Long-term growth, feed efficiency, enteric methane emission, and blood metabolite responses to in utero hyperthermia in Holstein heifers

Dairy producers are experiencing production and animal welfare pressures from the increasing frequency and severity of heat stress events due to global climate change. Offspring performance during the preweaning and lactating periods is compromised when exposed to heat stress during late gestation (in utero). However, knowledge of the lingering effects of in utero heat stress on yearling dairy heifers is limited. Herein, we investigated the long-term effects of in utero heat stress on heifer growth, feed efficiency, and enteric methane emissions in postpubertal heifers. During the last 56 d of gestation, 38 pregnant cows carrying heifer calves were exposed to either heat stress (IUHT; n = 17) or artificial cooling (IUCL; n = 21). At 18 ± 1 mo of age, the resulting IUCL and IUHT heifers were enrolled in the present 63-d study. Heifers were blocked by weight and randomly assigned to 3 pens with Calan gates. Body weights were recorded on 3 consecutive days at the start and end of the trial and used to calculate ADG. Body condition score, hip width, body length, and chest girth were measured at the start and end of the study. All heifers were fed a TMR comprised of 46.6% oatlage, 44.6% grass/alfalfa haylage, 7.7% male-sterile corn silage, 0.3% urea, and 0.8% mineral/vitamin supplement (on a DM basis). The TMR and refusal samples were obtained daily, composited weekly, and dried to calculate DMI. During the study, each pen had access to a GreenFeed unit for 8 ± 1d to measure CH4 and CO2 gas fluxes. During the last 3 d of measuring CH4 and CO2 fluxes, fecal samples were collected, composited by animal, dried, and analyzed to calculate NDF, OM, and DM digestibility. On the last day of fecal sampling, blood samples were also collected via coccygeal venipuncture, and GC time-of-flight MS analysis was performed. Residual feed intake (RFI; predicted DMI - observed DMI), and feed conversion efficiency (FCE; DMI/ADG) were calculated to estimate feed efficiency. No differences were found in initial or final BW, hip width, chest girth, or BCS; however, IUCL heifers were longer in body length compared with IUHT heifers. Dry matter intake, ADG, RFI, and FCE were similar between IUHT and IUCL heifers. In utero heat-stressed and IUCL heifers produced similar amounts of CH4 and CO2, and no differences were found in the number of GreenFeed visits or latency to approach the GreenFeed. The concentrations of 6 blood metabolites involved in lipogenic pathways were different between in utero treatments. In conclusion, in utero heat stress does not seem to have long-term effects on feed efficiency or methane emissions during the postpubertal growing phase; however, IUCL heifers maintained a body-length advantage over their IUHT counterparts and differed in concentrations of several candidate metabolites that encourage further exploration of their potential function in key organs, such as the liver and mammary gland.

Immune cells phenotype and bioenergetic measures in CD4+ T cells differ between high and low feed efficient dairy cows

Identifying sources of variance that contribute to residual feed intake (RFI) can aid in improving feed efficiency. The objectives of this study were to investigate immune cells phenotype and bioenergetic measures in CD4+ T cells in low feed efficient (LE) and high feed efficient (HE) dairy cows. Sixty-four Holstein cows were enrolled at 93 ± 22 days in milk (DIM) and monitored for 7 weeks to measure RFI. Cows with the highest RFI (LE; n = 14) or lowest RFI (HE; n = 14) were selected to determine immune cells phenotype using flow cytometry. Blood was sampled in the same LE and HE cows at 234 ± 22 DIM to isolate peripheral blood mononuclear cells, followed by magnetic separation of CD4+ T lymphocytes using bovine specific monoclonal antibodies. The metabolic function of isolated CD4+ T lymphocytes was evaluated under resting and activated states. An increased expression of CD62L+ cells within CD8+ T lymphocytes and CD21+ B lymphocytes was observed in HE cows compared to LE cows. CD4+ T lymphocytes of HE cows exhibited an increased mitochondrial and glycolytic activity in resting and activated states compared to LE cows. These data suggest that immune cells in HE cows exhibit an increased metabolic function, which might influence nutrient partitioning and utilization and serve as a source of variation in feed efficiency that warrants future investigation.

