On-farm estimation of energy balance in dairy cows using only frequent body weight measurements and body condition score

Precise energy balance estimates for individual cows are of great importance to monitor health, reproduction, and feed management. Energy balance is usually calculated as energy input minus output (EB(inout)), requiring measurements of feed intake and energy output sources (milk, maintenance, activity, growth, and pregnancy). Except for milk yield, direct measurements of the other sources are difficult to obtain in practice, and estimates contain considerable error sources, limiting on-farm use. Alternatively, energy balance can be estimated from body reserve changes (EB(body)) using body weight (BW) and body condition score (BCS). Automated weighing systems exist and new technology performing semi-automated body condition scoring has emerged, so frequent automated BW and BCS measurements are feasible. We present a method to derive individual EB(body) estimates from frequently measured BW and BCS and evaluate the performance of the estimated EB(body) against the traditional EB(inout) method. From 76 Danish Holstein and Jersey cows, parity 1 or 2+, on a glycerol-rich or a whole grain-rich total mixed ration, BW was measured automatically at each milking. The BW was corrected for the weight of milk produced and for gutfill. Changes in BW and BCS were used to calculate changes in body protein, body lipid, and EB(body) during the first 150 d in milk. The EB(body) was compared with the traditional EB(inout) by isolating the term within EB(inout) associated with most uncertainty; that is, feed energy content (FEC); FEC=(EB(body)+EMilk+EMaintenance+Eactivity)/dry matter intake, where the energy requirements are for milk produced (EMilk), maintenance (EMaintenance), and activity (EActivity). Estimated FEC agreed well with FEC values derived from tables (the mean estimate was 0.21 MJ of effective energy/kg of dry matter or 2.2% higher than the mean table value). Further, the FEC profile did not suggest systematic bias in EB(body) with stage of lactation. The EB(body) estimated from daily BW, adjusted for milk and meal-related gutfill and combined with frequent BCS, can provide a successful tool. This offers a pragmatic solution to on-farm calculation of energy balance with the perspective of improved precision under commercial conditions.     

Genetic parameters for level and change of body condition score and body weight in dairy cows

(Co)variance components for body condition score (BCS), body weight (BW), BCS change, BW change, and milk yield traits were estimated. The data analyzed included 6646 multiparous Holstein-Friesian cows with records for BCS, BW, and(or) milk yield at different stages of lactation from 74 dairy herds throughout Southern Ireland. Heritability estimates for BCS ranged from 0.27 to 0.37, while those for BCS change ranged from 0.02 to 0.10. Heritability estimates for BW records varied from 0.39 to 0.50, while heritabilities for BW change were similar to those observed for BCS change (0.03 to 0.09). The genetic correlations between BCS and BW at the same days in milk deviated little from 0.50, and the genetic correlations between BCS change and BW change over the same period ranged from 0.42 to 0.55. BCS and BW directly postpartum were both phenotypically and genetically negatively correlated with both BW change and BCS change in early lactation. The genetic correlations between BCS and milk yield were negative. The results of the present study show that animals that lose most BCS in early lactation tend to gain most BCS in late lactation, a trend also exhibited by BW.     

Genetic parameters for energy balance, feed efficiency, and related traits in Holstein cattle

Objectives of the current study were to estimate genetic parameters in Holstein cows for energy balance (EB) and related traits including dry matter intake (DMI), body weight (BW), body condition score (BCS), energy-corrected milk (ECM) production, and gross feed efficiency (GFE), defined as the ratio of total ECM yield to total DMI over the first 150d of lactation. Data were recorded for the first half of lactation on 227 and 175 cows in their first or later lactation, respectively. Random regression models were fitted to longitudinal data. Also, each trait was averaged over monthly intervals and analyzed by single and multivariate animal models. Heritability estimates ranged from 0.27 to 0.63, 0.12 to 0.62, 0.12 to 0.49, 0.63 to 0.72, and 0.49 to 0.53 for DMI, ECM yield, EB, BW, and BCS, respectively, averaged over monthly intervals. Daily heritability estimates ranged from 0.18 to 0.30, 0.10 to 0.26, 0.07 to 0.22, 0.43 to 0.67, and 0.25 to 0.38 for DMI, ECM yield, EB, BW, and BCS, respectively. Estimated heritability for GFE was 0.32. The genetic correlation of EB at 10d in milk (DIM) with EB at 150 DIM was -0.19, suggesting the genetic regulation of this trait differs by stage of lactation. Positive genetic correlations were found among DMI, ECM yield, and BW averaged over monthly intervals, whereas correlations of these traits with BCS depended upon stage of lactation. Total ECM yield for the lactation was positively correlated with DMI, but a negative genetic correlation between total ECM yield and EB was found. However, the genetic correlation between total ECM yield and EB in the first month of lactation was -0.02, indicating that total production is not genetically correlated with EB during the first month of lactation, when negative EB is most closely associated with diminished fitness. The genetic correlation between GFE and EB ranged from -0.73 to -0.99, indicating that selection for more efficient cows would favor a lower energy status. However, the genetic correlation between EB in the first month of lactation and GFE calculated from 75 to 150 DIM was not significant, indicating that the unfavorable correlation between GFE and EB in early lactation may be minimized with alternative definitions of efficiency. Thus, EB, GFE and related traits will likely respond to genetic selection in Holstein cows. However, the impact of selection for improved feed efficiency on EB must be carefully considered to avoid potential negative consequences of further reductions in EB at the onset of lactation.     

