Short communication: Validation of genomic breeding value predictions for feed intake and feed efficiency traits

Validating genomic prediction equations in independent populations is an important part of evaluating genomic selection. Published genomic predictions from 2 studies on (1) residual feed intake and (2) dry matter intake (DMI) were validated in a cohort of 78 multiparous Holsteins from Australia. The mean realized accuracy of genomic prediction for residual feed intake was 0.27 when the reference population included phenotypes from 939 New Zealand and 843 Australian growing heifers (aged 5–8 mo) genotyped on high density (770k) single nucleotide polymorphism chips. The 90% bootstrapped confidence interval of this estimate was between 0.16 and 0.36. The mean realized accuracy was slightly lower (0.25) when the reference population comprised only Australian growing heifers. Higher realized accuracies were achieved for DMI in the same validation population and using a multicountry model that included 958 lactating cows from the Netherlands and United Kingdom in addition to 843 growing heifers from Australia. The multicountry analysis for DMI generated 3 sets of genomic predictions for validation animals, one on each country scale. The highest mean accuracy (0.72) was obtained when the genomic breeding values were expressed on the Dutch scale. Although the validation population used in this study was small (n = 78), the results illustrate that genomic selection for DMI and residual feed intake is feasible. Multicountry collaboration in the area of dairy cow feed efficiency is the evident pathway to achieving reasonable genomic prediction accuracies for these valuable traits.     

Economic values of production and functional traits,including residual feed intake,in Finnish milk production

Improving the feed efficiency of dairy cattle has a substantial effect on the economic efficiency and on the reduction of harmful environmental effects of dairy production through lower feeding costs and emissions from dairy farming. To assess the economic importance of feed efficiency in the breeding goal for dairy cattle, the economic values for the current breeding goal traits and the additional feed efficiency traits for Finnish Ayrshire cattle under production circumstances in 2011 were determined. The derivation of economic values was based on a bioeconomic model in which the profit of the production system was calculated, using the generated steady state herd structure. Considering beef production from dairy farms, 2 marketing strategies for surplus calves were investigated: (A) surplus calves were sold at a young age and (B) surplus calves were fattened on dairy farms. Both marketing strategies were unprofitable when subsidies were not included in the revenues. When subsidies were taken into account, a positive profitability was observed in both marketing strategies. The marginal economic values for residual feed intake (RFI) of breeding heifers and cows were −25.5 and −55.8 €/kg of dry matter per day per cow and year, respectively. The marginal economic value for RFI of animals in fattening was −29.5 €/kg of dry matter per day per cow and year. To compare the economic importance among traits, the standardized economic weight of each trait was calculated as the product of the marginal economic value and the genetic standard deviation; the standardized economic weight expressed as a percentage of the sum of all standardized economic weights was called relative economic weight. When not accounting for subsidies, the highest relative economic weight was found for 305-d milk yield (34% in strategy A and 29% in strategy B), which was followed by protein percentage (13% in strategy A and 11% in strategy B). The third most important traits were calving interval (9%) and mature weight of cows (11%) in strategy A and B, respectively. The sums of the relative economic weights over categories for RFI were 6 and 7% in strategy A and B, respectively. Under production conditions in 2011, the relative economic weights for the studied feed efficiency traits were low. However, it is possible that the relative importance of feed efficiency traits in the breeding goal will increase in the future due to increasing requirements to mitigate the environmental impact of milk production.     

Reliability of breeding values for feed intake and feed efficiency traits in dairy cattle: When dry matter intake recordings are sparse under different scenarios