Assessing short-term feed efficiency and its association with biological markers in herbage-fed dairy cows

Feed efficiency is an important trait of dairy production. However, assessing feed efficiency is constrained by the associated cost and difficulty in measuring individual feed intake, especially on pastures. The objective of this study was to investigate short-term feed efficiency traits of herbage-fed dairy cows and screening of potential biomarkers (n = 238). Derived feed efficiency traits were ratio-based (i.e., feed conversion ratio (FCR) and N use efficiency (NUE)) or residual-based (i.e., residual feed intake (RFI), residual energy intake (REI), and residual N intake (RNI)). Thirty-eight Holstein and 16 Swiss Fleckvieh dairy cows underwent a 7-d measurement period during mid- and/or late-lactation. The experimental data (n = 100 measurement points) covered different lactational and herbage-fed system situations: mid-lactation grazing (n = 56), late-lactation grazing (n = 28), and late-lactation barn feeding (n = 16). During each measuring period, the individual herbage intake of each cow was estimated using the n-alkane marker technique. For each cow, biomarkers representing milk constituents (n = 109), animal characteristics (n = 13), behaviour, and activity (n = 46), breath emissions (n = 3), blood constituents (n = 35), surface, and rectal temperature (n = 29), hair cortisol (n = 1), and near-infrared (NIR) spectra of faeces and milk (n = 2) were obtained. The relationships between biomarkers and efficiency traits were statistically analysed with univariate linear regression and for NIR spectra using partial least squares regression with feed efficiency traits. The feed efficiency traits were interrelated with each other (r: -0.57 to -0.86 and 0.49-0.81). The biomarkers showed varying R2 values in explaining the variability of feed efficiency traits (FCR: 0.00-0.66, NUE: 0.00-0.74, RFI: 0.00-0.56, REI: 0.00-0.69, RNI: 0.00-0.89). Overall, the feed efficiency traits were best explained by NIR spectral characteristics of milk and faeces (R2: 0.25-0.89). Biomarkers show potential for predicting feed efficiency in herbage-fed dairy cows. NIR spectra data analysis of milk and faeces presents a promising method for estimating individual feed efficiency upon further validation of prediction models. Future applications will depend on the ability to improve the robustness of biomarkers to predict feed efficiency in a greater variety of environments (locations), managing conditions, feeding systems, production intensities, and other aspects.

Investigating relationships between the host genome, rumen microbiome, and dairy cow feed efficiency using mediation analysis with structural equation modeling

The rumen microbiome is crucial for converting feed into absorbable nutrients used for milk synthesis, and the efficiency of this process directly impacts the profitability and sustainability of the dairy industry. Recent studies have found that the rumen microbial composition explains part of the variation in feed efficiency traits, including dry matter intake, milk energy, and residual feed intake. The main goal of this study was to reveal relationships between the host genome, rumen microbiome, and dairy cow feed efficiency using structural equation models. Our specific objectives were to (i) infer the mediation effects of the rumen microbiome on feed efficiency traits, (ii) estimate the direct and total heritability of feed efficiency traits, and (iii) calculate the direct and total breeding values of feed efficiency traits. Data consisted of dry matter intake, milk energy, and residual feed intake records, SNP genotype data, and 16S rRNA rumen microbial abundances from 448 mid-lactation Holstein cows from 2 research farms. We implemented structural equation models such that the host genome directly affects the phenotype (GP → P) and the rumen microbiome (GM → P), while the microbiome affects the phenotype (M → P), partially mediating the effect of the host genome on the phenotype (G → M → P). We found that 7 to 30% of microbes within the rumen microbial community had structural coefficients different from zero. We classified these microbes into 3 groups that could have different uses in dairy farming. Microbes with heritability <0.10 but significant causal effects on feed efficiency are attractive for external interventions. On the other hand, 2 groups of microbes with heritability ≥0.10, significant causal effects, and genetic covariances and causal effects with the same or opposite sign to feed efficiency are attractive for selective breeding, improving or decreasing the trait heritability and response to selection, respectively. In general, the inclusion of the different microbes in genomic models tends to decrease the trait heritability rather than increase it, ranging from -15% to +5%, depending on the microbial group and phenotypic trait. Our findings provide more understanding to target rumen microbes that can be manipulated, either through selection or management interventions, to improve feed efficiency traits.

