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.     

Performance and metabolic profile of dairy cows during a lactational and deliberately induced negative energy balance with subsequent realimentation

Homeorhetic and homeostatic controls in dairy cows are essential for adapting to alterations in physiological and environmental conditions. To study the different mechanisms during adaptation processes, effects of a deliberately induced negative energy balance (NEB) by feed restriction near 100 d in milk (DIM) on performance and metabolic measures were compared with lactation energy deficiency after parturition. Fifty multiparous cows were studied in 3 periods (1 = early lactation up to 12 wk postpartum; 2 = feed restriction for 3 wk beginning at 98 ± 7 DIM with a feed-restricted and control group; and 3 = a subsequent realimentation period for the feed-restricted group for 8 wk). In period 1, despite NEB in early lactation [−42 MJ of net energy for lactation (NE_L)/d, wk 1 to 3] up to wk 9, milk yield increased from 27.5 ± 0.7 kg to a maximum of 39.5 ± 0.8 kg (wk 6). For period 2, the NEB was induced by individual limitation of feed quantity and reduction of dietary energy density. Feed-restricted cows experienced a greater NEB (−63 MJ of NE_L/d) than did cows in early lactation. Feed-restricted cows in period 2 showed only a small decline in milk yield of −3.1 ± 1.1 kg and milk protein content of −0.2 ± 0.1% compared with control cows (30.5 ± 1.1 kg and 3.8 ± 0.1%, respectively). In feed-restricted cows (period 2), plasma glucose was lower (−0.2 ± 0.0 mmol/L) and nonesterified fatty acids higher (+0.1 ± 0.1 mmol/L) compared with control cows. Compared with the NEB in period 1, the decreases in body weight due to the deliberately induced NEB (period 2) were greater (56 ± 4 vs. 23 ± 3 kg), but decreases in body condition score (0.16 ± 0.03 vs. 0.34 ± 0.04) and muscle diameter (2.0 ± 0.4 vs. 3.5 ± 0.4 mm) were lesser. The changes in metabolic measures in period 2 were marginal compared with the adjustments directly after parturition in period 1. Despite the greater induced energy deficiency at 100 DIM than the early lactation NEB, the metabolic load experienced by the dairy cows was not as high as that observed in early lactation. The different effects of energy deficiency at the 2 stages in lactation show that metabolic problems in early lactating dairy cows are not due only to the NEB, but mainly to the specific metabolic regulation during this period.     

Dietary energy source in dairy cows in early lactation: metabolites and metabolic hormones

Negative energy balance-related metabolic disorders suggest that the balance between available lipogenic and glucogenic nutrients is important. The objectives of this study were to compare the effects of a glucogenic or a lipogenic diet on liver triacylglycerides (TAG), metabolites, and metabolic hormones in dairy cows in early lactation and to relate metabolite concentrations to the determined energy retention in body mass (ER). Sixteen dairy cows were fed either a lipogenic or glucogenic diet from wk 3 prepartum to wk 9 postpartum (pp) and were housed in climate respiration chambers from wk 2 to 9 pp. Diets were isocaloric (net energy basis). Postpartum, cows fed a lipogenic diet tended to have higher nonesterified fatty acid concentration (NEFA; 0.46 ± 0.04 vs. 0.37 ± 0.04 mmol/L) and lower insulin concentration (4.0 ± 0.5 vs. 5.5 ± 0.6 μIU/mL). No difference was found in plasma glucose, β-hydroxybutyrate, insulin-like growth factor-I, and thyroid hormones. Liver TAG was equal between both diets in wk −2 and 2 pp. In wk 4 pp cows fed the glucogenic diet had numerically lower TAG levels, although there was no significant dietary effect. Negative relationships were detected between ER and milk fat and between ER and NEFA. A positive relationship was detected between ER and insulin concentration. Overall, results suggest that insulin plays a regulating role in altering energy partitioning between milk and body tissue. Feeding lactating dairy cows a glucogenic diet decreased mobilization of body fat compared with a lipogenic diet. The relative abundance of lipogenic nutrients, when feeding a more lipogenic diet, is related to more secretion of lipogenic nutrients in milk, lower plasma insulin, and higher plasma NEFA concentration.     