Genetic relationships among body condition score,body weight,milk yield,and fertility in dairy cows

Genetic (co)variances between body condition score (BCS), body weight (BW), milk production, and fertility-related traits were estimated. The data analyzed included 8591 multiparous Holstein-Friesian cows with records for BCS, BW, milk production, and/or fertility from 78 seasonal calving grass-based farms throughout southern Ireland. Of the cows included in the analysis, 4402 had repeated records across the 2 yr of the study. Genetic correlations between level of BCS at different stages of lactation and total lactation milk production were negative (-0.51 to -0.14). Genetic correlations between BW at different stages of lactation and total lactation milk production were all close to zero but became positive (0.01 to 0.39) after adjusting BW for differences in BCS. Body condition score at different stages of lactation correlated favorably with improved fertility; genetic correlations between BCS and pregnant 63 d after the start of breeding season ranged from 0.29 to 0.42. Both BW at different stages of lactation and milk production tended to exhibit negative genetic correlations with pregnant to first service and pregnant 63 d after the start of the breeding season and positive genetic correlations with number of services and the interval from first service to conception. Selection indexes investigated illustrate the possibility of continued selection for increased milk production without any deleterious effects on fertility or average BCS, albeit, genetic merit for milk production would increase at a slower rate.     

Short communication: genetic relationships among daily energy balance, feed intake, body condition score, and fat to protein ratio of milk in dairy cows

Postpartum energy status is critically important to health and fertility, and it remains a major task to find suitable indicator traits for energy balance. Therefore, genetic parameters for daily energy balance (EB) and dry matter intake (DMI), weekly milk fat to protein ratio (FPR), and monthly body condition score (BCS) were estimated using random regression on data collected from 682 Holstein-Friesian primiparous cows recorded between lactation d 11 to 180. Average energy-corrected milk (ECM), EB, DMI, BCS, and FPR were 32.0 kg, 9.6 MJ of NE_L, 20.3 kg, 2.95, and 1.12, respectively. Heritability estimates for EB, DMI, BCS, and FPR ranged from 0.03 to 0.13, 0.04 to 0.19, 0.34 to 0.59, and 0.20 to 0.54. Fat to protein ratio was a more valid measure for EB in early lactation than DMI, BCS, or single milk components. Correlations between FPR and EB were highest at the beginning of lactation [genetic correlation (r_g) = −0.62 at days in milk (DIM) 15] and decreased toward zero. Dry matter intake was the trait most closely correlated with EB in mid lactation (r_g = 0.73 at DIM 120 and 150). Energy balance in early lactation was negatively correlated to EB in mid lactation. The same applied to DMI. Genetic correlations between FPR across lactation stages were all positive; the lowest genetic correlation (0.55) was estimated between the beginning of lactation and early mid lactation. Hence, to improve EB at the beginning of lactation, EB and indicator traits need to be recorded in early lactation. We concluded that FPR is an adequate indicator for EB during the energy deficit phase. Genetic correlations of FPR with ECM, fat percentage, and protein percentage showed that a reduction of FPR in early lactation would have a slightly negative effect on ECM, whereas milk composition would change in a desirable manner.     

Associations between ultrasound hepatic measurements,body measures,and milk production traits in Holstein cows

