined proportion of polymorphonuclear leukocytes and lymphocytes in somatic cells, to investigate how mastitis affected milk production. Using generalized additive models, we analyzed 50,618 test-day records from 8,081 lactations from 7,912 cows in 197 herds between January 2021 and March 2022 to estimate the nonlinear interaction between SCS and DSCC, and the effects of lactation stages and seasons on milk yield, milk component percentages, and milk component yields by parity of cows. The results show that the interaction between SCS and DSCC on these traits was significant, nonlinear, and complex. When DSCC was high, the negative effects of SCS were minimal, even when SCS reached 8 (i.e., 3,200,000 somatic cells/mL). Cows with high DSCC could have milk yields similar to healthy cows, implying that these cows may have been in the early stages of mastitis and that the milk yield had yet to be affected. Contrastingly, when DSCC was low, milk loss due to high SCS was drastic, especially for cows in third or later lactations, whose milk yield could reduce from more than 35 kg/d to less than 15 kg/d (-59.9%). This tremendous milk loss in high-parity cows was likely due to their higher milk yield and higher risks of chronic mastitis. High SCS and low DSCC also led to a pronounced change in milk composition. The decrease in the percentage of lactose can be directly related to the damage of inflammation to the mammary gland, while the increase in fat and protein percentages was more attributable to the concentration effect resulting from the reduced milk yield. Compared with analyses based on categorized SCS and DSCC values, modeling these 2 indices directly helps us more precisely assess mastitis effects on milk yield and milk composition. For efficient milk production, our results indicate that we should prevent high-parity cows from entering a state of high SCS and low DSCC.

The relationship of bovine milk somatic cell count to neutrophil level in samples of cow's milk assessed by an automatic cell counter

This research communication describes the application of a fluorescent automatic cell counter Lactoscan SCC for simultaneous determination of somatic cell count and neutrophils in bovine milk. The obtained results were compared with results obtained by a flow cytometer and a light microscope. The Pearson correlations between the methods were calculated. A comparison between the main characteristics of the three kinds of analysis was made - the assay duration and the intra-assay precision. A relation between the SCC and neutrophil cells was observed in 55 milk samples. The obtained results confirm that the simultaneous determination of SCC and neutrophil analysis are necessary and support the early diagnosis of mastitis, the timely treatment of the animal and the avoidance of major economic losses.

Associations between differential somatic cell count and milk yield, quality, and technological characteristics in Holstein cows

The aim of this study was to investigate the associations between differential somatic cell count (DSCC) and milk quality and udder health traits, and for the first time, between DSCC and milk coagulation properties and cheesemaking traits in a population of 1,264 Holstein cows reared in northern Italy. Differential somatic cell count represents the combined proportions of polymorphonuclear neutrophils plus lymphocytes (PMN-LYM) in the total somatic cell count (SCC), with macrophages (MAC) making up the remaining proportion. The milk traits investigated in this study were milk yield (MY), 8 traits related to milk composition and quality (fat, protein, casein, casein index, lactose, urea, pH, and milk conductivity), 9 milk coagulation traits [3 milk coagulation properties (MCP) and 6 curd firming (CF) traits], 7 cheesemaking traits, 3 cheese yield (CY) traits, and 4 milk nutrient recovery in the curd (REC) traits. A linear mixed model was fitted to explore the associations between SCS combined with DSCC and the aforementioned milk traits. An additional model was run, which included DSCC expressed as the PMN-LYM and MAC counts, obtained by multiplying the percentage of PMN-LYM and MAC by SCC in the milk for each cow in the data set. The unfavorable association between SCS and milk quality and technological traits was confirmed. Increased DSCC was instead associated with a linear increase in MY, casein index, and lactose proportion and a linear decrease in milk fat and milk conductivity. Accordingly, DSCC was favorably associated with all MCP and CF traits (with the exception of the time needed to achieve maximum, CF), particularly with rennet coagulation time, and it always displayed linear relationships. Differential somatic cell count was also positively associated with the recovery of milk nutrients in the curd (protein, fat, and energy), which increased linearly with increasing DSCC. The PMN-LYM count was rarely associated with milk traits, even though the pattern observed confirmed the results obtained when both SCS and DSCC were included in the model. The MAC count, however, showed the opposite pattern: MY, casein index, and lactose percentage decreased and milk conductivity increased with an increasing MAC count. No significant association was found between PMN-LYM count and MCP, CF, CY, and REC traits, whereas MAC count was unfavorably associated with MCP, CF traits, some CY traits, and all REC traits. Our results showed that the combined information derived from SCS and DSCC might be useful to monitor milk quality and cheesemaking-related traits.