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.     

Predicting energy balance for dairy cows using high-density single nucleotide polymorphism information

The objective of this study was to investigate the genetic basis of energy balance (EB) and the potential use of genomic selection to enable EB to be incorporated into selection programs. Energy balance provides an essential link between production and nonproduction traits because both depend on a common source of energy. A small number (527) of Dutch Holstein-Friesian heifers with phenotypes for EB were genotyped. Direct genomic values were predicted for these heifers using a model that included the genotypic information. A polygenic model was also applied to predict estimated breeding values using only pedigree information. A 10-fold cross-validation approach was employed to assess the accuracies of the 2 sets of predicted breeding values by correlating them with phenotypes. Because of the small number of phenotypes, accuracies were relatively low (0.29 for the direct genomic values and 0.21 for the estimated breeding values), where the maximum possible accuracy was the square root of heritability (0.57). Despite this, the genomic model produced breeding values with reliability double that of the breeding values produced by the polygenic model. To increase the accuracy of the genomic breeding values and make it possible to select for EB, measurement and recording of EB would need to improve. The study suggests that it may be possible to select for minimally recorded traits; for instance, those measured on experimental farms, using genomic selection. Overall, the study demonstrated that genomic selection could be used to select for EB, confirming its genetic background.     

Identifying poor metabolic adaptation during early lactation in dairy cows using cluster analysis

Currently, cows with poor metabolic adaptation during early lactation, or poor metabolic adaptation syndrome (PMAS), are often identified based on detection of hyperketonemia. Unfortunately, elevated blood ketones do not manifest consistently with indications of PMAS. Expected indicators of PMAS include elevated liver enzymes and bilirubin, decreased rumen fill, reduced rumen contractions, and a decrease in milk production. Cows with PMAS typically are higher producing, older cows that are earlier in lactation and have greater body condition score at the start of lactation. It was our aim to evaluate commonly used measures of metabolic health (input variables) that were available [i.e., blood β-hydroxybutyrate acid, milk fat:protein ratio, blood nonesterified fatty acids (NEFA)] to characterize PMAS. Bavarian farms (n = 26) with robotic milking systems were enrolled for weekly visits for an average of 6.7 wk. Physical examinations of the cows (5–50 d in milk) were performed by veterinarians during each visit, and blood and milk samples were collected. Resulting data included 790 observations from 312 cows (309 Simmental, 1 Red Holstein, 2 Holstein). Principal component analysis was conducted on the 3 input variables, followed by K-means cluster analysis of the first 2 orthogonal components. The 5 resulting clusters were then ascribed to low, intermediate, or high PMAS classes based on their degree of agreement with expected PMAS indicators and characteristics in comparison with other clusters. Results revealed that PMAS classes were most significantly associated with blood NEFA levels. Next, we evaluated NEFA values that classify observations into appropriate PMAS classes in this data set, which we called separation values. Our resulting NEFA separation values [<0.39 mmol/L (95% confidence limits = 0.360–0.410) to identify low PMAS observations and ≥0.7 mmol/L (95% confidence limits = 0.650–0.775) to identify high PMAS observations] were similar to values determined for Holsteins in conventional milking settings diagnosed with hyperketonemia and clinical symptoms such as anorexia and a reduction in milk yield, as reported in the literature. Future studies evaluating additional clinical and laboratory data, breeds, and milking systems are needed to validate these finding. The aim of future studies would be to build a PMAS prediction model to alert producers of cows needing attention and help evaluate on-farm metabolic health management at the herd level.     