Currently, routine recordings of dry matter intake (DMI) in commercial herds are practically nonexistent. Recording DMI from commercial herds is a prerequisite for the inclusion of feed efficiency (FE) traits in dairy cattle breeding goals. To develop future on-farm phenotyping strategies, recording strategies that are low cost and less demanding logistically and that give relatively accurate estimates of the animal's genetic merit are therefore needed. The objectives of this study were (1) to estimate genetic parameters for daily DMI and FE traits and use the estimated parameters to simulate daily DMI phenotypes under different DMI recording scenarios (SCN) and (2) to use the simulated data to estimate for different scenarios the associated reliability of estimated breeding value and accuracies of genomic prediction for varying sizes of reference populations. Five on-farm daily DMI recording scenarios were simulated: once weekly (SCN1), once monthly (SCN2), every 2 mo (SCN3), every 3 mo (SCN4), and every 4 mo (SCN5). To estimate reliability of estimated breeding values, DMI and FE observations and true breeding values were simulated based on variance components estimated for daily observations of Nordic Red cows. To emulate realistic on-farm recording, 5 data set replicates, each with 36,037 DMI and FE records, were simulated for real pedigree and data structure of 789 Holstein cows. Observations for the 5 DMI recording scenarios were generated by discarding data in a step-wise manner from the full simulated data per the scenario's definitions. For each of these scenarios, reliabilities were calculated as correlation between the true and estimated breeding values. Variance components and genetic parameters were estimated for daily DMI, residual feed intake (RFI), and energy conversion efficiency (ECE) fitting the random regression model. Data for variance components were from 227 primiparous Nordic Red dairy cows covering 8 to 280 d in milk. Lactation-wise heritability for DMI, RFI, and ECE was 0.33, 0.12, and 0.32, respectively, and daily heritability estimates during lactation ranged from 0.18 to 0.45, 0.08 to 0.32, and 0.08 to 0.45 for DMI, RFI, and ECE, respectively. Genetic correlations for DMI between different stages of lactation ranged from ?0.50 to 0.99. The comparison of different on-farm DMI recording scenarios indicated that adopting a less-frequent recording scenario (SCN3) gave a similar level of accuracy as SCN1 when 17 more daughters are recorded per sire over the 46 needed for SCN1. Such a strategy is less demanding logistically and is low cost because fewer observations need to be collected per animal. The accuracy of genomic predictions associated with the 5 recording scenarios indicated that setting up a relatively larger reference population and adopting a less-frequent DMI sampling scenario (e.g., SCN3) is promising. When the same reference population size was considered, the genomic prediction accuracy of SCN3 was only 5.0 to 7.0 percentage points lower than that for the most expensive DMI recording strategy (SCN1). We concluded that DMI recording strategies that are sparse in terms of records per cow but with slightly more cows recorded per sire are advantageous both in genomic selection and in traditional progeny testing schemes when accuracy, logistics, and cost implications are considered.     

Effect of solid feed level and types of roughage on passage kinetics of milk replacer,concentrate, and roughage in veal calves

This study aimed (1) to provide estimates of total mean retention times of milk replacer (MR), concentrates, and roughage in veal calves fed a mixed diet; (2) to determine the effect of level and type of solid feed (SF) on passage kinetics of MR, concentrates, and roughages in veal calves; and (3) to compare passage kinetics in veal calves using the fecal excretion curves of indigestible markers and a noninvasive ¹³C tracer breath test approach to determine whether the latter technique can serve as an alternative. At the start of the trial, 48 Holstein-Friesian calves (6 wk of age; 68 ± 7.7 kg of body weight; BW) were assigned to 1 of 4 dietary treatments (for statistical analysis, only 39 calf observations were used). Three treatments contained chopped wheat straw as roughage in the SF mixture in a concentrate:roughage ratio of 90:10 (dry matter basis). The SF level was 20 g/kg of metabolic BW per day (low straw), 30 g/kg of metabolic BW per day (middle straw), or 40 g/kg of metabolic BW per day (high straw). The fourth treatment (high hay) contained long perennial ryegrass hay as roughage in the SF mixture in a concentrate:roughage ratio of 70:30 (dry matter basis, at 40 g/kg of metabolic BW per day). The quantity of MR was fixed for the high straw treatment, whereas the amount of MR for the other treatments during the adaptation period was adjusted based on a pair gain strategy (i.e., exchanging ration components but keeping similar net energy). At the end of the adaptation period, calves ranged from 12 to 15 wk of age with an average BW of 123 ± 8.6 kg. Passage kinetics of concentrates were estimated by measuring ¹³C enrichment excess of CO₂ in breath from a pulsed-dose of [1-¹³C]octanoate. Passage kinetics of roughage, concentrates, and MR were also estimated using fecal excretion curves obtained after ingestion of chromium-mordanted roughage, Yb₂O₃, and Co-EDTA, respectively. We conclude that [1-¹³C]octanoate cannot serve as a measure for oro-duodenal transit of concentrates because of unrealistic estimates. Based on the fecal excretion curves, we concluded that the total mean retention time of MR (i.e., time to peak; the moment that the excretion curve reaches peak concentration) was, on average, 12.4 h, and that the passage kinetics of MR was not affected by the level or type of SF. The mean retention time of concentrates was shorter (21.4 h) than that of both straw (59.1 h) and hay (36.8 h), and was not affected by the level or type of SF. Also, the mean retention time of the slowest compartment (i.e., the rumen) was shorter for concentrates (39.6 h) than that of straw (110.0 h) and hay (59.2 h). Contrary, the passage of roughage was affected by level and type of SF. Long hay increased time to peak by 22.3 h and decreased ruminal mean retention time by 50.8 h relative to chopped straw, indicating that the passage rate of long hay is faster than that of chopped straw. We conclude that the level and type of SF only affects the passage kinetics of roughage and not that of MR and concentrates.     

