Relationship between facility type and bulk tank milk bacteriology, udder health, udder hygiene, and milk production on Vermont organic dairy farms.

The primary objective of this cross-sectional observational study was to determine whether bulk tank milk quality, udder health, udder hygiene, and milk production outcomes were associated with facility type on organic dairies. A secondary objective was to identify other management-related risk factors associated with bulk tank milk quality, udder health, udder hygiene, and milk production on organic dairy herds in Vermont. We aimed to enroll 40 farms, to compare herds using the 2 most common systems (freestalls, tiestalls) for housing organic dairy cattle in the state with those using a bedded pack during the nongrazing season (typically November-May). Two general styles of bedded packs were observed: cultivated bedded packs and untilled deep-bedded packs. Due to the limited number of herds using bedded packs to house lactating dairy cattle in Vermont, we combined untilled and cultivated bedded packs to describe udder hygiene, milk quality, and udder health on these loose-housing systems deeply bedded with organic material. The study was completed on 21 farms (5 bedded packs, 6 freestalls, 10 tiestalls) before interruption due to the COVID-19 pandemic. Data captured from DHIA records from the test closest to the date of the farm visit included average SCS, standardized 150-d milk (pounds), percentage of cows with current high SCS (SCS ≥4.0), percentage of cows with newly elevated SCS (previous SCS <4.0 to current ≥4.0), and percentage of cows with chronically elevated SCS (SCS ≥4.0 last 2 tests). Multivariable linear regression models were used to describe outcomes by facility type, but suffered from limited statistical power due to small group sample sizes. Unconditional comparisons failed to find statistically significant differences between farms grouped by facility type in metrics captured from DHIA test data, bulk tank milk somatic cell count (BTSCC) and aerobic culture data, or udder hygiene scores. A secondary analysis was conducted using univariate linear regression to identify associations between herd-management factors and outcomes for all 21 farms combined. Although not all differences found were statistically significant in this secondary analysis combining all farms, numeric differences that may be biologically important are reported showing farms with deeper bedding had a lower BTSCC, lower newly elevated SCS, lower chronically elevated SCS, lower elevated current SCS, lower average SCS, and better udder hygiene metrics. Farms with lower mean udder hygiene scores had numerically lower chronically elevated SCS, lower elevated current SCS, and lower average SCS. We could not reject the null hypothesis that milk quality and udder health outcomes did not differ by facility type, and this does not preclude the existence of biological differences in these outcomes between facility types. The current study provides insight on factors affecting bulk tank milk quality, udder health and hygiene measures on organic dairy farms in Vermont. Bedded packs may be a viable option for confinement housing during the winter nongrazing season for pasture-based herds interested in a loose-housing system in the northeastern United States, but more research, such as longitudinal studies with a larger sample size, is needed to test this hypothesis.

Troubleshooting high laboratory pasteurization counts in organic raw milk requires characterization of dominant thermoduric bacteria, which includes nonsporeformers as well as sporeformers.