Differential Somatic Cell Count as a Novel Indicator of Milk Quality in Dairy Cows

Recent available instruments allow to record the number of differential somatic cell count (DSCC), representing the combined proportion of polymorphonuclear leukocytes and lymphocytes, on a large number of milk samples. Milk DSCC provides indirect information on the udder health status of dairy cows. However, literature is limited regarding the effect of DSCC on milk composition at the individual cow level, as well as its relation to the somatic cell score (SCS). Hence, the aims of this study were to (i) investigate the effect of different levels of DSCC on milk composition (fat, protein, casein, casein index, and lactose) and (ii) explore the combined effect of DSCC and SCS on these traits. Statistical models included the fixed effects of days in milk, parity, SCS, DSCC and the interaction between SCS × DSCC, and the random effects of herd, animal within parity, and repeated measurements within cow. Results evidenced a decrease of milk fat and an increase in milk fatty acids at increasing DSCC levels, while protein, casein and their proportion showed their lowest values at the highest DSCC. A positive association was found between DSCC and lactose. The interaction between SCS and DSCC was important for lactose and casein index, as they varied differently upon high and low SCS and according to DSCC levels.

Advances in research on cis-9, trans-11 conjugated linoleic acid: a major functional conjugated linoleic acid isomer

Conjugated linoleic acid (CLA) consists of a group of positional and geometric conjugated isomers of linoleic acid. Since the identification of CLA as a factor that can inhibit mutagenesis and carcinogenesis, thousands of studies have been conducted in the last several decades. Among the many isomers discovered, cis-9, trans-11 CLA is the most intensively studied because of its multiple, isomer-specific effects in humans and animals. This paper provides an overview of the available data on cis-9, trans-11 CLA, including its isomer-specific effects, biosynthesis, in vivo/in vitro research models, quantification, and the factors influencing its content in ruminant products.

Evaluation of Tunisian milk quality in dairy herds: Inter-relationship between chemical, physical and hygienic criteria

The objective of this paper was to evaluate the global milk quality in Tunisian dairy herds. Samples of milk were analyzed for chemical, physical and hygienic parameters. Milk total solids, fat content and density were consistently correlated and one of them can be used as a chemical indicator of milk quality. The somatic cell count value of 689 × 10(3) /mL was higher than the recommended threshold. All milk samples were positive for the major pathogen Staphylococcus aureus. These hygienic parameters were related more closely with chloride content, minerals and electrical conductivity, which allows them to be used as indicators of mammary gland infection. It was concluded that milk producers have at hand rapid and easy tools for assessing the overall quality of milk.

Analysis of raw milk quality at reception and during cold storage: combined effects of somatic cell counts and psychrotrophic bacteria on lipolysis

The objective of the article was to analyze the influence of psychrotrophic bacteria counts (PBCs) and somatic cell counts (SCCs) on the extent of lipolysis in bulk samples of cow's milk at reception and during cold storage. Samples of milk were analyzed on the day of sampling and subsequently during cold storage. The acidity, fat, density, chloride content, electrical conductivity (EC), bulk milk SCCs (BMSCC), and PBC values were analyzed on the day of sampling and the levels of acidity, EC, SCC, and PBC were analyzed during cold storage at 4 °C for 72 h. The SCC value 869 × 10(3) mL(-1) was higher than the recommended threshold. Lipolysis level at sampling day was related more closely with SCC than with PBC. There was no significant correlation between milk acidity and PBC among others parameters, while the milk mean density was only significant (P < 0.01) correlated with the fat content. The EC and chloride content were consistently correlated (P < 0.001) with BMSCC that allowed them to be used as indicators of mammary gland infection. The milk acidity, EC, PBC, and lipolysis levels increased in relation to the storage time at 4 °C. The lipolysis level during storage was in closer relation to the SCC, but not relation to the PBC. Effects of SCC and PBC on lipolysis decreased throughout the chilling period. It was concluded that initial lipolysis level and intrinsic milk lipoprotein lipase appear more effective than SCC and PBC on the development of lipolysis during storage.

