Fat and protein contents, acidity and somatic cell counts in bulk milk of Holstein cows in the Khorasan Razavi Province, Iran

Relationships between total bulk milk somatic cell score (SCS) and milk fat and protein contents and acidity were investigated in the Khorasan Razavi Province, a region that contributes 6.83% of total milk production in Iran. A total of 1476 samples were analysed. Data were obtained by randomly collecting 123 samples of bulk tank milk from 41 dairy farms during April 2006 to March 2007, every month. Milk was analysed for titratable acidity, protein and fat contents and somatic cell counts (direct microscopic cell count and with Somatos, Russia). Microscopic and Somatos somatic cell counts were comparable. Results showed that the season of raw milk production did not have a significant effect on acidity. Milk fat content increased gradually from spring to winter and there were significant differences ( P <  0.05) between spring and other seasons. Higher levels of milk protein fractions were observed during the autumn and winter than in other seasons. The highest total bulk milk somatic cell counts were observed in July. Total bulk milk SCS had significant effects ( P <  0.05) on acidity and fat and protein contents. Moreover, the level of acidity and fat in milk decreased with increasing SCS. A significant positive relationship was observed between total bulk milk SCS and the protein content of milk. Elevated SCS were associated with lowered milk quality in Holsteins in the Khorasan Razavi Province.     

Effect of storage and separation of milk at udder quarter level on milk composition, proteolysis, and coagulation properties in relation to somatic cell count

Coagulation properties of milk are altered by elevated somatic cell count (SCC), partly due to increased proteolytic and lipolytic activity in the milk and, thereby, degradation of protein and fat during storage. Milk is commonly stored on the farm at cooling conditions for up to 2 d before transport to the dairy for processing. This study evaluated the effects of storage on milk with altered composition due to high SCC and the effects of exclusion of milk from individual udder quarters with high SCC on milk composition, proteolysis, and coagulation properties. Udder-quarter milk and cow-composite milk samples from 13 cows having at least 1 quarter with SCC above 100,000 cells/mL were collected on 1 occasion. In addition, commingled milk from only healthy quarters (<100,000 cells/mL) of each cow was collected, representing a cow sample where milk with elevated SCC was excluded. The milk samples were analyzed for total protein content; protein content in the whey fraction; casein, fat, and lactose contents; SCC; proteolysis; curd yield; coagulation time; and total bacterial count, on the day of sampling and after 2 and 5 d of storage at +4°C. In addition to SCC, duration of storage and total bacterial count had an effect on milk quality. The content of total protein, fat and protein contents in the whey fraction, and curd yield were found to have different storage characteristics depending on the level of SCC at udder-quarter level. The exclusion of milk from udder quarters with elevated SCC decreased the content of total protein and protein content in the whey fraction and increased the content of lactose at cow level. However, the effect of separating milk at udder-quarter level needs to be further studied at bulk tank level to evaluate the effect on overall total milk quality.     

Short communication: Relationships between α-lactalbumin and quality traits in bulk milk

The main objective of this study was to investigate whether the α-lactalbumin (α-LA) content of bulk milk is related with some known inflammatory markers and milk quality traits. An additional objective was to study whether combining α-LA, haptoglobin (Hp), and serum amyloid A (SAA) in an acute phase index (API) could be useful as an alternative marker for bulk milk quality. For the dairy industry, it is of great importance to receive high quality bulk milk for manufacture of liquid milk and dairy products. The somatic cell count (SCC) is currently used as an indirect marker for bulk milk quality, but because it is somewhat insensitive and unspecific, interest exists in alternative markers. Bulk milk samples were analyzed for α-LA, SCC, polymorphonuclear leukocyte count, Hp, SAA, fat, lactose, total protein and casein contents, casein number, protein composition, proteolysis, and coagulating properties. No significant differences were found in SCC, polymorphonuclear leukocyte count, Hp, or SAA between milk samples containing low, medium, or high concentrations of α-LA. Differences between α-LA groups were, however, found in some milk quality traits because high α-LA concentration was related to low concentrations of α_S1-, α_S2-, and β-caseins and high concentrations of lactose and β-lactoglobulin. A high API was related to low lactose content and casein number. Samples with high SCC contained less casein and had a lower casein number than milk with a low SCC, and proteolysis was significantly higher in high SCC milk than in low SCC milk. Neither α-LA nor API proved to be a better marker than SCC for the quality traits investigated, and α-LA was not considered to be a useful inflammatory marker in bulk milk.     

