Multiple-trait random regression modeling of feed efficiency in US Holsteins

Residual feed intake (RFI) and feed saved (FS) are important feed efficiency traits that have been increasingly considered in genetic improvement programs. Future sustainability of these genetic evaluations will depend upon greater flexibility to accommodate sparsely recorded dry matter intake (DMI) records on many more cows, especially from commercial environments. Recent multiple-trait random regression (MTRR) modeling developments have facilitated days in milk (DIM)-specific inferences on RFI and FS, particularly in modeling the effect of change in metabolic body weight (MBW). The MTRR analyses, using daily data on the core traits of DMI, MBW, and milk energy (MilkE), were conducted separately for 2,532 primiparous and 2,379 multiparous US Holstein cows from 50 to 200 DIM. Estimated MTRR variance components were used to derive genetic RFI and FS and DIM-specific genetic partial regressions of DMI on MBW, MilkE, and change in MBW. Estimated daily heritabilities of RFI and FS varied across lactation for both primiparous (0.05–0.07 and 0.11–0.17, respectively) and multiparous (0.03–0.13 and 0.10–0.17, respectively) cows. Genetic correlations of RFI across DIM varied (>0.05) widely compared with FS (>0.54) within either parity class. Heritability estimates based on average lactation-wise measures were substantially larger than daily heritabilities, ranging from 0.17 to 0.25 for RFI and from 0.35 to 0.41 for FS. The partial genetic regression coefficients of DMI on MBW (0.11 to 0.16 kg/kg^0.75 for primiparous and 0.12 to 0.14 kg/kg^0.75 for multiparous cows) and of DMI on MilkE (0.45 to 0.68 kg/Mcal for primiparous and 0.36 to 0.61 kg/Mcal for multiparous cows) also varied across lactation. In spite of the computational challenges encountered with MTRR, the model potentially facilitates an efficient strategy for harnessing more data involving a wide variety of data recording scenarios for genetic evaluations on feed efficiency.     

Feeding behavior parameters and temporal patterns in mid-lactation Holstein cows across a range of residual feed intake values

Residual feed intake (RFI) is a measurement of the difference between actual and predicted feed intake when adjusted for energy sinks; more efficient cows eat less than predicted (low RFI) and inefficient cows eat more than predicted (high RFI). Data evaluating the relationship between RFI and feeding behaviors (FB) are limited in dairy cattle; therefore, the objective of this study was to determine daily and temporal FB in mid-lactation Holstein cows across a range of RFI values. Mid-lactation Holstein cows (n = 592 multiparous; 304 primiparous) were enrolled in 17 cohorts at 97 ± 26 d in milk (± standard deviation), and all cows within a cohort were fed a common diet using automated feeding bins. Cow RFI was calculated as the difference between predicted and observed dry matter intake (DMI) after accounting for parity, days in milk, milk energy, metabolic body weight and change, and experiment. The associations between RFI and FB at the level of meals and daily totals were evaluated using mixed models with the fixed effect of RFI and the random effects of cow and cohort. Daily temporal FB analyses were conducted using 2-h blocks and analyzed using mixed models with the fixed effects of RFI, time, RFI × time, and cohort, and the random effect of cow (cohort). There was a positive linear association between RFI and DMI in multiparous cows and a positive quadratic relationship in primiparous cows, where the rate of increase in DMI was less at higher RFI. Eating rate, DMI per meal, and size of the largest daily meal were positively associated with RFI. Daily temporal analysis of FB revealed an interaction between RFI and time for eating rate in multiparous and primiparous cows. The eating rate increased with greater RFI at 11 of 12 time points throughout the day, and eating rate differed across RFI between multiple time points. There tended to be an interaction between RFI and time for eating time and bin visits in multiparous cows but not primiparous cows. Overall, there was a time effect for all FB variables, where DMI, eating time and rate, and bin visits were greatest after the initial daily feeding at 1200 h, increased slightly after each milking, and reached a nadir at 0600 h (6 h before feeding). Considering the relationship between RFI and eating rate, additional efforts to determine cost-effective methods of quantifying eating rate in group-housed dairy cows is warranted. Further investigation is also warranted to determine if management strategies to alter FB, especially eating rate, can be effective in increasing feed efficiency in lactating dairy cattle.     

Three-breed rotational crossbreds of Montbéliarde,Viking Red,and Holstein compared with Holstein cows for feed efficiency,income over feed cost,and residual feed intake