The effect of multiplex-PCR-assessed major pathogens causing subclinical mastitis on somatic cell profiles

The major pathogens causing mastitis were evaluated by multiplex-polymerase chain reaction (M-PCR) with self-designed primers in four quarters of the first, third, and fifth parities in industrial, semi-industrial, and traditional dairy cattle farms in Iran. With the incidence of infection in the quarters by Staphylococcus aureus and Streptococcus agalactiae, the mean log somatic cell count (log SCC) increased from 5.06 to 5.77. The smallest changes occurred with Escherichia coli. Contagious pathogens, when compared with environmental pathogens, were more prevalent and common and created more profound quantitative and qualitative changes in SCC profiles. The second part of the study surveyed the diversity of contaminating pathogens and their effect on quantitative and qualitative profiles of somatic cells. M-PCR was used to determine the absence (M-PCR(-)) and presence of one (M-PCR(+1)), two (M-PCR(+2)), and three (M-PCR(+3)) major pathogens in raw milk samples. Quarter log SCC increased from 5.06 (for M-PCR(-1)) to 5.5 (for M-PCR(+1)), 5.7 (for M-PCR(+2)), and 6 (for M-PCR(+3)). Percent changes in polymorphonuclears (PMNs) were not significant between different quarters and parities but were significant between different farms in terms of pathogen diversity (P < 0.05). Therefore, by increasing the number of types of major pathogens involved in subclinical mastitis, SCC of udder quarters and the proportion of PMNs significantly increased, whereas the proportion of lymphocytes significantly decreased. This subject is very important in increasing the shelf life of dairy products, because PMNs are introduced to the enzymatic pools.

Somatic cells count in cow's bulk tank milk

The objective of this study was therefore to present factors affecting somatic cell counts in bovine bulk milk as a result of intramammary infections as well as non-infectious factors. The paper presents also the impact of on-farm management practices on the level of bulk milk somatic cell counts and presents quality indicators in bulk tank milk. At the farm level bulk milk bacterial infection takes place through three main sources: bacterial contamination from the external surface of the udder and teats, from the surface of the milking equipment, and from mastitis microorganisms within the udder. The threshold of 200,000 cells/ml identifies bacteriological negative quarters of the udder. The counts of mammary pathogens in bulk tank milk are relatively low, on average not exceeding 1,000 cfu/ml. Environmental pathogens predominate in bulk tank milk samples with somatic cells count <300 × 10(3) ml.

Microbiological quality of raw milk produced in Estonia

AIMS

The microbial quality of farm bulk-tank raw milk produced in Estonia during years 2004-2007 was investigated.

METHODS AND RESULTS

Bulk-tank milk samples were analysed for lactic acid bacteria count (LABC), psychrotrophic bacteria count (PBC), aerobic spore-forming bacteria count (ASFBC), total bacterial counts using BactoScan and somatic cell count (SCC) using Fossomatic. Randomly selected psychrotrophic isolates were subjected to 16S-23S PCR-ribotyping. LABC remained below 10(4) CFU ml(-1) in most samples, while psychrotrophic micro-organisms dominated in 60% of farms. PBC ranged from 4.2 × 10(2) to 6.4 × 10(4) CFU ml(-1), and ASFBC varied from 5 to 836 CFU ml(-1).

CONCLUSIONS

In general, the microbiological quality of the farm bulk-tank milk was good - more than 91% of samples contained <50,000 CFU ml(-1), and SCC in the majority of samples did not exceed the internationally recommended limits. Genus Pseudomonas spp. was the dominating spoilage flora with Pseudomonas fluorescens as the prevailing species.

SIGNIFICANCE AND IMPACT OF THE STUDY

Specific bacterial groups (LABC, PBC and ASFBC), not analysed routinely by dairies, were determined in bulk-tank raw milk of numerous dairy farms during 4-year period. Based on the survey, dairy plants can better control their supply chains and select farms (milk) for the production of specific products, i.e. milk with low PBC and high LABC for cheesemaking.

Relationship between somatic cell count, polymorphonuclear leucocyte count and quality parameters in bovine bulk tank milk

The somatic cell count (SCC) in bovine bulk tank milk is presently used as an indicator of raw milk quality, reflecting the udder health status of the herd. During mastitis, SCC increases, mostly owing to an influx of polymorphonuclear leucocytes (PMN) from blood into milk, with a concomitant change in milk composition. Bulk tank milk samples were categorized according to their SCC, as well as polymorphonuclear leucocyte count (PMNC), to study relationships between SCC, PMNC and various raw milk quality traits, i.e. contents of total protein, whey protein, casein, fat and lactose, casein number, proteolysis and rheological properties. The proportion of PMN, obtained by direct microscopy, was significantly higher in samples with high SCC compared with low SCC samples. SCC and PMNC were strongly correlated, yielding a correlation coefficient of 0·85. High SCC samples had lower lactose and casein contents, lower casein number and more proteolysis than low SCC samples. Samples with high PMNC had a lower casein number than low PMNC samples. Samples with high and low SCC or PMNC did not differ in respect to rheological properties. Our results do not indicate that PMNC is a better biomarker than SCC for raw bulk tank milk quality, as previously proposed.