The genetic and biological basis of feed efficiency in mid-lactation Holstein dairy cows

The objective of this study was to identify genomic regions and candidate genes associated with feed efficiency in lactating Holstein cows. In total, 4,916 cows with actual or imputed genotypes for 60,671 single nucleotide polymorphisms having individual feed intake, milk yield, milk composition, and body weight records were used in this study. Cows were from research herds located in the United States, Canada, the Netherlands, and the United Kingdom. Feed efficiency, defined as residual feed intake (RFI), was calculated within location as the residual of the regression of dry matter intake (DMI) on milk energy (MilkE), metabolic body weight (MBW), change in body weight, and systematic effects. For RFI, DMI, MilkE, and MBW, bivariate analyses were performed considering each trait as a separate trait within parity group to estimate variance components and genetic correlations between them. Animal relationships were established using a genomic relationship matrix. Genome-wide association studies were performed separately by parity group for RFI, DMI, MilkE, and MBW using the Bayes B method with a prior assumption that 1% of single nucleotide polymorphisms have a nonzero effect. One-megabase windows with greatest percentage of the total genetic variation explained by the markers (TGVM) were identified, and adjacent windows with large proportion of the TGVM were combined and reanalyzed. Heritability estimates for RFI were 0.14 (±0.03; ±SE) in primiparous cows and 0.13 (±0.03) in multiparous cows. Genetic correlations between primiparous and multiparous cows were 0.76 for RFI, 0.78 for DMI, 0.92 for MBW, and 0.61 for MilkE. No single 1-Mb window explained a significant proportion of the TGVM for RFI; however, after combining windows, significance was met on Bos taurus autosome 27 in primiparous cows, and nearly reached on Bos taurus autosome 4 in multiparous cows. Among other genes, these regions contain β-3 adrenergic receptor and the physiological candidate gene, leptin, respectively. Between the 2 parity groups, 3 of the 10 windows with the largest effects on DMI neighbored windows affecting RFI, but were not in the top 10 regions for MilkE or MBW. This result suggests a genetic basis for feed intake that is unrelated to energy consumption required for milk production or expected maintenance as determined by MBW. In conclusion, feed efficiency measured as RFI is a polygenic trait exhibiting a dynamic genetic basis and genetic variation distinct from that underlying expected maintenance requirements and milk energy output.     

Assessing feed efficiency in early and mid lactation and its associations with performance and health in Holstein cows

Objectives were to evaluate the associations between residual dry matter (DM) intake (RFI) and residual N intake (RNI) in early lactation, from 1 to 5 wk postpartum, and in mid lactation, from 9 to 15 wk postpartum, and assess production performance and risk of diseases in cows according to RFI in mid lactation. Data from 4 experiments including 399 Holsteins cows were used in this study. Intakes of DM and N, yields of milk components, body weight, and body condition were evaluated daily or weekly for the first 105 d postpartum. Milk yield by 305 d postpartum was also measured. Incidence of disease was evaluated for the first 90 d postpartum and survival up to 300 d postpartum. Residual DM and N intake were calculated in early and mid lactation as the observed minus the predicted values, which were based on linear models that accounted for major energy or N sinks, including daily milk energy or N output, metabolic body weight, and daily body energy or N changes, and adjusting for parity, season of calving, and treatment within experiment. Cows were ranked by RFI and RNI in mid lactation and categorized into quartiles (Q1 = smallest RFI, to Q4 = largest RFI). Increasing efficiency in mid lactation resulted in linear decreases in RFI (depicted from Q1 to Q4; ?0.93, ?0.05, ?0.04, and 0.98 kg/d), DMI (16.0, 16.9, 17.3, and 18.4 kg/d), net energy for lactation (NE_L) intake (26.8, 28.4, 29.0, and 30.8 Mcal/d), and NE_L balance (?9.0, ?8.1, ?8.2, and ?5.5 Mcal/d) during early lactation, but no differences were observed in body NE_L or N changes or yield of energy-corrected milk in the first 5 wk of lactation. Residual DM intake in mid lactation was associated with RFI (Pearson r = 0.43, and Spearman ρ = 0.32) and RNI (r = 0.44, ρ = 0.36) in early lactation, and with RNI in mid lactation (r = 0.91, ρ = 0.84). Similarly, RNI in mid lactation was associated with RNI in early lactation (r = 0.42, ρ = 0.35). During the first 15 wk postpartum, more efficient cows in mid lactation consumed 3.5 kg/d less DM (Q1 = 19.3 vs. Q4 = 22.8 kg/d) and were more N efficient (Q1 = 31.6 vs. Q4 = 25.8%), at the same time that yields of milk (Q1 = 39.0 vs. Q4 = 39.4 kg/d), energy-corrected milk (Q1 = 38.6 vs. Q4 = 39.3 kg/d), and milk components did not differ compared with the quartile of least efficient cows. Furthermore, RFI in mid lactation was not associated with 305-d milk yield, incidence of diseases in the first 90 d postpartum, or survival by 300 d postpartum. Collectively, rankings of RFI and RNI are associated and repeatable across lactation stages. The most feed-efficient cows were also more N efficient in early and mid lactation. Phenotypic selection of RFI based on measurements in mid lactation is associated with improved efficiency without affecting production or health in dairy cows.     