Relationship between haptoglobin and serum amyloid A in milk and milk quality

The objective of this study was to evaluate relationships between the presence in milk of the major bovine acute phase proteins, haptoglobin (Hp) and serum amyloid A (SAA), and milk quality parameters. Composite milk samples were collected from 89 clinically healthy dairy cows and analysed for Hp and SAA, total protein, casein, and whey protein levels, casein number, proteolysis, total fat and lactose levels, and somatic cell count (SCC). Milk samples with detectable levels of Hp showed lower total protein and casein levels than those samples without Hp, whereas milk samples with detectable levels of SAA had lower casein number and lactose level than samples without detectable SAA. Samples with detectable levels of acute phase proteins also showed an elevated SCC. The results suggest that the presence of Hp and SAA in milk might indicate unfavourable changes in milk composition, especially in relation to protein quality.     

Process audits versus product quality monitoring of bulk milk

Assessment of milk quality is based on bulk milk testing and farm certification on process quality audits. It is unknown to what extent dairy farm audits improve milk quality. A statistical analysis was conducted to quantify possible associations between bulk milk testing and dairy farm audits. The analysis comprised 64.373 audit outcomes on 26,953 dairy farms, which were merged with all conducted laboratory tests of bulk milk samples 12 mo before the audit. Each farm audit record included 271 binary checklist items and 52 attention point variables (given to farmers if serious deviations were observed), both indicating possible deviations from the desired farm situation. Test results included somatic cell count (SCC), total bacterial count (TBC), antimicrobial drug residues (ADR), level of butyric acid spores (BAB), freezing point depression (FPD), level of free fatty acid (FFA), and milk sediment (SED). Results show that numerous audit variables were related to bulk milk test results, although the goodness of fit of the models was generally low. Cow hygiene, clean cubicles, hygiene of milking parlor, and utility room were positively correlated with superior product quality, mainly with respect to SCC, TBC, BAB, FPD, FFA, and SED. Animal health or veterinary drugs management (i.e., drug treatment recording, marking of treated animals, and storage of veterinary drugs) related to SCC, FPD, FFA, and SED. The availability of drinking water was related to TBC, BAB, FFA, and SED, whereas maintenance of the milking equipment was related mainly to SCC, FPD, and FFA. In summary, bulk milk quality and farm audit outcomes are, to some degree, associated: if dairy farms are assessed negatively on specific audit aspects, the bulk milk quality is more likely to be inferior. However, the proportion of the total variance in milk test results explained by audits ranged between 4 and 13% (depending on the specific bulk milk test), showing that auditing dairy farms provides additional information but has a limited association with the outcome of a product quality control program. This study suggests that farm audits could be streamlined to include only relevant checklist items and that bulk milk quality monitoring could be used as a basis of selecting farms for more or less frequent audits.     

Effects of indirect indicators of udder health on nutrient recovery and cheese yield traits in goat milk

