Statistical Optimization and Analysis of Factors Maximizing Milk Productivity

This study was conducted to determine the biological and environmental factors affecting milk yield and dry matter consumption and to analyze the effects of these factors on animal production. The study determined the variables affecting milk yield as input factors, such as lactation period, number of days of gestation, age, TMR dry matter ratio, and environmental factors. As a result of regression analyses, it was determined that each 1% increase in the TMR dry matter ratio decreased the milk yield by 0.9148 L, and each increase in the number of lactations increased the daily milk yield by 3.753 L. However, it was observed that the increase in the number of lactation days caused a decrease in milk production, and milk yield decreased as the gestation period extended. The most appropriate independent variable values were determined using statistical optimization analyses to maximize milk yield and optimize dry matter consumption. As a result of the analyses, the optimum value for the TMR dry matter ratio was calculated as 46.77%, 5 for lactation number, 6 for lactation day number, 230 days for gestation period, 55.8 months for cow age, and 20 °C for air temperature. The optimum values of the dependent variables were determined to be 61.145 L for daily milk yield and 19.033 units for dry matter consumption. The prediction intervals provided by the model served as reference points for future observations and showed that milk production was strongly affected by certain environmental and biological factors.

Lactate induces oxidative stress by HIF1α stabilization and circadian clock disturbance in mammary gland of dairy cows

BACKGROUND

Lactate is a classical byproduct of glucose metabolism, and the main lactate production pathway depends on glycolysis. Lactate stabilized HIF1α by inhibiting PHD activity, leading to hypoxic stress response and exacerbating glycolysis in multiple tissues. However, the redox induction mechanism of lactate in mammary gland has not been understood yet. Herein, we describe a lactate-responsive HIF1α/circadian control mechanism in oxidative stress in the mammary glands of dairy cows.

RESULTS

The in vivo study showed that dairy cows with high lactate concentrations are associated with reduced milk yield and more ROS accumulation in mammary gland. Western blot results in MAC-T cells showed positive correlation between lactate concentrations, expression of HIF1α and oxidative stress indicators, but not circadian core components. To test how lactate-mediated HIF1α dysfunction leads to cell protection process, we investigated altered expression of circadian core related genes following HIF1α stabilization. We found that stabilized HIF1α by lactate inhibited stimulated expression of circadian core components due to the similarity of HRE and E-box transcription elements. Furthermore, we found that lactate treatment strengthened the binding of HIF1α with BMAL1, HMOX1 and FOXO3 in MAC-T cells. Moreover, HIF1α knockdown altered expression of circadian rhythm related genes and reduced oxidative stress state.

CONCLUSION

In summary, our study highlights the central role of competitive transcriptional element occupancy in lactate-mediated oxidative stress of mammary gland, which is caused by HIF1α stabilization and circadian rhythm dysfunction. Our findings introduce a novel nutritional strategy with potential applications in dairy farming for optimizing milk production and maintaining mammary gland health.

Overexpression of PER2 Promotes De Novo Fatty Acid Synthesis, Fatty Acid Desaturation, and Triglyceride Accumulation in Bovine Mammary Epithelial Cells

The core clock gene Period2 (PER2) is associated with mammary gland development and lipid synthesis in rodents and has recently been found to have a diurnal variation in the process of lactation, but has not yet been demonstrated in bovine mammary epithelial cells (BMECs). To explore the regulatory function of PER2 on milk fat synthesis in bovine mammary epithelial cells, we initially assessed the expression of clock genes and milk fat metabolism genes for 24 h using real-time quantitative PCR and fitted the data to a cosine function curve. Subsequently, we overexpressed the PER2 in BMECs using plasmid vector (pcDNA3.1-PER2), with empty vector pcDNA3.1-myc as the control. After transfecting BMECs for 48 h, we assessed the protein abundance related to milk fat synthesis by Western blot, the expression of genes coding for these proteins using real time-quantitative PCR, the production of triacylglycerol, and the fatty acid profile. The findings indicated that a total of nine clock genes (PER1/2, CRY1/2, REV-ERBα, BMAL1, NCOR1, NR2F2, FBXW11), seven fatty acid metabolism genes (CD36, ACSS2, ACACA, SCD, FADS1, DGAT1, ADFP), and six nuclear receptor-related genes (INSIG1, SCAP, SREBF1, C/EBP, PPARG, LXR) exhibited oscillation with a period close to 24 h in non-transfected BMECs (R2 ≥ 0.7). Compared to the control group (transfected with empty pcDNA3.1-myc), the triglyceride content significantly increased in the PER2 overexpression group (p < 0.05). The lipogenic genes for fatty acid transport and triglyceride synthesis (ACACA, SCD, LPIN1, DGAT1, and SREBF1) were upregulated after PER2 overexpression, along with the upregulation of related protein abundance (p < 0.05). The contents and ratios of palmitic acid (C16:0), oleic acid (C18:1n9c), and trans-oleic acid (C18:1n9t) were significantly increased in the overexpression group (p < 0.05). Overall, the data supported that PER2 participated in the process of milk fat metabolism and is potentially involved in the de novo synthesis and desaturation of fatty acid in bovine mammary epithelial cells.

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.

Stress indicators in dairy cows adapting to virtual fencing

Virtual fencing (VF) enables livestock grazing without physical fences by conditioning animals to a virtual boundary delimited with an audio tone (AT) and an electric pulse (EP). The present study followed the adaptation process of lactating dairy cows to a VF system with changing virtual boundaries and investigated its impact on animal welfare. Twenty cows were divided into stratified groups (2× VF; 2× electric fencing, EF) of five individuals. Each group grazed half-days in a separate EF paddock of comparable size during 3 d of acclimation (P0), followed by 21, 14, 14, and 7 d of experimental treatment (P1 to P4). At the start of the trial, all cows were equipped with an IceQube pedometer (Peacock Technology Ltd, Stirling, UK) and a VF collar (Nofence AS, Batnfjordsøra, Norway). During P0, cows were accustomed to their first paddock with a deactivated virtual boundary and wearing the sensors. In P1 to P4, an active virtual boundary for the VF groups, and a second EF for the EF groups was set up parallel to an outer EF within their paddock. Throughout the trial, the sensors continuously tracked cow positions and activity behavior at 15-min intervals. From P1 onwards, the VF collars additionally recorded each AT and EP per cow with a georeferenced time stamp. During P0 to P4, daily feed intake, body weight, and milk yield were recorded in the barn. A total of 26 milk samples were collected per cow to determine milk cortisol levels. Behavioral observations were conducted for 2 h on day 23 to record agonistic behaviors, vocalizations, and excretions. The total number of stimuli per cow ranged from 37 to 225 ATs (mean ± SD: 1.9 ± 3.3 per day) and 3 to 11 EPs (mean ± SD: 0.1 ± 0.7 per day) throughout the trial. The maximum number of EPs per day was 8 for an individual cow and occurred once on D1. Mean EP/AT decreased by 55% during the first three half-days of grazing and with each paddock change from 0.2 EP/AT in week 1 to 0.03, 0.02, and 0 EP/AT in weeks 4, 6, and 8, respectively. Linear and generalized mixed effects models revealed that milk yield and cortisol, feed intake, body weight, and activity and lying behavior did not significantly differ between VF and EF groups. A higher number of agonistic behaviors were observed in the VF groups when the VF system was activated. However, due to the short observation periods only few contacts were observed in total. Overall, all cows adapted to the VF system without evidence of lasting adverse effects on animal welfare.