Ultrasound (US) imaging has been proposed as a noninvasive tool for monitoring liver dysfunction in dairy cows. This study, carried out on 306 clinically healthy Holstein cows in the first 120 d of lactation kept in 2 herds in northern Italy, aimed at investigating the association between US imaging-derived traits, namely predicted liver triacylglycerol content (pTAG, mg/g), liver depth (LD, mm), portal vein depth (PVD, mm) and area (PVA, mm²), and body size measurements, body condition score (BCS), and milk productivity indicators. Transcutaneous US examination, milk sampling, body size measurements (withers height and heart girth), and BCS were collected once from all cows in 10 sampling batches. The body weights (BW) of a subsample of 73 cows were recorded and used together with an existing data set of BW and measures of Holstein Friesian cows (n = 399) to develop a regression equation to predict BW, which was then used to compute productivity indicators by scaling the milk production traits to predicted BW. Body size measures, BCS, milk traits, and productivity indicators were classified (low, medium, and high) in 0.75 units of standard deviation of the residuals generated from a linear model that included the effects of parity, days in milk, and sampling batch. Liver pTAG, PVA, PVD, and LD were analyzed with a sequence of linear mixed models that included the fixed effects of days in milk and parity and the random effect of sampling batch as common terms, whereas the classes of body and milk traits and the productivity indicators were included one by one. The US-related traits were found to be associated with body size measurements and BCS. Specifically, pTAG was inversely related to BCS, whereas PVD and LD increased with increasing heart girth, BCS, and predicted BW. Generally, no relevant associations were observed between the US parameters and milk production traits, including when expressed in terms of productivity. In conclusion, this study suggests that US measures of liver dimensions of clinically healthy cows are related to their size, whereas pTAG concentrations reflect body condition status, with no particular implications for milk production and productivity. Moreover, healthy cows seemed able to counteract the metabolic stress of the first 120 d of the lactation period without straining liver functionality. Finally, US imaging proved to be a promising technique to assess liver metabolic conditions. However, further studies are needed to confirm its potential as a noninvasive tool for monitoring liver conditions in healthy cows.     

Genetic analysis of efficiency traits in Austrian dairy cattle and their relationships with body condition score and lameness

This study is part of a larger project whose overall objective was to evaluate the possibilities for genetic improvement of efficiency in Austrian dairy cattle. In 2014, a 1-yr data collection was carried out. Data from 6,519 cows kept on 161 farms were recorded. In addition to routinely recorded data (e.g., milk yield, fertility, disease data), data of novel traits [e.g., body weight (BW), body condition score (BCS), lameness score, body measurements] and individual feeding information and feed quality were recorded on each test-day. The specific objective of this study was to estimate genetic parameters for efficiency (related) traits and to investigate their relationships with BCS and lameness in Austrian Fleckvieh, Brown Swiss, and Holstein cows. The following efficiency (related) traits were considered: energy-corrected milk (ECM), BW, dry matter intake (DMI), energy intake (INEL), ratio of milk output to metabolic BW (ECM/BW^0.75), ratio of milk output to DMI (ECM/DMI), and ratio of milk energy output to total energy intake (LE/INEL, LE = energy in milk). For Fleckvieh, the heritability estimates of the efficiency (related) traits ranged from 0.11 for LE/INEL to 0.44 for BW. Heritabilities for BCS and lameness were 0.19 and 0.07, respectively. Repeatabilities were high and ranged from 0.30 for LE/INEL to 0.83 for BW. Heritability estimates were generally lower for Brown Swiss and Holstein, but repeatabilities were in the same range as for Fleckvieh. In all 3 breeds, more-efficient cows were found to have a higher milk yield, lower BW, slightly higher DMI, and lower BCS. Higher efficiency was associated with slightly fewer lameness problems, most likely due to the lower BW (especially in Fleckvieh) and higher DMI of the more-efficient cows. Body weight and BCS were positively correlated. Therefore, when selecting for a lower BW, BCS is required as additional information because, otherwise, no distinction between large animals with low BCS and smaller animals with normal BCS would be possible.     

Genetic parameters of feed intake, production, body weight, body condition score, and selected type traits of Holstein cows in commercial tie-stall barns

The objectives of this study were to determine the feasibility of measuring feed intake in commercial tie-stall dairies and infer genetic parameters of feed intake, yield, somatic cell score, milk urea nitrogen, body weight (BW), body condition score (BCS), and linear type traits of Holstein cows. Feed intake, BW, and BCS were measured on 970 cows in 11 Pennsylvania tie-stall herds. Historical test-day data from these cows and 739 herdmates who were contemporaries during earlier lactations were also included. Feed intake was measured by researchers once per month over a 24-h period within 7 d of 6 consecutive Dairy Herd Information test days. Feed samples from each farm were collected monthly on the same day that feed intake was measured and were used to calculate intakes of dry matter, crude protein, and net energy of lactation. Test-day records were analyzed with multiple-trait animal models, and 305-d fat-corrected milk yield, dry matter intake, crude protein intake, net energy of lactation intake, average BW, and average BCS were derived from the test-day models. The 305-d traits were also analyzed with multiple-trait animal models that included a prediction of 40-wk dry matter intake derived from National Research Council equations. Heritability estimates for 305-d intake of dry matter, crude protein, and net energy of lactation ranged from 0.15 to 0.18. Genetic correlations of predicted dry matter intake with 305-d dry matter, crude protein, and net energy of lactation intake were 0.84, 0.90, and 0.94, respectively. Genetic correlations among the 3 intake traits and fat-corrected milk yield, BW, and stature were moderate to high (0.52 to 0.63). Results indicate that feed intake measured in commercial tie-stalls once per month has sufficient accuracy to enable genetic research. High-producing and larger cows were genetically inclined to have higher feed intake. The genetic correlation between observed and predicted intakes was less than unity, indicating potential variation in feed efficiency.     