Preference for feed bins shared with cows of the same or different parity and relationships with feeding behavior and feed efficiency

Our objectives were to (1) evaluate cows' preferences for visiting feed bins limited to either same- versus mixed-parity social interactions, depending on their parity; (2) examine the effect of parity and bin social dynamic type on competition behavior and feeding patterns, and (3) investigate cow-level relationships between feed bunk competition behavior, feeding patterns, and feed efficiency. Twenty-eight primiparous and 28 multiparous (2.4 ± 0.6 lactations) lactating Holstein cows (127.8 ± 30.1 and 145.3. ± 10.4 DIM, respectively) were housed in a freestall pen with 28 roughage intake control bins (2:1 stocking density). Each cow was assigned to 2 bins, including 1 shared with 3 other cows of the same parity (SM) and 1 with 3 cows of mixed parities (MX, 50% primiparous and 50% multiparous). Feed bunk competition was recorded via video in the first hour after morning feed delivery for 2 d, and feeding patterns were recorded from 24-h roughage intake control data. Residual feed intake was calculated as the difference between predicted and observed dry matter intake after accounting for known energy sinks. Based on the first visit to the feed bunk after fresh feed delivery, multiparous cows tended to prefer the MX bin compared with the SM one; cows showed no other overall preference for bin type based on number of visits. Over time, multiparous cows remained consistent in their magnitude of preference for visiting each bin type, but involvement in competition was not consistent over time. Primiparous cows tended to be involved in more total competitive contacts and ate faster at the SM bin compared with the MX one. Those primiparous cows who visited the SM bin more often within the first hour after morning feed delivery tended to be less feed efficient. Multiparous cows initiated more successful replacements after a displacement at the MX versus SM bin, with no difference in feeding patterns between bin types. Regardless of parity or bin type, visiting the bunk sooner after feed delivery was correlated with involvement in more competitive interactions and more time eating within the first 30 min. Consuming more feed during a longer first visit to the bunk after fresh feed delivery was correlated with being less feed efficient. Overall, when given the choice of feeding from bins shared with cows of the same or mixed parities at a 2:1 stocking density, primiparous cows showed differences in behavior between those bin types, with implications for feed efficiency; these effects are perhaps an unintended consequence of compensatory strategies to avoid direct competition with multiparous cows.

Effect of increasing dietary inclusion of whole cottonseed on nutrient digestibility and milk production of high-producing dairy cows

We determined the effects increasing dietary inclusion of whole cottonseed (WCS) on nutrient digestibility and milk production responses of high-producing dairy cows. Twenty-four multiparous Holstein cows (mean ± SD; 52.7 ± 2.63 kg/d of milk; 104 ± 23 DIM) were randomly assigned to treatment sequences in a replicated 4 × 4 Latin square design with 21-d periods. Treatments were increasing doses of WCS at 0, 8, 16, and 24% DM, with WCS replacing soybean meal and hulls to maintain similar diet nutrient composition (%DM) of NDF (32%), forage NDF (21%), starch (27%), and CP (17%). Total fatty acid (FA) content of each treatment was 1.70, 2.96, 4.20, and 5.40%DM, respectively. Three preplanned contrasts were used to test the linear, quadratic, and cubic effects of increasing dietary WCS. Increasing dietary WCS from 0 to 24% DM quadratically influenced intakes of DM and NDF, with the highest value being for the 8% WCS, and intakes of 16- and 18-carbon, and total FA, with maximum values obtained up to 24% WCS. Increasing dietary WCS affected digestibility of DM (cubic) and NDF (quadratic), with the lowest values being for the 8% WCS. Increasing WCS increased 16-carbon digestibility (quadratic) but decreased digestibility of 18-carbon and total FA (both quadratic), with highest and lowest values for the 24% WCS, respectively. Increasing dietary WCS quadratically increased absorbed 16- and 18-carbon, and total FA, with maximum values obtained for 24% WCS. Increasing dietary WCS quadratically increased yields of milk, milk fat, milk protein, milk lactose, 3.5% fat corrected milk, and energy corrected milk, and linearly increased body weight gain. The source of milk FA was affected by dietary WCS, with a quadratic decrease in the yield of de novo and mixed milk FA and a quadratic increase in preformed milk FA. Increasing dietary WCS linearly increased trans-10 C18:1 milk FA content. As dietary WCS increased, plasma insulin linearly decreased, and plasma gossypol levels linearly increased. Despite the decrease in total FA digestibility, increasing dietary WCS from 0 to 24% DM increased FA absorption. Increasing dietary inclusion of WCS up to 16% DM increased milk production responses and DM intake. Under the current dietary conditions, high-producing dairy cows benefited best from a diet containing 8-16% DM inclusion of WCS.