Intraday and interday variations of milk fatty acids in dairy cows in early and late lactation

The composition of milk fatty acid (FA) was determined using Fourier-transform mid-infrared spectroscopy, which enables the rapid measurement of many samples. Milk FA is one indicator supporting the management of dairy cows and herds. This study aimed to determine an appropriate sampling method for milk FA in a practical farm condition based on intraday and interday variations in milk FA composition during early and late lactation stages. Milk samples were collected in the morning (07:00-08:00 h) and afternoon (16:30-17:30 h) for five consecutive days during early and late lactation. Within the day, de novo FA as the total FA basis was higher in the morning than in the afternoon, whereas preformed FA as the total FA basis was lower in the morning than in the afternoon. The weighted averages of milk FA composition according to milk yield collected in the morning and afternoon were significantly different between cows in early and late lactation; however, these were not significantly different among the consecutive five sampling days in each period. It was concluded that milk samples collected in the morning and afternoon for 1 day are suitable for milk FA determination. These results provide basic data for determining precise sampling methods for practical farms.

Effects of cow reproductive status, parity and lactation stage on behaviour and heavy breathing indications of a commercial accelerometer during hot weather conditions

Heat stress presents one of the most urgent challenges to modern dairy farming, having major detrimental impacts on cow welfare, health, and production. Understanding the effect of cow factors (reproductive status, parity, and lactation stage) on the physiological and behavioural response to hot weather conditions is essential for the accurate detection and practical application of heat mitigation strategies. To study this, collars with commercial accelerometer-based sensors were fitted on 48 lactation dairy cows to record behaviour and heavy breathing from late spring to late summer. The temperature-humidity index (THI) was calculated from measurements of 8 barn sensors. We found that, above a THI of 84, cows in advanced pregnancy (>90 days) spent more time breathing heavily and less time eating and in low activity than other cows, while cows in early pregnancy (≤90 days) spent less time breathing heavily, more time eating and in low activity. Cows with 3+ lactations showed less time breathing heavily and in high activity and more time ruminating and in low activity than cows with fewer lactations. Although lactation stage interacted significantly with THI on time spent breathing heavily, ruminating, eating, and in low activity, there was no clear indication at which lactation stage cows were more sensitive to heat. These findings show that cow factors affect the cow's physiological and behavioural response to heat, which could be used to provide group-specific heat abatement strategies, thereby improving heat stress management.

The Effect of Short-Wavelength White LED Illumination throughout the Night on the Milk Fatty Acid Profile of High-Yielding Dairy Cows

Fatty acid levels in milk vary between day and night milking. Many dairy cows are still kept under white light-emitting diode (W-LED) illumination throughout the night, although it is known to disrupt endogenous circadian rhythms. We investigated the effects of whole-night W-LED illumination (125 lux) on milk yield and circadian composition, compared to a natural light−dark (LD) cycle of 10 h light. Mid−late lactation cows (n = 34) that were exposed to natural LD cycle showed circadian variation in milk fat composition, characterized by higher health-promoting monounsaturated fatty acid (MUFA; 24.2 ± 0.4 vs. 23.2 ± 0.4 g/100 g fat, p < 0.001) and lower saturated fatty acid levels (71.2 ± 0.4 vs. 72.5 ± 0.4, p < 0.001) at 13:30 h (day milk) than at 03:30 h (night milk). Compared to natural LD (n = 16), W-LED (n = 18) did not affect milk production or milk fat yields, yet abolished the milking time variation in milk fat composition towards a less healthy fatty acid profile. This lowered MUFA levels of day milk (23.8 ± 0.4 vs. 26.7 ± 0.4, p < 0.01). Therefore, W-LED has no commercial advantage over the tested natural LD cycle, and conversely, even shows circadian disruption. Accordingly, a natural LD cycle of 10 h light is preferable over W-LED from the perspective of cost savings, the cows’ well-being, and preserving the natural milk fat profile, as the nutritional value of the day milk is slightly higher.

Evaluation of Heat Stress Effects in Different Geographical Areas on Milk and Rumen Characteristics in Holstein Dairy Cows Using Robot Milking and Rumen Sensors: A Survey in South Korea

This survey investigated, using robotic milking and rumen sensors, the effects of an adjusted temperature−humidity index (THI) in different geographical areas on milk yield, fat and protein, rumen temperature, and activity in lactating Holstein cows. We additionally explored the effect of parity on milk and rumen temperature and activity under different THI levels during the summer. From January to September 2020, four farms (276 dairy cows) were subjected to the use of robot milking machines, and two farms (162 dairy cows) to the use of rumen sensors. For the temperature and humidity data, the THI was calculated on the basis of the data from the Korea Meteorological Administration (KMA). The data were analyzed using the GLM procedure of SAS. Milk yield and milk protein decreased (p < 0.05), and milk fat increased (p < 0.05) at all farms during the summer, from July to August, when the temperature and humidity were high (THI = 72−79). Milk yields were the highest in the fifth, sixth, seventh, and eighth parities, and the lowest in the fourth (p < 0.05). Milk fat concentration was the highest in the fourth parity and the lowest in the first parity (p < 0.05). In the first parity, the highest levels of milk protein and lactose were seen (5.24% and 4.90%, respectively). However, milk protein concentration was the lowest in the third parity, and the lactose concentration was the lowest in the fifth, sixth, seventh, and eighth parities. According to the rumen sensor, the rumen temperature of the dairy cows at the two farms also continued to increase (p < 0.05) from July to August, and then decreased (p < 0.05) in September. However, the activity in the rumen was increased (p < 0.05) from July to September. In the second parity, the highest rumen temperature (39.02 °C) was observed, while the lowest value (38.28 °C) was observed in the third parity. The highest value of rumen activity (12.26 mg) was observed in the second parity and the lowest value (11.31 mg) in the fourth parity. These data, taken together, confirm that a high THI during summer conditions negatively affects milk yield, milk protein content, and rumen temperature and activity in lactating Holstein cows. It is also demonstrated that various parities affect milk characteristics and the rumen environment in the summer season.

Determining extracellular vesicles properties and miRNA cargo variability in bovine milk from healthy cows and cows undergoing subclinical mastitis

Background

Subclinical mastitis, the inflammation of the mammary gland lacking clinical symptoms, is one of the most prevalent and costly diseases in dairy farming worldwide. Milk microRNAs (miRNAs) encapsulated in extracellular vesicles (EVs) have been proposed as potential biomarkers of different mammary gland conditions, including subclinical mastitis. However, little is known about the robustness of EVs analysis regarding sampling time-point and natural infections. To estimate the reliability of EVs measurements in raw bovine milk, we first evaluated changes in EVs size and concentration using Tunable Resistive Pulse Sensing (TRPS) during three consecutive days of sampling. Then, we analysed daily differences in miRNA cargo using small RNA-seq. Finally, we compared milk EVs differences from naturally infected udder quarters with their healthy adjacent quarters and quarters from uninfected udders, respectively.

Results

We found that the milk EV miRNA cargo was very stable over the course of three days regardless of the health status of the quarter, and that infected quarters did not induce relevant changes in milk EVs of adjacent healthy quarters. Chronic subclinical mastitis induced changes in milk EV miRNA cargo, but neither in EVs size nor concentration. We observed that the changes in immunoregulatory miRNAs in quarters with chronic subclinical mastitis were cow-individual, however, the most upregulated miRNA was bta-miR-223-3p across all individuals.

Conclusions

Our results showed that the miRNA profile and particle size characteristics remained constant throughout consecutive days, suggesting that miRNAs packed in EVs are physiological state-specific. In addition, infected quarters were solely affected while adjacent healthy quarters remained unaffected. Finally, the cow-individual miRNA changes pointed towards infection-specific alterations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08377-z.