Rotational 3-breed crossbred cows of Montbéliarde, Viking Red, and Holstein (CB) were compared with Holstein (HO) cows for alternative measures of feed efficiency as well as income over feed cost (IOFC) and residual feed intake (RFI) during the first 150 d of first, second, and third lactations. Primiparous and multiparous CB (n = 63 and n = 43, respectively) and HO (n = 60 and n = 37, respectively) cows were fed the same total mixed ration twice daily with refusals weighed once daily. Feed was analyzed for dry matter content, net energy for lactation, and crude protein content. Body weight (BW) was recorded twice weekly. Daily production of milk, fat, and protein were estimated from monthly test days with best prediction. Measures of efficiency from 4 to 150 d in milk (DIM) were feed conversion efficiency (FCE), defined as fat plus protein production (kg) per kilogram of dry matter intake (DMI); ECM/DMI, defined as kilograms of energy-corrected milk (ECM) per kilogram of DMI; net energy for lactation efficiency (NE_LE), defined as ECM (kg) per megacalorie of net energy for lactation intake; crude protein efficiency (CPE), defined as true protein production (kg) per kilogram of crude protein intake; and DMI/BW, defined as DMI (kg) per kilogram of BW. The IOFC was defined as revenue from fat plus protein production minus feed cost. The RFI from 4 to 150 DIM for each lactation was the residual error remaining from regression of DMI on milk energy output (Mcal), metabolic BW, and energy required for change in BW (Mcal). Statistical analysis of measures of feed efficiency and RFI for primiparous cows included the fixed effects of year of calving and breed group. For multiparous cows, statistical analysis included breed as a fixed effect and cow as a repeated effect nested within breed group. Primiparous CB cows had higher means for FCE (+5.5%), ECM/DMI (+4.0%), NE_LE (+4.0%), and CPE (+5.2%) and a lower mean DMI/BW (–5.3%) than primiparous HO cows. Primiparous CB cows ($875) also had higher mean IOFC than primiparous HO cows ($825). In addition, mean RFI from 4 to 150 DIM was significantly lower (more desirable) for primiparous CB cows than HO cows. Likewise, multiparous CB cows had higher means for FCE (+8.2%), ECM/DMI (+5.9%), NE_LE (+5.8%), and CPE (+8.1%) and a lower mean for DMI/BW (–4.8%) than multiparous HO cows. Multiparous CB cows ($1,296) also had a higher mean for IOFC than multiparous HO cows ($1,208) and a lower mean for RFI from 4 to 150 DIM than HO cows.     

Neglect of lactation stage leads to naive assessment of residual feed intake in dairy cattle

Residual feed intake (RFI) is a candidate trait for feed efficiency in dairy cattle. We investigated the influence of lactation stage on the effect of energy sinks in defining RFI and the genetic parameters for RFI across lactation stages for primiparous dairy cattle. Our analysis included 747 primiparous Holstein cows, each with recordings on dry matter intake (DMI), milk yield, milk composition, and body weight (BW) over 44 lactation weeks. For each individual cow, energy-corrected milk (ECM), metabolic BW (MBW), and change in BW (ΔBW) were calculated in each week of lactation and were taken as energy sinks when defining RFI. Two RFI models were considered in the analyses; RFI model [1] was a 1-step RFI model with constant partial regression coefficients of DMI on energy sinks (ECM, MBW, and ΔBW) over lactation. In RFI model [2], data from 44 lactation weeks were divided into 11 consecutive lactation periods of 4 wk in length. The RFI model [2] was identical to model [1] except that period-specific partial regressions of DMI on ECM, MBW, and ΔBW in each lactation period were allowed across lactation. We estimated genetic parameters for RFI across lactation by both models using a random regression method. Using RFI model [2], we estimated the period-specific effects of ECM, MBW, and ΔBW on DMI in all lactation periods. Based on results from RFI model [2], the partial regression coefficients of DMI on ECM, MBW, and ΔBW differed across lactation in RFI. Constant partial regression coefficients of DMI on energy sinks over lactation was not always sufficient to account for the effects across lactation and tended to give roughly average information from all period-specific effects. Heritability for RFI over 44 lactation weeks ranged from 0.10 to 0.29 in model [1] and from 0.10 to 0.23 in model [2]. Genetic variance and heritability estimates for RFI from model [2] tended to be slightly lower and more stable across lactation than those from model [1]. In both models, RFI was genetically different over lactation, especially between early and later lactation stages. Genetic correlation estimates for RFI between early and later lactation tended to be higher when using model [2] compared with model [1]. In conclusion, partial regression coefficients of DMI on energy sinks differed across lactation when modeling RFI. Neglect of lactation stage when defining RFI could affect the assessment of RFI and the estimation of genetic parameters for RFI across lactation.     