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.     

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.     

Methane production,rumen fermentation,and diet digestibility of Holstein and Jersey dairy cows being divergent in residual feed intake and fed at 2 forage-to-concentrate ratios

Improving feed efficiency of dairy cows through breeding is expected to reduce enteric methane production per unit of milk produced. This study examined the effect of 2 forage-to-concentrate ratios on methane production, rumen fermentation, and nutrient digestibility in Holstein and Jersey dairy cows divergent in residual feed intake (RFI). Before experimental onset, RFI was estimated using a random regression model on phenotypic herd data. Ten lactating Holstein and 10 lactating Jersey cows were extracted from the herd and allocated to a high or low pre-experimental RFI group of 5 animals each within breed. Cows were fed ad libitum with total mixed rations either low (LC) or high (HC) in concentrates during 3 periods in a crossover design with a back-cross and staggered approach. Forage-to-concentrate ratio was 68:32 for LC and 39:61 for HC. Cows adapted to the diets in 12 to 24 d and feces were subsequently collected on 2 d. Afterward, gas exchange was measured in respiration chambers and rumen liquid was collected once after cows exited the chambers. Pre-experimental RFI was included in the statistical analysis as a class (low and high RFI) or continuous variable. Methane per kilogram of dry matter intake (DMI) was lower for Holsteins than Jerseys and the response to increased concentrate level was more pronounced for Holsteins than Jerseys (27.2 vs.13.8%); a similar pattern was found for the acetate:propionate ratio. However, methane production per kilogram of energy-corrected milk (ECM) was unaffected by breed. Further, total-tract digestibility of neutral detergent fiber was higher for Jerseys than Holsteins. For RFI as a class variable, DMI, methane production regardless of the expression, and digestibility were unaffected by RFI. For RFI as a continuous variable, DMI was lower and methane per kilogram of DMI was higher for cows with negative (efficient) than positive (inefficient) RFI values, and neutral detergent fiber digestibility was higher for Holsteins with negative than positive RFI values, but not for Jerseys. Daily methane production and methane per kilogram of ECM were unaffected by RFI. In conclusion, methane per kilogram of DMI of Jerseys was lowered to a smaller extent in response to the HC diet than of Holsteins. When pre-experimental RFI was used as a continuous variable, higher methane per kilogram of DMI was found for cows with negative RFI than positive RFI values, but not for methane per kilogram of ECM. These findings call for validation in larger studies.     

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.     