The influence of shade availability on the effectiveness of the Dairy Heat Load Index (DHLI) to predict lactating cow behavior, physiology, and production traits

Numerous climatic indices have been utilized to predict the effect of hot, and cold, climatic conditions on animal production and welfare. To date, the dairy industry has relied extensively on the Temperature Humidity Index (THI) to predict adverse climatic conditions; however, neither solar radiation nor air movement is accounted for in the THI equation. The Dairy Heat Load Index (DHLI) was initially developed as an alternative climate index. In its current format, the DHLI does not account for the effects of heat load mitigation strategies, such as shade, which decreases the negative effects of hot climatic conditions on lactating cows. Therefore, this experiment aimed to determine the effectiveness of the DHLI as a predictor of heat load responses in both shaded and unshaded cows, as compared with the THI. Forty lactating Holstein Friesian (n = 40) cows were selected and paired based on live weight, milk yield, and days in milk. One cow from each pair was randomly allocated to one of two treatments: shaded (n = 20) or unshaded (n = 20). Cows were given 7 days to acclimate prior to the commencement of data collection. After 28 days, cows were transitioned into the alternate treatment in a crossover design and given 7 days to acclimate prior to data collection. Behavioral observations (0800, 1200, 1400, and 1800 h daily), daily milk yield (kg), milk composition (various days), and vaginal temperature (T_VAG, °C; 5 pairs/week, over a 4-week rotation) were recorded. Overall, data from this experiment indicated that the DHLI was a better predictor of standing and feeding behaviors in unshaded cows and drinking behaviors in shaded cows. Conversely, the THI was a better predictor of standing behavior and shade usage in shaded cows. Furthermore, the THI was a better predictor of mean panting score (MPS) in shaded cows, whereas the DHLI performed better in unshaded cows. Additionally the DHLI was a better predictor of T_VAG in these cows. Finally, when evaluating the 7-day average of each climatic index, the DHLI was a better predictor of change in milk yield. Incorporation of additional animal and management factors is required if the DHLI is to become an effective heat load management tool.

Circadian Gene PER2 Silencing Downregulates PPARG and SREBF1 and Suppresses Lipid Synthesis in Bovine Mammary Epithelial Cells

Simple Summary

The present study was constructed to determine the effects of the core circadian clock gene, Period 2 (PER2), on lipid synthesis in bovine mammary epithelial cells (BMECs). Data revealed that PER2-regulated genes were involved in fatty acid de novo synthesis, desaturation, TAG accumulation, and lipid droplet secretion in primary BMECs, partly by inhibiting PPARG and SREBF1. Our overall data suggests that PER2 in bovine mammary cells plays a role in regulating milk fat synthesis directly, or via the activation of the transcription regulators PPARG and SREBF1. This study provides molecular evidence underscoring a link between the circadian clock and lipid metabolism in bovines.

Abstract

PER2, a circadian clock gene, is associated with mammary gland development and lipid synthesis in rodents, partly via regulating peroxisome proliferator-activated receptor gamma (PPARG). Whether such a type of molecular link existed in bovines was unclear. We hypothesized that PER2 was associated with lipid metabolism and regulated cell cycles and apoptosis in bovine mammary epithelial cells (BMECs). To test this hypothesis, BMECs isolated from three mid-lactation (average 110 d postpartum) cows were used. The transient transfection of small interfering RNA (siRNA) was used to inhibit PER2 transcription in primary BMECs. The silencing of PER2 led to lower concentrations of cellular lipid droplets and triacylglycerol along with the downregulation of lipogenic-related genes such as ACACA, FASN, LPIN1, and SCD, suggesting an overall inhibition of lipogenesis and desaturation. The downregulation of PPARG and SREBF1 in response to PER2 silencing underscored the importance of circadian clock signaling and the transcriptional regulation of lipogenesis. Although the proliferation of BMECs was not influenced by PER2 silencing, the number of cells in the G2/GM phase was upregulated. PER2 silencing did not affect cell apoptosis. Overall, the data provided evidence that PER2 participated in the coordination of mammary lipid metabolism and was potentially a component of the control of lipid droplets and TAG synthesis in ruminant mammary cells. The present data suggested that such an effect could occur through direct effects on transcriptional regulators.

Influence of environmental factors and parity on milk yield dynamics in barn-housed dairy cattle

We investigated the effects of environmental factors on average daily milk yield and day-to-day variation in milk yield of barn-housed Scottish dairy cows milked with an automated milking system. An incomplete Wood gamma function was fitted to derive parameters describing the milk yield curve including initial milk yield, inclining slope, declining slope, peak milk yield, time of peak, persistency (time in which the cow maintains high yield beyond the peak), and predicted total lactation milk yield (PTLMY). Lactation curves were fitted using generalized linear mixed models incorporating the above parameters (initial milk yield, inclining and declining slopes) and both the indoor and outdoor weather variables (temperature, humidity, and temperature-humidity index) as fixed effects. There was a higher initial milk yield and PTLMY in multiparous cows, but the incline slope parameter and persistency were greatest in primiparous cows. Primiparous cows took 54 d longer to attain a peak yield (mean ± standard error) of 34.25 ± 0.58 kg than multiparous (47.3 ± 0.45 kg); however, multiparous cows yielded 2,209 kg more PTLMY. The best models incorporated 2-d lagged minimum temperature. However, effect of temperature was minimal (primiparous decreased milk yield by 0.006 kg/d and multiparous by 0.001 kg/d for each degree increase in temperature). Both primiparous and multiparous cows significantly decreased in day-to-day variation in milk yield as temperature increased (primiparous cows decreased 0.05 kg/d for every degree increase in 2-d lagged minimum temperature indoors, which was greater than the effect in multiparous cows of 0.008 kg/d). Though the model estimates for both indoor and outdoor were different, a similar pattern of the average daily milk yield and day-to-day variation in milk yield and milk yield's dependence on environmental factors was observed for both primiparous and multiparous cows. In Scotland, primiparous cows were more greatly affected by the 2-d lagged minimum temperature compared with multiparous cows. After peak lactation had been reached, primiparous and multiparous cows decreased milk yield as indoor and outdoor minimum temperature increased.

Milk from cows fed clover-rich silage compared with cows fed grass silage is higher in n-3 fatty acids

The present study investigated the effect of a high proportion of different forage species in the diet, parity, milking time, and days in milk (DIM) on milk fatty acid (FA) profile, and transfer efficiency of C18:2n-6, C18:3n-3, n-6, and n-3 in dairy cows. Swards with perennial ryegrass [early maturity stage (EPR) and late maturity stage (LPR)], festulolium, tall fescue (TF), red clover (RC), and white clover (WC) were cut in the primary growth, wilted, and ensiled without additives. Thirty-six Danish Holstein cows in an incomplete Latin square design were fed ad libitum with total mixed rations containing a high forage proportion (70% on dry matter basis). The total mixed rations differed only in forage source, which was either 1 of the 6 pure silages or a mixture of LPR silage with either RC or WC silage (50:50 on dry matter basis). Proportion of C18:2n-6 in milk FA was affected by diet, and RC and WC diets resulted in the highest proportion of C18:2n-6 in milk FA (21.6 and 21.8 g/kg of FA, respectively). The highest and lowest milk C18:3n-3 proportion was observed in WC and LPR, respectively. In addition, WC diet resulted in highest transfer efficiency of C18:3n-3 from feed to milk (12.2%) followed by RC diet (10.7%), whereas EPR diet resulted in the lowest transfer efficiency of C18:3n-3 (3.45%). The highest milk proportion of cis-9,trans-11 conjugated linoleic acid (CLA) was observed in cows fed TF (3.20 g/kg of FA), which was 23 to 64% higher than the proportion observed in the cows fed the other diets. The highest α-tocopherol concentration (µg/mL) in milk was observed in EPR (1.15), LPR (1.10), and festulolium (1.06). Primiparous cows showed higher proportion of cis-9,trans-11 CLA (2.63 g/kg of FA) than multiparous cows (2.21 g/kg of FA). Cows early in lactation had a higher proportion of long-chain FA in milk than cows later in lactation, as long-chain FA decreased with 0.184 g/kg of FA per DIM, whereas medium-chain FA increased with 0.181 g/kg of FA per DIM. Proportion of C18:2n-6 in milk from evening milking was higher than in milk from morning milking (16.7 vs. 15.8 g/kg of FA). In conclusion, the results showed that milk FA profile of cows was affected by forage source in the diet, and RC and WC increased the health-promoting FA components, particularly n-3, whereas the TF diet increased proportion of CLA isomers in milk. Proportion of CLA isomers in milk FA from primiparous cows was higher than in milk from multiparous cows. In addition, evening milk contained more FA originating from diets compared with morning milk.