Natural antibodies related to energy balance in early lactation dairy cows

The objectives of this study were to determine the presence of natural antibodies (NAb) in plasma and milk of individual dairy cows and to study the relation between NAb concentrations and energy balance (EB) and dietary energy source. Cows (n = 76) were fed a mainly glucogenic, lipogenic, or a mixture of both diets (50:50 dry matter basis) from wk 3 before the expected calving date until wk 9 postpartum. Diets were isocaloric (net energy basis) and equal in intestinal digestible protein. Blood and milk were sampled weekly. Liver biopsies were taken in wk −2, 2, 4, and 6 relative to calving. Data are expressed as LSM ± SEM. The NAb titers are expressed as the ²log values of the highest dilution giving a positive reaction. The NAb concentration in plasma binding either keyhole limpet hemocyanin (KLH) or Escherichia coli lipopolysaccharide (LPS) increased with parity. The NAb concentration binding KLH was greater for cows fed the glucogenic diet (9.63 ± 0.08) compared with the lipogenic diet (9.26 ± 0.08). In milk, cows fed the glucogenic diet had smaller NAb concentrations binding KLH (3.98 ± 0.18) and LPS (2.88 ± 0.17) compared with cows fed the mixed diet (KLH: 4.93 ± 0.18; LPS: 3.70 ± 0.17). The NAb concentration in plasma had a positive relation with energy balance variables: EB, dry matter intake, milk yield, and plasma cholesterol, whereas NAb concentration in milk had a negative relation with energy balance variables: EB, dry matter intake, and plasma cholesterol. Additionally, NAb concentrations in milk had a positive relation with plasma nonesterified fatty acid concentration and milk fat and protein percentage. There was a tendency for a positive relation of NAb concentration binding LPS in plasma and somatic cell count in milk. No significant relations were detected between NAb concentrations in milk or plasma and plasma β-hydroxybutyrate concentration and liver triacyl glyceride content. In conclusion, NAb are present in both milk and plasma of dairy cows peripartum and NAb concentrations increase with parity. Furthermore, our data indicate that a negative energy balance in dairy cows in early lactation can be associated with compromised innate immune function as indicated by decreased NAb concentration in plasma.     

Modeling daily energy balance of dairy cows in the first three lactations

Daily energy balance was calculated for 111 Holstein cows in their first 3 lactations, based on combinations of smoothed preadjusted phenotypic records for milk yield, feed intake, live weight, and body condition score. Two energy balance traits were defined: one based on milk yield and feed intake (EB1) and the other on live weight and body condition score change (EB2). Bessel functions (BF), Legendre polynomials (LP), sinusoidal functions (SF), and cubic splines (CS) were used to model energy balance within and across lactations. Models with BF or LP fitted fixed regressions of order 1 to 6 and random regressions of order 1 to 10. Cubic splines were fitted at 5 to 30 equally spaced knot points. In within-lactation analyses with BF and LP models, likelihood ratio tests revealed that the fit improved significantly up to random regression order of 5 for EB1 and 4 for EB2, independently of the fixed regression order. For EB1 analyses with LP, improvement was marginal albeit significant even for higher random regression order. For CS models, optimal number of knot points was 13 and 12 for EB1 and EB2, respectively. Residual variance and comparisons between actual and predicted energy balance showed that LP of minimum order 8 and 5 modeled, respectively, EB1 and EB2 better than the other 3 functions. In across-lactation analyses with BF and LP models, likelihood ratio tests were significant as the random regression order increased, for any order of the fixed regression. For CS models, optimal number of knot points was 14 and 16 for EB1 and EB2, respectively. Residual variance and comparisons between actual and predicted energy balance showed that models fitting CS and high (>8) random order BF or LP provided the best fit to both traits. However, in an across-lactation analysis, even higher order of LP or BF will be required to provide as good a fit as within-lactation analyses.     