In dairy goats, very little is known about the effect of the 2 most important indirect indicators of udder health [somatic cell count (SCC) and total bacterial count (TBC)] on milk composition and cheese yield, and no information is available regarding the effects of lactose levels, pH, and NaCl content on the recovery of nutrients in the curd, cheese yield traits, and daily cheese yields. Because large differences exist among dairy species, conclusions from the most studied species (i.e., bovine) cannot be drawn for all types of dairy-producing animals. The aims of this study were to quantify, using milk samples from 560 dairy goats, the contemporary effects of a pool of udder health indirect indicators (lactose level, pH, SCC, TBC, and NaCl content) on the recovery of nutrients in the curd (%REC), cheese yield (%CY), and daily cheese yields (dCY). Cheese-making traits were analyzed using a mixed model, with parity, days in milk (DIM), lactose level, pH, SCC, TBC, and NaCl content as fixed effects, and farm, breed, glass tube, and animal as random effects. Results indicated that high levels of milk lactose were associated with reduced total solids recovery in the curd and lower cheese yields, because of the lower milk fat and protein contents in samples rich in lactose. Higher pH correlated with higher recovery of nutrients in the curd and higher cheese yield traits. These results may be explained by the positive correlation between pH and milk fat, protein, and casein in goat milk. High SCC were associated with higher recovery of solids and energy in the curd but lower recovery of protein. The higher cheese yield obtained from milk with high SCC was due to both increased recovery of lactose in the curd and water retention. Bacterial count proved to be the least important factor affecting cheese-making traits, but it decreased daily cheese yields, suggesting that, even if below the legal limits, TBC should be considered in order to monitor flock management and avoid economic losses. The effect of NaCl content on milk composition was linked with lower recovery of all nutrients in the curd during cheese-making. In addition, high milk NaCl content led to reductions in fresh cheese yield and cheese solids. The indirect indicators of the present study significantly affected the cheese-making process. Such information should be considered, to adjust the milk-to-cheese economic value and the milk payment system.     

Influence of milk components,somatic cells and supplemental zinc on milk processability

Individual milk samples from cows given different amounts of supplemental zinc were analysed for somatic cell count (SCC) and milk composition. The concentrations of immunoglobulins (IgA, IgG1, IgG2 and IgM), lactoferrin (LF), bovine serum albumin as well as total fat, total protein and lactose were analysed. The growth of starter cultures in milk samples was studied by the conductance technique used as a model for processability of milk. The concentrations of IgA, IgG2, IgM and LF as well as conductance measurements were found to be markers of processability in addition to SCC. Relatively low SCC in milk affected the growth of starter culture with a delayed start of the fermentation process up to 2–4 h. Supplemental zinc influenced the concentration of IgA, IgG2, IgM and LF while no effect on SCC was observed. The lag phase for growth of starter cultures was prolonged in milk from cows given additional zinc.     

Effect of extended storage on microbiological quality, somatic cell count, and composition of raw goat milk on a farm

Dairy goat herds in the United States generally are small, widely scattered, and distant from processing facilities. Unlike the situation for cow milk, it is not cost-effective to collect goat milk everyday or every other day. In some areas, goat milk is collected only once each week, which is in violation of regulations specified in the Pasteurized Milk Ordinance for grade A milk. This study was conducted to determine the effect of up to 7 days of refrigerated bulk tank storage on composition, somatic cell count (SCC), pH, and microbiological quality of goat milk. Duplicate farm bulk tank samples were taken daily after the morning milking for seven consecutive days each month during the lactation season. Samples were analyzed immediately for all variables except free fatty acids. There were no significant changes (P > 0.05) detected in milk fat, protein, lactose, nonfat solids, SCC, or pH during extended storage, although significant effects of stage of lactation (P < 0.05) were observed. The mean standard plate count (SPC) increased to 1.8 x 10(5) CFU/ml after 6 days of storage, exceeding the grade A limit (i.e., 1.0 x 10(5) CFU/ml). The mean psychrotrophic bacteria count increased steadily to 1.5 x 10(4) CFU/ml after 6 days of storage, whereas the mean coliform count was approximately 500 CFU/ml for the first 3 days and less than 2500 CFU/ml throughout the 7 days of storage. No significant changes (P > 0.05) in the concentrations of free fatty acids, except for butyric and caprylic acids, were observed during milk storage. When stored under refrigerated and sanitary conditions, goat milk in farm bulk tanks met the grade A criteria for both SPC and SCC during 5 days of storage but was of low quality thereafter because of the growth of psychrotrophic bacteria.     