Benchmarking of farms with automated milking systems in Canada and associations with milk production and quality

The objective of this study was to benchmark the herd-level housing and management strategies of automated milking system (AMS) farms across Canada and assess the associations of these herd-level housing factors and management practices with milk production and quality. Canadian AMS farms (n = 197; Western Canada: n = 50, Ontario: n = 77, Quebec: n = 59, Atlantic Canada: n = 11) were each visited once from April to September 2019, and details were collected related to barn design and herd management practices. Milk-recording data for the 6 mo before farm visits were collected. Farms averaged (± standard deviation) 110 ± 102 lactating cows, 2.4 ± 1.9 AMS units/farm, 47.5 ± 14.9 cows/AMS, 36.7 ± 5.0 kg/d of milk, 4.13 ± 0.34% fat, 3.40 ± 0.16% protein, and a herd-average somatic cell count of 186,400 ± 80,800 cells/mL. Farms mainly used freestall housing systems (92.5%), organic bedding substrates (73.6%), and free flow cow traffic systems (87.8%); farms predominantly milked Holsteins (90.4%). Multivariable regression models were used to associate herd-level housing factors and management practices with milk production and quality. At the herd level, feed push-up frequency (mean = 12.8 ± 8.3 times per day) and feed bunk space (mean = 64 ± 21.5 cm/cow) were positively associated with milk yield. Greater milk yield was associated with herds using inorganic (sand) versus organic bedding, milking Holsteins versus non-Holsteins, and using a form of mechanical ventilation versus natural ventilation alone. Milk fat and milk protein content were only associated with breed. Herds with lower somatic cell counts had more frequent alley cleaning (mean = 12.1 ± 7.5 times per day), wider lying alleys (mean = 304.5 ± 40.0 cm), and sand bedding. The results highlight the importance of using sand bedding, using mechanical ventilation, keeping feed pushed up, ensuring alleys are clean, and ensuring adequate space at the feed bunk for maintaining herd-level productivity and milk quality in farms with AMS.

Qualitative indicators of milk of Simmental and Holstein cows in different seasons of lactation

Background and Aim:

Milk producers need to ensure that their cows are producing high-quality, nutritional milk, which is influenced by the breed, age, nutrition, and health status of lactating animals. The aim of this study was to determine the effect of animal breed, season, and milk production on the physicochemical characteristics of milk and predicting the effect of these changes on the composition and quality of milk products.

Materials and Methods:

In total, 80 milk samples (40 Simmental and 40 Holstein) were analyzed from LLP “Kirova” of Pavlodar region (Simmental breed) and JSC “Astana-Onim” of Akmola region (Holstein breed) in the Republic of Kazakhstan. The physicochemical parameters, including fatty acid (FA) content, were studied.

Results:

The Simmental cows had the lowest mass fraction of fat in the spring at 3.94% and the highest fat content in the winter at 4.09%, which was the overall highest fat content measured in both breeds (p<0.001). The lowest protein in the Simmentals was also measured in the spring. The Holstein cows had the highest fat content at 3.8% and the highest protein content at 3.3% in autumn.

Conclusion:

It was found that the season and breed significantly affected the physicochemical parameters and the FA contents in cow milk. The superiority of the Simmental cows over the Holstein cows throughout the year was statistically significant.

Associations between Mammary Gland Echotexture and Milk Composition in Cows

Simple Summary

Transcutaneous ultrasonography of the four quarters of the cow’s mammary gland with the 5-MHz ultrasound transducer combined with computer-assisted analysis of the resultant grey-scale images have the makings of an inexpensive and rapid technique to determine certain physicochemical properties of the pooled milk. The latter include crude protein, casein and lactose content. The relative ease and practically unlimited frequency with which this method can be used in farm settings makes it an attractive alternative to laboratory testing of milk samples. More studies are needed to determine the suitability of this approach for detecting changes in milk chemical composition in animals with mastitis.

Abstract

Thirty clinically healthy Holstein-Friesian cows underwent twice daily machine milking and ultrasonographic examinations of the udder just prior to and after milking. Digital ultrasonographic images of each udder quarter were subjected to computer-assisted echotextural analyses to obtain mean numerical pixel values (NPVs) and pixel heterogeneity (PSD) of the mammary gland parenchyma. The average milk yield and pH were higher (p < 0.05) in the morning, whereas crude fat, total solids, solids non-fat and citric acid content were higher (p < 0.05) during the evening milking period. Mean NPVs and PSDs of the mammary gland parenchyma were greater (p < 0.05) after than before milking. There were significant correlations among echotextural characteristics of the udder and protein percentage, lactose content and freezing point depression determined in the milk samples collected in the morning and crude protein, casein, lactose and solids non-fat in the evening. Our results can be interpreted to suggest that computerized analysis of the mammary gland ultrasonograms has the makings of a technique for estimating non-fat milk constituents in cows. However, future validating studies are necessary before this method can be employed in commercial settings and research. Moreover, significant inter-quarter differences in udder echogenicity may necessitate further echotextural studies of separate quarters.

Modeling cow somatic cell count using sensor data as input to generalized additive models

This research paper presents a study investigating if sensor data from an automatic milking rotary could be used to model cow somatic cell count (composite milk SCC: CMSCC). CMSCC is valuable for udder health monitoring and individual cow udder health surveillance could be improved by predicting CMSCC between routine samplings. Data regularly recorded in the automatic milking rotary, in one German dairy herd, were collected for analysis. The cows (Holstein-Friesian, n = 372) were milked twice daily and sampled once weekly in afternoon milkings for 8 weeks for CMSCC. From the potential independent variables, including quarter conductivity, milk flow, blood in milk, kick-offs, not milked quarters and incomplete milkings, new variables that combined quarter data were created. Past period records, i.e. lags, of up to seven days before the actual CMSCC sampling event were added in the dataset to investigate if they were of use in modeling the cell count. Univariable generalized additive models (GAM) were used to screen the data to select potential independent variables. Furthermore, several multivariable GAM were fitted in order to compare the importance of the potential independent variables and to explore how the model performance would be affected by using data from various number of days before the CMSCC sampling event. The result of the model selection showed that the best explanation of CMSCC was provided by the model incorporating all significant variables from the variable screening for the seven preceding days, including the day of the CMSCC sampling event. However, using data from only three days before the CMSCC sampling event is suggested to be sufficient to model CMSCC. Variables combining conductivity quarter data, together with quarter conductivity, are suggested to be important in describing CMSCC. We conclude that CMSCC can be modeled with a high degree of explanation using the information routinely recorded by the milking robot.

