On the use of milk composition measures to predict the energy balance of dairy cows

Milk composition varies with energy status and was proposed for measuring energy balance on-farm, but the accuracy of prediction using monthly samples is not high. With automated sampling and inline milk analysis, a much higher measurement frequency is possible, and thus improved accuracy of energy balance determination may be expected. Energy balance was evaluated using data in which milk composition was measured at each milking. Three breeds (Danish Holstein, Danish Red, and Jerseys) of cows (623 lactations from 299 cows) in parities 1, 2, and 3+ were used. Data were smoothed using a rolling local regression. Energy balance (EBal) was calculated from changes in body reserves (body weight and body condition score). The relationship between EBal and milk measures was quantified by partial least squares regression (PLS) using group means data. For each day in lactation, the within-breed and parity mean EBal and mean milk measures were used. Further PLS was done using the individual cow data. The initial PLS models included 25 combinations of milk measures allowing a range of nonlinear effects. These combinations were as follows: days in milk (DIM); DIM raised to the powers 2, 3, and 4; milk yield; fat content; protein content; lactose content; fat yield; protein yield; lactose yield; fat:protein ratio; fat:lactose ratio; protein:lactose ratio; and milk yield:lactose ratio, together with 10 “diff()” variables. These variables are the current minus the previous value of the milk measure in question. Using group means data, a very high proportion (96%) of the variability in EBal was explained by the PLS model. A reduced model with only 6 variables explained 94% of the variation in EBal. This model had a prediction error of 3.82 MJ/d; the 25-variable model had a prediction error of 3.11 MJ/d. When using individual rather than group means data, the PLS prediction error was 17.3 MJ/d. In conclusion, the mean Ebal of different parities of Holstein, Danish Red, and Jersey cows can be predicted throughout lactation using 1 common equation based on DIM, milk yield, milk fat, and milk protein measures.     

Estimation of energy balance at the individual and herd level using blood and milk traits in high-yielding dairy cows

This study aimed to estimate individual and herd-level energy balance (EB) using blood and milk traits in 90 multiparous high-yielding Holstein cows, held on a research farm, from wk 1 to 10 postpartum (p.p.) and to investigate the precision of prediction with successively decreased data sets simulating smaller herd sizes and with pooled samples. Dry matter intake, milk yield, and BW were measured daily from parturition through wk 10 p.p. Milk composition was determined 4 times per week, and milk acetone was measured weekly. Blood samples for the determination of metabolites, hormones, electrolytes, and enzyme activities were taken weekly from wk 1 to 10 p.p. between 0730 and 0900. Body condition scores and ultrasonic measurements of backfat thickness and fat depth in the pelvic area were evaluated in wk 1, 4, and 8 p.p. Concentrations of glucose, cholesterol, urea, insulin, insulin-like growth factor-1, triiodothyronine, and thyroxine (T4) in blood plasma and of lactose and urea in milk were positively correlated with EB, whereas concentrations of nonesterified fatty acids (NEFA), creatinine, albumin, beta-hydroxybutyrate, and growth hormone and enzyme activities in blood, and concentrations of fat, protein, fat:lactose ratio, and acetone in milk were negatively correlated with EB. Leptin concentration was not correlated to EB over the first 10 wk p.p. To estimate EB linear mixed-effects, models were developed by backward selection procedures. The most informative traits for estimation of EB were the fat:lactose ratio in milk and NEFA and T4 concentrations in blood. The precision of estimation of EB in individual cows was low. Using blood in addition to milk traits did not result in higher precision of estimation of herd-level EB, and decreasing sample sizes considerably lowered the precision of EB prediction. Estimation of overall mean herd-level EB over the first 10 wk p.p. using pooled samples was precise even with small sample sizes, but does not consider the level of EB in particular weeks. In conclusion, estimation of herd-level EB at individual weeks using milk traits only has practical implication with herd sizes of > or = 100 cows if calving is highly seasonal and of or = 400 cows if calving is uniformly distributed. Using blood in addition to milk traits does not improve precision of estimation of herd-level EB, regardless of sample size.     