Holstein-Friesian calves selected for divergence in residual feed intake during growth exhibited significant but reduced residual feed intake divergence in their first lactation

Residual feed intake (RFI), as a measure of feed conversion during growth, was estimated for around 2,000 growing Holstein-Friesian heifer calves aged 6 to 9 mo in New Zealand and Australia, and individuals from the most and least efficient deciles (low and high RFI phenotypes) were retained. These animals (78 New Zealand cows, 105 Australian cows) were reevaluated during their first lactation to determine if divergence for RFI observed during growth was maintained during lactation. Mean daily body weight (BW) gain during assessment as calves had been 0.86 and 1.15 kg for the respective countries, and the divergence in RFI between most and least efficient deciles for growth was 21% (1.39 and 1.42 kg of dry matter, for New Zealand and Australia, respectively). At the commencement of evaluation during lactation, the cows were aged 26 to 29 mo. All were fed alfalfa and grass cubes; it was the sole diet in New Zealand, whereas 6 kg of crushed wheat/d was also fed in Australia. Measurements of RFI during lactation occurred for 34 to 37 d with measurements of milk production (daily), milk composition (2 to 3 times per week), BW and BW change (1 to 3 times per week), as well as body condition score (BCS). Daily milk production averaged 13.8 kg for New Zealand cows and 20.0 kg in Australia. No statistically significant differences were observed between calf RFI decile groups for dry matter intake, milk production, BW change, or BCS; however a significant difference was noted between groups for lactating RFI. Residual feed intake was about 3% lower for lactating cows identified as most efficient as growing calves, and no negative effects on production were observed. These results support the hypothesis that calves divergent for RFI during growth are also divergent for RFI when lactating. The causes for this reduced divergence need to be investigated to ensure that genetic selection programs based on low RFI (better efficiency) are robust.     

Different protein sources in concentrate feed for dairy cows affect cheese-making properties and yield

Soybean meal (SBM) is a commonly used protein source in feed. Yeast microbial protein could be used as a substitute for SBM, but its effect on cheese-making properties and yield is not known. Norwegian Red dairy cows (n = 48) in early or mid lactation were divided in 3 groups and fed a ration consisting of grass silage and concentrate, where the concentrates were barley based but with different additional protein sources. These were: completely barley based with no additional protein source (BAR), additional protein from SBM, or additional protein from yeast (Cyberlindnera jadinii; YEA). The SBM and YEA concentrates had a higher protein content than the barley concentrate. Four batches of cheese were made from pooled milk from each of the 3 groups of dairy cows. Milk samples were collected 5 times during the experiment. Milk from cows fed BAR concentrate showed inferior cheese-making properties (lower casein content, longer renneting time, lower content of phosphorus, and lower cheese yield) compared with SBM and YEA concentrates. Overall, SBM or YEA bulk milk had similar cheese-making properties, but when investigating individual milk samples, YEA milk showed better coagulation properties.     

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.     