An Innovative Concept for a Multivariate Plausibility Assessment of Simultaneously Recorded Data

The aim of this work was to develop an innovative multivariate plausibility assessment (MPA) algorithm in order to differentiate between 'physiologically normal', 'physiologically extreme' and 'implausible' observations in simultaneously recorded data. The underlying concept is based on the fact that different measurable parameters are often physiologically linked. If physiologically extreme observations occur due to disease, incident or hormonal cycles, usually more than one measurable trait is affected. In contrast, extreme values of a single trait are most likely implausible if all other traits show values in a normal range. For demonstration purposes, the MPA was applied on a time series data set which was collected on 100 cows in 10 commercial dairy farms. Continuous measurements comprised climate data, intra-reticular pH and temperature, jaw movement and locomotion behavior. Non-continuous measurements included milk yield, milk components, milk mid-infrared spectra and blood parameters. After the application of the MPA, in particular the pH data showed the most implausible observations with approximately 5% of the measured values. The other traits showed implausible values up to 2.5%. The MPA showed the ability to improve the data quality for downstream analyses by detecting implausible observations and to discover physiologically extreme conditions even within complex data structures. At this stage, the MPA is not a fully developed and validated management tool, but rather corresponds to a basic concept for future works, which can be extended and modified as required.

Comparison of methods for predicting cow composite somatic cell counts

One of the most common and reliable ways of monitoring udder health and milk quality in dairy herds is by monthly cow composite somatic cell counts (CMSCC). However, such sampling can be time consuming, and more automated sampling tools entail extra costs. Machine learning methods for prediction have been widely investigated in mastitis detection research, and CMSCC is normally used as a predictor or gold standard in such models. Predicted CMSCC between samplings could supply important information and be used as an input for udder health decision-support tools. To our knowledge, methods to predict CMSCC are lacking. Our aim was to find a method to predict CMSCC by using regularly recorded quarter milk data such as milk flow or conductivity. The milk data were collected at the quarter level for 8 wk when milking 372 Holstein-Friesian cows, resulting in a data set of 30,734 records with information on 87 variables. The cows were milked in an automatic milking rotary and sampled once weekly to obtain CMSCC values. The machine learning methods chosen for evaluation were the generalized additive model (GAM), random forest, and multilayer perceptron (MLP). For each method, 4 models with different predictor variable setups were evaluated: models based on 7-d lagged or 3-d lagged records before the CMSCC sampling and additionally for each setup but removing cow number as a predictor variable (which captures indirect information regarding cows' overall level of CMSCC based on previous samplings). The methods were evaluated by a 5-fold cross validation and predictions on future data using models with the 4 different variable setups. The results indicated that GAM was the superior model, although MLP was equally good when fewer data were used. Information regarding the cows' level of previous CMSCC was shown to be important for prediction, lowering prediction error in both GAM and MLP. We conclude that the use of GAM or MLP for CMSCC prediction is promising.

Night-restricted feeding of dairy cows modifies daily rhythms of feed intake, milk synthesis and plasma metabolites compared with day-restricted feeding

The timing of feed intake can alter circadian rhythms of peripheral tissues. Milk synthesis displays a daily rhythm across several species, but the effect of feeding time on these rhythms is poorly characterised. The objective of this experiment was to determine if the time of feed intake modifies the daily patterns of milk synthesis, plasma metabolites and body temperature in dairy cows. Sixteen lactating Holstein dairy cows were randomly assigned to one of the two treatment sequences in a cross-over design with 17 d periods. Treatments included day-restricted feeding (DRF; feed available from 07.00 to 23.00 hours) and night-restricted feeding (NRF; feed available from 19.00 to 11.00 hours). Cows were milked every 6 h on the last 7 d of each period, and blood samples were collected to represent every 4 h over the day. Peak milk yield was shifted from morning in DRF to evening in NRF, while milk fat, protein and lactose concentration peaked in the evening in DRF and the morning in NRF. Plasma glucose, insulin, NEFA and urea nitrogen concentration fit daily rhythms in all treatments. Night feeding increased the amplitude of glucose, insulin and NEFA rhythms and shifted the daily rhythms by 8 to 12 h (P < 0·05). Night feeding also phase-delayed the rhythm of core body temperature and DRF increased its amplitude. Altering the time of feed availability shifts the daily rhythms of milk synthesis and plasma hormone and metabolite concentrations and body temperature, suggesting that these rhythms may be entrained by food intake.

Identifying gram-negative and gram-positive clinical mastitis using daily milk component and behavioral sensor data

Opportunities exist for automated animal health monitoring and early detection of diseases such as mastitis with greater on-farm adoption of precision technologies. Our objective was to evaluate time series changes in individual milk component or behavioral variables for all clinical mastitis (CM) cases (ACM), for CM caused by gram-negative (GN) or gram-positive (GP) pathogens, or CM cases in which no pathogen was isolated (NPI). We developed algorithms using a combination of milk and activity parameters for predicting each of these infection types. Milk and activity data were collated for the 14 d preceding a CM event (n = 170) and for controls (n = 166) matched for breed, parity, and days in milk. Explanatory variables in the univariate and multiple regression models were the slope change in milk (milk yield, conductivity, somatic cell count, lactose percentage, protein percentage, and fat percentage) and activity parameters (steps, lying time, lying bout duration, and number of lying bouts) over 7 d. Slopes were estimated using linear regression between d -7 and -5, d -7 and -4, d -7 and -3, d -7 and -2, and d -7 and -1 relative to CM detection for all parameters. Univariate analyses determined significant slope ranges for explanatory variables against the 4 responses: ACM, GN, GP, and NPI. Next, all slope ranges were offered into the multivariate models for the same 4 responses using 3 baselines: d -10, -7, and -3 relative to CM detection. In the univariate analysis, no explanatory variables were significant indicators of ACM, whereas at least 1 parameter was significant for each of GN, GP, and NPI models. Superior sensitivity (Se) and specificity (Sp) estimates were observed for the best GP (Se = 82%, Sp = 87%) and NPI (Se = 80%, Sp = 94%) multiple regression models compared with the best ACM (Se = 73%, Sp = 75%) and GN (Se = 71%, Sp = 74%) models. Sensitivity for the GN model was greater at the baseline closest to the day of CM detection (d -3), whereas the opposite was observed for the GP and NPI model as Se was maximized at the d -10 baseline. Based on this screening of relationships, milk and activity sensor data could be used in CM detection systems.

Factors associated with milking-to-milking variability in somatic cell counts from healthy cows in an automatic milking system

Fully automated on-line analysis equipment is available for analysis of somatic cell count (SCC) at every milking in automatic milking systems. In addition to results from on-line cell counters (OCC), an array of additional cow-level and quarter-level factors considered important for udder health are recorded in these systems. However, the amount of variability in SCC that can be explained by available data is unknown, and so is the proportion of the variability that may be due to physiological or normal variability. Our aim was to increase our knowledge on OCC as an indicator for disturbances in udder health by assessing the variability in OCC in cows free from clinical mastitis. The first objective was to evaluate how much of the variability in OCC could be explained by different potential sources of variability, including intramammary infection (IMI) status (assessed by bacterial culture of quarter milk samples). The second objective was to evaluate the repeatability of the OCC sensor used in our study and the agreement between OCC values and SCC measured in a dairy herd improvement (DHI) laboratory. A longitudinal study was performed in the research herd of the Norwegian University of Life Sciences from January 5th 2016 to May 22nd 2017. Data from 62,471 milkings from 173 lactations in 129 cows were analyzed. We used ln-transformed OCC values (in 1000 cells/ml) as the outcome (lnOCC) in linear mixed models, with random intercepts at cow-level and lactation-level within cow. We were able to explain 15.0% of the variability in lnOCC with the following fixed effects: lactation stage, parity, milk yield, OCC in residual milk from the previous milking, inter-quarter difference between the highest and lowest conductivity, season, IMI status, and genetic lineage. When including the random intercepts, the degree of explanation was 55.2%. The individual variables explained only a small part of the total variability in lnOCC. We concluded that physiological or normal variability is probably responsible for a large part of the overall variability in OCC in cows without clinical mastitis. This is important to consider when using OCC data for research purposes or in decision-support tools. Sensor repeatability was evaluated by analyzing milk from the same sample multiple times. The coefficient of variation was 0.11 at an OCC level relevant for detection of subclinical mastitis. The agreement study showed a concordance correlation coefficient of 0.82 when comparing results from the OCC with results from a DHI laboratory.