Effect of dry period length and dietary energy source on energy balance,milk yield,and milk composition of dairy cows

The objective of this study was to evaluate the effects of dry period length and dietary energy source in early lactation on milk production, feed intake, and energy balance (EB) of dairy cows. Holstein-Friesian dairy cows (60 primiparous and 108 multiparous) were randomly assigned to dry period lengths (0, 30, or 60 d) and early lactation ration (glucogenic or lipogenic), resulting in a 3 × 2 factorial design. Rations were isocaloric and equal in intestinal digestible protein. The experimental period lasted from 8 wk prepartum to 14 wk postpartum and cows were monitored for milk yield, milk composition, dry matter intake (DMI), energy balance, and milk fat composition. Prepartum average milk yield for 60 d precalving was 13.8 and 7.7 ± 0.5 kg/d for cows with a 0- and 30-d dry period, respectively. Prepartum DMI and energy intake were greater for cows without a dry period and 30-d dry period, compared with cows with a 60-d dry period. Prepartum EB was greater for cows with a 60-d dry period. Postpartum average milk yield until wk 14 was lower for cows without a dry period and a 30-d dry period, compared with cows with a 60-d dry period (32.7, 38.7, and 43.3 ± 0.7 kg/d for 0-, 30-, and 60-d dry period, respectively). Postpartum DMI did not differ among treatments. Postpartum EB was greater for cows without a dry period and a 30-d dry period, compared with cows with a 60-d dry period. Young cows (parity 2) showed a stronger effect of omission of the dry period, compared with a 60-d dry period, on additional milk precalving (young cows: 15.1 kg/d; older cows: 12.0 kg/d), reduction in milk yield postcalving (young cows: 28.6 vs. 34.8 kg/d; older cows: 41.8 vs. 44.1 kg/d), and improvement of the EB postcalving (young cows: 120 vs. −93 kJ/kg^0.75·d; older cows: −2 vs. −150 kJ/kg^0.75·d. Ration did not affect milk yield and DMI, but a glucogenic ration tended to reduce milk fat content and increased EB, compared with a more lipogenic ration. Reduced dry period length (0 and 30 d) increased the proportion of short- and medium-chain fatty acids in milk fat and omitting the dry period decreased the proportion of long-chain fatty acids in milk fat. In conclusion, shortening and omitting the dry period shifts milk yield from the postpartum to the prepartum period; this results in an improvement of the EB in early lactation. An increased energy status after a short dry period can be further improved by feeding a more glucogenic ration in early lactation.     

Associations between the detailed milk mineral profile,milk composition,and metabolic status in Holstein cows

The causes of variation in the milk mineral profile of dairy cattle during the first phase of lactation were studied under the hypothesis that the milk mineral profile partially reflects the animals' metabolic status. Correlations between the minerals and the main milk constituents (i.e., protein, fat, and lactose percentages), and their associations with the cows' metabolic status indicators were explored. The metabolic status indicators (MET) that we used were blood energy-protein metabolites [nonesterified fatty acids, β-hydroxybutyrate (BHB), glucose, cholesterol, creatinine, and urea], and liver ultrasound measurements (predicted triacylglycerol liver content, portal vein area, portal vein diameter and liver depth). Milk and blood samples, and ultrasound measurements were taken from 295 Holstein cows belonging to 2 herds and in the first 120 d in milk (DIM). Milk mineral contents were determined by ICP-OES; these were considered the response variable and analyzed through a mixed model which included DIM, parity, milk yield, and MET as fixed effects, and the herd/date as a random effect. The MET traits were divided in tertiles. The results showed that milk protein was positively associated with body condition score (BCS) and glucose, and negatively associated with BHB blood content; milk fat was positively associated with BHB content; milk lactose was positively associated with BCS; and Ca, P, K and S were the minerals with the greatest number of associations with the cows' energy indicators, particularly BCS, predicted triacylglycerol liver content, glucose, BHB and urea. We conclude that the protein, fat, lactose, and mineral contents of milk partially reflect the metabolic adaptation of cows during lactation and within 120 DIM. Variations in the milk mineral profile were consistent with changes in the major milk constituents and the metabolic status of cows.     