Updating predictions of dry matter intake of lactating dairy cows

Our objective was to model dry matter intake (DMI) by Holstein dairy cows based on milk energy (MilkE), body weight (BW), change in BW (ΔBW), body condition score (BCS), height, days in milk (DIM), and parity (primiparous and multiparous). Our database included 31,631 weekly observations on 2,791 cows enrolled in 52 studies from 8 states of the United States, mostly in the Upper Midwest. The means ± standard deviations of these variables were 24 ± 5 kg of DMI, 30 ± 6 Mcal of MilkE/d, 624 ± 83 kg of BW, 0.24 ± 1.50 kg of ΔBW/d, 3.0 ± 0.5 BCS, 149 ± 6 cm height, and 102 ± 45 DIM. Data analysis was performed using a mixed-effects model containing location, study within location, diet within study, and location and cow within study as random effects, whereas the fixed effects included the linear effects of the covariates described previously and all possible 2-way interactions between parity and the other covariates. A nonlinear (NLIN) mixed model analysis was developed using a 2-step approach for computational tractability. In the first step, we used a linear (LIN) model component of the NLIN model to predict DMI using only data from mid-lactation dairy cows (76–175 DIM) without including information on DIM. In the second step, a nonlinear adjustment for DIM using all data from 0 to 368 DIM was estimated. Additionally, this NLIN model was compared with an LIN model containing a fourth-order polynomial for DIM using data throughout the entire lactation (0–368 DIM) to assess the utility of an NLIN model for the prediction of DMI. In summary, a total of 8 candidate models were evaluated as follows: 4 ways to express energy required for maintenance (BW, BW^0.75, BW adjusted for a BCS of 3, and BW^0.75 adjusted for a BCS of 3) × 2 modeling strategies (LIN vs. NLIN). The candidate models were compared using a 5-fold across-studies cross-validation approach repeated 20 times with the best-fitting model chosen as the proposed model. The metrics used for evaluation were the mean bias, slope bias, concordance correlation coefficient (CCC), and root mean squared error of prediction (RMSEP). The proposed prediction equation was DMI (kg/d) = [(3.7 + parity × 5.7) + 0.305 × MilkE (Mcal/d) + 0.022 × BW (kg) + (?0.689 + parity × ?1.87) × BCS] × [1 – (0.212 + parity × 0.136) × exp^{(?0.053 × DIM)}] (mean bias = 0.021 kg, slope bias = 0.059, CCC = 0.72, and RMSEP = 2.89 kg), where parity is equal to 1 if the animal is multiparous and 0 otherwise. Finally, the proposed model was compared against the Nutrient Requirements of Dairy Cattle (2001) prediction equation for DMI using an independent data set of 9,050 weekly observations on 1,804 Holstein cows. The proposed model had smaller mean bias and RMSEP and higher CCC than the Nutrient Requirements of Dairy Cattle equation to predict DMI and has potential to improve diet formulation for lactating dairy cows.     

The effects of supplementation with a blend of cinnamaldehyde and eugenol on feed intake and milk production of dairy cows

Plant extracts (PE) are naturally occurring chemicals in plants, and many of these molecules have been reported to influence production efficiency of dairy and beef animals. Two experiments were conducted to determine the effect of a PE additive (CE; an encapsulated blend of cinnamaldehyde and eugenol) on the milk production performance of lactating dairy cows across a range of doses. In experiment 1, 32 Holstein multi- and primiparous dairy cows in mid-lactation were assigned to no additive or supplementation with CE (350 mg/d; n = 16 cows/treatment) for 6 wk. In experiment 2, 48 Holstein multi- and primiparous dairy cows were assigned to no additive or supplementation with CE (200, 400, or 600 mg/d; n = 12 animals/treatment) for 8 wk. A 1-wk covariate period was included in both experiments. In both experiments, individual dry matter intake (DMI), milk production, milk composition, and somatic cell count were recorded daily. In experiment 1, CE was associated with an increase in DMI in both parity groups but an increase in milk production of multiparous cows only. In experiment 2, milk yield of multiparous cows was decreased at the 2 highest doses, whereas milk yield of primiparous cows was increased at the low and high doses of CE. These responses were accompanied by similar changes in DMI; therefore, CE did not affect feed efficiency. We observed no effect of CE on SCC or milk composition; however, treatment by parity interactions were detected for each of these variables that have not been described previously. Based on the results of these experiments, we conclude that a blend of cinnamaldehyde and eugenol can increase DMI and milk production in lactating dairy cows. In addition, environmental factors appear to influence the response to CE, including dose and parity, and these should be explored further.     

Residual feed intake in peripartal dairy cows is associated with differences in milk fat yield,ruminal bacteria,biopolymer hydrolyzing enzymes,and circulating biomarkers of immunometabolism