Laboratory pasteurization count (LPC) enumerates thermoduric bacteria and is one parameter used to assess raw milk quality. No regulatory limit has presently been set for LPC, but LPC data are used by some dairy processors and cooperatives to designate raw milk quality premiums paid to farmers and may also be used for troubleshooting bacterial contamination issues. Although it is occasionally used as a proxy for levels of bacterial spores in raw milk, limited knowledge is available on the types of organisms that are enumerated by LPC in contemporary raw milk supplies. Although historical studies have reported that thermoduric bacteria quantified by LPC may predominantly represent gram-positive cocci, updated knowledge on microbial populations enumerated by LPC in contemporary organic raw milk supplies is needed. To address this gap, organic raw milk samples from across the United States (n = 94) were assessed using LPC, and bacterial isolates were characterized. LPC ranged from below detection (<0.70 log cfu/mL) to 4.07 log cfu/mL, with a geometric mean of 1.48 log cfu/mL. Among 380 isolates characterized by 16S rDNA sequencing, 52.6%, 44.5%, and 2.4% were identified as gram-positive sporeformers, gram-positive nonsporeformers, and gram-negatives, respectively; 0.5% could not be categorized into those groups because they could only be assigned a higher level of taxonomy. Isolates identified as gram-positive sporeformers were predominantly Bacillus (168/200), and gram-positive nonsporeformers were predominantly Brachybacterium (56/169) and Kocuria (47/169). To elucidate if the LPC level can be an indicator of the type of thermoduric (e.g., sporeforming bacteria) present in raw milk, we evaluated the proportion of sporeformers in raw milk samples with LPC of ≤100 cfu/mL, 100 to 200 cfu/mL, and ≥200 cfu/mL (51%, 67%, and 35%), showing a trend for sporeformers to represent a smaller proportion of the total thermoduric population when LPC increases, although overall linear regression showed no significant association between the proportion of sporeformers and the LPC concentration. Hence, LPC level alone provides no insight into the makeup of the thermoduric population in raw milk, and further characterization is needed to elucidate the bacterial drivers of elevated LPC in raw milk. We therefore further characterized the isolates from this study using MALDI-TOF mass spectrometry (MALDI-TOF MS), a rapid microbial identification tool that is more readily available to dairy producers than 16S rDNA PCR and sequencing. Although our data indicated agreement between 16S rDNA sequencing and MALDI-TOF MS for 66.6% of isolates at the genus level, 24.2% and 9.2% could not be reliably identified or were mischaracterized using MALDI-TOF MS, respectively. This suggests that further optimization of this method is needed to allow for accurate characterization of thermoduric organisms commonly found in raw milk. Ultimately, our study provides a contemporary perspective on thermoduric bacteria selected by the LPC method and establishes that the LPC alone is not sufficient for identifying the bacterial drivers of LPC levels. Further development of rapid characterization methods that are accessible to producers, cooperatives, and processors will support milk quality troubleshooting efforts and ultimately improve outcomes for dairy industry community members.

Performance comparison of machine learning models used for predicting subclinical mastitis in dairy cows: Bagging, boosting, stacking, and super-learner ensembles versus single machine learning models.

Mastitis has a substantial impact on the dairy industry across the world, causing dairy producers to suffer losses due to the reduced quality and quantity of produced milk. A further problem, related to this issue, is the excessive use of antibiotics that leads to the development of resistance in different bacterial strains. The growing consumer awareness oriented toward food safety and rational use of antibiotics has promoted the search for new methods of early identification of cows that may be at risk of developing the disease. Subclinical mastitis does not cause any visible changes to the udder or milk, and therefore it is more difficult to detect than clinical mastitis. The collection of large amounts of data related to milk performance of cows allows using machine learning (ML) methods to build models that could be used for classifying cows into healthy and at risk of subclinical mastitis. The data used for the purpose of this study included information from routine milk recording procedures. The dataset consisted of 19,856 records of 2,227 Polish Holstein-Friesian cows from 3 herds. The authors decided to use the approach of building ensemble ML models, in particular bagging, boosting, stacking, and super-learner models, and comparing them for accuracy of identification of disease-affected cows against single ML models based on the support vector machines, logistic regression, Gaussian Naive Bayes, k-nearest neighbors, and decision tree algorithms. The models were trained and evaluated based on the information recorded for herd 1 and using an 80:20 train-test split ratio according to animal ID (to avoid data leakage). The information recorded for herds 2 and 3 was only used to evaluate on unseen data models developed using the herd 1 dataset. Among the single ML models, the support vector machines model was found to be the most accurate in predicting subclinical mastitis at subsequent test day when used both for the training set (mean F1-score of 0.760) and the testing sets containing data for herds 1, 2, and 3 (F1-score of 0.778, 0.790, and 0.741 respectively). The gradient boosting model was found to be the best performing model among the ensemble ML models (F1-score of 0.762, 0.779, 0.791, and 0.723 for the training set and the testing sets, respectively). The super-learner model, featuring the most advanced design and logistic regression in the meta layer, achieved the highest mean F1-score of 0.775 during the cross validation; however, it was characterized by a slightly worse prediction accuracy of the testing sets (mean F1-score of 0.768, 0.790, and 0.693 for herds 1, 2 and 3 respectively). The study findings confirm the promising role of ensemble ML methods, which were found to be slightly superior with respect to most of the single ML models.

Milking system and diet forage type effect on milk quality of Italian Holstein-Friesian.