Identification of biological traits associated with differences in residual energy intake among lactating Holstein cows

Residual feed intake, which is usually used to estimate individual variation of feed efficiency, requires frequent and accurate measurements of individual feed intake to be carried out. Developing a breeding scheme based on residual feed intake in dairy cows is therefore complicated, especially because feed intake is not measurable for a large population. Another solution could be to focus on biological determinants of feed efficiency, which could potentially be directly and broadband measurable on farm. Several phenotypes have been identified in literature as being associated with differences in feed efficiency. The present study therefore aims to identify which biological mechanisms are associated with residual energy intake (REI) differences among dairy cows. Several candidate phenotypes were recorded frequently and simultaneously throughout the first 238 d in milk for 60 Holstein cows fed on a constant diet based on maize silage. A multiple linear regression of the 238 d in milk average of net energy intake was fitted on the 238 d in milk averages for milk energy output, metabolic body weight, the sum over the 238 d in milk of both, body condition score loss and gain, and the residuals were defined as REI. A partial least square regression was fitted over all biological traits to explain REI variability. Linear multiple regression explained 93.6% of net energy intake phenotypic variation, with 65.5% associated with lactation requirement, 23.2% with maintenance, and 4.9% with body reserves change; the 6.4% residuals represented REI. Overall, measured biological traits contributed to 58.9% of REI phenotypic variability, which were mainly explained by activity (26.5%) and feeding behavior (21.3%). However, apparent confounding was observed between behavior, activity, digestibility, and rumen-temperature variables. Drawing a conclusion on biological traits that explain feed efficiency differences among dairy cows was not possible due to this apparent confounding between the measured variables. Further investigation is needed to validate these results and to characterize the causal relationship of feed efficiency with feeding behavior, digestibility, body reserves change, activity, and rumen temperature.     

Residual carbon dioxide as an index of feed efficiency in lactating dairy cows

High feed costs make feed conversion efficiency a desirable target for genetic improvement. Residual feed intake (RFI), calculated as the difference between observed and predicted intake, is a commonly used estimate of feed efficiency. However, determination of feed efficiency in dairy herds is challenging due to difficulties in measuring feed intake of individual animals reliably. Using residual CO₂ (RCO₂) production as an estimate of feed efficiency would allow ranking the cows according to feed efficiency, provided that CO₂ production is closely related to heat production and feed intake. The objective of this study was to evaluate the potential of RCO₂ as an index of feed efficiency using data from respiration calorimetry studies (289 cow per period observations). Heat production was precisely predicted from CO₂ production [root mean square error (RMSE)] adjusted for random effects was 1.5% of observed mean]. Dry matter intake (DMI) was better predicted from energy-corrected milk (ECM) yield and CO₂ production than from ECM yield and body weight in the model (adjusted RSME = 0.92 vs. 1.39 kg/d). Residual CO₂ production estimated as the difference between actual CO₂ production and that predicted from ECM yield, metabolic body weight was closely related to RFI (adjusted RMSE = 0.42) that was calculated as the difference between actual DMI and that predicted from ECM, metabolic body weight, and energy balance (EB). When the cows were categorized in 3 groups of equal sizes on the basis of RCO₂ (low, medium, and high), low RCO₂ cows had lower DMI, RFI, methane production and intensity (g/kg ECM), and heat production, but higher efficiency of metabolizable energy utilization for lactation than high RCO₂ cows. When RFI was predicted from RCO₂, the residuals (observed – predicted) were negatively related to EB and digestibility. Predicting RFI with a 2-variable model based on RCO₂ and digestibility, adjusted RMSE decreased to 0.23 kg/d, and residuals were not significantly related to EB. The cows in low RCO₂ group had a higher energy digestibility than the cows in the high RCO₂ group, and differences in EB were observed between the groups. Error of the model predicting residual ECM production from RCO₂ was 1.41 kg/d. The residuals were positively related to ECM yield and energy digestibility. Predicting residual ECM from RCO₂ and ECM yield decreased adjusted RMSE to 1.07 kg/d, and further to 0.78 kg/d when digestibility was included in the 2-variable model. It is concluded that RCO₂ has a potential for ranking individual cows based on feed efficiency.     