Contribution of genetic variability to phenotypic differences in on-farm efficiency metrics of dairy cows based on body weight and milk solids yield

Milk solids per kilogram of body weight (BW) is growing in popularity as a measure of dairy cow lactation efficiency. Little is known on the extent of genetic variability that exist in this trait but also the direction and strength of genetic correlations with other performance traits. Such genetic correlations are important to know if producers are to consider actively selecting cows excelling in milk solids per kilogram of BW. The objective of the present study was to use a large data set of commercial Irish dairy cows to quantify the extent of genetic variability in milk solids per kilogram of BW and related traits but also their genetic and phenotypic inter-relationships. Mid-lactation BW and body condition score (BCS), along with 305-d milk solids yield (i.e., fat plus protein yield) were available on 12,413 lactations from 11,062 cows in 85 different commercial dairy herds. (Co)variance components were estimated using repeatability animal linear mixed models. The genetic correlation between milk solids and body weight was only 0.05, which when coupled with the observed large genetic variability in both traits, indicate massive potential to select for both traits in opposite directions. The genetic correlations between both milk solids and BW with BCS; however, need to be considered in any breeding strategy. The genetic standard deviation, heritability, and repeatability of milk solids per kilogram of BW was 0.08, 0.37, and 0.57, respectively. The genetic correlation between milk solids per kilogram of BW with milk solids, BW, and BCS was 0.62, −0.75, and −0.41, respectively. Therefore, based on genetic regression, each increase of 0.10 units in genetic merit for milk solids per kilogram of BW is expected to result in, on average, an increase in 16.1 kg 305-d milk solids yield, a reduction of 25.6 kg of BW and a reduction of 0.05 BCS units (scale of 1–5 where 1 is emaciated). The genetic standard deviation (heritability) for 305-d milk solids yield adjusted phenotypically to a common BW was 27.3 kg (0.22). The genetic correlation between this adjusted milk solids trait with milk solids, BW, and BCS was 0.91, −0.12, and −0.26, respectively. Once also adjusted phenotypically to a common BCS, the genetic standard deviation (heritability) for milk solids adjusted phenotypically to a common BW was 26.8 kg (0.22) where the genetic correlation with milk solids, BW and BCS was 0.91, −0.21, and −0.07, respectively. The genetic standard deviation (heritability) of BW adjusted phenotypically for differences in milk solids was 35.3 kg (0.61), which reduced to 33.2 kg when also phenotypically adjusted for differences in BCS. Results suggest considerable opportunity exists to change milk solids yield independent of BW, and vice versa. The opportunity is reduced slightly once also corrected for differences in BCS. Inter-animal BCS differences should be considered if selection on such metrics is contemplated.     

Body composition and estimated tissue energy balance in Jersey and Holstein cows during early lactation

The rate and extent of estimated energy mobilization and the relationship between fat depth at the rib and thurl and body condition score (BCS) were investigated in Jersey and Holstein cows in early lactation. Twenty-six cows were paired by breed, parity, and calving date, and were individually fed a total mixed ration ad libitum from parturition through 120 d in milk. Feed intake and milk production were measured daily; body weight (BW), BCS, subcutaneous fat depth, milk composition, and concentration of plasma nonesterified fatty acids were measured every 2 wk. Estimated tissue energy balance (TEB) was calculated using 1989 NRC equations. Net energy intake was greater in early lactation for Holsteins compared with Jerseys, 37.8 and 28.2 Mcal/d, respectively. Milk energy was greater for Holsteins relative to Jerseys, 30.5 versus 21.2 Mcal/d. Fat depth and BCS did not differ between breeds. A positive relationship existed between fat depth and BCS for Jerseys; however, there was no significant relationship for Holsteins. The best-fit regression model for predicting TEB for Holsteins and Jerseys in early lactation included week of lactation, milk composition, and BCS. Jerseys remained in negative TEB for a shorter period of time relative to Holsteins. The TEB nadir was -6.19 and -12.9 Mcal/d, for Jerseys and Holsteins, respectively. Expressed as a proportion of metabolic BW (BW(0.75)), net energy intake did not differ between breeds, yet milk energy and estimated tissue energy loss were greater for Holsteins compared with Jerseys.     

Genetic parameters for body condition score, body weight, milk yield, and fertility estimated using random regression models

Genetic (co)variances between body condition score (BCS), body weight (BW), milk yield, and fertility were estimated using a random regression animal model extended to multivariate analysis. The data analyzed included 81,313 BCS observations, 91,937 BW observations, and 100,458 milk test-day yields from 8725 multiparous Holstein-Friesian cows. A cubic random regression was sufficient to model the changing genetic variances for BCS, BW, and milk across different days in milk. The genetic correlations between BCS and fertility changed little over the lactation; genetic correlations between BCS and interval to first service and between BCS and pregnancy rate to first service varied from -0.47 to -0.31, and from 0.15 to 0.38, respectively. This suggests that maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in midlactation when the genetic variance for BCS is largest. Selection for increased BW resulted in shorter intervals to first service, but more services and poorer pregnancy rates; genetic correlations between BW and pregnancy rate to first service varied from -0.52 to -0.45. Genetic selection for higher lactation milk yield alone through selection on increased milk yield in early lactation is likely to have a more deleterious effect on genetic merit for fertility than selection on higher milk yield in late lactation.     