Strategies for implementing genomic selection for feed efficiency in dairy cattle breeding schemes

Alternative genomic selection and traditional BLUP breeding schemes were compared for the genetic improvement of feed efficiency in simulated Norwegian Red dairy cattle populations. The change in genetic gain over time and achievable selection accuracy were studied for milk yield and residual feed intake, as a measure of feed efficiency. When including feed efficiency in genomic BLUP schemes, it was possible to achieve high selection accuracies for genomic selection, and all genomic BLUP schemes gave better genetic gain for feed efficiency than BLUP using a pedigree relationship matrix. However, introducing a second trait in the breeding goal caused a reduction in the genetic gain for milk yield. When using contracted test herds with genotyped and feed efficiency recorded cows as a reference population, adding an additional 4,000 new heifers per year to the reference population gave accuracies that were comparable to a male reference population that used progeny testing with 250 daughters per sire. When the test herd consisted of 500 or 1,000 cows, lower genetic gain was found than using progeny test records to update the reference population. It was concluded that to improve difficult to record traits, the use of contracted test herds that had additional recording (e.g., measurements required to calculate feed efficiency) is a viable option, possibly through international collaborations.     

Defining the optimal period length and stage of growth or lactation to estimate residual feed intake in dairy cows

Residual feed intake (RFI) is an estimate of animal feed efficiency, calculated as the difference between observed and expected feed intake. Expected intake typically is derived from a multiple regression model of dry matter intake on energy sinks, including maintenance and growth in growing animals, or maintenance, gain in body reserves, and milk production in lactating animals. The best period during the production cycle of a dairy cow to estimate RFI is not clear. Here, we characterized RFI in growing Holstein heifers (RFI_Growth; ∼10 to 14 mo of age; n = 226) and cows throughout a 305-d lactation (RFI_Lac-Full; n = 118). The goals were to characterize relationships between RFI estimated at different production stages of the dairy cow; determine effects of selection for efficiency during growth on subsequent lactation and feed efficiency; and identify the most desirable testing scheme for RFI_Lac-Full. For RFI_Growth, intake was predicted from multiple linear regression of metabolizable energy (ME) intake on mid-test body weight (BW)^0.75 and average daily gain (ADG). For RFI_Lac-Full, predicted intake was based on regression of BW^0.75, ADG, and energy-corrected milk yield. Mean energy intake of the least and most efficient growing heifers (±0.5 standard deviations from mean RFI_Growth of 0) differed by 3.01 Mcal of ME/d, but the groups showed no difference in mid-test BW or ADG. Phenotypic correlation between RFI_Growth and RFI of heifers estimated in the first 100 d in milk (RFI_Lac100DIM; n = 130) was 0.37. Ranking of these heifers as least (mean + 0.5 standard deviations), middle, or most efficient (mean – 0.5 standard deviations) based on RFI_Growth resulted in 43% maintaining the same ranking by RFI_Lac100DIM. On average, the most efficient heifers ate 3.27 Mcal of ME/d less during the first 100 DIM than the least efficient heifers, but exhibited no differences in average energy-corrected milk yield, ADG, or BW. The correlation between RFI_Lac100DIM and RFI_Lac-Full was 0.72. Thus, RFI_Growth may serve as an indicator trait for RFI during lactation, and selection for heifers exhibiting low RFI_Growth should improve overall herd feed efficiency during lactation. Correlation analysis between RFI_Lac-Full (10 to 305 DIM) and subperiod estimates of RFI during lactation indicated a test period of 64 to 70 d in duration occurring between 150 to 220 DIM provided a reliable approximation (r ≥ 0.90) of RFI_Lac-Full among the test periods evaluated.     

Relationship between residual feed intake and digestibility for lactating Holstein cows fed high and low starch diets