Residual feed intake (RFI) measures feed efficiency independent of milk production level, and is typically calculated using data past peak lactation. In the current study, we retrospectively classified multiparous Holstein cows (n = 320) from 5 of our published studies into most feed-efficient (M-eff) or least feed-efficient (L-eff) groups using performance data collected during the peripartal period. Objectives were to assess differences in profiles of plasma biomarkers of immunometabolism, relative abundance of key ruminal bacteria, and activities of digestive enzymes in ruminal digesta between M-eff and L-eff cows. Individual data from cows with ad libitum access to a total mixed ration from d ?28 to d +28 relative to calving were used. A linear regression model including dry matter intake (DMI), energy-corrected milk (ECM), changes in body weight (BW), and metabolic BW was used to classify cows based on RFI divergence into L-eff (n = 158) and M-eff (n = 162). Plasma collected from the coccygeal vessel at various times around parturition (L-eff = 60 cows; M-eff = 47 cows) was used for analyses of 30 biomarkers of immunometabolism. Ruminal digesta collected via esophageal tube (L-eff = 19 cows; M-eff = 29 cows) was used for DNA extraction and assessment of relative abundance (%) of 17 major bacteria using real-time PCR, as well as activity of cellulase, amylase, xylanase, and protease. The UNIVARIATE procedure of SAS 9.4 (SAS Institute Inc.) was used for analyses of RFI coefficients. The MIXED procedure of SAS was used for repeated measures analysis of performance, milk yield and composition, plasma immunometabolic biomarkers, ruminal bacteria, and enzyme activities. The M-eff cows consumed less DMI during the peripartal period compared with L-eff cows. In the larger cohort of cows, despite greater overall BW for M-eff cows especially in the prepartum (788 vs. 764 kg), no difference in body condition score was detected due to RFI or the interaction of RFI × time. Milk fat content (4.14 vs. 3.75 ± 0.06%) and milk fat yield (1.75 vs. 1.62 ± 0.04 kg) were greater in M-eff cows. Although cumulative ECM yield did not differ due to RFI (1,138 vs. 1,091 ± 21 kg), an RFI × time interaction due to greater ECM yield was found in M-eff cows. Among plasma biomarkers studied, concentrations of nonesterified fatty acids, β-hydroxybutyrate, bilirubin, ceruloplasmin, haptoglobin, myeloperoxidase, and reactive oxygen metabolites were overall greater, and glucose, paraoxonase, and IL-6 were lower in M-eff compared with L-eff cows. Among bacteria studied, abundance of Ruminobacter amylophilus and Prevotella ruminicola were more than 2-fold greater in M-eff cows. Despite lower ruminal activity of amylase in M-eff cows in the prepartum, regardless of RFI, we observed a marked linear increase after calving in amylase, cellulase, and xylanase activities. Protease activity did not differ due to RFI, time, or RFI × time. Despite greater concentrations of biomarkers reflective of negative energy balance and inflammation, higher feed efficiency measured as RFI in peripartal dairy cows might be associated with shifts in ruminal bacteria and amylase enzyme activity. Further studies could help address such factors, including the roles of the liver and the mammary gland.     

Genetic and genomic dissection of dry matter intake at different lactation stages in primiparous Holstein cows

Dry matter intake (DMI) and feed efficiency are economically relevant traits. Simultaneous selection for low DMI and high milk yield might improve feed efficiency, but bears the risk of aggravating the negative energy balance and related health problems in early lactation. Lactation stage-specific selection might provide a possibility to optimize the trajectory of DMI across days in milk (DIM), but requires in-depth knowledge about genetic parameters within and across lactation stages. Within the current study, daily heritabilities and genetic correlations between DMI records from different lactation stages were estimated using random regression models based on 910 primiparous Holstein cows. The heritability estimates from DIM 11 to 180 follow a slightly parabolic curve varying from 0.26 (DIM 121) to 0.37 (DIM 11 and 180). Genetic correlations estimated between DIM 11, 30, 80, 130, and 180 were all positive, ranging from 0.29 (DIM 11 and 180) to 0.97 (DIM 11 and 30; i.e., the correlations are inversely related to the length of the interval between compared DIM). Deregressed estimated breeding values for the same lactation days were used as phenotypes in sequential genome-wide association studies using 681 cows drawn from the study population and genotyped for the Illumina SNP50 BeadChip (Illumina Inc., San Diego, CA). A total of 21 SNP on 10 chromosomes exceeded the chromosome-wise significance threshold for at least 1 analyzed DIM, pointing to some interesting candidate genes directly involved in the regulation of feed intake. Association signals were restricted to certain lactation stages, thus supporting the genetic correlations. Partitioning the explained variance onto chromosomes revealed a large contribution of Bos taurus autosome 7 not harboring any associated marker in the current study. The results contribute to the knowledge about the genetic architecture of the complex phenotype DMI and might provide valuable information for future selection efforts.     

Effect of prepartum anionic supplementation on periparturient feed intake, health, and milk production

Our objectives were to determine if dietary cation-anion difference (DCAD) and source of anions influence periparturient feed intake and milk production of dairy cattle during the transition period. Diets differed in DCAD (cationic or anionic) and anionic supplement. The 4 diets used prepartum were (1) control [DCAD +20 mEq/100 g of dry matter (DM)], (2) Bio-Chlor (DCAD −12 mEq/100 g of DM; Church & Dwight Co. Inc., Princeton, NJ), (3) Fermenten (DCAD −10 mEq/100 g of DM; Church & Dwight Co. Inc.), and (4) salts (DCAD −10 mEq/100 g of DM). Urine pH was lower for cows that consumed an anionic diet prepartum compared with control. Prepartum diet had no effect on prepartum dry matter intake (DMI) of multiparous or primiparous cows. Postpartum DMI and milk yield for multiparous cows fed anionic diets prepartum were greater compared with those fed the control diet. Postpartum DMI and milk yield of primiparous cows were similar for prepartum diets. Feeding prepartum anionic diets did not affect plasma Ca at or near calving. However, cows fed anionic diets began their decline in plasma Ca later than control cows. Postpartum β-hydroxybutyrate and nonesterified fatty acids were lower for primiparous cows fed prepartum anionic diets compared with those fed the control diet. Prepartum and postpartum plasma glucose concentrations were not affected by prepartum diet for all cows. Liver triglyceride differed for parity by day. Parities were similar at 21 d prepartum, but at 0 d and 21 d postpartum, levels were greater for multiparous cows. Results indicate that decreasing the DCAD of the diet during the prepartum period can increase postpartum DMI and milk production of multiparous cows without negatively affecting performance of primiparous cows.     