Predicting average feed intake of lactating Holstein cows fed totally mixed rations

A dry matter intake (DMI) prediction equation was estimated by using a data file that contained 124 treatment means collected from published studies. Animal factors considered for inclusion in the prediction model were body weight (BW) and its natural logarithm, BW(0.75), milk yield (MY) and its natural logarithm, milk fat and protein yields, month of lactation and its square, as well as its natural logarithm. The dietary factors considered were the percentages of neutral detergent fiber, acid detergent fiber, crude protein and hemicellulose in the ration dry matter together with the square of all these predictors. The multiple regression model selected by using the maximum R2 method include both animal and dietary factors as independent variables. The accuracy of this DMI prediction equation was evaluated and compared with that of five other equations previously published by using three independent datasets also containing treatment means collected from literature. Even though the latest NRC equation was slightly more accurate than the equation proposed in this study with the three evaluation datasets, the latter can be used for some applications for which the NRC equation is not appropriate.     

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.     

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.     

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.     

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.     

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.     

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.     

Genetics of alternative definitions of feed efficiency in grazing lactating dairy cows

The objective of the present study was to estimate genetic parameters across lactation for measures of energy balance (EB) and a range of feed efficiency variables as well as to quantify the genetic inter-relationships between them. Net energy intake (NEI) from pasture and concentrate intake was estimated up to 8 times per lactation for 2,481 lactations from 1,274 Holstein-Friesian cows. A total of 8,134 individual feed intake measurements were used. 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 NEI minus predicted energy requirements [e.g., net energy of lactation (NE_L), maintenance, and body tissue anabolism] or supplied from body tissue mobilization; residual energy production was defined as the difference between actual NE_L and predicted NE_L based on NEI, maintenance, and body tissue anabolism/catabolism. Energy conversion efficiency was defined as NE_L divided by NEI. Random regression animal models were used to estimate residual, additive genetic, and permanent environmental (co)variances across lactation. Heritability across lactation stages varied from 0.03 to 0.36 for all efficiency traits. Within-trait genetic correlations tended to weaken as the interval between lactation stages compared lengthened for EB, REI, residual energy production, and NEI. Analysis of eigenvalues and associated eigenfunctions for EB and the efficiency traits indicate the ability to genetically alter the profile of these lactation curves to potentially improve dairy cow efficiency differently at different stages of lactation. Residual energy intake and EB were moderately to strongly genetically correlated with each other across lactation (genetic correlations ranged from 0.45 to 0.90), indicating that selection for lower REI alone (i.e., deemed efficient cows) would favor cows with a compromised energy status; nevertheless, selection for REI within a holistic breeding goal could be used to overcome such antagonisms. The smallest (8.90% of genetic variance) and middle (11.22% of genetic variance) eigenfunctions for REI changed sign during lactation, indicating the potential to alter the shape of the REI lactation profile. Results from the present study suggest exploitable genetic variation exists for a range of efficiency traits, and the magnitude of this variation is sufficiently large to justify consideration of the feed efficiency complex in future dairy breeding goals. Moreover, it is possible to alter the trajectories of the efficiency traits to suit a particular breeding objective, although this relies on very precise across-parity genetic parameter estimates, including genetic correlations with health and fertility traits (as well as other traits).     

Variation in residual feed intake in Holstein-Friesian dairy heifers in southern Australia