Polymorphism association and expression analysis of alpha-lactalbumin (LALBA) gene during lactation in Nili Ravi buffalo

Alpha-lactalbumin has been reported as a highly polymorphic gene that potentially alters the gene expression and is associated with milk composition in dairy breeds. Current study was conducted in two phases. In the first phase, polymorphisms identification in alpha-lactalbumin (LALBA) gene and its association with milk composition was performed. To identify the genetic polymorphism, Nili Ravi buffaloes at their second lactation were selected from Government livestock farm (Buffalo Research Institute, Pattoki). Genomic DNA was extracted from blood samples. After PCR amplification, products were sequenced, and data was analyzed. Results showed that the identified polymorphisms at chromosomal position 34310940 were found associated with major whey protein. In the second phase of study, milk samples were collected from five healthy mastitis-free Nili Ravi buffaloes in their second lactation for expression analysis of alpha-lactalbumin gene at their transition (day 15), mid (day 90), and late (day 250) lactation. Gene expression was observed highest in transition phase with a gradual decrease of expression in mid and late phase of lactation. Further studies are needed to explore the regulation of milk production genes and their translational efficiency during the course of lactation.

The Impact of Heat Load on Cattle

Heat stress and cold stress have a negative influence on cattle welfare and productivity. There have been some studies investigating the influence of cold stress on cattle, however the emphasis within this review is the influence of heat stress on cattle. The impact of hot weather on cattle is of increasing importance due to the changing global environment. Heat stress is a worldwide phenomenon that is associated with reduced animal productivity and welfare, particularly during the summer months. Animal responses to their thermal environment are extremely varied, however, it is clear that the thermal environment influences the health, productivity, and welfare of cattle. Whilst knowledge continues to be developed, managing livestock to reduce the negative impact of hot climatic conditions remains somewhat challenging. This review provides an overview of the impact of heat stress on production and reproduction in bovines.

Co-Expression Network and Pathway Analyses Reveal Important Modules of miRNAs Regulating Milk Yield and Component Traits

Co-expression network analyses provide insights into the molecular interactions underlying complex traits and diseases. In this study, co-expression network analysis was performed to detect expression patterns (modules or clusters) of microRNAs (miRNAs) during lactation, and to identify miRNA regulatory mechanisms for milk yield and component traits (fat, protein, somatic cell count (SCC), lactose, and milk urea nitrogen (MUN)) via miRNA target gene enrichment analysis. miRNA expression (713 miRNAs), and milk yield and components (Fat%, Protein%, lactose, SCC, MUN) data of nine cows at each of six different time points (day 30 (D30), D70, D130, D170, D230 and D290) of an entire lactation curve were used. Four modules or clusters (GREEN, BLUE, RED and TURQUOISE) of miRNAs were identified as important for milk yield and component traits. The GREEN and BLUE modules were significantly correlated (|r| > 0.5) with milk yield and lactose, respectively. The RED and TURQUOISE modules were significantly correlated (|r| > 0.5) with both SCC and lactose. In the GREEN module, three abundantly expressed miRNAs (miR-148a, miR-186 and miR-200a) were most significantly correlated to milk yield, and are probably the most important miRNAs for this trait. DDR1 and DDHX1 are hub genes for miRNA regulatory networks controlling milk yield, while HHEX is an important transcription regulator for these networks. miR-18a, miR-221/222 cluster, and transcription factors HOXA7, and NOTCH 3 and 4, are important for the regulation of lactose. miR-142, miR-146a, and miR-EIA17-14144 (a novel miRNA), and transcription factors in the SMAD family and MYB, are important for the regulation of SCC. Important signaling pathways enriched for target genes of miRNAs of significant modules, included protein kinase A and PTEN signaling for milk yield, eNOS and Noth signaling for lactose, and TGF β, HIPPO, Wnt/β-catenin and cell cycle signaling for SCC. Relevant enriched gene ontology (GO)-terms related to milk and mammary gland traits included cell differentiation, G-protein coupled receptor activity, and intracellular signaling transduction. Overall, this study uncovered regulatory networks in which miRNAs interacted with each other to regulate lactation traits.

Genetic and nongenetic factors associated with milk color in dairy cows

Milk color is one of the sensory properties that can influence consumer choice of one product over another and it influences the quality of processed dairy products. This study aims to quantify the cow-level genetic and nongenetic factors associated with bovine milk color traits. A total of 136,807 spectra from Irish commercial and research herds (with multiple breeds and crosses) were used. Milk lightness (Lˆ*), red-green index (aˆ*) and yellow-blue index (bˆ*) were predicted for individual milk samples using only the mid-infrared spectrum of the milk sample. Factors associated with milk color were breed, stage of lactation, parity, milking-time, udder health status, pasture grazing, and seasonal calving. (Co)variance components for Lˆ*,aˆ*, and bˆ* were estimated using random regressions on the additive genetic and within-lactation permanent environmental effects. Greater bˆ* value (i.e., more yellow color) was evident in milk from Jersey cows. Milk Lˆ* increased consistently with stage of lactation, whereas aˆ* increased until mid lactation to subsequently plateau. Milk bˆ* deteriorated until 31 to 60 DIM, but then improved thereafter until the end of lactation. Relative to multiparous cows, milk yielded by primiparae was, on average, lighter (i.e., greater Lˆ*), more red (i.e., greater aˆ*), and less yellow (i.e., lower bˆ*). Milk from the morning milk session had lower Lˆ*,aˆ*, and bˆ* Heritability estimates (±SE) for milk color varied between 0.15 ± 0.02 (30 DIM) and 0.46 ± 0.02 (210 DIM) for Lˆ*, between 0.09 ± 0.01 (30 DIM) and 0.15 ± 0.02 (305 DIM) for aˆ*, and between 0.18 ± 0.02 (21 DIM) and 0.56 ± 0.03 (305 DIM) for bˆ* For all the 3 milk color features, the within-trait genetic correlations approached unity as the time intervals compared shortened and were generally <0.40 between the peripheries of the lactation. Strong positive genetic correlations existed between bˆ* value and milk fat concentration, ranging from 0.82 ± 0.19 at 5 DIM to 0.96 ± 0.01 at 305 DIM and confirming the observed phenotypic correlation (0.64, SE = 0.01). Results of the present study suggest that breeding strategies for the enhancement of milk color traits could be implemented for dairy cattle populations. Such strategies, coupled with the knowledge of milk color traits variation due to nongenetic factors, may represent a tool for the dairy processors to reduce, if not eliminate, the use of artificial pigments during milk manufacturing.

The prevalence, temporal and spatial trends in bulk tank equivalent milk fat depression in Irish milk recorded herds

BACKGROUND

Milk fat is important in terms of economic value and in its potential to provide information concerning cow diet and health. Under current milk payment schemes in Ireland farmer income is directly linked to milk fat production.

METHODS

A descriptive analysis of milk fat depression (MFD) as calculated from test day milk recording data across all milk recording herds from 2004 to 2014 was undertaken. A dataset of 17 million test day records was used to calculate the prevalence of MFD in Irish milk recorded herds and to create a graphical description of the major descriptive epidemiological trends in milk fat depression in time and space in Ireland. The bulk tank equivalent (BTE) for test day milk fat was calculated for each herd and for cohorts of cows within herds using the formula; BTE milk fat = sum test day fat kg/sum test day milk kg. Milk fat depression was defined as BTE <3.3% milk fat and BTE > 3.2% milk protein.