Relationships between body condition score change,prior mid-lactation phenotypic residual feed intake,and hyperketonemia onset in transition dairy cows

Extensive efforts have been made to identify more feed-efficient dairy cows, yet it is unclear how selection for feed efficiency will influence metabolic health. The objectives of this research were to determine the relationships between residual feed intake (RFI), a measure of feed efficiency, body condition score (BCS) change, and hyperketonemia (HYK) incidence. Blood and milk samples were collected twice weekly from cows 5 to 18 d postcalving for a total of 4 samples. Hyperketonemia was diagnosed at a blood β-hydroxybutyrate (BHB) ≥1.2 mmol/L and cows were treated upon diagnosis. Dry period, calving, and final blood sampling BCS was recorded. Prior mid-lactation production, body weight, body weight change, and dry matter intake (DMI) data were used to determine RFI phenotype, calculated as the difference between observed DMI and predicted DMI. The maximum BHB concentration (BHB_max) for each cow was used to group cows into HYK or not hyperketonemic. Lactation number, BCS, and RFI data were analyzed with linear and quadratic orthogonal contrasts. Of the 570 cows sampled, 19.7% were diagnosed with HYK. The first positive HYK test occurred at 9 ± 0.9 d postpartum and the average BHB concentration at the first positive HYK test was 1.53 ± 0.14 mmol/L. In the first 30 d postpartum, HYK-positive cows had increased milk yield and fat concentration, decreased milk protein concentration, and decreased somatic cell count. Cows with a dry BCS ≥4.0, or that lost 1 or more BCS unit across the transition to lactation period, had greater BHB_max than cows with lower BCS. Prior-lactation RFI did not alter BHB_max. Avoiding over conditioning of dry cows and subsequent excessive fat mobilization during the transition period may decrease HYK incidence; however, RFI during a prior lactation does not appear to be associated with HYK onset.     

Blood plasma traits associated with genetic merit for feed utilization in Holstein cows

The objective of this study was to evaluate the potential of selection for feed utilization on associated blood plasma metabolite and hormone traits. Dry matter intake (DMI) was recorded in 970 Holsteins from 11 commercial farms in Pennsylvania and used to derive dry matter efficiency (DME; fat-corrected milk yield/DMI), crude protein efficiency (CPE; protein yield/crude protein intake), and residual feed intake (RFI, defined as actual feed intake minus expected feed intake for maintenance and milk production, based on calculation of DMI adjusted for yield, body weight, and body condition score). Estimated breeding values for the 4 feed utilization traits (DMI, DME, CPE, and RFI), yield traits, body traits, and days open were standardized according to their respective genetic standard deviations. Up to 631 blood samples from 393 cows from 0 to 60 d in milk (DIM) were evaluated for blood plasma concentrations of glucose, nonesterified fatty acids (NEFA), β-hydroxybutyrate (BHB), creatinine, urea, growth hormone (GH), 3,5,3′-triiodothyronine (T3), and other parameters. Blood plasma traits were regressed on DIM, lactation number, herd, and standardized genetic merit. Cows with higher genetic merit for yield had significantly higher concentrations of GH, NEFA (milk and protein yield), and BHB (fat yield) from 31 to 60 DIM, but lower concentrations of glucose from 0 to 30 DIM, and T3 (milk yield, 0–60 DIM). The high GH–low glucose–low T3 concentration pattern was further accentuated for cows with genetic merit for enhanced feed efficiency (higher DME and lower RFI). Cows with a genetic tendency to be thin (low body condition score) also had elevated GH concentrations, but lower blood glucose, creatinine, and T3 concentrations. Those characteristics associated with enhanced feed efficiency (higher GH and lower glucose and T3 concentrations) were unfavorably associated with fertility, as indicated by elevated days open. Elevated NEFA and BHB concentrations were also associated with extended days open. Consideration of metabolic profiles when evaluating feed efficiency might be a method of maintaining high levels of health and reproductive fitness when selecting for feed efficiency.     