Feed conversion efficiency of dairy cattle is an important component of the profitability of dairying, given that the cost of feed accounts for much of total farm expenses. Residual feed intake (RFI) is a useful measure of feed conversion efficiency, as it can be used to compare individuals with the same or differing levels of production during the period of measurement. If genetic variation exists in RFI among dairy cattle, selection for lower RFI could improve profitability. In this experiment, RFI was defined as the difference between an animal's actual feed intake and its expected feed intake, which was determined by regression of dry matter (DM) intake against mean body weight (BW) and growth rate. Nine hundred and three Holstein-Friesian heifer calves, aged between 5 and 7 mo, were measured for RFI in 3 cohorts of approximately 300 animals. Calves were housed under feedlot style conditions in groups of 15 to 20 for 85 to 95 d and had ad libitum access to a cubed alfalfa hay. Intakes of individual animals were recorded via an electronic feed recording system and BW gain was determined by weighing animals once or twice weekly, over a period of 60 to 70 d. Calves had DM intake (mean ± SD) of 8.3 ± 1.37 kg of DM/d over the measurement period with BW gains of 1.1 ± 0.17 kg/d. In terms of converting feed energy for maintenance and growth, the 10% most efficient calves (lowest RFI) ate 1.7 kg of DM less each day than the 10% least efficient calves (highest RFI) for the same rate of growth. Low-RFI heifers also had a significantly lower rate of intake (g/min) than high-RFI heifers. The heritability estimate of RFI (mean ± SE) was 0.27 (±0.12). These results indicate that substantial genetic variation in RFI exists, and that the magnitude of this variation is large enough to enable this trait to be considered as a candidate trait for future dairy breeding goals. A primary focus of future research should be to ensure that calves that are efficient at converting feed energy for maintenance and growth also become efficient at converting feed energy to milk. Future research will also be necessary to identify the consequences of selection for RFI on other traits (especially fertility and other fitness traits) and if any interactions exist between RFI and feeding level.     

Responses of dairy cows with divergent residual feed intake as calves to metabolic challenges during midlactation and the nonlactating period

Residual feed intake (RFI) is defined as the difference between the actual and expected feed intake required to support animal maintenance and growth. Thus, a cow with a low RFI can obtain nutrients for maintenance and growth from a reduced amount of feed compared with a cow with a high RFI. Variation in RFI is underpinned by a combination of factors, including genetics, metabolism, thermoregulation and body composition; hypothalamic-pituitary-adrenal (HPA) axis responsiveness is also a possible contributor. Responses to 3 metabolic challenges were measured in lactating and nonlactating dairy cattle. Sixteen Holstein Friesian cows with phenotypic RFI measurements that were obtained during the growth period (188–220 d old) were grouped as either low-calfhood RFI (n = 8) or high-calfhood RFI (n = 8). An ACTH (2 µg/kg of body weight), insulin (0.12 U/kg), and epinephrine (a low dose of 0.1 µg/kg and a high dose of 1.6 µg/kg of epinephrine) challenge were each conducted during both midlactation (122 ± 23.4 d in milk) and the nonlactating period (dry period; approximately 38 d after cessation of milking). Cows were housed in metabolism stalls for the challenges and were fed a diet of alfalfa cubes ad libitum for at least 10 d before the experiment (lactating cows also were offered a total of 6 kg of dry matter/d of crushed wheat grain plus minerals fed as 3 kg of dry matter at each milking) and were fasted for 12 h before the challenges. The efficiency of conversion of feed into milk (the ratio of feed consumed to milk produced over the 7 d before the experiment) during midlactation was better (lower) in low-calfhood RFI cows, although dry matter intake did not differ between RFI groups. Low-calfhood RFI cows exhibited a lower plasma cortisol response to the ACTH challenge than high-calfhood RFI cows, particularly in midlactation (?15%). The low-calfhood RFI cows had a greater plasma insulin-like growth factor-1 response to the insulin challenge and plasma fatty acid response to epinephrine compared with the high-calfhood RFI cows. These data suggest that high-calfhood RFI cows exhibit a more responsive HPA axis. As divergence in RFI measured during growth is retained (although reduced) during lactation, it is possible that energy is used to respond to HPA axis activation at the expense of production in high-calfhood RFI dairy cattle during lactation and contributes to a decrease in overall feed use efficiency.     