Test accuracy of metabolic indicators in predicting decreased fertility in dairy cows

Negative energy balance is a known risk factor for decreased fertility in dairy cows. This study evaluated the accuracy of plasma concentrations of nonesterified fatty acids (NEFA), β-hydroxybutyrate (BHBA), and insulin-like growth factor 1 (IGF-1)—factors related to negative energy balance—in predicting decreased fertility. One plasma sample per cow was collected from 480 cows in 12 herds during the period from d 4 to 21 in milk and analyzed for NEFA, BHBA, and IGF-1. For each cow, data on breed, parity, calving date, gynecological examinations, and insemination dates were obtained. Milk samples from 241 cows in 7 of the participating herds were analyzed for progesterone concentration to define the first day of luteal activity. The diagnostic sensitivity (Se) and specificity (Sp) at different cut-off concentrations of NEFA, BHBA, or IGF-1 were calculated and related to individual cow fertility status, measured as anestrus (ANEST), delayed first artificial insemination (DFAI), or delayed conception. Positive and negative predictive values (PV+; PV−) were calculated considering different levels of (within-herd) prevalence. Strata (i.e., subgroup)-specific Se and Sp and associations between test results and fertility parameters were investigated using logistic regression. The NEFA and BHBA tests for ANEST and DFAI had the highest combined Se and Sp and were thus evaluated further. Cut-off values with Sp around 80% were used in this step to provide a reasonable number of test-positive cows, representing a practical situation. This corresponded to a cut-off value for the NEFA test of 400 µEq/L (Se 0.27–0.45) and for the BHBA test of 1.8 mM (Se 0.15–0.30) across all cows included in the study. The estimated Sp was generally higher than the original 80%, but the corresponding Se was further decreased when the test was used in heifers compared with older cows. The true prevalence of ANEST in the study population was 27%, which gave a PV+ of 0.36 to 0.45 and a PV− of 0.76 to 0.79. With 35% true prevalence of DFAI, PV+ was 0.29 to 0.38 and PV− was 0.64 to 0.66. Thus, overall test performance was low when metabolic indicators measured as single values in early lactation were used to predict fertility in dairy cows, but accuracy was influenced by cow-level factors such as parity. The prevalence of the target condition (in this case, decreased fertility) also influences test usefulness and should be considered when planning test systems and interpreting test results.     

Milk metabolites and fatty acids as noninvasive biomarkers of metabolic status and energy balance in early-lactation cows