Day-to-day variation in milk yield and milk composition at the udder-quarter level

Automatic in-line measurement of milk composition and milk yield could be a useful tool in management of the dairy herd. Data on milk components and milk yield provide information on milk quality alterations and cow health status but are also useful in planning feeding and breeding. In automatic milking systems, udder quarters are milked individually, enabling analysis and recording at the udder-quarter level. Frequent records of components require knowledge about day-to-day variations. A component with greater day-to-day variation needs more frequent sampling when used as a diagnostic tool and for management decisions. Earlier studies have described the day-to-day variations in milk components for cow composite milk, but with the quarter milking technique and the possible sampling at the udder-quarter level, knowledge about day-to-day variations at the udder-quarter level is needed. In this study, udder-quarter and cow composite milk samples were collected from 42 consecutive milkings of 10 cows during 21 d. Milk yield was recorded and the milk was analyzed for total protein, whey protein, casein, fat, lactose, and somatic cell count. The results showed that the day-to-day variations and mean values for 4 healthy udder quarters within a cow were similar. In addition, different milk components had different levels of day-to-day variation, the least variation being found in lactose (0.9%) and the greatest in fat (7.7%). This suggests that repeated milk sampling and analysis at the udder-quarter level can be used to detect alterations in composition and cow health and would, thus, be helpful in the management of the dairy herd.     

Predicting energy × protein interaction on milk yield and milk composition in dairy cows

Feed management is one of the principal levers by which the production and composition of milk by dairy cows can be modulated in the short term. The response of milk yield and milk composition to variations in either energy or protein supplies is well known. However, in practice, dietary supplies of energy and protein vary simultaneously, and their interaction is still not well understood. The objective of this trial was to determine whether energy and protein interacted in their effects on milk production and milk composition and whether the response to changes in the diets depended on the parity and potential production of cows. From the results, a model was built to predict the response of milk yield and milk composition to simultaneous variations in energy and protein supplies relative to requirements of cows. Nine treatments, defined by their energy and protein supplies, were applied to 48 cows divided into 4 homogeneous groups (primiparous or multiparous × high or low milk potential) over three 4-wk periods. The control treatment was calculated to cover the predicted requirements of the group of cows in the middle of the trial and was applied to each cow. The other 8 treatments corresponded to fixed supplies of energy and protein, higher or lower than those of the control treatment. The results highlighted a significant energy × protein interaction not only on milk yield but also on protein content and yield. The response of milk yield to energy supply was zero with a negative protein balance and increased with protein supply equal to or higher than requirements. The response of milk yield to changes in the diet was greater for cows with high production potential than for those with low production potential, and the response of milk protein content was higher for primiparous cows than for multiparous cows. The model for the response of milk yield, protein yield, and protein content obtained in this trial made it possible to predict more accurately the variations in production and composition of milk relative to the potential of the cow because of changes in diet composition. In addition, the interaction obtained was in line with a response corresponding to the more limiting of 2 factors: energy or protein.     

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

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

The use of an upgraded GreenFeed system and milk fatty acids to estimate energy balance in early-lactation cows

Measurements of energy balance (EB) require the use of respiration chambers, which are quite expensive and laborious. The GreenFeed (GF) system (C-Lock Inc.) has been developed to offer a less expensive, user friendly alternative. In this study, we used the GF system to estimate the EB of cows in early lactation and compared it with EB predicted from energy requirements for dairy cows in the Finnish feeding standards. We also evaluated the association between milk fatty acids and the GF estimated EB. The cows were fed the same grass silage but supplemented with either cereal grain or fibrous by-product concentrate. Cows were followed from 1 to 18 wk of lactation, and measurements of energy metabolism variables were taken. Data were subjected to ANOVA using the mixed model procedure of SAS (SAS Institute Inc.). The repeatability estimates of the gaseous exchanges from the GF were moderate to high, presenting an opportunity to use it for indirect calorimetry in EB estimates. Energy metabolism variables were not different between cows fed different concentrates. However, cows fed the grain concentrate produced more methane (24.0 MJ/d or 62.9 kJ/MJ of gross energy) from increased digestibility than cows fed the by-product concentrate (21.3 MJ/d or 56.5 kJ/MJ of gross energy). Nitrogen metabolism was also not different between the diets. Milk long-chain fatty acids displayed an inverse time course with EB and de novo fatty acids. There was good concordance (0.85) between EB predicted using energy requirements derived from the Finnish feed table and EB estimated by the GF system. In conclusion, the GF can accurately estimate EB in early-lactating dairy cows. However, more data are needed to further validate the system for a wide range of dietary conditions.     