Heritability and correlations among body condition score loss,body condition score,production and reproductive performance

The objectives of this study were to estimate the heritability of body condition score loss (BCSL) in early lactation and estimate genetic and phenotypic correlations among BCSL, body condition score (BCS), production, and reproductive performance. Body condition scores at calving and postpartum, mature equivalents for milk, fat and protein yield, days to first service, and services per conception were obtained from Dairy Records Management Systems in Raleigh, NC. Body condition score loss was defined as BCS at calving minus postpartum BCS. Heritabilities and correlations were estimated with a series of bivariate animal models with average-information REML. Herd-year-season effects and age at calving were included in all models. The length of the prior calving interval was included for all second lactation traits, and all nonproduction traits were analyzed with and without mature equivalent milk as a covariable. Initial correlations between BCS and BCSL were obtained using BCSL and BCS observations from the same cows. Additional genetic correlation estimates were generated through relationships between a group of cows with BCSL observations and a separate group of cows with BCS observations. Heritability estimates for BCSL ranged from 0.01 to 0.07. Genetic correlation estimates between BCSL and BCS at calving ranged from -0.15 to -0.26 in first lactation and from -0.11 to -0.48 in second lactation. Genetic correlation estimates between BCSL and postpartum BCS ranged from -0.70 to -0.99 in first lactation and from -0.56 to -0.91 in second lactation. Phenotypic correlation estimates between BCSL and BCS at calving were near 0.54, whereas phenotypic correlation estimates between BCSL and postpartum BCS were near -0.65. Genetic correlations between BCSL and yield traits ranged from 0.17 to 0.50. Genetic correlations between BCSL and days to first service ranged from 0.29 to 0.68. Selection for yield appears to increase BCSL by lowering postpartum BCS. More loss in BCS was associated with an increase in days to first service.     

Heritability of gross feed efficiency and associations with yield, intake, residual intake, body weight, and body condition score in 11 commercial Pennsylvania tie stalls

The objectives of this study were to calculate the heritability of feed efficiency and residual feed intake, and examine the relationships between feed efficiency and other traits of productive and economic importance. Intake and body measurement data were collected monthly on 970 cows in 11 tie-stall herds for 6 consecutive mo. Measures of efficiency for this study were: dry matter intake efficiency (DMIE), defined as 305-d fat-corrected milk (FCM)/305-d DMI, net energy for lactation efficiency (NE_LE), defined as 305-d FCM/05-d NE_L intake, and crude protein efficiency (CPE), defined as 305-d true protein yield/305-d CP intake. Residual feed intake (RFI) was calculated by regressing daily DMI on daily milk, fat, and protein yields, body weight (BW), daily body condition score (BCS) gain or loss, the interaction between BW and BCS gain or loss, and days in milk (DIM). Data were analyzed with 3- and 4-trait animal models and included 305-d FCM or protein yield, DM, NE_L, or CP intake, BW, BCS, BCS change between DIM 1 and 60, milk urea nitrogen, somatic cell score, RFI, or an alternative efficiency measure. Data were analyzed with and without significant covariates for BCS and BCS change between DIM 1 and 60. The average DMIE, NE_LE, and CPE were 1.61, 0.98, and 0.32, respectively. Heritability of gross feed efficiency was 0.14 for DMIE, 0.18 for NE_LE, and 0.21 for CPE, and heritability of RFI was 0.01. Body weight and BCS had high and negative correlations with the efficiency traits (−0.64 to −0.70), indicating that larger and fatter cows were less feed efficient than smaller and thinner cows. When BCS covariates were included in the model, cows identified as being highly efficient produced 2.3 kg/d less FCM in early lactation due to less early lactation loss of BCS. Results from this study suggest that selection for higher yield and lower BW will increase feed efficiency, and that body tissue mobilization should be considered.     