The objective was to study the effects of week of lactation (WOL) and experimental nutrient restriction on concentrations of selected milk metabolites and fatty acids (FA), and assess their potential as biomarkers of energy status in early-lactation cows. To study WOL effects, 17 multiparous Holstein cows were phenotyped from calving until 7 WOL while allowed ad libitum intake of a lactation diet. Further, to study the effects of nutrient restriction, 8 of these cows received a diet containing 48% straw (high-straw) for 4 d starting at 24 ± 3 days in milk (mean ± SD), and 8 cows maintained on the lactation diet were sampled to serve as controls. Blood and milk samples were collected weekly for the WOL data set, and daily from d ?1 to 3 of nutrient restriction (or control) for the nutritional challenge data set. Milk β-hydroxybutyrate (BHB), isocitrate, glucose, glucose-6-phosphate (glucose-6P), galactose, glutamate, creatinine, uric acid, and N-acetyl-β-d-glucosaminidase activity (NAGase) were analyzed in p.m. and a.m. samples, and milk FA were analyzed in pooled p.m. and a.m. samples. Average energy balance (EB) per day ranged from ?27 MJ/d to neutral when cows received the lactation total mixed ration, and from ?109 to ?87 ± 7 MJ/d for high-straw (least squares means ± standard error of the mean). Plasma nonesterified FA concentration was 1.67 ± 0.13 mM and BHB was 2.96 ± 0.39 mM on the d 3 of high-straw (least squares means ± standard error of the mean). Milk concentrations of BHB, glucose, glucose-6P, glutamate, and uric acid differed significantly between p.m. and a.m. milkings. Milk isocitrate, glucose-6P, creatinine, and NAGase decreased, whereas milk glucose and galactose increased with WOL. Changes in milk BHB, isocitrate, glucose, glucose-6P, and creatinine were concordant during early lactation and in response to nutrient restriction. Milk galactose and NAGase were modulated by WOL only, whereas glutamate and uric acid concentrations responded to nutrient restriction only. The high-straw increased milk concentrations of FA potentially mobilized from adipose tissue (e.g., C18:0 and cis-9 C18:1 and sum of odd- and branched-chain FA (OBCFA) with carbon chain greater than 16; ∑ OBCFA >C16), and decreased concentrations of FA synthesized de novo by the mammary gland (e.g., sum of FA with 6 to 15 carbons; ∑ C6:0 to C15:0). Similar observations were made during early lactation. Plasma nonesterified FA concentrations had the best single linear regression with EB (R² = 0.62). Milk isocitrate, Σ C6:0 to C15:0. and cis-9 C18:1 had the best single linear regressions with EB (R² ≥ 0.44). Milk BHB, isocitrate, galactose, glutamate, and creatinine explained up to 64% of the EB variation observed in the current study using multiple linear regression. Milk concentrations of ∑ C6:0 to C15:0, C18:0, cis-9 C18:1, and ∑ OBCFA >C16 presented some of the best correlations and regressions with other indicators of metabolic status, lipomobilization, and EB, and their responses were concordant during early lactation and during experimental nutrient restriction. Metabolites and FA secreted in milk may serve as noninvasive indicators of metabolic status and EB of early-lactation cows.     

Pre-conception energy balance and secondary sex ratio--partial support for the Trivers-Willard hypothesis in dairy cows

According to the Trivers-Willard hypothesis, maternal condition at or around conception affects the secondary sex ratio in mammals. However, there are little or no data available on indicators of maternal condition in dairy cows on the sex of the resultant offspring. A total of 76,607 body condition score (BCS; scale of 1 to 5) records and 76,611 body weight (BW) records from 3,209 lactations across 1,172 cows were extracted from a research database collated from one research herd between 1986 and 2004, inclusive. Exclusion of multiple births and cows with no information before calving (e.g., nulliparous animals) resulted in 2,029 records with BCS and BW observations from the previous calving, and 2,002 and 1,872 lactations with BCS and BW observations at conception and midgestation, respectively. Change in BCS and BW between calving and conception and between conception and midgestation was calculated per lactation. Generalized estimating equations were used to model the logit of the probability of a male calf, in which cow was included as a repeated effect with a first-order autoregressive correlation structure assumed among records within cow. Of the BCS variables investigated, there was a linear relationship between the logit of the probability of a male calf and BCS change between calving and conception, the rate of BCS change over this period (BCS divided by days in milk), and BCS at the calving event immediately before conception. The birth of a bull calf was 1.85 times more likely in cows that lost no BCS from calving to conception compared with cows that lost one BCS unit from calving to conception. This increase in odds was equivalent to a 14% unit increase in the probability of a male calf (from 54 to 68%). The amount of BW lost between calving and conception and the rate of loss affected the sex of the resultant offspring. Less BW loss or greater BW gain between calving and conception was associated with greater likelihood of a male calf. Results suggested a positive effect of pre-conception BCS and BW change on secondary sex ratio, agreeing with the Trivers-Willard hypothesis that females in good physiological condition are more likely to produce male offspring.     