RESULTS

The annual prevalence of MFD decreased significantly over time in a linear manner until 2014. Across all years the highest prevalence of MFD occurred in April or May. The highest prevalence occurred most commonly in May, with 9.1% of herds experiencing MFD in 2014. The highest prevalence of MFD in autumn calved cohorts occurred at 181-210 days in milk whereas it occurred at days 61-90 in milk in spring calving cohorts. The stage of lactation for the most common occurrence of MFD in both the spring and autumn cohorts corresponded with the month of May. There were some notable spatial patterns regarding variations in prevalence of MFD across the country. Cohorts of cows with the highest genetic values for milk yield had the highest prevalence of MFD whereas cohorts of cows with the highest breeding values for milk fat percent had the lowest prevalence of MFD.

CONCLUSIONS

A subpopulation of Irish herds experienced the condition of MFD. Descriptive analysis suggested spatial, temporal and animal level associations. This condition warrants further investigation.

The impact of crossbreeding Egyptian and Italian buffalo on milk yield and composition under subtropical environmental conditions

Buffalo are the second most valuable species in the world for milk production and their milk prices have been based on fat and protein composition. The aim of the paper was to compare the milk yield and composition of pure Egyptian buffalo (EB) and their crosses with the Italian buffalo and to investigate the impact of temperature humidity index (THI) on milk yield and composition under subtropical stressful conditions. 516 lactating buffalo were used (152 EB; 176 F1 crosses 50% EB and 50% Italian buffalo and 188 back cross (BC) 75% EB and 25% Italian buffalo). The results revealed that, milk yield (5·79 and 10·32%) and peak yield (6·36 and 7·67%) were significantly higher in F1 and BC than in EB, respectively. BC had 7·74 and 3·67% significantly higher daily yield when compared with EB and F1, respectively. EB were robust in the hot condition as the only reduction was in the peak of milk production from 15·02 in low THI to 13·72 kg in high THI, but fat and total solids%, were increased from 5·61 and 16·31 THI in low to 7·01 and 17·59 in high THI, respectively. BC was similar to some extent to EB as their milk was similar to EB under sever hot climate conditions (2331·92 and 2327·50 kg, respectively). A statistically significant reduction in the average daily milk yields was detected only in F1 from 10·33 to 8·38 kg in low and high THI level, respectively. The current study showed that BC produced a higher milk with higher daily average milk yield and peak yield with some evidence of robust under sever hot condition which were approximately similar to EB. Thus, it is recommended to encourage the producers to increase the number of BC animals in their farm for improving the milk production to fulfil the demand of Egyptian markets.

Diurnal differences in milk composition and its influence on in vitro growth of Staphylococcus aureus and Escherichia coli in bovine quarter milk

In experimental intramammary inoculation studies, it has been observed that mastitis susceptibility is influenced, among others, by cow factors. To identify milk characteristics leading to these differences, quarter milk samples of morning and evening milk were collected and analyzed for their composition (protein, fat, lactose, urea, lactoferrin, lactoperoxidase, and β-lactoglobulin concentrations), somatic cell count, and antibodies against Staphylococcus aureus. Furthermore, in vitro growth of S. aureus and Escherichia coli in fresh quarter milk samples was determined. All measured parameters differed significantly between quarters and also between morning and evening milk with the exception of lactose levels. In addition, quantitative growth of S. aureus and E. coli was significantly different in morning milk compared with evening milk. Mixed model analysis revealed that replication of S. aureus was negatively associated with the presence of fat, S. aureus-specific IgG1 antibodies, contamination of the milk sample and morning milk. Replication of E. coli was negatively associated with fat concentrations, and positively associated with morning milk. The significant difference between morning and evening milk supports the theory that changes in milk composition influence bacterial growth. Although all determined milk components differed significantly between quarters and in time no significant association with bacterial growth could be identified with the exception of fat for both studied species and IgG1 titers for S. aureus. The negative association of fat with bacterial growth was assumed to occur due to activation of lipolysis by milk handling and can most likely be neglected for in vivo relevance. The fact that S. aureus-specific IgG1 titers were negatively associated with S. aureus growth in vitro encourages the ongoing effort to develop a vaccine against S. aureus-induced mastitis.

Estudo longitudinal da mastite subclínica e produção de leite em um rebanho mestiço Holandês-Zebu criado em sistema semi-intensivo

Acompanhou-se durante 15 meses um rebanho leiteiro, composto por diferentes graus de sangue Holandês-Zebu (HZ), em sistema semi-intensivo. Objetivou-se avaliar o comportamento longitudinal da contagem de células somáticas (CCS) e a influência da mastite subclínica (MS) na produção total e no pico de produção de leite de vacas mestiças HZ. Inicialmente, coletaram-se amostras de leite individual para análise microbiológica, a fim de identificar o perfil de patógenos causadores de mastite. Realizou-se mensalmente a CCS com o intuito de monitorar a MS. Semanalmente, avaliou-se a produção de leite. Para avaliar o efeito da CCS sobre a produção de leite, as vacas foram divididas em dois grupos, <200.000 e ≥200.000 células/mL. Os patógenos encontrados foram Streptococcusambientais (34%), células leveduriformes (29%), Staphylococcuscoagulase negativa (31%) e Staphylococcus aureus (6%), com CCS de 1.100.000, 845.000, 275.000 e 620.000, respectivamente. A CCS média variou de 255.000 a 975.000 cél./mL, com prevalência média de 42% de MS. Vacas primíparas com MS apresentaram redução da produção total de leite quando comparadas às primíparas sem MS (P<0,05). Em contraste, a produção total das vacas multíparas não foi alterada. Não foram observadas diferenças entre a CCS, a produção total e o pico de produção nos diferentes graus de sangue HZ (P>0,05). A CCS das vacas diferiu (P<0,01) entre a secagem e o pós-parto imediato. A manutenção das condições de elevado risco ambiental em rebanho leiteiro manejado em sistema semi-intensivo pode minimizar as variações na ocorrência de MS nos períodos de verão e inverno, possibilitando a expressão do problema em vacas de diferentes graus de sangue HZ. Em um rebanho caracterizado pela ocorrência de mastite predominantemente ambiental, a produção de leite na lactação total de vacas primíparas com CCS superior a 200.000 cél./mL é reduzida em comparação com vacas com CCS inferior a 200.000 cél./mL, o que não foi observado em vacas multíparas.

Recent advances on the circadian gene PER2 and metabolic rhythm of lactation of mammary gland

Due to regulation by circadian rhythm, the lactation of the mammary gland has rhythmicity. As one of prominent members of period protein family which regulates biological rhythms, PER2 plays an important role in developing the milk duct and maintaining the polarity and the morphology of the mammary epithelium; at the same time, it is also closely related with the metabolism of milk protein and milk fat. This paper summarized recent researches on PER2 gene and related researches on mammary gland development and metabolism to provide some information for the studies of the theory and technology on physiological functions of the mammary gland and milk quality control.

Cortisol levels in skimmed milk during the first 22 weeks of lactation and response to short-term metabolic stress and lameness in dairy cows

Background

Cortisol is secreted into blood in reaction to acute stress, but also in phases of diminished feed intake and changed animal behavior. As cows do not always show clear signs of discomfort, reliable diagnostic markers could be used to provide information regarding individual cows’ distress. The objective of this study was to establish an ether free immunoassay for the detection of cortisol and to determine values during the first 22 weeks of lactation. Furthermore, the response in milk cortisol levels was assessed during times of metabolic stress and pain associated symptoms of lameness.

Methods

Milk yield and composition, blood serum glucose, NEFA and BHBA as well as milk cortisol were determined in 24 multiparous Holstein-Friesian cows over the course of the first 22 weeks of lactation. Animals were further checked for signs of clinical diseases on a daily basis. Two feed restrictions over three days (FR; 70 % of precious ad libitum intake) were performed during the 4^th wk and the 21^st wk, respectively. An ELISA for cortisol measurement in easily accessible bovine skimmed milk was established and applied.