Body and milk traits as indicators of dairy cow energy status in early lactation

The inclusion of feed intake and efficiency traits in dairy cow breeding goals can lead to increased risk of metabolic stress. An easy and inexpensive way to monitor postpartum energy status (ES) of cows is therefore needed. Cows' ES can be estimated by calculating the energy balance from energy intake and output and predicted by indicator traits such as change in body weight (ΔBW), change in body condition score (ΔBCS), milk fat:protein ratio (FPR), or milk fatty acid (FA) composition. In this study, we used blood plasma nonesterified fatty acids (NEFA) concentration as a biomarker for ES. We determined associations between NEFA concentration and ES indicators and evaluated the usefulness of body and milk traits alone, or together, in predicting ES of the cow. Data were collected from 2 research herds during 2013 to 2016 and included 137 Nordic Red dairy cows, all of which had a first lactation and 59 of which also had a second lactation. The data included daily body weight, milk yield, and feed intake and monthly BCS. Plasma samples for NEFA were collected twice in lactation wk 2 and 3 and once in wk 20. Milk samples for analysis of fat, protein, lactose, and FA concentrations were taken on the blood sampling days. Plasma NEFA concentration was higher in lactation wk 2 and 3 than in wk 20 (0.56 ± 0.30, 0.43 ± 0.22, and 0.13 ± 0.06 mmol/L, respectively; all means ± standard deviation). Among individual indicators, C18:1 cis-9 and the sum of C18:1 in milk had the highest correlations (r = 0.73) with NEFA. Seven multiple linear regression models for NEFA prediction were developed using stepwise selection. Of the models that included milk traits (other than milk FA) as well as body traits, the best fit was achieved by a model with milk yield, FPR, ΔBW, ΔBCS, FPR × ΔBW, and days in milk. The model resulted in a cross-validation coefficient of determination (R²cv) of 0.51 and a root mean squared error (RMSE) of 0.196 mmol/L. When only milk FA concentrations were considered in the model, NEFA prediction was more accurate using measurements from evening milk than from morning milk (R²cv = 0.61 vs. 0.53). The best model with milk traits contained FPR, C10:0, C14:0, C18:1 cis-9, C18:1 cis-9 × C14:0, and days in milk (R²cv = 0.62; RMSE = 0.177 mmol/L). The most advanced model using both milk and body traits gave a slightly better fit than the model with only milk traits (R²cv = 0.63; RMSE = 0.176 mmol/L). Our findings indicate that ES of cows in early lactation can be monitored with moderately high accuracy by routine milk measurements.     

Relationships among body condition score, body weight, and milk production variables in pasture-based dairy cows

The objective of the present study was to identify and quantify relationships among dairy cow body condition score (BCS) and body weight (BW) and production variables in pasture-based, seasonal-calving herds. More than 2,500 lactation records from 897 spring-calving Holstein-Friesian and Jersey dairy cows were used in the analyses. Six variables related to BCS and BW, including observations precalving, at calving, and nadir as well as days to nadir and change precalving and between calving and nadir were generated. An exponential function was fitted within lactation to milk and 4% fat-corrected milk (FCM) yield data to model lactation curves. The milk production variables investigated were the parameters of the fitted function as well as accumulated yield of milk and FCM at 60 and 270 days in milk and average milk composition. Mixed models were used to identify BCS and BW variables that significantly affected milk production. After adjusting for the fixed effect of year of calving, parity, and days dry, milk and FCM yields were nonlinearly associated with calving and nadir BCS, increasing at a declining rate up to BCS 6.0 to 6.5 (10-point scale; approximately 3.5 in the 5-point scale) and declining thereafter. However, there was very little increase in milk and FCM yields above a calving BCS of 5.0 (approximately 3.0 in the 5-point scale). Average milk fat content over 60 and 270 days in milk was positively correlated with increasing calving and nadir BCS. In comparison, milk protein percentage was not influenced by calving BCS but was positively associated with nadir BCS and negatively associated with BCS lost between calving and nadir. The effect of BW and changes in BW were similar to the effect of BCS, although the scale of the effect was breed-dependent. For example, milk and FCM yield increased linearly with increasing calving BCS, but the effect was greater in Holstein-Friesians compared with Jersey cows. The results are consistent with the literature and highlight the important role that BCS and BW loss has on milk production, irrespective of the system of farming.     

Concentrate supplementation of a diet based on medium-quality grass silage for 4 weeks prepartum: Effects on cow performance,health, metabolic status,and immune function