We determined if differences in digestibility among cows explained variation in residual feed intake (RFI) in 4 crossover design experiments. Lactating Holstein cows (n = 109; 120 ± 30 d in milk; mean ± SD) were fed diets high (HS) or low (LS) in starch. The HS diets were 30% (±1.8%) starch and 27% (±1.2%) neutral detergent fiber (NDF); LS diets were 14% (±2.2%) starch and 40% (±5.3%) NDF. Each experiment consisted of two 28-d treatment periods, with apparent total-tract digestibility measured using indigestible NDF as an internal marker during the last 5 d of each period. Individual cow dry matter (DM) intake and milk yield were recorded daily, body weight was measured 3 to 5 times per week, and milk components were analyzed 2 d/wk. Individual DM intake was regressed on milk energy output, metabolic body weight, body energy gain, and fixed effects of parity, experiment, cohort (a group of cows that received treatments in the same sequence) nested within experiment, and diet nested within cohort and experiment, with the residual being RFI. High RFI cows ate more than expected and were deemed less efficient. Residual feed intake correlated negatively with digestibility of starch for both HS (r = ?0.31) and LS (r = ?0.23) diets, and with digestibilities of DM (r = ?0.30) and NDF (r = ?0.23) for LS diets but was not correlated with DM or NDF digestibility for HS diets. For each cohort within an experiment, cows were classified as high RFI (HRFI; >0.5 SD), medium RFI (MRFI; ±0.5 SD), and low RFI (LRFI; <?0.5 SD). Digestibility of DM was similar (~66%) among HRFI and LRFI for HS diets but greater for LRFI when fed LS diets (64 vs. 62%). For LS diets, digestibility of DM could account for up to 31% of the differences among HRFI and LRFI for apparent diet energy density, as determined from individual cow performance, indicating that digestibility explains some of the between-animal differences for the ability to convert gross energy into net energy. Some of the differences in digestibility between HRFI and LRFI were expected because cows with high RFI eat at a greater multiple of maintenance, and greater intake is associated with increased passage rate and digestibility depression. Based on these data, we conclude that a cow’s digestive ability explains none of the variation in RFI for cows eating high starch diets but 9 to 31% of the variation in RFI when cows are fed low starch diets. Perhaps differences in other metabolic processes, such as tissue turnover, heat production, or others related to maintenance, can account for more variation in RFI than digestibility.     

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.     

Residual feed intake of lactating Holstein-Friesian cows predicted from high-density genotypes and phenotyping of growing heifers

A genomic prediction for residual feed intake (RFI) developed in growing dairy heifers (RFI_gro) was used to predict and test breeding values for RFI in lactating cows (RFI_lac) from an independent, industry population. A selection of 3,359 cows, in their third or fourth lactation during the study, of above average genetic merit for milk production, and identified as at least 15/16ths Holstein-Friesian breed, were selected for genotyping from commercial dairy herds. Genotyping was carried out using the bovine SNP50 BeadChip (Illumina Inc., San Diego, CA) on DNA extracted from ear-punch tissue. After quality control criteria were applied, genotypes were imputed to the 624,930 single nucleotide polymorphisms used in the growth study. Using these data, genomically estimated breeding values (GEBV) for RFI_gro were calculated in the selected cow population based on a genomic prediction for RFI_gro estimated in an independent group of growing heifers. Cows were ranked by GEBV and the top and bottom 310 identified for possible purchase. Purchased cows (n = 214) were relocated to research facilities and intake and body weight (BW) measurements were undertaken in 99 “high” and 98 “low” RFI_gro animals in 4 consecutive groups [beginning at d 61 ± 1.0 standard error (SE), 91 ± 0.5 SE, 145 ± 1.3 SE, and 191 ± 1.5 SE d in milk, respectively] to measure RFI during lactation (RFI_lac). Each group of ~50 cows (~25 high and ~25 low RFI_gro) was in a feed intake facility for 35 d, fed pasture-alfalfa cubes ad libitum, milked twice daily, and weighed every 2 to 3 d. Milk composition was determined 3 times weekly. Body weight change and BW at trial mid-point were estimated by regression of pre- and posttrial BW measurements. Residual feed intake in lactating cows was estimated from a linear model including BW, BW change, and milk component yield (as MJ/d); RFI_lac differed consistently between the high and low selection classes, with the overall means for RFI_lac being +0.32 and −0.31 kg of dry matter (DM) per day for the high and low classes, respectively. Further, we found evidence of sire differences for RFI_lac, with one sire, in particular, being highly represented in the low RFI_gro class, having a mean RFI_lac of −0.83 kg of DM per day in 47 daughters. In conclusion, genomic prediction of RFI_gro based on RFI measured during growth will discriminate for RFI_lac in an independent group of lactating cows.     

Dry matter intake and feed efficiency profiles of 3 genotypes of Holstein-Friesian within pasture-based systems of milk production