Moving from conventional (CMS) to automatic (AMS) milking systems could affect milk quality. Moreover, the type and preservation methods of the forages used in the TMR, such as alfalfa hay (HTMR) or corn silage (STMR) have been demonstrated to modify milk composition. Thus, this study investigated the effect of implementing AMS and different diet forage types on the quality of Italian Holstein-Friesian bulk milk. Milk samples (n = 168) were collected monthly from 21 commercial farms in northern Italy during a period of 8 mo. Farms were categorized into 4 groups according to their milking system (CMS vs. AMS) and diet forage type (HTMR vs. STMR). Milk quality data were analyzed through the mixed procedure for repeated measurement of SAS with the milking system, diet forage type, and sampling day as fixed effects. Milking through the AMS led to lower milk fat, freezing point, and ß-LG A; longer coagulation time; and higher K content, pH, and ß-LG B than CMS. Cows fed STMR produced milk with greater fat, protein, casein, Mg content, titratable acidity, and ß-LG A, but with reduced curd firming time, freezing point, and ß-LG B than those fed HTMR. In conclusion, milk quality is not only altered by the diet's forage type and characteristics but also by the milking system.

The A1/A2 ß-casein genotype of cows, but not their horn status, influences peptide generation during simulated digestion of milk.

The effect of the horn status of cows on their milk composition and quality is a controversial research topic. In this study, 128 milk samples from 64 horned and 64 disbudded Brown Swiss and Original Braunvieh cows were collected from alpine farms where both horned and disbudded cows were grazing on mountain pastures. The samples were analyzed for their detailed composition and protein digestion in a simulated in vitro digestion (INFOGEST). To exclude probable influences on digestion, the ß-CN genotype with its variants A1 and A2 was also included in the study. The effects of horn status and ß-CN genotype were investigated in linear mixed models, which included additional influencing random factors such as Original Braunvieh blood proportion, stage of lactation, and farm. Horn status did not have any effect on milk composition or digestion. In contrast, milk from A1A1 cows showed a different protein digestion than milk of A1A2 and A2A2 cows in the gastric phase, including smaller amounts of ß-casomorphin(BCM)21-associated peptides and larger amounts of BCM11-associated peptides. Abundances of BCM7 did not differ between ß-CN genotypes. At the end of the intestinal phase, the digested milk of A1A1 and A2A2 ß-CN genotypes did not differ.

Fluctuations in somatic cell count and their impact on individual goat milk quality throughout lactation.

The somatic cell count (SCC) is used by the dairy industry as an indicator of milk quality and udder health. However, in goats, its reliability is significantly masked by non-infectious variables such as the milk secretion process and physiological lactation changes. Additionally, notable individual variability between goats might exist. This study aimed to investigate fluctuations in SCC in individual goats during an entire lactation and to examine the relationship between SCC and milk parameters such as bacterial count and chemical composition. Individual milk samples from 40 Norwegian dairy goats from the University herd were collected monthly across an entire lactation including the pasture period. The goats were categorized based on SCC levels to analyze patterns in chemical components within these groups. Notably, goats exhibited increased SCC and decreased bacterial counts when moved to summer grazing pastures. At that stage milk samples from goats with the highest SCC (>2000 ×103 cells/mL) showed a distinct decrease in individual bacterial counts (IBC). Several milk components, especially lactose, protein, and various minerals were affected by the SCC level, as well as pH. These effects were further amplified when considering the interaction with the lactation stage, influencing a broader range of variables. The results presented in this study provide new insights into the SCC's effect on milk composition and its critical role. These insights underscore the necessity for establishing lactation-specific thresholds for interpretation, as well as for making adjustments in quality payments.

Characterization of variables related to high stability of raw cow milk.

This research paper analyzes the stability of raw cow milk in the alcohol test and seeks to understand to know the factors that influence milk stability and the occurrence of unstable non-acid milk. Milk samples were collected from the cooling tanks of rural farmers in the state of Paraná twice in summer and twice in winter. The farms were classified according to the production system: pasture with supplementation and feedlot. The following variables were analyzed: stability in the alcohol test, titratable acidity, ionized calcium concentration (iCa), chemical composition of milk, somatic cell count and standard plate count. The results showed that milk stability was greater in winter vs. summer, when the milk contained higher iCa, and in the feedlot vs. pasture system. The Pearson Correlation between variables (ethanol stability, milk composition, iCa, cooling tank temperature, milk volume, number of milking, number of cows milked, fat/protein ratio, distance and travel time) were analyzed. Stability was negatively correlated with iCa concentration and positively with lactose content. Logistic regression of the risk of unstable non-acid milk at 72% alcohol (UNAM72) showed that only iCa and lactose were determinants, while evaluation of the same risk at 78% alcohol revealed iCa, titratable acidity, lactose and milk urea nitrogen as risk factors. Under the dairy farming conditions of Paraná state, the frequency of UNAM72 was low (12.16%) and was higher in summer and in pasture systems with supplementation. In conclusion, in dairy herds bred with high technological level, with adequate nutritional and health management, the frequency of UNAM is low and is related to nutritional management abnd, perhaps, heat stress, factors that alter iCa and lactose levels.