High-density genome-wide association study for residual feed intake in Holstein dairy cattle

Improving feed efficiency (FE) of dairy cattle may boost farm profitability and reduce the environmental footprint of the dairy industry. Residual feed intake (RFI), a candidate FE trait in dairy cattle, can be defined to be genetically uncorrelated with major energy sink traits (e.g., milk production, body weight) by including genomic predicted transmitting ability of such traits in genetic analyses for RFI. We examined the genetic basis of RFI through genome-wide association (GWA) analyses and post-GWA enrichment analyses and identified candidate genes and biological pathways associated with RFI in dairy cattle. Data were collected from 4,823 lactations of 3,947 Holstein cows in 9 research herds in the United States. Of these cows, 3,555 were genotyped and were imputed to a high-density list of 312,614 SNP. We used a single-step GWA method to combine information from genotyped and nongenotyped animals with phenotypes as well as their ancestors' information. The estimated genomic breeding values from a single-step genomic BLUP were back-solved to obtain the individual SNP effects for RFI. The proportion of genetic variance explained by each 5-SNP sliding window was also calculated for RFI. Our GWA analyses suggested that RFI is a highly polygenic trait regulated by many genes with small effects. The closest genes to the top SNP and sliding windows were associated with dry matter intake (DMI), RFI, energy homeostasis and energy balance regulation, digestion and metabolism of carbohydrates and proteins, immune regulation, leptin signaling, mitochondrial ATP activities, rumen development, skeletal muscle development, and spermatogenesis. The region of 40.7 to 41.5 Mb on BTA25 (UMD3.1 reference genome) was the top associated region for RFI. The closest genes to this region, CARD11 and EIF3B, were previously shown to be related to RFI of dairy cattle and FE of broilers, respectively. Another candidate region, 57.7 to 58.2 Mb on BTA18, which is associated with DMI and leptin signaling, was also associated with RFI in this study. Post-GWA enrichment analyses used a sum-based marker-set test based on 4 public annotation databases: Gene Ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, Reactome pathways, and medical subject heading (MeSH) terms. Results of these analyses were consistent with those from the top GWA signals. Across the 4 databases, GWA signals for RFI were highly enriched in the biosynthesis and metabolism of amino acids and proteins, digestion and metabolism of carbohydrates, skeletal development, mitochondrial electron transport, immunity, rumen bacteria activities, and sperm motility. Our findings offer novel insight into the genetic basis of RFI and identify candidate regions and biological pathways associated with RFI in dairy cattle.     

Dietary restriction improved feed efficiency of inefficient lactating cows

The aim of this study was to reduce voluntary dry matter intake (DMI) to increase feeding efficiency of preclassified inefficient (INE) dairy cows through restricted feeding. We studied the effects of dietary restriction on eating behavior, milk and energy-corrected milk (ECM) production, in vivo digestibility, energy balance, and measures of feed efficiency [residual feed intake (RFI) and ECM/DMI]. Before the experiment, 12 pairs of cows were classified as INE. The 2 dietary treatments consisted of ad libitum feeding versus restricted feeding of the same total mixed ration containing 36.5% roughage. Inefficient cows fed the restricted total mixed ration had a shorter eating time and lower meal and visit frequency, but a similar rate of eating, meal size, and meal duration compared with INE cows fed ad libitum. Compared with the INE cows fed ad libitum, restricted INE cows had 12.8% lower intake, their dry matter and neutral detergent fiber digestibility remained similar, and their ECM yield was 5.3% lower. Feed efficiency, measured as RFI, ECM/DMI, and net energy retained divided by digestible energy intake, was improved in the restricted INE cows as compared with the ad libitum cows. Our results show that moderate DMI restriction has the potential to improve feed efficiency of preclassified INE cows.     

Incorporating heifer feed efficiency in the Australian selection index using genomic selection

The economic benefit of expanding the Australian Profit Ranking (APR) index to include residual feed intake (RFI) was evaluated using a multitrait selection index. This required the estimation of genetic parameters for RFI and genetic correlations using single nucleotide polymorphism data (genomic) correlations with other traits. Heritabilities of RFI, dry matter intake (DMI), and all the traits in the APR (milk, fat, and protein yields; somatic cell count; fertility; survival; milking speed; and temperament), and genomic correlations between these traits were estimated using a Bayesian framework, using data from 843 growing Holstein heifers with phenotypes for DMI and RFI, and bulls with records for the other traits. Heritability estimates of DMI and RFI were 0.44 and 0.33, respectively, and the genomic correlation between them was 0.03 and nonsignificant. The genomic correlations between the feed-efficiency traits and milk yield traits were also close to zero, ranging between −0.11 and 0.10. Positive genomic correlations were found for DMI with stature (0.16) and with overall type (0.14), suggesting that taller cows eat more as heifers. One issue was that the genomic correlation estimates for RFI with calving interval (ClvI) and with body condition score were both unfavorable (−0.13 and 0.71 respectively), suggesting an antagonism between feed efficiency and fertility. However, because of the relatively small numbers of animals in this study, a large 95% probability interval existed for the genomic correlation between RFI and ClvI (−0.66, 0.36). Given these parameters, and a genetic correlation between heifer and lactating cow RFI of 0.67, inclusion of RFI in the APR index would reduce RFI by 1.76 kg/cow per year. Including RFI in the APR would result in the national Australian Holstein herd consuming 1.73 × 10⁶ kg less feed, which is worth 0.55 million Australian dollars (A$) per year and is 3% greater than is currently possible to achieve. Other traits contributing to profitability, such as milk production and fertility, will also improve through selection on this index; for example, ClvI would be reduced by 0.53d/cow per year, which is 96% of the gain for this trait that is achieved without RFI in the APR.     