The primary objective of the study was to quantify the effect of genetic improvement using the Irish total merit index (Economic Breeding Index) on dry matter intake and feed efficiency across lactation and to quantify the variation in performance among alternative definitions of feed efficiency. Three genotypes of Holstein-Friesian dairy cattle were established from within the Moorepark dairy research herd: 1) low Economic Breeding Index North American Holstein-Friesian representative of the Irish national average dairy cow, 2) high genetic merit North American Holstein-Friesian, and 3) high genetic merit New Zealand Holstein-Friesian. Animals from within each genotype were randomly allocated to 1 of 2 possible intensive pasture-based feed systems: 1) the Moorepark pasture system (2.64 cows/ha and 500 kg of concentrate supplement per cow per lactation) and 2) a high output per hectare pasture system (2.85 cows/ha and 1,200 kg of concentrate supplement per cow per lactation). A total of 128 and 140 spring-calving dairy cows were used during the years 2007 and 2008, respectively. Each group had an individual farmlet of 17 paddocks, and all groups were managed similarly throughout the study. The effects of genotype, feed system, and the interaction between genotype and feed system on dry matter intake, milk production, body weight, body condition score, and different definitions of feed efficiency were studied using mixed models with factorial arrangements of genotypes and feed systems accounting for the repeated cow records across years. No significant genotype-by-feed-system interactions were observed for any of the variables measured. Results showed that aggressive selection using the Irish Economic Breeding Index had no effect on dry matter intake across lactation when managed on intensive pasture-based systems of milk production, although the ranking of genotypes for feed efficiency differed depending on the definition of feed efficiency used. Performance of animals grouped on alternative definitions of feed efficiency showed that conventional definitions such as feed conversion efficiency or residual feed intake may be inappropriate measures of efficiency for lactating dairy cows. An alternative definition, residual solids production, is proposed. This definition of feed efficiency identifies animals that produce greater volumes of milk solids at similar levels of feed intake without excessive body tissue mobilization and with improved fertility performance. The results also suggest that although there are differences in feed efficiency between strains of Holstein-Friesian, there is also variation within genotypes so that improvements in feed efficiency can be realized if the appropriate definition of feed efficiency is incorporated into breeding programs.     

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.     

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.     

Genetic parameters of rumination time and feed efficiency traits in primiparous Holstein cows under research and commercial conditions

Feed efficiency has the potential to be improved both through feeding, management, and breeding. Including feed efficiency in a selection index is limited by the fact that dry matter intake (DMI) recording is only feasible under research facilities, resulting in small data sets and, consequently, uncertain genetic parameter estimates. As a result, the need to record DMI indicator traits on a larger scale exists. Rumination time (RT), which is already recorded in commercial dairy herds by a sensor-based system, has been suggested as a potential DMI indicator. However, RT can only be a DMI indicator if it is heritable, correlates with DMI, and if the genetic parameters of RT in commercial herd settings are similar to those in research facilities. Therefore, the objective of our study was to estimate genetic parameters for RT and the related traits of DMI in primiparous Holstein cows, and to compare genetic parameters of rumination data between a research herd and 72 commercial herds. The estimated heritability values were all moderate for DMI (0.32–0.49), residual feed intake (0.23–0.36), energy-corrected milk (ECM) yield (0.49–0.70), and RT (0.14–0.44) found in the research herd. The estimated heritability values for ECM were lower for the commercial herds (0.08–0.35) than that for the research herd. The estimated heritability values for RT were similar for the 2 herd types (0.28–0.32). For the research herd, we found negative individual level correlations between RT and DMI (?0.24 to ?0.09) and between RT and RFI (?0.34 to ?0.03), and we found both positive and negative correlations between RT and ECM (?0.08 to 0.09). For the commercial herds, genetic correlations between RT and ECM were both positive and negative (?0.27 to 0.10). In conclusion, RT was not found to be a suitable indicator trait for feed intake and only a weak indicator of feed efficiency.     

Drinking water intake of newborn dairy calves and its effects on feed intake,growth performance,health status,and nutrient digestibility