Dry matter intake in US Holstein cows: exploring the genomic and phenotypic impact of milk components and body weight composite

Large data sets allow estimating feed required for individual milk components or body maintenance. Phenotypic regressions are useful for nutrition management, but genetic regressions are more useful in breeding programs. Dry matter intake (DMI) records from 8,513 lactations of 6,621 Holstein cows were predicted from phenotypes or genomic evaluations for milk components and body size traits. The mixed models also included days in milk, age-parity subclass, trial date, management group, and body weight change during 28- and 42-d feeding trials in mid-lactation. Phenotypic regressions of DMI on milk (0.014 ± 0.006), fat (3.06 ± 0.01), and protein (4.79 ± 0.25) were much less than corresponding genomic regressions (0.08 ± 0.03, 11.30 ± 0.47, and 9.35 ± 0.87) or sire genomic regressions multiplied by 2 (0.048 ± 0.04, 6.73 ± 0.94, and 4.98 ± 1.75). Thus, marginal feed costs as fractions of marginal milk revenue were higher from genetic than phenotypic regressions. According to the energy-corrected milk formula, fat production requires 69% more DMI than protein production. In the phenotypic regression, it was estimated that protein production requires 56% more DMI than fat. However, the genomic regression for the animal showed a difference of only 21% more DMI for protein compared with fat, while the sire genomic regressions indicated approximately 35% more DMI for fat than protein. Estimates of annual maintenance in kg DMI / kg body weight/lactation were similar from phenotypic regression (5.9 ± 0.14), genomic regression (5.8 ± 0.31), and sire genomic regression multiplied by 2 (5.3 ± 0.55) and are larger than those estimated by NASEM (2021) based on NEL equations. Multiple regressions on genomic evaluations for the 5 type traits in body weight composite (BWC) showed that strength was the type trait most associated with body weight and DMI, agreeing with the current BWC formula, whereas other traits were less useful predictors, especially for DMI. The Net Merit formula used to weight different genetic traits to achieve an economically optimal overall selection response was revised in 2021 to better account for these estimated regressions. To improve profitability, breeding programs should select smaller cows with negative residual feed intake that produce more milk, fat, and protein.

Host and rumen microbiome contributions to feed efficiency traits in Holstein cows

It is now widely accepted that dairy cow performance is influenced by both the host genome and rumen microbiome composition. The contributions of the genome and the microbiome to the phenotypes of interest are quantified by heritability (h2) and microbiability (m2), respectively. However, if the genome and microbiome are included in the model, then the h2 reflects only the contribution of the direct genetic effects quantified as direct heritability (hd2), and the holobiont effect reflects the joint action of the genome and the microbiome, quantified as the holobiability (ho2). The objectives of this study were to estimate h2, hd2,m2, and ho2 for dry matter intake, milk energy, and residual feed intake; and to evaluate the predictive ability of different models, including genome, microbiome, and their interaction. Data consisted of feed efficiency records, SNP genotype data, and 16S rRNA rumen microbial abundances from 448 mid-lactation Holstein cows from 2 research farms. Three kernel models were fit to each trait: one with only the genomic effect (model G), one with the genomic and microbiome effects (model GM), and one with the genomic, microbiome, and interaction effects (model GMO). The model GMO, or holobiont model, showed the best goodness-of-fit. The hd2 estimates were always 10% to 15% lower than h2 estimates for all traits, suggesting a mediated genetic effect through the rumen microbiome, and m2 estimates were moderate for all traits, and up to 26% for milk energy. The ho2 was greater than the sum of hd2 and m2, suggesting that the genome-by-microbiome interaction had a sizable effect on feed efficiency. Kernel models fitting the rumen microbiome (i.e., models GM and GMO) showed larger predictive correlations and smaller prediction bias than the model G. These findings reveal a moderate contribution of the rumen microbiome to feed efficiency traits in lactating Holstein cows and strongly suggest that the rumen microbiome mediates part of the host genetic effect.