Within-herd prevalence of intramammary infection caused by Mycoplasma bovis and associations between cow udder health,milk yield,and composition

Subclinical mastitis is one of the major health problems in dairy herds due to decreased milk production and reduced milk quality. The aim of this study was to examine the within-herd prevalence of subclinical intramammary infection caused by Mycoplasma bovis and to evaluate associations between M. bovis and cow daily milk yield, udder health, and milk composition. Individual cow composite milk samples (n = 522) were collected from all lactating dairy cows in 1 Estonian dairy farm in November 2014. Daily milk yield, days in milk, and parity were recorded. Collected milk samples were analyzed for somatic cell count, milk protein, fat, and urea content. The presence of M. bovis, Staphylococcus aureus, Streptococcus agalactiae, and Streptococcus uberis in the milk samples was confirmed by quantitative PCR analysis. The within-herd prevalence of M. bovis was 17.2% in the study herd. No association was observed between days in milk and parity to the presence of M. bovis in milk. According to linear regression analysis, the daily milk yield from cows positive for M. bovis was on average 3.0 kg lower compared with cows negative for M. bovis. In addition, the presence of M. bovis in milk samples was significantly associated with higher somatic cell count and lower fat and urea content compared with milk samples negative for M. bovis. In conclusion, subclinical M. bovis intramammary infection is associated with decreased milk yield and lower milk quality.     

不同体细胞数的原料乳品质变化的比较研究

通过分析比较5组不同体细胞数(SCC)原料乳的主要成分和特性(蛋白质、脂肪含量、酪蛋白的含量等)、脂肪分解情况(脂肪酶活力、游离脂肪酸及其占总脂肪的比例)以及蛋白质水解程度(水溶性氮、非蛋白氮占总氮的比例以及酪蛋白构成)的变化情况,探讨不同SCC对原料乳品质的影响。结果表明：当SCC小于4.0×105个/mL时,原料乳的成分没有显著的差异(P＞0.05);随着SCC的增大,原料乳的脂肪水解程度增强,但SCC小于4.0×105个/mL的两组原料乳的脂肪水解程度没有显著差异(P＞0.05);不同SCC原料乳的酪蛋白构成表现不同,其蛋白质水解程度(WSN/TN,NPN/TN)随SCC的增大而增加,但SCC在4.0×105 个/mL以下的两组原料乳的蛋白水解程度没有显著差异(P＞0.05)。     

Effects of somatic cell counts on the physicochemical and rheological properties of yoghurt made from sheep’s milk

In the present work, yoghurts were made from sheep’s milk with two different somatic cell count (SCC), at low (200 000 cells mL^?1) and high (750 000 cells mL^?1) levels. The characteristics of the final product were analysed for pH, acidity, protein, total solids, fat, syneresis, water holding capacity (WHC) and apparent viscosity. Samples were analysed on days 1, 7 and 14 after production of yoghurts. The SCC had no significant effect either on the acidity or pH of the yoghurt at 24 h (P > 0.05) but a significant effect (P < 0.05) was observed at 168 h. No effects of SCC were observed on total solids and fat content of the yoghurt after 24 and 168 h. High SCC (HSCC) yoghurt had higher protein content (P < 0.05). The yoghurt with the highest SCC had the highest level of syneresis. Viscosity of HSCC yoghurt was higher than that of the low SCC yoghurt on days 1, 7 and 14 of storage. The flow properties also showed that the low SCC yoghurt was softer than that from milk with high content in somatic cells.     

Factors associated with herd bulk milk composition and technological traits in the Italian dairy industry

The aim of the present study was to investigate sources of variation of milk composition and technological characteristics routinely collected in field conditions in the Italian dairy industry. A total of 40,896 bulk milk records from 620 herds and 10 regions across Italy were analyzed. Composition traits were fat, protein, and casein percentages, urea content, and somatic cell score; and technological characteristics were rennet coagulation time, curd firming time, curd firmness 30 min after rennet addition to milk, and titratable acidity. Data of herd bulk milks were analyzed using a model that included fixed effects of region, herd nested within region, and season of milk analysis. An average good milk quality was reported in the dairy industry (especially concerning fat, protein, and casein percentages), and moderate to high correlations between composition and technological traits were observed. All factors included in the statistical model were significant in explaining the variation of the studied traits except for region effect in the analysis of casein and somatic cell score. Northeast and central-southern Italian regions showed the best performance for composition and technological features, respectively. Traits varied greatly across regions, which could reflect differences in herd management and strategies. Overall, less suitable milk for dairy processing was observed in summer. Results of the present study suggested that a constant monitoring of technological traits in the dairy industry is necessary to improve production quality at herd level and it may be a way to segregate milk according to its processing characteristics.     