Rumen biohydrogenation and milk fatty acid profile in dairy ewes divergent for feed efficiency

A sustainable increase in livestock production would require selection for improved feed efficiency, but the mechanisms underlying this trait and explaining its large individual variation in dairy ruminants remain unclear. This study was conducted in lactating ewes to test the hypothesis that rumen biohydrogenation (BH) would differ between high- and low-efficiency animals, and these differences would be reflected in rumen fatty acid (FA) profile and affect milk FA composition. A second aim was to identify differences in FA that may serve as biomarkers of feed efficiency. Data of daily feed intake and milk yield and composition, as well as body weight, were collected individually over a 3-wk period in 40 ewes. The difference between the mean actual and predicted feed intake (estimated through metabolizable energy requirements for maintenance, production, and body weight change) over the period was used as the feed efficiency index (FEI) to select 8 of the highest feed efficiency (H-FE) and 8 of the lowest feed efficiency (L-FE) animals. In addition, residual feed intake (RFI) was estimated as the residual term from the regression of feed intake on various energy sinks. Rumen and milk FA composition were characterized by using gas chromatography, and results were analyzed using a statistical model that included the fixed effect of the group (H-FE vs. L-FE). The FEI averaged ?0.29 ± 0.046 and 0.81 ± 0.084 in H-FE and L-FE, respectively, whereas RFI averaged ?0.16 ± 0.084 and 0.18 ± 0.082, respectively. The correlation coefficient between both metrics was 0.69. Feed intake was similar in both groups, but H-FE showed greater milk yield, with increases in lactose content and yield, and in milk protein and fat production. Results from rumen FA profiles included a lower proportion of 18:2n-6, cis-9 18:1, and of several of their BH metabolites, and a greater concentration of 18:0, which may indicate that the apparent BH would be more complete in more efficient sheep. Milk FA analysis suggested that the greater fat yield in the H-FE group was mostly explained by increased de novo FA synthesis, whereas their milk would have lower proportions of cis-9 18:1 and C20 to 22n-6 polyunsaturated FA than L-FE. Stepwise multiple linear regression suggested that milk C20 to 22n-6 PUFA might be convenient biomarkers to discriminate more efficient dairy sheep. Further research is needed to validate these findings (e.g., under different dietary conditions).     

Short communication: Increased somatic cell count is associated with milk loss and reduced feed efficiency in lactating dairy cows

The objective was to evaluate the relationship of somatic cell count (SCC; cells/mL) with milk yield, energy-corrected milk yield (ECM; kg/d), dry matter intake (DMI; kg/d), feed efficiency for milk (FE_MY; kg of milk/kg of DMI), and feed efficiency for ECM (FE_ECM; kg of ECM/kg of DMI) in lactating dairy cows. We analyzed an SCC database consisting of 7 experiments, which were conducted at The Pennsylvania State University's Dairy Teaching and Research Center between 2009 and 2015. The experiments included in the SCC database were randomized block designs and investigated dietary effects on cow performance over 6 to 11 wk. Each experiment took repeated measurements of SCC, milk yield, milk composition, and DMI. After exclusion of records from cows without lactation number, days in milk, and only 1 measurement, the database comprised 1,094 observations of 254 cows for estimating the effect of SCC on milk yield, DMI, and FE_MY and 1,079 observations of 250 cows for estimating the effect of SCC on ECM and FE_ECM. Data were analyzed in R using a linear mixed model with natural logarithm of SCC, lactation number (1, 2, and ≥3), days in milk, and the interactions of the linear predictors as fixed effects and cow within block and experiment as random effect. Natural logarithm of SCC was negatively correlated with milk yield, ECM, DMI, FE_MY, and FE_ECM. Our results suggest that a cow with relatively high SCC (250,000 cells/mL) compared with a cow with a relatively low SCC (50,000 cells/mL) produces, on average, 1.6 kg/d less milk, consumes 0.3 kg/d less DMI, produces 0.04 kg less milk per kg of DMI, and produces 0.03 less ECM per kg of DMI. The observed decrease of feed efficiency with increased SCC adds to previously known economic losses and environmental impacts associated with mastitis, which should provide a further incentive to control mastitis in dairy cows.