Long-Term Effects of Pre-Weaning Individual or Pair Housing of Dairy Heifer Calves on Subsequent Growth and Feed Efficiency

Our objective in this exploratory study was to evaluate the long-term impacts of pre-weaning social isolation vs. contact on subsequent growth and feed efficiency of Holstein heifers. As pre-weaned calves, 41 heifers were housed individually (n = 15 heifers) or in pairs (n = 13 pairs; 26 heifers). At 18 months of age, heifers were blocked by body weight and randomly assigned to one of three pens within a block (six to eight heifers per pen; six pens total), with original pairs maintained. Body weight (BW), hip height and width, and chest girth were measured at the start and end of the study. Each pen was given 3 days of access to a GreenFeed greenhouse gas emissions monitor to assess potential physiological differences between treatments in enteric methane emissions or behavioral differences in propensity to approach a novel object. During the 9-week study, heifers were fed a common diet containing 62.3% male-sterile corn silage, 36.0% haylage, 0.7% urea, and 1.0% mineral (DM basis). To calculate daily feed intake, as-fed weights and refusals were recorded for individual heifers using Calan gates. Feed samples were collected daily, composited by week, and dried to calculate dry matter intake (DMI). Feed refusal and fecal samples were collected on 3 consecutive days at 3 timepoints, composited by heifer, dried, and analyzed to calculate neutral detergent fiber (NDF), organic matter (OM), and DM digestibility. Feed efficiency was calculated as feed conversion efficiency (FCE; DMI/average daily gain [ADG]) and residual feed intake (RFI; observed DMI-predicted DMI). Paired and individually housed heifers did not differ in DMI, ADG, FCE, or RFI. Although no differences were found in initial or final hip height, hip width, or chest girth, heifers which had been pair-housed maintained a greater BW than individually housed heifers during the trial. Methane production, intensity, and yield were similar between treatments. Pre-weaning paired or individual housing did not impact the number of visits or latency to approach the GreenFeed; approximately 50% of heifers in each treatment visited the GreenFeed within 8 h of exposure. Digestibility of OM, DM, and NDF were also similar between housing treatments. In conclusion, pre-weaning pair housing had no adverse effects on growth, feed efficiency, or methane emissions at 18 to 20 months of age.

An artificial intelligence approach of feature engineering and ensemble methods depicts the rumen microbiome contribution to feed efficiency in dairy cows

Genetic selection has remarkably helped U.S. dairy farms to decrease their carbon footprint by more than doubling milk production per cow over time. Despite the environmental and economic benefits of improved feed and milk production efficiency, there is a critical need to explore phenotypical variance for feed utilization to advance the long-term sustainability of dairy farms. Feed is a major expense in dairy operations, and their enteric fermentation is a major source of greenhouse gases in agriculture. The challenges to expanding the phenotypic database, especially for feed efficiency predictions, and the lack of understanding of its drivers limit its utilization. Herein, we leveraged an artificial intelligence approach with feature engineering and ensemble methods to explore the predictive power of the rumen microbiome for feed and milk production efficiency traits, as rumen microbes play a central role in physiological responses in dairy cows. The novel ensemble method allowed to further identify key microbes linked to the efficiency measures. We used a population of 454 genotyped Holstein cows in the U.S. and Canada with individually measured feed and milk production efficiency phenotypes. The study underscored that the rumen microbiome is a major driver of residual feed intake (RFI), the most robust feed efficiency measure evaluated in the study, accounting for 36% of its variation. Further analyses showed that several alpha-diversity metrics were lower in more feed-efficient cows. For RFI, [Ruminococcus] gauvreauii group was the only genus positively associated with an improved feed efficiency status while seven other taxa were associated with inefficiency. The study also highlights that the rumen microbiome is pivotal for the unexplained variance in milk fat and protein production efficiency. Estimation of the carbon footprint of these cows shows that selection for better RFI could reduce up to 5 kg of diet consumed per cow daily, potentially reducing up to 37.5% of CH4. These findings shed light that the integration of artificial intelligence approaches, microbiology, and ruminant nutrition can be a path to further advance our understanding of the rumen microbiome on nutrient requirements and lactation performance of dairy cows to support the long-term sustainability of the dairy community.

Consistency of dry matter intake in Holstein cows: Heritability estimates and associations with feed efficiency