Short communication: Repeatability of differential goat bulk milk culture and associations with somatic cell count, total bacterial count, and standard plate count

The aims of this study were to assess how different bacterial groups in bulk milk are related to bulk milk somatic cell count (SCC), bulk milk total bacterial count (TBC), and bulk milk standard plate count (SPC) and to measure the repeatability of bulk milk culturing. On 53 Dutch dairy goat farms, 3 bulk milk samples were collected at intervals of 2 wk. The samples were cultured for SPC, coliform count, and staphylococcal count and for the presence of Staphylococcus aureus. Furthermore, SCC (Fossomatic 5000, Foss, Hillerød, Denmark) and TBC (BactoScan FC 150, Foss) were measured. Staphylococcal count was correlated to SCC (r = 0.40), TBC (r = 0.51), and SPC (r = 0.53). Coliform count was correlated to TBC (r = 0.33), but not to any of the other variables. Staphylococcus aureus did not correlate to SCC. The contribution of the staphylococcal count to the SPC was 31%, whereas the coliform count comprised only 1% of the SPC. The agreement of the repeated measurements was low. This study indicates that staphylococci in goat bulk milk are related to SCC and make a significant contribution to SPC. Because of the high variation in bacterial counts, repeated sampling is necessary to draw valid conclusions from bulk milk culturing.     

Effect of somatic cell count on Prato cheese composition

The objective of this research was to evaluate the effect of 2 levels of somatic cell counts (SCC) in raw milk on Prato cheese composition, protein and fat recovery, cheese yield, and ripening. A 2 × 6 factorial design with 3 replications was performed in this study: 2 levels of SCC and 6 levels of storage time. Initially, 2 groups of dairy cows were selected to obtain low (<200,000 cells/ mL) and high (>600,000 cells/mL) SCC in milks that were used to manufacture 2 vats of cheese: 1) low SCC and 2) high SCC. Milk, whey, and cheese compositions were evaluated; clotting time was measured; and cheese yield, protein recovery, and fat recovery were calculated. The cheeses were evaluated after 5, 12, 19, 26, 33, and 40 d of ripening according to pH, moisture, pH 4.6 soluble nitrogen, 12% trichloroacetic acid soluble nitrogen as a percentage of total nitrogen, and firmness. High-SCC milk presented significantly higher total protein and nonprotein nitrogen and lower true protein and casein concentrations than did low-SCC milk, indicating an increased whey protein content and a higher level of proteolysis. Although the pH of the milk was not affected by the somatic cell level, the cheese obtained from high-SCC milk presented significantly higher pH values during manufacture and a higher clotting time. No significant differences in cheese yield and protein recovery were observed for these levels of milk somatic cells. The cheese from high-SCC milk was higher in moisture and had a higher level of proteolysis during ripening, which could compromise the typical sensory quality of the product.     

Risk-based audit selection of dairy farms

Dairy farms are audited in the Netherlands on numerous process standards. Each farm is audited once every 2 years. Increasing demands for cost-effectiveness in farm audits can be met by introducing risk-based principles. This implies targeting subpopulations with a higher risk of poor process standards. To select farms for an audit that present higher risks, a statistical analysis was conducted to test the relationship between the outcome of farm audits and bulk milk laboratory results before the audit. The analysis comprised 28,358 farm audits and all conducted laboratory tests of bulk milk samples 12 mo before the audit. The overall outcome of each farm audit was classified as approved or rejected. Laboratory results included somatic cell count (SCC), total bacterial count (TBC), antimicrobial drug residues (ADR), level of butyric acid spores (BAB), freezing point depression (FPD), level of free fatty acids (FFA), and cleanliness of the milk (CLN). The bulk milk laboratory results were significantly related to audit outcomes. Rejected audits are likely to occur on dairy farms with higher mean levels of SCC, TBC, ADR, and BAB. Moreover, in a multivariable model, maxima for TBC, SCC, and FPD as well as standard deviations for TBC and FPD are risk factors for negative audit outcomes. The efficiency curve of a risk-based selection approach, on the basis of the derived regression results, dominated the current random selection approach. To capture 25, 50, or 75% of the population with poor process standards (i.e., audit outcome of rejected), respectively, only 8, 20, or 47% of the population had to be sampled based on a risk-based selection approach. Milk quality information can thus be used to preselect high-risk farms to be audited more frequently.     