Effects of glucagon infusions on protein and amino acid composition of milk from dairy cows

Changing the composition of milk proteins and AA affects the nutritional and physical properties of dairy products. Intravenous infusions of glucagon decreases milk protein production and concentration by promoting the use of gluconeogenic blood AA for hepatic glucose synthesis. Little is known about how the diversion of AA to gluconeogenesis affects the composition of milk proteins and AA. The objective was to quantify changes in composition of milk protein and AA in response to i.v. glucagon infusions. Three separate experiments were used: 1) 8 Holstein cows were fed ad libitum and infused with glucagon at 10 mg/d for 14 d, 2) 7 Holstein cows were feed restricted and infused with glucagon at 10 mg/d for 14 d, and 3) 4 Brown Swiss cows were infused with glucagon at 5 and 10 mg/d for 2 d each. Milk and milk component yields and milk protein and amino acid composition of samples, collected with blood samples at the first and last day of the glucagon infusion period, were compared with those collected 1 d before and after the glucagon infusion period. Glucagon infusions decreased milk protein production and concentration in each experiment by at least 0.2 ± 0.05 kg/d and 4 ± 0.4 g/L, respectively. The decrease was accompanied by changes in milk protein composition, the most consistent being an increase in κ-casein (1.68 ± 0.27%). Overall, glucagon infusions resulted in higher proportions of κ-casein and α_S2-casein (1.34 ± 0.51%) and smaller proportions of α_S1-casein (−3.83 ± 1.75%) and α-lactalbumin (−0.91 ± 0.32%). Glucagon had little impact on milk AA composition except an increase in glycine (0.26 ± 0.11%). The results suggest that milk protein synthesis is regulated by many factors including AA and glucose availability.     

Effects of animal selection on milk composition and processability

One goal of animal breeding is to increase the economic output through increased production, improved milk quality, and cow health. The objective of this study was to evaluate genetic progress in relation to milk composition, processability, and yield as a correlated response to selection for the Swedish breeding objective. Dairy cows with high genetic merit, classified as elite dairy cows, of the Swedish Red and Swedish Holstein breeds were used. Milk samples were collected on the farm level in winter and summer from a research herd at Nötcenter Viken, a bovine research farm in Sweden. Comparisons were made with milk from a Swedish Red herd, a Swedish Holstein herd, and a Swedish dairy processor in the same geographical area. Protein, lipid, and carbohydrate profiles as well as minerals were analyzed, and technological properties, including rennet-induced gelation characteristics, lipid oxidation, total antioxidant capacity, and fat globule size, were determined. Higher yields were found for elite cows for components of the protein, lipid, and carbohydrate profiles as well as for minerals, implying genetic progress in relation to milk yield; however, the content of some milk components (e.g., lipid and whey protein contents) had decreased on average. Milk from the elite cows had good gelation characteristics, but was more susceptible to lipid autooxidation and had a lower total antioxidant capacity. These results demonstrate that milk composition and processing characteristics could be used to adjust breeding practices to optimize the quality and stability of milk and dairy products.     