Resilience can be defined as the capacity to maintain performance or bounce back to normal functioning after a perturbation, and studying fluctuations in daily feed intake may be an effective way to identify resilient dairy cows. Our goal was to develop new phenotypes based on daily dry matter intake (DMI) consistency in Holstein cows, estimate genetic parameters and genetic correlations with feed efficiency and milk yield consistency, and evaluate their relationships with production, longevity, health, and reproduction traits. Data consisted of 397,334 daily DMI records of 6,238 lactating Holstein cows collected from 2007 to 2022 at 6 research stations across the United States. Consistency phenotypes were calculated based on the deviations from expected daily DMI for individual cows during their respective feeding trials, which ranged from 27 to 151 d in duration. Expected values were derived from different models, including simple average, quadratic and cubic quantile regression with a 0.5 quantile, and locally estimated scatterplot smoothing (LOESS) regression with span parameters 0.5 and 0.7. We then calculated the log of variance (log-Var-DMI) of daily deviations for each model as the consistency phenotype. Consistency of milk yield was also calculated, as a reference, using the same methods (log-Var-Milk). Genetic parameters were estimated using an animal model, including lactation, days in milk and cohort as fixed effects, and animal as random effect. Relationships between log-Var-DMI and traits currently considered in the US national genetic evaluation were evaluated using Spearman's rank correlations between sires' breeding values. Heritability estimates for log-Var-DMI ranged from 0.11 ± 0.02 to 0.14 ± 0.02 across models. Different methods (simple average, quantile regressions, and LOESS regressions) used to calculate log-Var-DMI yielded very similar results, with genetic correlations ranging from 0.94 to 0.99. Estimated genetic correlations between log-Var-DMI and log-Var-Milk ranged from 0.51 to 0.62. Estimated genetic correlations between log-Var-DMI and feed efficiency ranged from 0.55 to 0.60 with secreted milk energy, from 0.59 to 0.63 with metabolic body weight, and from 0.26 to 0.31 with residual feed intake (RFI). Relationships between log-Var-DMI and the traits in the national genetic evaluation were moderate and positive correlations with milk yield (0.20 to 0.21), moderate and negative correlations with female fertility (-0.07 to -0.20), no significant correlations with health and longevity, and favorable correlations with feed efficiency (-0.23 to -0.25 with feed saved and 0.21 to 0.26 with RFI). We concluded that DMI consistency is heritable and may be an indicator of resilience. Cows with lower variation in the difference between actual and expected daily DMI (more consistency) may be more effective in maintaining performance in the face of challenges or perturbations, whereas cows with greater variation in observed versus expected daily DMI (less consistency) are less feed efficient and may be less resilient.

Impact of negative energy balance and postpartum diseases during the transition period on oocyte quality and embryonic development in dairy cows

Transition period is a critical time for dairy cows because a large proportion of clinical and subclinical diseases are observed in the first month after parturition. Occurrence of negative energy balance is associated with depressed immunity and these conditions can affect oocyte quality and further embryonic development. The aim of this study was to assess the effects of negative energy balance-associated disorders on in vitro embryo production (IVP) in dairy cattle. We hypothesized that subclinical metabolic and/or inflammatory disorders have a negative effect on oocyte developmental competence and morphokinetic parameters of the resulting embryos. The study was conducted on 30 lactating Holstein-Friesian cows which were assigned into four groups: healthy (HEAL, n = 6), metabolic disease (META, n = 8), inflammatory disease (INFL, n = 8), or combined metabolic and inflammatory disease (COMB, n = 8). Ovum pick-up (OPU) was performed twice weekly on all cows over a period of four weeks (n = 8 OPU sessions/cow) starting on the fifth week postpartum, and the collected oocytes were subjected to routine IVP. Donor's health status did not affect the number of oocytes/OPU or the recovery rate (p > 0.05). The number of quality 1 oocytes collected from INFL and COMB cows was lower compared to HEAL cows (p < 0.05). Also, the percentage of quality 1 embryos was reduced in META and COMB compared to HEAL cows (p < 0.05). Cleavage, blastocyst and hatching rates were similar among groups (p > 0.05). Presence of disease did not affect the time required by zygotes to reach specific developmental stages, as recorded by means of time-lapse monitoring. Nevertheless, there was a higher probability of direct cleavage after IVF in oocytes of COMB cows compared to those of HEAL cows (p < 0.05). In conclusion, oocytes and embryos derived from dairy cows diagnosed with subclinical metabolic and/or inflammatory diseases during the transition period showed reduced quality but similar developmental potential and morphokinetics when compared to healthy cows. These results shed light on the consequences of subclinical disease on embryonic development in dairy cows which might be important for embryo transfer programs.