Results

On the last day of FR in early lactation, a reduction in milk yield and changes in serum metabolites compared to respective previous values were detected. The FR in mid-lactation resulted in no changes in milk production and serum metabolites. Milk cortisol was highest during first wk of lactation and remained on comparable levels thereafter. Milk yield and composition were not influenced by FR. Lameness resulted in enhanced milk cortisol levels.

Conclusion

Milk cortisol could be used as an indicator of painful symptoms such as lameness. Higher values of milk cortisol levels during first wk of lactation should be taken into account for interpretation.

The daily rhythm of milk synthesis is dependent on the timing of feed intake in dairy cows

Regulation of the daily rhythm of milk synthesis is important to production animals and breastfeeding, but is difficult to observe in nursing animals. The rate of food intake varies over the day and is expected to create a daily rhythm of nutrient absorption. The objective of this study was to determine if the timing of food intake entrains a daily pattern of milk synthesis. Seventeen Holstein cows were used in a crossover design. Treatments were ad libitum feeding of a total mixed ration once daily (1× fed) or fed in four equal meals every 6 h (4× fed). Cows were milked every 6 h the last 7 days of each period. There was a treatment by time of day interaction for milk and milk component yield and concentration. Milk fat and protein concentration and yield exhibited a daily rhythm and the amplitude of the rhythm was reduced in 4× fed. In addition, milk fat percent was higher in 4× fed than 1× fed at three of the four milking intervals (0.22–0.45% higher) and 4× fed increased daily milk fat yield. Treatment by time of day interactions were detected for plasma glucose, insulin, and blood urea nitrogen. These variables also fit a cosine function with a 24 h period and the amplitudes of plasma glucose, insulin, and blood urea nitrogen rhythms were decreased by 4× feeding. In conclusion, there is a circadian pattern of milk synthesis in the dairy cow that is responsive to the timing of food intake.

Regulation of the daily rhythm of milk synthesis is important to production animals and breastfeeding. The objective of this study was to determine if the timing of food intake entrains a daily pattern of milk synthesis. A circadian pattern of milk synthesis was observed that was responsive to the timing of food intake.

Climatic effects on milk production traits and somatic cell score in lactating Holstein-Friesian cows in different housing systems

The objective of this study was to compare the effect of the temperature-humidity index (THI) on milk production traits and somatic cell score (SCS) of dairy cows raised in 4 different housing systems: (1) warm loose housing with access to grazing (WG), (2) warm loose housing without access to grazing (WI), (3) cold loose housing with access to grazing (CG), and (4) cold loose housing without access to grazing (CI). For each of the 4 housing systems, 5 farms with a herd size of 70 to 200 lactating cows in Lower Saxony, Germany, were studied. Ambient temperature and relative humidity were recorded hourly in each barn to calculate THI. Milk production data included 21,546 test-day records for milk, fat, and protein yield, and SCS. These data were associated with the average THI of the 3 d preceding the respective measurement, which was divided into 6 classes (<45, ≥45 to <50, ≥50 to <55, ≥55 to <60, ≥60 to <65, and ≥65). Furthermore, bulk milk samples including the fat and protein percentage, and SCS taken 4 to 6 times per month were associated with the average and maximum THI of the 3 d before sampling. Data were recorded from April 2010 to March 2011. In each of the housing systems, monthly THI values above 60, indicating heat stress, were recorded between June and September, with higher values in WI and WG. In all systems, fat-corrected milk, fat, and protein yields of the test-day records decreased in tendency from 60 ≤ THI<65 to THI >65. In WI and CI, values for SCS were greater in the class THI > 65 than in 60 ≤ THI<65, whereas no difference between any of the THI classes was found in WG and CG. The fat and protein percentage of the bulk milk samples decreased with increasing 3-d maximum THI in all 4 systems, whereas the SCS increased with increasing 3-d average THI. In conclusion, negative effects of heat stress conditions under a temperate climate on milk production traits and SCS were found, although a housing system being superior to the other systems in altering heat stress effects was not identified.

Effects of seasonal change and parity on raw milk composition and related indices in Chinese Holstein cows in northern China

This study was to investigate the effects of seasonal change and parity on milk composition and related indices, and to analyze the relationships among milk indices in Chinese Holstein cows from an intensive dairy farm in northern China. The 6,520 sets of complete Dairy Herd Improvement data were obtained and grouped by natural month and parity. The data included daily milk yield (DMY), milk solids percentage (MSP), milk fat percentage (MFP), milk protein percentage (MPP), milk lactose percentage (MLP), somatic cell count (SCC), somatic cell score (SCS), milk production loss (MPL), and fat-to-protein ratio (FPR). Data analysis showed that the above 9 indices were affected by both seasonal change and parity. However, the interaction between parity and seasonal change showed effects on MLP, SCS, MPL, and DMY, but no effects on MFP, MPP, MSP, and FPR. Duncan's multiple comparison on seasonal change showed that DMY (23.58 kg/d), MSP (12.35%), MPP (3.02%), and MFP (3.81%) were the lowest in June, but SCC (288.7 × 10(3)/mL) and MPL (0.69 kg/d) were the lowest in January; FPR (1.32) was the highest in February. Meanwhile, Duncan's multiple comparison on parities showed that MSP, MPP, and MLP were reduced rapidly in the fourth lactation, but SCC and MPL increased with increasing parities. The canonical correlation analysis for indices showed that SCS had high positive correlation with MPL (0.8360). Therefore, a few models were developed to quantify the effects of seasonal change and parity on raw milk composition using the Wood model. The changing patterns of milk composition and related indices in different months and parities could provide scientific evidence for improving feeding management and nutritional supplementation of Chinese Holstein cows.

Real-time evaluation of milk quality as reflected by clotting parameters of individual cow's milk during the milking session, between day-to-day and during lactation

Real-time analysis of milk coagulation properties as performed by the AfiLab™ milk spectrometer introduces new opportunities for the dairy industry. The study evaluated the performance of the AfiLab™ in a milking parlor of a commercial farm to provide real-time analysis of milk-clotting parameters -Afi-CF for cheese manufacture and determine its repeatability in time for individual cows. The AfiLab™ in a parlor, equipped with two parallel milk lines, enables to divert the milk on-line into two bulk milk tanks (A and B). Three commercial dairy herds of 220 to 320 Israeli Holstein cows producing ∼11 500 l during 305 days were selected for the study. The Afi-CF repeatability during time was found significant (P < 0.001) for cows. The statistic model succeeded in explaining 83.5% of the variance between Afi-CF and cows, and no significant variance was found between the mean weekly repeated recordings. Days in milk and log somatic cell count (SCC) had no significant effect. Fat, protein and lactose significantly affected Afi-CF and the empirical van Slyke equation. Real-time simulations were performed for different cutoff levels of coagulation properties where the milk of high Afi-CF cutoff value was channeled to tank A and the lower into tank B. The simulations showed that milk coagulation properties of an individual cow are not uniform, as most cows contributed milk to both tanks. Proportions of the individual cow's milk in each tank depended on the selected Afi-CF cutoff. The assessment of the major causative factors of a cow producing low-quality milk for cheese production was evaluated for the group that produced the low 10% quality milk. The largest number of cows in those groups at the three farms was found to be cows with post-intramammary infection with Escherichia coli and subclinical infections with streptococci or coagulase-negative staphylococci (∼30%), although the SCC of these cows was not significantly different. Early time in lactation together with high milk yield >50 l/day, and late in lactation together with low milk yield<15 l/day and estrous (0 to 5 days) were also important influencing factors for low-quality milk. However, ∼50% of the tested variables did not explain any of the factors responsible for the cow producing milk in the low - 10% Afi-CF.