Importance of casein micelle size and milk composition for milk gelation

The economic output of the dairy industry is to a great extent dependent on the processing of milk into other milk-based products such as cheese. The yield and quality of cheese are dependent on both the composition and technological properties of milk. The objective of this study was to evaluate the importance and effects of casein (CN) micelle size and milk composition on milk gelation characteristics in order to evaluate the possibilities for enhancing gelation properties through breeding. Milk was collected on 4 sampling occasions at the farm level in winter and summer from dairy cows with high genetic merit, classified as elite dairy cows, of the Swedish Red and Swedish Holstein breeds. Comparisons were made with milk from a Swedish Red herd, a Swedish Holstein herd, and a Swedish dairy processor. Properties of CN micelles, such as their native and rennet-induced CN micelle size and their ζ-potential, were analyzed by photon correlation spectroscopy, and rennet-induced gelation characteristics, including gel strength, gelation time, and frequency sweeps, were determined. Milk parameters of the protein, lipid, and carbohydrate profiles as well as minerals were used to obtain correlations with native CN micelle size and gelation characteristics. Milk pH and protein, CN, and lactose contents were found to affect milk gelation. Smaller native CN micelles were shown to form stronger gels when poorly coagulating milk was excluded from the correlation analysis. In addition, milk pH correlated positively, whereas Mg and K correlated negatively with native CN micellar size. The milk from the elite dairy cows was shown to have good gelation characteristics. Furthermore, genetic progress in relation to CN micelle size was found for these cows as a correlated response to selection for the Swedish breeding objective if optimizing for milk gelation characteristics. The results indicate that selection for smaller native CN micelles and lower milk pH through breeding would enhance gelation properties and may thus improve the initial step in the processing of cheese.     

Dynamic forecasting of individual cow milk yield in automatic milking systems

Accurate forecasting of dairy cow milk yield is useful to dairy farmers, both in relation to financial planning and for detection of deviating yield patterns, which can be an indicator of mastitis and other diseases. In this study we developed a dynamic linear model (DLM) designed to forecast milk yields of individual cows per milking, as they are milked in milking robots. The DLM implements a Wood's function to account for the expected total daily milk yield. It further implements a second-degree polynomial function to account for the effect of the time intervals between milkings on the proportion of the expected total daily milk yield. By combining these 2 functions in a dynamic framework, the DLM was able to continuously forecast the amount of milk to be produced in a given milking. Data from 169,774 milkings on 5 different farms in 2 different countries were used in this study. A separate farm-specific implementation of the DLM was made for each of the 5 farms. To determine which factors would influence the forecast accuracy, the standardized forecast errors of the DLM were described with a linear mixed effects model (lme). This lme included lactation stage (early, middle, or late), somatic cell count (SCC) level (nonelevated or elevated), and whether or not the proper farm-specific version of the DLM was used. The standardized forecast errors of the DLM were only affected by SCC level and interactions between SCC level and lactation stage. Therefore, we concluded that the implementation of Wood's function combined with a second-degree polynomial is useful for dynamic modeling of milk yield in milking robots, and that this model has potential to be used as part of a mastitis detection system.     

Method for short-term prediction of milk yield at the quarter level to improve udder health monitoring

Udder health problems are often associated with milk losses. These losses are different between quarters, as infected quarters are affected both by systemic and pathogen-specific local effects, whereas noninfected quarters are only subject to systemic effects. To gain insight in these losses and the milk yield dynamics during disease, it is essential to have a reliable reference for quarter-level milk yield in an unperturbed state, mimicking its potential yield. We developed a novel methodology to predict this quarter milk yield per milking session, using an historical data set of 504 lactations collected on a test farm by an automated milking system from DeLaval (Tumba, Sweden). Using a linear mixed model framework in which covariates associated with the linearized Wood model and the milking interval are included, we were able to describe quarter-level yield per milking session with a proportional error below 10%. Applying this model enables us to predict the milk yield of individual quarters 1 to 50 d ahead with a mean prediction error ranging between 8 and 20%, depending on the amount of historical data available to estimate the random effect covariates for the predicted lactation. The developed methodology was illustrated using 2 examples for which quarter-level milk losses are calculated during clinical mastitis. These showed that the quarter-level mixed model allows us to gain insight in quarter lactation dynamics and enables to calculate milk losses in different situations.     