Genotype and diet effects on energy balance in the first three lactations of dairy cows

Dairy cows make strategic use of body energy to support early lactation and replenish this lost energy later in lactation, thereby creating body energy profiles that vary both within lactation and across lactations. The interaction between genotype and diet energy content is interesting from a management viewpoint and from a cow survival viewpoint. In this study, we modeled energy balance over 3 lactations using a multivariate random regression model, for cows from the Langhill Dairy Cattle Research Centre. This herd has been selected for maximum production or to remain at the UK national average for production (control group) and has been fed 2 diets of different energy density (high or low concentrate). Cows in the various groups differed in body condition score and the way they lost and regained body lipid. Cows selected for maximum production on a low-concentrate diet lost the greatest amount of body lipid (0.54 condition score units) after 3 lactations. Cows selected for maximum production lost more than control cows on either diet, indicating that selection mainly for yield has predisposed cows to utilize body energy to support lactation on diets spanning the range used here. Cows selected for maximum production were heavier at first calving than control cows but lost more weight and regained more weight so that at the end of each lactation, cows in the 2 groups did not differ significantly in weight. Cows use body lipid to support lactation over 3 lactations and the profile of that use varies according to genotype and diet.     

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.     

Energy balance profiles for the first three lactations of dairy cows estimated using random regression

Daily animal solutions were predicted using random regression analysis for feed intake, milk yield, live weight, and condition score recorded on 189 cows at the Langhill Dairy Cattle Research Centre. All cows had three successive lactations. Energy balance for days 1 to 305 of each of the three lactations was calculated both from daily measures of feed intake and milk output and from weekly measures of live weight and condition score. Cows returned to positive energy balance at days 72, 75, and 95 in lactations 1, 2, and 3, respectively, based on energy balance calculated from feed intake and milk output records (EB1), and at days 77, 83, and 73 based on energy balance calculated from body energy state changes (EB2). Correlations between energy balance at the same time in successive lactations ranged from 0.01 to 0.66 depending on the method of calculation and the stage of lactation. Energy balance over three lactations was modelled using sinusoidal functions which were associated with individual cows and allowed to vary between cows. The parameters of these curves are potentially useful since they have a biological interpretation. The phase relates to the period from calving to return to positive energy balance, and the amplitude relates to the degree of body energy loss (and recovery). The sinusoidal functions fitted to the curve removed a significant proportion of the variation, but accounted for only 45% and 40% of the variation in EB1 and EB2, respectively. The relationship between energy balance in the first three lactations is likely to be more complex than a simple linear function, but the profile of energy balance over the first three lactations may be a useful selection criteria in a multi-trait index. Energy balance profile over lactations one to three can be modelled with moderate accuracy using sinusoidal functions, and this warrants further research.     

Endocrine changes and liver mRNA abundance of somatotropic axis and insulin system constituents during negative energy balance at different stages of lactation in dairy cows

The liver has an important role in metabolic regulation and control of the somatotropic axis to adapt successfully to physiological and environmental changes in dairy cows. The aim of this study was to investigate the adaptation to negative energy balance (NEB) at parturition and to a deliberately induced NEB by feed restriction at 100 days in milk. The hepatic gene expression and the endocrine system of the somatotropic axis and related parameters were compared between the early and late NEB period. Fifty multiparous cows were subjected to 3 periods (1 = early lactation up to 12 wk postpartum, 2 = feed restriction for 3 wk beginning at around 100 days in milk with a feed-restricted and a control group, and 3 = subsequent realimentation period for the feed-restricted group for 8 wk). In period 1, plasma growth hormone reached a maximum in early lactation, whereas insulin-like growth factor-I (IGF-I), leptin, the thyroid hormones, insulin, and the revised quantitative insulin sensitivity check index increased gradually after a nadir in early lactation. Three days after parturition, hepatic mRNA abundance of growth hormone receptor 1A, IGF-I, IGF-I receptor and IGF-binding protein-3 (IGFBP-3) were decreased, whereas mRNA of IGFBP-1 and -2 and insulin receptor were upregulated as compared with wk 3 antepartum. During period 2, feed-restricted cows showed decreased plasma concentrations of IGF-I and leptin compared with those of control cows. The revised quantitative insulin sensitivity check index was lower for feed-restricted cows (period 2) than for control cows. Compared with the NEB in period 1, the changes due to the deliberately induced NEB (period 2) in hormones were less pronounced. At the end of the 3-wk feed restriction, the mRNA abundance of IGF-I, IGFBP-1, -2, -3, and insulin receptor was increased as compared with the control group. The different effects of energy deficiency at the 2 stages in lactation show that the endocrine regulation changes qualitatively and quantitatively during the course of lactation.     