Effects of an exogenous enzyme preparation extracted from a mixed culture of Aspergillus spp. on lactational performance,metabolism, and digestibility in primiparous and multiparous cows

The objective of this study was to investigate the effects of an exogenous enzyme preparation from Aspergillus oryzae and Aspergillus niger on lactational performance of dairy cows. Forty-eight Holstein cows (32 primiparous and 16 multiparous) averaging (± SD) 36.3 ± 8.7 kg/d milk yield and 141 ± 52 d in milk were enrolled in a 10-wk randomized complete block design experiment (total of 24 blocks) and assigned to 1 of 2 treatments: basal diet, no enzyme supplementation (CON) or the basal diet supplemented with 4.2 g/kg dry matter intake (DMI) of an exogenous enzyme preparation containing amylolytic and fibrolytic activities (ENZ). After a 2-wk covariate period, premixes with the enzyme preparation or control were top-dressed daily by mixing with approximately 500 g of total mixed ration. Production data were collected daily and averaged by week. Milk samples were collected every other week, and milk composition was averaged by week. Blood, fecal, and urine samples were collected over 2 consecutive days at 0, 4, 8, 12, and 36 h after feeding during the last week of the experiment. Compared with CON, cows fed ENZ tended to increase DMI and had increased milk concentrations of true protein, lactose, and other solids. Milk fat content tended to be higher in CON cows. A treatment × parity interaction was found for some of the production variables. Primiparous cows receiving ENZ had greater yields of milk, energy-corrected milk, milk true protein, and lactose compared with CON primiparous cows; these production variables did not differ between treatments for multiparous cows. Intake and total-tract digestibility of nutrients did not differ between treatments. Concentrations of blood glucose and total fatty acids were not affected by ENZ supplementation, but β-hydroxybutyrate concentration tended to be greater in ENZ cows. Overall, the exogenous enzyme preparation used in this study increased milk protein and lactose concentrations in all cows, and milk production in primiparous but not multiparous cows. The differential production response between primiparous and multiparous cows was likely a result of a greater increase in DMI with ENZ supplementation in the younger animals.     

Estimates of genetic parameters for feeding behavior traits and their associations with feed efficiency in Holstein cows

Residual feed intake (RFI) is commonly used to measure feed efficiency but individual intake recording systems are needed. Feeding behavior may be used as an indicator trait for feed efficiency using less expensive precision livestock farming technologies. Our goal was to estimate genetic parameters for feeding behavior and the genetic correlations with feed efficiency in Holstein cows. Data consisted of 75,877 daily feeding behavior records of 1,328 mid-lactation Holstein cows in 31 experiments conducted from 2009 to 2020 with an automated intake recording system. Feeding behavior traits included number of feeder visits per day, number of meals per day, duration of each feeder visit, duration of each meal, total duration of feeder visits, intake per visit, intake per meal [kg of dry matter (DM)], feeding rate per visit, and feeding rate per meal (kg of DM per min). The meal criterion was estimated as 26.4 min, which means that any pair of feeder visits separated by less than 26.4 min were considered part of the same meal. The statistical model included lactation and days in milk as fixed effects, and experiment-treatment, animal, and permanent environment as random effects. Genetic parameters for feeding behavior traits were estimated using daily records and weekly averages. Estimates of heritability for daily feeding behavior traits ranged from 0.09 ± 0.02 (number of meals; mean ± standard error) to 0.23 ± 0.03 (feeding rate per meal), with repeatability estimates ranging from 0.23 ± 0.01 (number of meals) to 0.52 ± 0.02 (number of feeder visits). Estimates of heritability for weekly averages of feeding behavior traits ranged from 0.19 ± 0.04 (number of meals) to 0.32 ± 0.04 (feeding rate per visit), with repeatability estimates ranging from 0.46 ± 0.02 (duration of each meal) to 0.62 ± 0.02 (feeding rate per visit and per meal). Most of the feeding behavior measures were strongly genetically correlated, showing that with more visits or meals per day, cows spend less time in each feeder visit or meal with lower intake per visit or meal. Weekly averages for feeding behavior traits were analyzed jointly with RFI and its components. Number of meals was genetically correlated with milk energy (0.48), metabolic body weight (?0.27), and RFI (0.19). Duration of each feeder visit and meal were genetically correlated with milk energy (0.43 and 0.44, respectively). Total duration of feeder visits per day was genetically correlated with DM intake (0.29), milk energy (0.62), metabolic body weight (?0.37), and RFI (0.20). Intake per visit and meal were genetically correlated with DM intake (0.63 and 0.87), milk energy (0.47 and 0.69), metabolic body weight (0.47 and 0.68), and RFI (0.31 and 0.65). Feeding rate was genetically correlated with DM intake (0.69), metabolic body weight (0.67), RFI (0.47), and milk energy (0.21). We conclude that measures of feeding behavior could be useful indicators of dairy cow feed efficiency, and individual cows that eat at a slower rate may be more feed efficient.     