Influence of raw milk quality on fluid milk shelf life

Pasteurized fluid milk shelf life is influenced by raw milk quality. The microbial count and somatic cell count (SCC) determine the load of heat-resistant enzymes in milk. Generally, high levels of psychrotrophic bacteria in raw milk are required to contribute sufficient quantities of heat-stable proteases and lipases to cause breakdown of protein and fat after pasteurization. Sanitation, refrigeration, and the addition of CO2 to milk are used to control both total and psychrotrophic bacteria count. It is not uncommon for total bacterial counts of raw milk to be < 10,000 cfu/mL. In the past, fluid milk processors have not focused much attention on milk SCC. Increased SCC is correlated with increased amounts of heat-stable protease (plasmin) and lipase (lipoprotein lipase) in milk. When starting with raw milk that has a low bacterial count, and in the absence of microbial growth in pasteurized milk, enzymes associated with high SCC will cause protein and fat degradation during refrigerated storage, and produce off-flavors. As the ability to kill, remove, or control microbial growth in pasteurized refrigerated milk continues to improve, the original milk SCC will be the factor limiting the time of refrigerated storage before development of an off-flavor in milk. Most healthy cows in a dairy herd have a milk SCC < 50,000 cell/mL. Bulk tank SCC > 200,000 cell/mL are usually due to the contribution of high SCC milk from a small number of cows in the herd. Technology to identify these cows and keep their milk out of the bulk tank could substantially increase the value of the remaining milk for use in fluid milk processing. To achieve a 60- to 90-d shelf life of refrigerated fluid milk, fluid processors and dairy farmers need to work together to structure economic incentives that allow farmers to produce milk with the SCC needed for extended refrigerated shelf life.     

Factors affecting test-day milk composition in dairy ewes,and relationships amongst various milk components

A total of 7492 test-day observations for mean contents of fat, protein, casein, serum protein and lactose and individual laboratory cheese yield (ILCY) were obtained, at approximately monthly intervals, from 1119 ewes belonging to eight Churra dairy flocks. The effect of various factors on these variables was examined and phenotypic correlations among all traits were estimated. Least squares analyses showed significant effects of flock test-date, stage of lactation, age of ewe, and number of lambs weaned on almost all variables. Protein content and composition were not affected by the number of lambs weaned. ILCY had an unadjusted mean (26-55 kg cheese/100 l milk) close to those reported for real cheese yield in dairy ewes and was affected similarly to the main milk components. Fat, protein, casein, and serum protein contents, and ILCY, showed a generally increasing trend as lactation progressed. These components reached a minimum at 1 month into lactation, when milk yield was highest, and increased for the remainder of the lactation. ILCY depended mainly on fat, protein and casein contents. Protein and casein contents were closely related and equally correlated with ILCY. An increase in somatic cell count (SCC) was associated with decreased milk yield and decreased lactose content.     

Guidelines for monitoring bulk tank milk somatic cell and bacterial counts

This study was conducted to establish guidelines for monitoring bulk tank milk somatic cell count and bacterial counts, and to understand the relationship between different bacterial groups that occur in bulk tank milk. One hundred twenty-six dairy farms in 14 counties of Pennsylvania participated, each providing one bulk tank milk sample every 15 d for 2 mo. The 4 bulk tank milk samples from each farm were examined for bulk tank somatic cell count and bacterial counts including standard plate count, preliminary incubation count, laboratory pasteurization count, coagulase-negative staphylococcal count, environmental streptococcal count, coliform count, and gram-negative noncoliform count. The milk samples were also examined for presence of Staphylococcus aureus, Streptococcus agalactiae, and Mycoplasma. The bacterial counts of 4 bulk tank milk samples examined over an 8-wk period were averaged and expressed as mean bacterial count per milliliter. The study revealed that an increase in the frequency of isolation of Staphylococcus aureus and Streptococcus agalactiae was significantly associated with an increased bulk tank somatic cell count. Paired correlation analysis showed that there was low correlation between different bacterial counts. Bulk tank milk with low (<5000 cfu/mL) standard plate count also had a significantly low level of mean bulk tank somatic cell count (<200,000 cells/mL), preliminary incubation count (<10,000 cfu/mL), laboratory pasteurization count (<100 cfu/mL), coagulase-negative staphylococci and environmental streptococcal counts (<500 cfu/mL), and noncoliform count (<200 cfu/mL). Coliform count was less likely to be associated with somatic cell or other bacterial counts. Herd size and farm management practices had considerable influence on somatic cell and bacterial counts in bulk tank milk. Dairy herds that used automatic milking detachers, sand as bedding material, dip cups for teat dipping instead of spraying, and practiced pre-and postdipping had significantly lower bulk tank somatic cell and/or bacterial counts. In conclusion, categorized bulk tank somatic cell and bacterial counts could serve as indicators and facilitate monitoring of herd udder health and milk quality.     