Although it is recommended to offer free drinking water (called drinking water hereafter) immediately after birth, producers wait, on average, 17 d to first offer drinking water to newborn dairy calves. The objective of this study was to examine water and feed intake, growth performance, health status, and nutrient digestibility of Holstein heifer calves offered drinking water from birth (W0) as compared with those offered it at 17 d of age (W17), when fed an ad libitum volume of milk. Thirty Holstein heifer calves, balanced for parity of the dam, birth weight, and birth week, were randomly assigned (n = 15) to W0 or W17. Calves had free access to drinking water and a starter ration, offered in 2 separate buckets, until they were 70 d of age. Calves were bottle-fed with pasteurized whole milk 3× per day (2.0 kg/feeding until d 14, and 3.2 kg/feeding thereafter). Calves were partially weaned (33% of the milk allowance 1 × per day) at 42 d of age and completely weaned at 49 d of age. Drinking water intake, starter intake, milk intake, ambient temperature, and the fecal consistency were recorded daily. Body weight, hip height, hip width, heart girth, and body length were measured weekly. Blood (drawn from a jugular vein) was analyzed for hematocrit and haptoglobin concentrations at 14 d of age. On d 69 and 70, total fecal output of individual calves was measured and analyzed for chemical composition to determine apparent total-tract digestibility of nutrients. When offered from birth, newborn calves consumed 0.75 ± 0.05 kg/d water aside from the water they received from ad libitum milk allowance during the first 16 d. Once offered, W17 calves drank more water (59%) than W0 calves during the preweaning period. Starter intake of W0 and W17 calves was similar, but W0 calves consumed 0.285 kg/d more milk and tended to achieve greater body weight and heart girth compared with W17 calves during the preweaning period. Offering water from birth versus offering it later did not affect the number of days with diarrhea, intensity of diarrhea, or blood hematocrit and haptoglobin concentrations of preweaned calves. Despite a similar starter intake, W0 calves had greater hip height, body length, apparent total-tract digestibility of acid detergent fiber and neutral detergent fiber, and feed efficiency than W17 calves postweaning (50 to 70 d of age). When followed up to 5 mo of age, W0 calves had greater body weight than W17 calves. Provision of drinking water immediately after birth could improve growth and development of calves pre- and postweaning, potentially by stimulating rumen development, thus increasing nutrient availability.     

Acrylamide-occurrence in mixed concentrate feed for dairy cows and carry-over into milk

During the preparation of cooked foods acrylamide is formed from asparagine and reducing sugars at high temperatures. By-products of oil, starch and sugar production, which may be found in animal feed, partially result from processing steps using heat treatment that are similarly likely to form acrylamide. Possibly, pelletizing during the processing of mixed concentrates may also be involved in acrylamide formation. Thus the occurrence of acrylamide in animal feed and the potential for carry-over into animal products should be tested. Independently of the feed matrix, 1.5 g per day of acrylamide was fed to a cow for ten days resulting in a mean concentration of 175 µg/kg of acrylamide in the milk. From the data obtained the mean carry-over was found to be 0.24%, and a mean half-life time of 2.8 h was estimated. This means acrylamide was rapidly transformed in the cow. The acrylamide concentrations in three commercial mixed concentrates were respectively 180, 145 and 140 µg/kg feed. To test the possible effect of pelletizing, the peripheral zones were separately analysed. No difference in concentration was observed. Based on the carry-over rate estimated in this study, a maximum concentration of approx. 0.2 µg/kg of acrylamide would be expected in milk from cows fed with such feeds.     

Identification of genetic markers associated with residual feed intake and meat quality traits in the pig

Residual feed intake (RFI) has become increasingly important and is being considered as a more reasonable approach to evaluate feed efficiency in livestock. However, the cost and technical difficulties in measuring this trait restrict the extensive adoption of RFI selection, and this makes marker assisted selection (MAS) a feasible tool. In addition, the effects on meat quality caused by low RFI selection have yet to be clarified. In this study, 11 SNPs from eight candidate genes were evaluated in a Yorkshire pig experimental population (n = 169) consisting of a low RFI selection line and a randomly selected control line. Associations of these SNPs with RFI, growth rate, carcass composition, and meat quality measures including water holding capacity, pH at 2 d postmortem, meat color and sensory traits were analyzed. The SNPs FTO p.Ala198Ala and TCF7L2 c.646+514A > G showed significant (P < 0.05) and suggestively significant (P < 0.1) associations with RFI, respectively. The MC4R SNP p.Asp298Asn was associated with backfat but it was not with ADG and meat quality attributes. Both SNPs within HNF1A were associated with intramuscular lipid content and sensory juiciness. The SNPs ACC1 c^∗384C > T and TCF7L2 c.646+514A > G were significantly (P < 0.05) associated with ADG. The SNPs CTSZ p.Arg64Lys and TCF7L2 c.646+514A > G were associated with both visual scoring of meat color and the objective L-value measure of meat color. This study has identified potential genetic markers suitable for MAS in improving RFI, ADG, and meat color traits, but these associations need to be validated in other larger populations.