Examining performance, milk, and meat in ruminants fed with macroalgae and microalgae: A meta-analysis perspective.

This meta-analysis consolidates various related studies to identify patterns in the impact of feeding algae on performance aspects, including milk fat, milk protein, and carcass yield in several ruminant species, such as cattle, sheep, and goats. The data were collected from 67 articles that examined factors such as the type of algae (macro- and microalgae), algal species, and animal breed. Barki sheep, Moghani sheep, and Zaraibi goats demonstrated an increased average daily gain (P < 0.05) when fed with both macro- and microalgae. Conversely, sheep such as Canadian Arcott and Ile-de-France showed adverse effects on the feed conversion ratio (FCR) (P < 0.05). Elevated FCR values were observed across castrated and young animals (P < 0.05). Algae extract notably increased the hot carcass weight (P < 0.001), particularly among Moghani sheep (P < 0.001). Raw algae significantly reduced the milk fat content (P < 0.001), particularly in cattle and sheep (P < 0.001). A decrease in milk fat was particularly noticeable in lactating females of Assaf sheep, Damascus goats, and Holstein cows (P < 0.001). Overall, algae inclusion tended to decrease the milk protein content (P < 0.05), leading to reduced milk production (P < 0.001) with cumulative algae feeding in Assaf sheep. However, conjugated linoleic acid (CLA; C18:2 c9,t11-CLA and C18:2 c12,t10-CLA) and docosahexaenoic acid (DHA; C22:6n-3) mostly increased in meat and milk from Holstein cow, Assaf sheep, Dorset sheep, and Ile-de-France sheep (P < 0.01). This meta-analysis highlights the necessity for additional research aimed at optimizing the sustainable use of algae in feed for ruminants, despite the demonstrated improvements in performance and the levels of CLA and DHA found in meat and milk.

Impact of diversified grazing systems on milk production, nutrient use and enteric methane emissions in dual-purpose cows.

This study evaluated three continuous grazing systems: Brachiaria Brizantha, Clitoria ternatea and naturalized pastures, complemented with commercial concentrate and C. ternatea silage on milk yield, nutrient use and enteric methane (CH4) emissions. Nine multiparous cows of local Zebu breeds, with an average weight of 448 ± 87 kg, were used. The chemical composition of the food was determined. Live weight, milk production, and quality were assessed. Furthermore, serum urea, urea nitrogen, creatinine and glucose in blood were monitored, and nitrogen use efficiency were calculated. Enteric methane (CH4) emissions were estimated using Tier-2 methodology. A 3 × 3 latin square experimental design was applied. The grazing systems of B. brizantha and C. ternatea had the greater live weights of 465.8 and 453.3 kg/cow, although the latter is similar to naturalized pasture. Milk production and quality were not affected by grazing system, with the exception of the non-fat solids, where the C. ternatea system was lower (102.2 g/kg) than the other grazing systems. The crude protein and N intake, and N excretion in feces and urine were lower in naturalized pasture systems (1139.0 g/day). N outputs in milk was high in the C. ternatea system (56.3 g/cow/day). The naturalized pastures systems showed the better feed use efficiency (25.7%) compared to others. Serum urea and blood urea nitrogen were greater in B. brizantha followed by C. ternatea. Enteric CH4 emissions were indifferent among grazing systems when expressed as a percentage of greenhouse gases (7.1%). In conclusion, the grazing C. ternatea supplemented with commercial concentrate and C. ternatea silage maintains milk production and quality, reduced cow/day emissions (by 2.5%) and lowered energy losses as methane.

Novel spa type and antimicrobial resistance gene profiles of Staphylococcus aureus strains isolated from bovine mastitis in Jordan.