Because negative energy balance (EB) contributes to transition-period immune dysfunction in dairy cows, dietary management strategies should aim to minimize negative EB during this time. Prepartum diets that oversupply energy may exacerbate negative EB in early lactation, with detrimental effects on immune function. However, with lower body condition score (BCS) cows, it has been shown that offering concentrates in addition to a grass silage-based diet when confined during an 8-wk dry period resulted in increased neutrophil function in early lactation. The aim of this study was to examine if similar benefits occur when concentrate feeding was restricted to a 4-wk period prepartum. Twenty-six multiparous and 22 primiparous Holstein-Friesian cows were offered ad libitum access to medium-quality grass silage until 28 d before their predicted calving dates (actual mean of 32 d prepartum; standard deviation = 6.4). At this time multiparous cows had a mean BCS of 2.9 (standard deviation = 0.12) and primiparous cows a mean BCS of 3.0 (standard deviation = 0.14) on a 1 to 5 scale. Cows were then allocated in a balanced manner to 1 of 2 treatments (13 multiparous cows and 11 primiparous cows on each treatment): silage only (SO) or silage plus concentrates (S+C) until calving. Cows on SO were offered the same grass silage ad libitum. Cows on S+C were offered an ad libitum mixed ration of the same grass silage and additional concentrates in a 60:40 dry matter (DM) ratio, which provided a mean concentrate DM intake (DMI) of 4.5 kg/cow per d. After calving, all cows were offered a common mixed ration (grass silage and concentrates, 40:60 DM ratio) for 70 d postpartum. Offering concentrates in addition to grass silage during the 4 wk prepartum increased prepartum DMI (12.0 versus 10.1 kg/cow per d), EB (+40.0 versus +10.6 MJ/cow per d), and body weight (BW; 640 versus 628 kg), and tended to increase BCS (3.02 versus 2.97). However, postpartum DMI, milk yield, milk composition, BW change, BCS change, serum nonesterified fatty acid, and β-hydroxybutryrate concentrations, health, and corpus luteum measures were unaffected by treatment. The in vitro assays of neutrophil phagocytosis, neutrophil oxidative burst, and interferon gamma production, conducted on blood samples obtained at d 14 prepartum and d 3, 7, 14, and 21 postpartum, were unaffected by treatment. Primiparous cows had higher phagocytic fluorescence intensity at d 14 prepartum and d 3 and 7 postpartum; a higher percentage of neutrophils undergoing oxidative burst at d 3, 7, and 21 postpartum; and a higher oxidative burst fluorescence intensity at d 14 prepartum and d 7, 14, and 21 postpartum compared with multiparous cows. This suggests that neutrophil function of primiparous cows was less sensitive to the changes occurring during the transition period than that of multiparous cows. In conclusion, offering concentrates during the 4-wk period prepartum had no effect on postpartum DMI, milk yield, body tissue mobilization, EB, measures of neutrophil or lymphocyte function, health, or corpus luteum activity.     

Genetic heterogeneity of feed intake,energy-corrected milk,and body weight across lactation in primiparous Holstein,Nordic Red,and Jersey cows

In this study, we aimed to estimate and compare the genetic parameters of dry matter intake (DMI), energy-corrected milk (ECM), and body weight (BW) as 3 feed efficiency–related traits across lactation in 3 dairy cattle breeds (Holstein, Nordic Red, and Jersey). The analyses were based on weekly records of DMI, ECM, and BW per cow across lactation for 842 primiparous Holstein cows, 746 primiparous Nordic Red cows, and 378 primiparous Jersey cows. A random regression model was applied to estimate variance components and genetic parameters for DMI, ECM, and BW in each lactation week within each breed. Phenotypic means of DMI, ECM, and BW observations across lactation showed to be in very similar patterns between breeds, whereas breed differences lay in the average level of DMI, ECM, and BW. Generally, for all studied breeds, the heritability for DMI ranged from 0.2 to 0.4 across lactation and was in a range similar to the heritability for ECM. The heritability for BW ranged from 0.4 to 0.6 across lactation, higher than the heritability for DMI or ECM. Among the studied breeds, the heritability estimates for DMI shared a very similar range between breeds, whereas the heritability estimates for ECM tended to be different between breeds. For BW, the heritability estimates also tended to follow a similar range between breeds. Among the studied traits, the genetic variance and heritability for DMI varied across lactation, and the genetic correlations between DMI at different lactation stages were less than unity, indicating a genetic heterogeneity of feed intake across lactation in dairy cattle. In contrast, BW was the most genetically consistent trait across lactation, where BW among all lactation weeks was highly correlated. Genetic correlations between DMI, ECM, and BW changed across lactation, especially in early lactation. Energy-corrected milk had a low genetic correlation with both DMI and BW at the beginning of lactation, whereas ECM was highly correlated with DMI in mid and late lactation. Based on our results, genetic heterogeneity of DMI, ECM, and BW across lactation generally was observed in all studied dairy breeds, especially for DMI, which should be carefully considered for the recording strategy of these traits. The genetic correlations between DMI, ECM, and BW changed across lactation and followed similar patterns between breeds.     