Assessing milk response to different combinations of branched-chain volatile fatty acids and valerate in Jersey cows

Some cellulolytic bacteria require 1 or more branched-chain volatile fatty acids (BCVFA) for the synthesis of branched-chain AA and branched-chain long-chain fatty acids because they are not able to uptake branched-chain AA or lack 1 or more enzymes to synthesize branched-chain AA de novo. Supplemental BCVFA and valerate were included previously as a feed additive that was later removed from the market; these older studies and more current studies have noted improvements in neutral detergent fiber digestibility and milk efficiency. However, most studies provided a single BCVFA or else isobutyrate (IB), 2-methylbutyrate (MB), isovalerate, and valerate altogether without exploring optimal combinations. Our objective was to determine a combination of isoacids that is optimal for milk production. Sixty (28 primiparous and 32 multiparous) lactating Jersey cows (106 ± 54 days in milk) were blocked and assigned randomly to either a control (CON) treatment without any isoacids, MB [12.3 mmol/kg dry matter (DM)], MB + IB (7.7 and 12.6 mmol/kg DM of MB and IB, respectively), or all 4 isoacids (6.2, 7.3, 4.2, and 5.1 mmol/kg DM of MB, IB, isovalerate, and valerate, respectively). Cattle were fed the CON treatment for a 2-wk period, then were assigned randomly within a block to treatments for 8 wk (n = 15). There was a trend for an interaction of supplement and parity for milk components. There were no differences in components for primiparous cows, whereas MB + IB tended to increase protein concentration by 0.04 and 0.08 percentage units in multiparous cows compared with the CON and MB treatments, respectively. Feeding MB + IB increased fat concentration by 0.23 to 0.31 percentage units compared with all other treatments in multiparous cows. Milk yield and dry matter intake (DMI) did not change with treatment. Treatment interacted with week for milk net energy for lactation/DMI; MB + IB tended to increase milk net energy of lactation/DMI by 0.10 Mcal/kg compared with MB and approached a trend for CON, mainly during the early weeks of the treatment period, whereas differences decreased during the last 2 wk of the treatment period. Cows fed MB had the highest 15:0 anteiso fatty acids in the total milk fatty acid profile, which was greater than that for CON or MB + IB cows, but not cows supplemented with isoacids. Cows fed MB alone had the numerically lowest milk net energy for lactation/DMI. The combination of MB + IB appeared optimal for increasing feed efficiency in our study and was not at the expense of average daily gain. Further research is needed for evaluating how potential changes in supplemental isoacid dosage should vary under differing dietary conditions.     

Three-breed rotational crossbreds of Montbéliarde,Viking Red,and Holstein compared with Holstein cows for dry matter intake,body traits,and production

Rotational crossbred cows of the Montbéliarde, Viking Red, and Holstein (HO) breeds (CB) were compared with HO cows for dry matter intake (DMI), body weight (BW), cow height, body condition score (BCS), and production during the first 150 d of first, second, and third lactations. Primiparous and multiparous CB (n = 63 and 43, respectively) and HO (n = 60 and 37, respectively) cows calved from September 2014 to June 2017. Cows were fed the same total mixed ration twice daily, with refusals weighed once daily. The BW was recorded twice weekly, and height at the withers and the hips was recorded monthly. The BCS was evaluated weekly. The fat plus protein production from 4 to 150 d in milk was calculated from monthly test days using best prediction. Primiparous and multiparous cows were analyzed separately. Statistical analysis for primiparous cows included the fixed effects of year of calving and breed group, and the analysis for multiparous cows included the fixed effect of breed group and the repeated effect of cow nested within breed group. Primiparous CB cows (2,807 kg) had lower mean DMI than HO cows (2,948 kg) from 4 to 150 d in milk of first lactation. Mean BW was not different for the CB (562 kg) and HO (556 kg) cows, but primiparous CB cows had mean wither height that was 4.0 cm shorter and mean hip height that was 2.0 cm shorter than that of HO cows. Primiparous CB cows (3.46) had higher mean BCS compared with HO cows (3.20). Mean fat plus protein production did not differ for the primiparous CB and HO cows (331 vs. 329 kg, respectively). Multiparous CB cows (3,360 kg) also had lower mean DMI than HO cows (3,592 kg) and did not differ (636 kg) from HO cows (644 kg) for mean BW. The CB cows had mean wither height that was 3.5 cm shorter than that of HO cows, but mean hip height did not differ for multiparous CB (145.2 cm) and HO (146.4 cm) cows. Mean BCS was higher for multiparous CB cows (3.25) than for HO cows (3.06), and mean fat plus protein production was not different for multiparous CB (445 kg) and HO (441 kg) cows. The lower DMI of the CB cows than HO cows resulted in less feed cost without loss of revenue from fat plus protein production.     

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.