Effect of dietary starch level and high rumen-undegradable protein on endocrine-metabolic status,milk yield,and milk composition in dairy cows during early and late lactation

Diet composition defines the amount and type of nutrients absorbed by dairy cows. Endocrine-metabolic interactions can influence these parameters, and so nutrient availability for the mammary gland can significantly vary and affect milk yield and its composition. Six dairy cows in early and then late lactation received, for 28 d in a changeover design, 2 diets designed to provide, within the same stage of lactation, similar amounts of rumen fermentable material but either high starch plus sugar (HS) content or low starch plus sugar content (LS). All diets had similar dietary crude protein and calculated supply of essential amino acids. Dry matter intake within each stage of lactation was similar between groups. Milk yield was similar between groups in early lactation, whereas a higher milk yield was observed in late lactation when feeding HS. At the metabolic level, the main difference observed between the diets in both stages of lactation was lower blood glucose in cows fed LS. The lower glucose availability during consumption of LS caused substantial modifications in the circulating and postprandial pattern of metabolic hormones. Feeding LS versus HS resulted in an increase in the ratio of bovine somatotropin to insulin. This increased mobilization of lipid reserves resulted in higher blood concentrations of nonesterified fatty acids and β-hydroxybutyrate, which contributed to the higher milk fat content in both stages of lactation in the LS group. This greater recourse to body fat stores was confirmed by the greater loss of body weight during early lactation and the slower recovery of body weight in late lactation in cows fed LS. The lower insulin to glucagon ratio observed in cows fed LS in early and late lactation likely caused an increase in hepatic uptake and catabolism of amino acids, as confirmed by the higher blood urea concentrations. Despite the higher catabolism of amino acids in LS in early lactation, similar milk protein output was observed for both diets, suggesting similar availability of amino acids for peripheral tissue and mammary gland. The latter could be the result of sparing of amino acids at the gut level due to starch that escaped from the rumen, and to the balanced amino acid profile of digestible protein. This last aspect appears worthy of further research, with the aim to enhance the efficiency of protein metabolism of dairy cows, reducing environmental nitrogen pollution without affecting milk yield potential.     

Effects of milk protein variants on the protein composition of bovine milk

The effects of β-lactoglobulin (β-LG), β-casein (β-CN), and κ-CN variants and β-κ-CN haplotypes on the relative concentrations of the major milk proteins α-lactalbumin (α-LA), β-LG, α_S1-CN, α_S2-CN, β-CN, and κ-CN and milk production traits were estimated in the milk of 1,912 Dutch Holstein-Friesian cows. We show that in the Dutch Holstein-Friesian population, the allele frequencies have changed in the past 16 years. In addition, genetic variants and casein haplotypes have a major impact on the protein composition of milk and explain a considerable part of the genetic variation in milk protein composition. The β-LG genotype was associated with the relative concentrations of β-LG (A » B) and of α-LA, α_S1-CN, α_S2-CN, β-CN, and κ-CN (B > A) but not with any milk production trait. The β-CN genotype was associated with the relative concentrations of β-CN and α_S2-CN (A² > A¹) and of α_S1-CN and κ-CN (A¹ > A²) and with protein yield (A² > A¹). The κ-CN genotype was associated with the relative concentrations of κ-CN (B > E > A), α_S2-CN (B > A), α-LA, and α_S1-CN (A > B) and with protein percentage (B > A). Comparing the effects of casein haplotypes with the effects of single casein variants can provide better insight into what really underlies the effect of a variant on protein composition. We conclude that selection for both the β-LG genotype B and the β-κ-CN haplotype A²B will result in cows that produce milk that is more suitable for cheese production.     