Genetic evaluations of dairy bulls for daughter energy balance profiles using linear type scores and body condition score analyzed using random regression

The difference in body lipid between the start and end of lactation represents the body energy lost (or gained) in support of maintaining lactation including the nonproduction components of lactation. This source of energy is ignored in current genetic evaluations for production for dairy sires. The depletion and accretion of body tissue creates a pattern of body energy content over time that is, in part, under genetic control. Using random regression and field data, we modeled changes in body condition score (BCS) and liveweight, predicted from linear type traits, on first parity cows to produce daily breeding values of their sires for energy balance. These curves show that sires differ in the way their daughters lose and regain body energy throughout lactation. For all sires, the overall mean maximum daughter body energy loss was 1499 MJ (SD = 144 MJ) and occurred at d 99 (SD = 12.8 d) of lactation and the mean total daughter body energy loss at d 305 of lactation was 779 MJ (SD = 224 MJ). In this study, the profiles of body energy loss indicate that daughters of most sires lost body energy before d 150 and then recovered body energy, whereas the daughters of a few sires continued to lose body energy through to the end of lactation. Some sires with high merit for production may have daughters with body tissue mobilization profiles associated with poorer health and fertility leading to higher costs. A method of accounting for this cost could be to correct yield for body tissue mobilization. Deducting kilograms of milk from the breeding value for milk for each sire, equivalent in energy content to the body energy lost, resulted in a correlation of 0.98 between the ranking of sires for milk kilograms before and after adjustment. However, some sires changed rank bylarge amounts, the largest being +355 positions. Breeding values for energy balance can be calculated from single observations of BCS and linear type traits on daughters of a sire; data that can routinely be collected in national conformation assessment schemes.     

Genetic profile of body energy and blood metabolic traits across lactation in primiparous Holstein cows

The objectives of this study were to characterize the changes of body condition score (BCS), energy content (EC), cumulative effective energy balance (CEEB), and blood serum concentrations of glucose, β-hydroxybutyrate (BHBA), and nonesterified fatty acids (NEFA) across the first lactation of Holstein cows, and to estimate variance components for these traits. Four hundred ninety-seven cows kept on a commercial farm in Greece that had calved during 2005 and 2006 were used. Body condition score, estimated live weight, and blood metabolic traits were recorded weekly for the first 3 mo of lactation and monthly thereafter until the end of lactation. Body condition score and estimated live weight records were used to calculate EC and CEEB throughout the first lactation. Estimates of fixed curves and genetic parameters for each trait, by week of lactation, were obtained with the use of random regression models. The estimated fixed curves were indicative of changes in the metabolic process and energy balance of the cows. Significant genetic variance existed in all studied traits, and was particularly high during the first weeks of lactation (except for the genetic variance of CEEB, which was not significant at the beginning of lactation). Significant heritability estimates for BCS ranged from 0.34 to 0.79, for EC from 0.19 to 0.87, for CEEB from 0.58 to 0.93, for serum glucose from 0.12 to 0.39, for BHBA from 0.08 to 0.40, and for NEFA from 0.08 to 0.35. Genetic correlations between different weeks of lactation were near unity for adjacent weeks and decreased for weeks further apart, becoming practically zero for measurements taken more than 3 to 4 mo apart, especially with regard to blood metabolic traits. Significant heritability estimates were also obtained for BCS recorded before first calving. Results suggest that genetic evaluation and selection of dairy cows for early-lactation body energy and blood metabolic traits is possible.