Genetic parameters of different measures of somatic cell counts in the Rendena breed

The objective of this study was to consider different and alternative methods of using somatic cell count (SCC) data recorded according to the Italian official milk recording system, estimating its genetic parameters and the correlations with the yield traits (milk, fat, and protein) in the Rendena breed. The SCC traits defined for genetic evaluation were somatic cell score, log of the total daily SCC (LTSCC, i.e., SCC multiplied by daily milk yield) individually recorded in a day of official control, and 3 different thresholds (≥80,000, ≥150,000, and ≥400,000 cells/mL) for somatic cells. A total of 187,052 test-day monthly records of milk, fat, and protein yields and SCC belonging to 11,718 cows were used to estimate heritability and genetic correlations between SCC and yield traits via a bi-trait repeatability test-day model using a Bayesian approach. The heritability values estimated for the threshold traits ranged from 0.036 to 0.065, less than those observed for monthly somatic cell score and LTSCC traits that were equivalent to 0.088 and 0.103, respectively. Higher genetic correlations were estimated between LTSCC trait and all productive traits (0.379 for milk, 0.240 for fat, and 0.370 for protein). The other SCC traits considered have shown low or almost null genetic correlations with the productive traits (from 0.008 between fat yield and SCC ≥150,000 cells/mL to 0.234 between protein yield and SCC ≥400,000 cells/mL) and almost all estimates included zero in the 95% highest posterior density region interval. These results indicated that genetic selection for milk, fat, and protein production negatively affects the LTSCC content and SCC ≥400,000 cells/mL but does not negatively influence the other somatic cell and threshold SCC traits in the Rendena breed. However, the complete framework of genetic relationships of SCC with all traits under selection should be considered when deciding on the possible inclusion of SCC in the breeding program of this small cattle population.     

Predicting somatic cell count standard violations based on herd's bulk tank somatic cell count. Part II: Consistency index

The present study examines the capability of 1,501 herds in the Upper Midwest and the performance of statistical process control charts and indices as a way of monitoring and controlling milk quality on the farm. For 24 mo, daily or every other day bulk tank somatic cell count (SCC) data were collected. Consistency indices for 5 different SCC standards were developed. The indices calculate the maximum variation allowed to meet a desired SCC level at a given mean bulk tank SCC and were used to identify herds not capable of meeting a specific SCC standard. Consistency index method was compared with a test identifying future bulk tank SCC standard violators based on herds’ past violations. The performance of the consistency index test and the past violation method was evaluated by logistic regression. The comparison focused on detection probability and certainty associated with a result. For the 5 SCC levels, detection probability and certainty associated with a result ranged from 51 to 98%. Detection probability of all violators and certainty associated with a negative result was greater for the consistency index across all 5 SCC levels (by 0.7 to 7.4% and 2.1 to 5.1%, respectively). Control charts were plotted and monthly consistency indices calculated for individual farms. Charts in combination with the consistency indices would warn from 66 to 80% of the herds about an upcoming violation within 30 d before it occurred. They offer a proactive approach to maintaining consistently high milk quality. By assessing process capability and distinguishing between significant changes and random variation in bulk tank SCC, tools presented in this article encourage fact-based decisions in dairy farm milk quality management.