Staphylococcu aureus is the most prevalent microorganism associated with mastitis in cattle. This study was designed to determine the spa types of Staph. aureus and to assess the resistance genes profile of isolated strains in dairy farms in Jordan. In total, 747 milk samples of cattle suffering from subclinical mastitis were collected from 37 dairy farms and tested for Staph. aureus. To detect antimicrobial resistance genes, all 219 strains of Staph. aureus were tested. Furthermore, 21 isolates of Staph. aureus were typed using spa typing. As a result, different proportions of resistance genes were found for Staph. aureus. High resistance genes were in tetK 100%, blaZ 99%, and tetM 97%. Moderate resistance genes were in aac(6')/aph(2'' 52%, ant(4')-Ia 48%, and ermC 41%. Low resistance genes were in ermA is 24%, aph(3')-III is 15%, and mecA is 15%. The spa typing of 21 isolates revealed six spa types, of which five were previously known. For the first time, a novel spa type (t17158) was identified as the main cause of mastitis in dairy cows in Jordan. The identification of resistance genes and spa types is helpful in determining the most effective treatments for cows and plays a significant role in reducing the transmission of pathogens.

Invited review: Redefining raw milk quality-Evaluation of raw milk microbiological parameters to ensure high-quality processed dairy products.

Raw milk typically has little bacterial contamination as it leaves the udder of the animal; however, through a variety of pathways, it can become contaminated with bacteria originating from environmental sources, the cow herself, and contact with contaminated equipment. Although the types of bacteria found in raw milk are very diverse, select groups are particularly important from the perspective of finished product quality. In particular, psychrophilic and psychrotolerant bacteria that grow quickly at low temperatures (e.g., species in the genus Pseudomonas and the family Enterobacteriaceae) and produce heat-stable enzymes, and sporeforming bacteria that survive processing hurdles in spore form, are the 2 primary groups of bacteria related to effects on processed dairy products. Understanding factors leading to the presence of these important bacterial groups in raw milk is key to reducing their influence on processed dairy product quality. Here we examine the raw milk microbiological parameters used in the contemporary dairy industry for their utility in identifying raw milk supplies that will perform well in processed dairy products. We further recommend the use of a single microbiological indicator of raw milk quality, namely the total bacteria count, and call for the development of a whole-farm approach to raw milk quality that will use data-driven, risk-based tools integrated across the continuum from production to processing and shelf-life to ensure continuous improvement in dairy product quality.

Effects of replacement of barley with oats on milk fatty acid composition in dairy cows fed grass silage-based diets.

This study consists of milk fatty acid (FA) data collected during 2 in vivo experiments. For this study, 8 cows from each experiment were included in a replicated 4 × 4 Latin square design. At the start of experiment 1 (Exp1) cows were at (mean ± standard deviation) 87 ± 34.6 d in milk, 625 ± 85.0 kg of body weight, and 32.1 ± 4.17 kg/d milk yield and at the start of experiment 2 (Exp2) cows were at 74 ± 18.2 d in milk, 629 ± 87.0 kg of body weight, and 37.0 ± 3.2 kg/d milk yield. In Exp1, we examined the effects of gradual replacement of barley with hulled oats (oats with hulls) on milk FA composition. The basal diet was grass silage and rapeseed meal (58 and 10% of diet DM, respectively), and the 4 grain supplements were formulated so that barley was gradually replaced by hulled oats at levels of 0, 33, 67, and 100% on dry matter basis. In Exp2, we examined (1) the effects of replacing barley with both hulled and dehulled oats (oats without hulls) and (2) the effects of gradual replacement of hulled oats with dehulled oats on milk FA composition. The basal diet was grass silage and rapeseed meal (60 and 10% of diet DM, respectively), and the 4 pelleted experimental concentrates were barley, hulled oats, a 50:50 mixture of hulled and dehulled oats, and dehulled oats on dry matter basis. In Exp1, gradual replacement of barley with hulled oats decreased relative proportions of 14:0, 16:0, and total saturated FA (SFA) in milk fat linearly, whereas proportions of 18:0, 18:1, total monounsaturated FA, and total cis unsaturated FA increased linearly. Transfer efficiency of total C18 decreased linearly when barley was replaced by hulled oats in Exp1. In Exp2, relative proportions of 14:0, 16:0, and total SFA were lower, whereas proportions of 18:0, 18:1, monounsaturated FA, and cis unsaturated FA were higher in milk from cows fed the oat diets than in milk from cows fed the barley diet. Moreover, in Exp2, gradual replacement of hulled oats with dehulled oats slightly decreased the relative proportion of 14:0 in milk fat but did not affect the proportions of 16:0, 18:0, 18:1, total SFA, monounsaturated FA, trans FA, or polyunsaturated FA. In Exp2, transfer efficiency of total C18 was lower when cows were fed the oat diets than when fed the barley diet and decreased linearly when hulled oats were replaced with dehulled oats. Predictions of daily CH4 emissions (g/d) using the on-farm available variables energy-corrected milk yield and body weight were not markedly improved by including milk concentrations of individual milk FA in prediction equations. In conclusion, replacement of barley with oats as a concentrate supplement for dairy cows fed a grass silage-based diet could offer a practical strategy to change the FA composition of milk to be more in accordance with international dietary guidelines regarding consumption of SFA.