Relationships between energy balance during early lactation and cow performance,blood metabolites,and fertility: A meta-analysis of individual cow data

This study was designed to contribute to the understanding of the relationships between energy balance (EB) in early lactation [4 to 21 d in milk (DIM)] and fertility traits [interval to start of luteal activity (SLA), interval to first observed heat (FOH), and conception to first artificial insemination (AI)], and their associated relationships with cow performance and blood metabolites between 4 to 150 DIM. Individual cow data (488 primiparous and 1,020 multiparous lactations) from 27 experiments was analyzed. Data on cow performance, EB (on a metabolizable energy basis), and fertility traits were available for all cows, whereas milk progesterone data (to determine SLA) and periodic blood metabolite data were available for 1,042 and 1,055 lactations, respectively. Data from primiparous and multiparous cows were analyzed separately, with the data sets for the 2 parity groups divided into quartiles (Q1–Q4) according to the average EB during 4 to 21 DIM (EB range for Q1 to Q4: primiparous, ?120 to ?49, ?49 to ?24, ?24 to ?3, and ?3 to 92 MJ/d, respectively: multiparous, ?191 to ?79, ?79 to ?48, ?48 to ?22, and ?22 to 93 MJ/d, respectively). Differences between EB quartiles for production and fertility traits were compared. In early lactation (4 to 21 DIM), moving from Q1 to Q4 mean DMI and metabolizable energy intake increased whereas mean ECM decreased. During the same period, moving from Q1 to Q4 milk fat content, milk fat-to-protein ratio, and plasma nonesterified fatty acid and β-hydroxybutyrate concentrations decreased, whereas milk protein content and plasma glucose concentrations increased in both primiparous and multiparous cows. When examined over the entire experimental period (4 to 150 DIM), many of the trends in intakes and milk production remained, although the magnitude of the difference between quartiles was much reduced, whereas milk fat content did not differ between quartiles in primiparous cows. The percentage of cows with FOH before 42 DIM increased from Q1 to Q4 (from 46 to 72% in primiparous cows, and from 41 to 58% in multiparous cows). Interval from calving to SLA and to FOH decreased with increasing EB during 4 to 21 DIM, with these occurring 9.8 and 10.2 d earlier, respectively, in Q4 compared with Q1 (primiparous cows), and 7.4 and 5.9 d earlier, respectively, in Q4 compared with Q1 (multiparous cows). For each 10 MJ/d decrease in mean EB during 4 to 21 DIM, FOH was delayed by 1.2 and 0.8 d in primiparous and multiparous cows, respectively. However, neither days to first AI nor the percentage of cows that conceived to first AI were affected by daily EB during 4 to 21 DIM in either primiparous or multiparous cows, and this is likely to reflect a return to a less metabolically stressed status at the time of AI. These results demonstrate that interval from calving to SLA and to FOH were reduced with increasing EB in early lactation, whereas early lactation EB had no effect on conception to the first service.     

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

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

Long-term effects of feeding monensin on milk fatty acid composition in lactating dairy cows

The objective of this study was to determine the long-term effects of feeding monensin on milk fatty acid (FA) profile in lactating dairy cows. Twenty-four lactating Holstein dairy cows (1.46 ± 0.17 parity; 620 ± 5.9 kg of live weight; 92.5 ± 2.62 d in milk) housed in a tie-stall facility were used in the study. The study was conducted as paired comparisons in a completely randomized block design with repeated measurements in a color-coded, double blind experiment. The cows were paired by parity and days in milk and allocated to 1 of 2 treatments: 1) the regular milking cow total mixed ration (TMR) with a forage-to-concentrate ratio of 60:40 (control TMR; placebo premix) vs. a medicated TMR [monensin TMR; regular TMR + 24 mg of Rumensin Premix per kg of dry matter (DM)] fed ad libitum. The animals were fed and milked twice daily (feeding at 0830 and 1300 h; milking at 0500 and 1500 h). Milk samples were collected before the introduction of treatments and monthly thereafter for 6 mo and analyzed for FA composition. Monensin reduced the percentage of the short-and medium-chain saturated FA 7:0, 9:0, 15:0, and 16:0 in milk fat by 26, 35, 19, and 6%, respectively, compared with the control group. Monensin increased the percentage of the long-chain saturated FA in milk fat by 9%, total monounsaturated FA by 5%, total n-6 polyunsaturated FA (PUFA) by 19%, total n-3 PUFA by 16%, total cis-18:1 by 7%, and total conjugated linoleic acid (CLA) by 43% compared with the control group. Monensin increased the percentage of docosahexaenoic acid (22:6n-3), docosapentaenoic acid (22:5n-3), and cis-9, trans-11 CLA in milk fat by 19, 13, and 43%, respectively, compared with the control. These results suggest that monensin was at least partly effective in inhibiting the biohydrogenation of unsaturated FA in the rumen and consequently increased the percentage of n-6 and n-3 PUFA and CLA in milk, thus enhancing the nutritional properties of milk with regard to human health.     