Body condition score and body weight effects on dystocia and stillbirths and consequent effects on postcalving performance

The objective of this study was to quantify the effect of periparturient body condition score (BCS) and body weight (BW) related traits on the incidence of calving dystocia and stillbirths, and to determine any consequent effect of dystocia and stillbirths on BCS, BW, milk production, udder health, and fertility in grazing Holstein-Friesian dairy cows. Up to 2,384 lactation records with data on calving dystocia or stillbirths were available from one research herd across 15 yr. Mixed models and generalized estimating equations were used to quantify all effects. Body condition score or BW 8 wk precalving or at calving, or change precalving did not significantly affect the odds of a difficult calving or stillbirth. Cows that experienced dystocia lost, on average, more BCS and BW between calving and nadir and had significantly reduced nadir BCS and BW. Incidence of stillbirths did not affect BCS in early lactation, although BW loss postpartum was greater following a stillbirth. A dystocia or stillbirth event was associated with reduced 60-d milk yield (42 and 52 kg less milk produced following a difficult calving or a stillbirth, respectively). The effect of stillbirth on milk yield was independent of dystocia. Cows that experienced dystocia had reduced milk concentration of fat, protein, and lactose, whereas average somatic cell score (natural logarithm of somatic cell count) in the first 60-d postpartum was elevated. There was no significant effect of dystocia or stillbirth on clinical mastitis, but pregnancy rates to first service and throughout the 12-wk breeding season were compromised in cows that had experienced difficulty at calving. The significance of the effects of stillbirth on somatic cell score and reduced fertility were mediated through its association with dystocia. In conclusion, periparturient BCS and BW within the range observed in the current study did not significantly affect incidence of dystocia and stillbirth, but these events negatively affected cow performance in early lactation.     

Relationships among milk yield,body condition,cow weight,and reproduction in spring-calved Holstein-Friesians

Relationships among milk production, body condition score (BCS), body weight (BW), and reproduction were studied using logistic regression on data from 6433 spring-calving Holstein-Friesian dairy cows in 74 commercial herds. Multivariate models were adjusted for herd, breeding value for milk yield, proportion of Holstein-Friesian genes, lactation number, calving period, and degree of calving assistance. Significant associations between reproductive measures and components of energy balance were identified. Higher 200-d milk protein content and higher protein-to-fat ratio at start of breeding were associated with increased likelihood of submission for breeding in the first 21 d of the breeding season (SR21). High 100-d cumulative milk yield as a proportion of estimated 305-d milk yield (low persistency) was associated with a lower likelihood of pregnancy to first service (PREG1), whereas cows reaching peak milk yields earlier tended to have higher PREG1. Cows that reached nadir milk protein content relatively late in lactation had lower PREG1. Milk yield at first service and 305-d milk protein content were positively associated with the likelihood of pregnancy after 42 d of breeding (PR42). Higher 305-d milk lactose content was associated with increased PREG1 and PR42. Mean BCS at 60 to 100 d of lactation was positively associated with both SR21 and PR42, whereas nadir BCS was positively associated with PREG1. Cows with precalving BCS > 3.0 that also lost > 0.5 BCS unit by first service had lower PR42. More BW gain for 90 d after start of breeding was associated with higher SR21 and PREG1; more BW gain for 90 d after first service was associated with higher PR42. Milk protein and lactose content, BCS, and BW changes are important tools to identify cows at risk of poor reproduction.     

Characteristics of feed efficiency within and across lactation in dairy cows and the effect of genetic selection

The objective of the present study was to investigate the phenotypic inter- and intra-relationships within and among alternative feed efficiency metrics across different stages of lactation and parities; the expected effect of genetic selection for feed efficiency on the resulting phenotypic lactation profiles was also quantified. A total of 8,199 net energy intake (NE_I) test-day records from 2,505 lactations on 1,290 cows were used. Derived efficiency traits were either ratio based or residual based; the latter were derived from least squares regression models. Residual energy intake (REI) was defined as NE_I minus predicted energy requirements based on lactation performance; residual energy production (REP) was defined as net energy for lactation minus predicted energy requirements based on lactation performance. Energy conversion efficiency was defined as net energy for lactation divided by NE_I. Pearson phenotypic correlations among traits were computed across lactation stages and parities, and the significance of the differences was determined using the Fisher r-to-z transformation. Sources of variation in the feed efficiency metrics were investigated using linear mixed models, which included the fixed effects of contemporary group, breed, parity, stage of lactation, and the 2-way interaction of parity by stage of lactation. With the exception of REI, parity was associated with all efficiency and production traits. Stage of lactation, as well as the 2-way interaction of parity by stage of lactation, were associated with all efficiency and production traits. Phenotypic correlations among the efficiency and production traits differed not only by stage of lactation but also by parity. For example, the strong phenotypic correlation between REI and energy balance (EB; 0.89) for cows in parity 3 or greater and early lactation was weaker for parity 1 cows at the same lactation stage (0.81), suggesting primiparous cows use the ingested energy for both milk production and growth. Nonetheless, these strong phenotypic correlations between REI and EB suggested negative REI animals (i.e., more efficient) are also in more negative EB. These correlations were further supported when assessing the effect on phenotypic performance of animals genetically divergent for feed intake and efficiency based on parental average. Animals genetically selected to have lower REI resulted in cows who consumed less NE_I but were also in negative EB throughout the entire lactation. Nonetheless, such repercussions of negative EB do not imply that selection for negative REI (as defined here) should not be practiced, but instead should be undertaken within the framework of a balanced breeding objective, which includes traits such as reproduction and health.