Relation between αS1-casein, genotype, and quality traits of milk from Swedish dairy goats.

Locally produced food is becoming popular among Swedish consumers. One product that has increased in popularity is artisan-manufactured goat cheese, and although the dairy goat industry in Sweden is small-scale, production is gradually increasing. In goats, the CSN1S1 gene regulates expression of the protein αS1-casein (αS1-CN), which has been found to be important for cheese yield. Over the years, breeding animals have been imported to Sweden from Norway. Historically, a high frequency of the Norwegian goat population carried a polymorphism at the CSN1S1 gene. This polymorphism, called the Norwegian null allele (D), leads to zero or significantly reduced expression of αS1-CN. Using milk samples from 75 goats, this study investigated associations between expression of αS1-CN and genotype at the CSN1S1 gene on milk quality traits from Swedish Landrace goats. Milk samples were grouped according to relative level of αS1-CN (low: 0-6.9% of total protein; medium-high: 7-25% of total protein) and genotype (DD, DG, DA/AG/AA). While the D allele leads to extremely low expression of αS1-CN, the G allele is low expressing and the A allele is highly expressing for this protein. Principal component analysis was used to explore the total variation in milk quality traits. To evaluate the effect of different allele groups on milk quality attributes, 1-way ANOVA and Tukey pairwise comparison tests were used. The majority (72%) of all goat milk samples investigated showed relative αS1-CN content of 0% to 6.82% of total protein. The frequency of individuals homozygous for the Norwegian null allele (DD) was 59% in the population of sampled goats, and only 15% carried at least one A allele. A low relative concentration of αS1-CN was associated with lower total protein, higher pH, and higher relative concentration of ß-casein and levels of free fatty acids. Milk from goats homozygous for the null allele (DD) showed a similar pattern as milk with low relative concentration of αS1-CN, but total protein was only numerically lower, and somatic cell count and αS2-CN were higher than for the other genotypes. The associations between levels of αS1-CN and the investigated genotype at the CSN1S1 gene indicate a need for a national breeding program for Swedish dairy goats.

Farm management and economic factors associated with bulk tank total bacterial count in Holstein dairy herds in Iran.

The objectives of this research were (1) to study different factors affecting milk total bacterial count (TBC) and (2) to estimate the economic value associated with TBC in Holstein dairy herds in Iran. The relationships between bulk tank TBC and farm management and economic factors were examined on 56 randomly selected intensive dairy farms. Herd management factors associated with bulk tank TBC were determined using mixed linear models. The median bulk tank TBC for the sample herds was 299 (range 81-1185) × 103 cfu/ml. The average economic premium opportunity from bulk tank TBC was US$ 1.32 per ton of milk ranging from US$ 0.02 per ton of milk for herds applying wet tissue procedures as teat cleaning material and washing the water troughs three times per day to US$ 5.20 per ton of milk for herds with dirty barns. Results showed that the following management factors were associated with low TBC and high economic value: frequency of cleaning water troughs, teat cleaning material, the frequency of milk delivery to the processor, bedding material, herd size, education level of workers, udder washing material, material of milking parlor wall, frequency of disinfection of the calving area, presence of veterinarian, water quality control, having a hospital pen and barn hygiene. In conclusion, our findings highlight the need to pay more attention to farm management issues, particularly farm hygiene practices to reduce milk TBC and so reduce the economic burden of TBC in dairy herds in Iran.

A Monoblock Light-Scattering Milk Fat Percentage and Somatic Cell Count Sensor for Use in Milking Systems.