Use of dietary feather meal to induce histidine deficiency or imbalance in dairy cows and effects on milk composition

Removing His from a postruminal AA infusion decreases milk protein and increases milk fat content. Feather meal is an inexpensive protein source, high in rumen undegradable protein but low in His. The objective of our study was to investigate dietary feather meal as a method for creating a His deficiency or imbalance to alter milk composition. Four dietary treatments were fed for 4 wk each to 8 multiparous mid-lactation Holstein cows in a replicated 4 × 4 Latin square design. A standard-protein control diet (SP-C) was formulated to provide 3,100 g/d of metabolizable protein (MP). Feather meal was added to the control diet either to replace the MP isonitrogenously (SP-FM) or to increase the MP supply to 3,484 g/d (HP-FM). As an isonitrogenous control for HP-FM, a high-protein diet (HP-C) was formulated with His-adequate protein sources to provide the same MP content as HP-FM. Dry matter intake tended to decrease when feather meal was fed. Predicted flows of digestible His, Met, and Lys, and plasma concentrations of these AA were reduced on both feather meal diets. Predicted flows of total digestible essential AA were not different between HP-FM and SP-C. We concluded that the DMI depression on HP-FM prevented an imbalance of excess AA over His, and created a deficiency of His, Met, and Lys compared with SP-C. Milk production decreased on the 2 feather meal treatments, partly explained by a tendency for DMI to decrease. Milk yield was lowest on SP-FM at 30.3 kg/d and highest on HP-C at 37.9 kg/d. Milk fat yield was not affected by diet but protein and lactose yields were both lower with feather meal. Protein yields were 860 and 998 g/d, whereas lactose yields were 1,384 and 1,561 g/d for SP-FM and HP-FM, respectively. This resulted in a higher fat content and lower protein percentage on FM diets. The ratio of solids-not-fat:fat in milk was lowest on SP-FM at 2.11 compared with 2.56 on SP-C. Adding feather meal to the diet by replacing MP isonitrogenously was more effective at lowering the solids-not-fat:fat ratio than increasing the MP content with an imbalanced protein source.     

Alternatives to linear analysis of energy balance data from lactating dairy cows

The current energy requirements system used in the United Kingdom for lactating dairy cows utilizes key parameters such as metabolizable energy intake (MEI) at maintenance (MEm), the efficiency of utilization of MEI for 1) maintenance, 2) milk production (kl), 3) growth (kg), and the efficiency of utilization of body stores for milk production (kt). Traditionally, these have been determined using linear regression methods to analyze energy balance data from calorimetry experiments. Many studies have highlighted a number of concerns over current energy feeding systems particularly in relation to these key parameters, and the linear models used for analyzing. Therefore, a database containing 652 dairy cow observations was assembled from calorimetry studies in the United Kingdom. Five functions for analyzing energy balance data were considered: straight line, two diminishing returns functions, (the Mitscherlich and the rectangular hyperbola), and two sigmoidal functions (the logistic and the Gompertz). Meta-analysis of the data was conducted to estimate kg and kt. Values of 0.83 to 0.86 and 0.66 to 0.69 were obtained for kg and kt using all the functions (with standard errors of 0.028 and 0.027), respectively, which were considerably different from previous reports of 0.60 to 0.75 for kg and 0.82 to 0.84 for kt. Using the estimated values of kg and kt, the data were corrected to allow for body tissue changes. Based on the definition of kl as the derivative of the ratio of milk energy derived from MEI to MEI directed towards milk production, MEm and kl were determined. Meta-analysis of the pooled data showed that the average kl ranged from 0.50 to 0.58 and MEm ranged between 0.34 and 0.64 MJ/kg of BW0.75 per day. Although the constrained Mitscherlich fitted the data as good as the straight line, more observations at high energy intakes (above 2.4 MJ/kg of BW0.75 per day) are required to determine conclusively whether milk energy is related to MEI linearly or not.     