A monoblock light-scattering sensor, which is capable of measuring the fat content of milk and indicating the excess by which the somatic cell count (SCC) is over the permissible level, has been developed for installation in dairy systems. In order for the sensor to perform measurements when the milking machine is working in the "milk plug" mode, a flow-through unit is designed in the form of a pipe with a lateral cylindrical branch, in which milk accumulates so as to eliminate large bubbles and achieve continuity of the milk flow. The operation of the sensor is based on the registration of the angular intensity distribution of light scattered in the transparent cylindrical segment of the tube branch. A semiconductor laser with a wavelength of 650 nm is used as a light source for determining scattering in milk. The angular distribution of the scattered light intensity (scattering indicatrix) is recorded using an axial photodiode array. The fat content is determined by the average slope of the measured scattering indicatrix in the range of scattering angles 72-162°. The SCC level is estimated from the relative deviation of the forward scatter intensity normalized to the backscatter intensity with respect to uninfected milk. The sensor has been tested on a Yolochka-type milking machine.

The Effects of Mammary Gland ATIII Overexpression on the General Health of Dairy Goats and Their Anti-Inflammatory Response to LPS Stimulation.

Antithrombin III is an important anticoagulant factor with anti-inflammatory properties. However, few studies have explored its anti-inflammatory actions in ATIII overexpressed transgenic animals. In this study, the dairy goats with mammary overexpression of ATIII were used to investigate their general health, milk quality and particularly their response to inflammatory challenge. The results showed that transgenic goats have a normal phenotype regarding their physiological and biochemical parameters, including whole blood cells, serum protein levels, total cholesterol, urea nitrogen, uric acid, and total bilirubin, compared to the WT. In addition, the quality of milk also improved in transgenic animals compared to the WT, as indicated by the increased milk fat and dry matter content and the reduced somatic cell numbers. Under the stimulation of an LPS injection, the transgenic goats had elevated contents of IGA, IGM and superoxide dismutase SOD, and had reduced proinflammatory cytokine release, including IL-6, TNF-α and IFN-ß. A 16S rDNA sequencing analysis also showed that the transgenic animals had a similar compositions of gut microbiota to the WT goats under the stimulation of LPS injections. Mammary gland ATIII overexpression in dairy goats is a safe process, and it did not jeopardize the general health of the transgenic animals; moreover, the compositions of their gut microbiota also improved with the milk quality. The LPS stimulation study suggests that the increased ATIII expression may directly or indirectly suppress the inflammatory response to increase the resistance of transgenic animals to pathogen invasion. This will be explored in future studies.

Analysis of Milk Microstructure Using Raman Hyperspectral Imaging.

Optical spectroscopic analysis of the chemical composition of milk in its natural state is complicated by a complex colloidal structure, represented by differently sized fat and protein particles. The classical techniques of molecular spectroscopy in the visible, near-, and mid-infrared ranges carry only bulk chemical information about a sample, which usually undergoes a destructive preparation stage. The combination of Raman spectroscopy with confocal microscopy provides a unique opportunity to obtain a vibrational spectrum at any single point of the sample volume. In this study, scanning confocal Raman microscopy was applied for the first time to investigate the chemical microstructure of milk using samples of various compositions. The obtained hyperspectral images of selected planes in milk samples are represented by three-dimensional data arrays. Chemometric data analysis, in particular the method of multivariate curve resolution, has been used to extract the chemical information from complex partially overlaid spectral responses. The results obtained show the spatial distribution of the main chemical components, i.e., fat, protein, and lactose, in the milk samples under study using intuitive graphical maps. The proposed experimental and data analysis method can be used in an advanced chemical analysis of natural milk and products on its basis.

Use of former food products in dairy buffalo nutrition: In vitro and in vivo evaluation.