Relationships among milk production, energy balance, plasma analytes, and reproduction in Holstein-Friesian cows

Associations were examined between components and indicators of early lactation energy balance (EB) and measures of fertility in Holstein cows. Milk production, dry matter intake (DMI), body condition score (BCS), and endocrine and metabolite data from 96 cows were analyzed using multivariate logistic regression and survival analysis. Fertility variables investigated were interval to commencement of luteal activity (C-LA), calving to conception interval (CCI), and conception rate to first service (CON1). Mean daily EB, milk protein content, and DMI during the first 28 d in milk were associated positively with CON1. Cows having poorer BCS (≤2.25) at first service had a lower CON1. Positive associations were identified among EB, milk protein content, DMI, and the likelihood of a shorter interval to C-LA. Cows having greater DMI and a more positive EB had an increased likelihood of a shorter CCI, whereas a lower nadir BCS was associated with an increased likelihood of a longer CCI. Milk yield was not associated with any of the fertility variables investigated. A greater plasma concentration of insulin-like growth factor I (IGF-I) during the first 2 wk of lactation was associated with a greater CON1 and an increased likelihood of a shorter interval to C-LA. In conclusion, we identified DMI as the principal component of EB influencing subsequent fertility. Furthermore, results indicate that milk protein content and plasma IGF-I concentration in early lactation may be useful indicators of reproductive efficiency.     

Short communication: Circulating and milk adiponectin change differently during energy deficiency at different stages of lactation in dairy cows

Adiponectin, one of the most abundant adipokines in circulation, is known for its role in regulation of body metabolism. The aim of this study was to evaluate the effects of a negative energy balance (NEB) at 2 stages of lactation (lactational NEB at the onset of lactation and an induced NEB by feed restriction near 100 d of lactation) on circulating adiponectin concentrations. We also investigated the effect of feed restriction on adiponectin concentrations in milk and the relationships of blood and milk adiponectin with selected plasma or milk variables and with measures of body condition. Plasma adiponectin was measured in 50 multiparous Holstein dairy cows throughout 3 experimental periods [i.e., period 1 = 3 wk antepartum up to 12 wk postpartum, period 2 = 3 wk of feed restriction starting at around 100 d in milk with a control (n = 25) and feed-restricted group (50% of energy requirements; n = 25), and period 3 = subsequent realimentation period for 8 wk]. Milk adiponectin was investigated among 21 multiparous cows at wk 2 and wk 12 of period 1 and wk 2 of period 2. Adiponectin concentrations in plasma and skim milk were measured using an in-house ELISA specific for bovine adiponectin. Major changes in circulating adiponectin concentrations were observed during the periparturient period, whereas energy deficiency during established lactation at around 100 d in milk and subsequent refeeding did not affect plasma adiponectin. Together with lower adiponectin concentrations in milk (µg/mL), the reduction in milk yield led to decreased adiponectin secretion via milk (mg/d) at the second week of feed restriction. Irrespective of time and treatment, milk adiponectin represented about 0.002% of total milk protein. Mean adiponectin concentrations in milk (0.61 ± 0.03 µg/mL) were about 92% lower than the mean plasma adiponectin concentrations (32.1 ± 1.0 µg/mL). The proportion of the steady-state plasma adiponectin pool secreted daily via milk was 2.7%. In view of the similar extent of NEB in both periods of energy deficiency, decreasing adiponectin concentrations seems important for accomplishing the adaptation to the rapidly increasing metabolic rates in early lactation, whereas the lipolytic reaction toward feed restriction-induced NEB during established lactation seems to occur largely independent of changes in circulating adiponectin.