A feeding strategy that maintains high content of functional molecules in buffalo milk has been verified by giving Sorghum vulgare as green fodder, but it is not available all year round. The aim of this study was to evaluate the inclusion of former food products (FFPs) containing 87% biscuit meal (nonstructural carbohydrate: 60.1%; starch 14.7; crude protein 10.6), in the diet of buffaloes in terms of: (a) fermentation characteristics through gas production technique; (b) milk yield (MY) and quality; (c) content of some biomolecules and total antioxidant activity. The experiment was performed involving 50 buffaloes divided into two groups: Green group and FFPs group (animals fed Total Mixed Ration with either green forage or FFPs respectively). Daily MY was recorded and milk qualitative analyses were determined monthly for 90 days. Furthermore, fermentation characteristics of the diets were studied in vitro. No significant differences were recorded in feed intake, BCS and MY and quality. Similar in vitro fermentation data of two diets were found, with slight differences in terms of gas production and degradability. During the incubation, kinetic parameters showed a faster fermentation process with the diet of the FFPs group in relation to Green group (p < 0.05). Green group had higher levels (p < 0.01) of γ-butyrobetaine, glycine betaine, l-carnitine and propionyl l-carnitine in milk, whereas no differences were observed for δ-valerobetaine and acetyl l-carnitine. Total antioxidant capacity and iron reduction antioxidant assay were higher (p < 0.05) in the plasma and milk of the Green group. The administration of a diet high in simple sugars, obtained with FFPs, seems to favour the ruminal biosynthesis of some metabolites in milk, such as δ-valerobetaine and acetyl- l-carnitine, similar to green forage administration. Overall, the use of biscuit meal can be an alternative to green fodder when it is not available to ensure environmental sustainability and optimize costs without compromising milk quality.

Association of GH, STAT5A, MYF5 gene polymorphisms with milk somatic cell count, EC and pH levels of Holstein dairy cattle.

This study was conducted to ivnestigate the associations of GH-AluI, STAT5A-AvaI and MYF5-TaqI gene polymorphisms with milk somatic cell count (SCC), electrical conductivity (EC) and pH levels in Holstein dairy cows. For this purpose, 167 blood and 1670 milk samples of 167 Holstein cows in their 2nd lactation were used. There were significant relationships between GH-AluI genotypes and milk EC (p < 0.001) and between STAT5A-AvaI genotypes and milk EC (p = 0.007), but there were not any significant relationships between MYF5 gene polymorphism and the investigated traits (p > 0.05). The greatest EC values were observed in GH-AluI-LV and STAT5A-AvaI-TT-genotyped individuals. Just because of association of EC with mastitis, it was concluded that present GH-AluI and STAT5A-AvaI polymorphisms could be used in further studies to be conducted to improve mastitis resistance and milk quality traits of Holstein dairy cows.

Impact of somatic cell count combined with differential somatic cell count on milk protein fractions in Holstein cattle.

Udder health in dairy herds is a very important issue given its implications for animal welfare and the production of high-quality milk. Somatic cell count (SCC) is the most widely used means of assessing udder health status. However, differential somatic cell count (DSCC) has recently been proposed as a new and more effective means of evaluating intramammary infection dynamics. Differential SCC represents the combined percentage of polymorphonuclear neutrophils and lymphocytes (PMN-LYM) in the total SCC, with macrophages (MAC) accounting for the remaining proportion. The aim of this study was to evaluate the association between SCC and DSCC and the detailed milk protein profile in a population of 1,482 Holstein cows. A validated reversed-phase HPLC method was used to quantify 4 caseins (CN), namely αS1-CN, αS2-CN, κ-CN, and ß-CN, and 3 whey protein fractions, namely ß-lactoglobulin, α-lactalbumin, and lactoferrin, which were expressed both quantitatively (g/L) and qualitatively (as a percentage of the total milk nitrogen content, %N). A linear mixed model was fitted to explore the associations between somatic cell score (SCS) combined with DSCC and the protein fractions expressed quantitatively and qualitatively. We ran an additional model that included DSCC expressed as PMN-LYM and MAC counts, obtained by multiplying the percentages of PMN-LYM and MAC by SCC for each cow in the data set. When the protein fractions were expressed as grams per liter, SCS was significantly negatively associated with almost all the casein fractions and positively associated with the whey protein α-lactalbumin, while DSCC was significantly associated with αS1-CN, ß-CN, and α-lactalbumin, but in the opposite direction to SCS. We observed the same pattern with the qualitative data (i.e., %N), confirming opposite effects of SCS and DSCC on milk protein fractions. The PMN-LYM count was only slightly associated with the traits of concern, although the pattern observed was the same as when both SCS and DSCC were included in the model. The MAC count, however, generally had a greater impact on many casein fractions, in particular decreasing both ß-CN content (g/L) and proportion (%N), and exhibited the opposite pattern to the PMN-LYM count. Our results show that information obtained from both SCS and DSCC may be useful in assessing milk quality and protein fractions. They also demonstrate the potential of MAC count as a novel udder health trait.