Unveiling the Genetic Landscape of Feed Efficiency in Holstein Dairy Cows: Insights into Heritability, Genetic Markers, and Pathways via Meta-Analysis

Improving the feeding efficiency of dairy cows is a key component to improve the utilization of land resources and meet the demand for high-quality protein. Advances in genomic methods and omics techniques have made it possible to breed more efficient dairy cows through genomic selection. The aim of this review is to obtain a comprehensive understanding of the biological background of feed efficiency (FE) complex traits in purebred Holstein dairy cows including heritability estimate, and genetic markers, genes, and pathways participating in FE regulation mechanism. Through a literature search, we systematically reviewed the heritability estimation, molecular genetic markers, genes, biomarkers, and pathways of traits related to feeding efficiency in Holstein dairy cows. A meta-analysis based on a random-effects model was performed to combine reported heritability estimates of FE complex. The heritability of residual feed intake, dry matter intake, and energy balance was 0.20, 0.34, and 0.22, respectively, which proved that it was reasonable to include the related traits in the selection breeding program. For molecular genetic markers, a total of 13 single-nucleotide polymorphisms and copy number variance loci, associated genes, and functions were reported to be significant across populations. A total of 169 reported candidate genes were summarized on a large scale, using a higher threshold (adjusted P value < 0.05). Then, the subsequent pathway enrichment of these genes was performed. The important genes reported in the articles were included in a gene list and the gene list was enriched by gene ontology (GO):biological process (BP), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis. Three GO:BP terms and four KEGG terms were statistically significant, which mainly focused on adenosine triphosphate (ATP) synthesis, electron transport chain, and OXPHOS pathway. Among these pathways, involved genes such as ATP5MC2, NDUFA, COX7A2, UQCR, and MMP are particularly important as they were previously reported. Twenty-nine reported biological mechanisms along with involved genes were explained mainly by four biological pathways (insulin-like growth factor axis, lipid metabolism, oxidative phosphorylation pathways, tryptophan metabolism). The information from this study will be useful for future studies of genomic selection breeding and genetic structures influencing animal FE. A better understanding of the underlying biological mechanisms would be beneficial, particularly as it might address genetic antagonism.

Milk yield residuals and their link with the metabolic status of dairy cows in the transition period

The transition period is one of the most challenging periods in the lactation cycle of high-yielding dairy cows. It is commonly known to be associated with diminished animal welfare and economic performance of dairy farms. The development of data-driven health monitoring tools based on on-farm available milk yield development has shown potential in identifying health-perturbing events. As proof of principle, we explored the association of these milk yield residuals with the metabolic status of cows during the transition period. Over 2 yr, 117 transition periods from 99 multiparous Holstein-Friesian cows were monitored intensively. Pre- and postpartum dry matter intake was measured and blood samples were taken at regular intervals to determine β-hydroxybutyrate, nonesterified fatty acids (NEFA), insulin, glucose, fructosamine, and IGF1 concentrations. The expected milk yield in the current transition period was predicted with 2 previously developed models (nextMILK and SLMYP) using low-frequency test-day (TD) data and high-frequency milk meter (MM) data from the animal's previous lactation, respectively. The expected milk yield was subtracted from the actual production to calculate the milk yield residuals in the transition period (MRT) for both TD and MM data, yielding MRTTD and MRTMM. When the MRT is negative, the realized milk yield is lower than the predicted milk yield, in contrast, when positive, the realized milk yield exceeded the predicted milk yield. First, blood plasma analytes, dry matter intake, and MRT were compared between clinically diseased and nonclinically diseased transitions. MRTTD and MRTMM, postpartum dry matter intake and IGF1 were significantly lower for clinically diseased versus nonclinically diseased transitions, whereas β-hydroxybutyrate and NEFA concentrations were significantly higher. Next, linear models were used to link the MRTTD and MRTMM of the nonclinically diseased cows with the dry matter intake measurements and blood plasma analytes. After variable selection, a final model was constructed for MRTTD and MRTMM, resulting in an adjusted R2 of 0.47 and 0.73, respectively. While both final models were not identical the retained variables were similar and yielded comparable importance and direction. In summary, the most informative variables in these linear models were the dry matter intake postpartum and the lactation number. Moreover, in both models, lower and thus also more negative MRT were linked with lower dry matter intake and increasing lactation number. In the case of an increasing dry matter intake, MRTTD was positively associated with NEFA concentrations. Furthermore, IGF1, glucose, and insulin explained a significant part of the MRT. Results of the present study suggest that milk yield residuals at the start of a new lactation are indicative of the health and metabolic status of transitioning dairy cows in support of the development of a health monitoring tool. Future field studies including a higher number of cows from multiple herds are needed to validate these findings.

Between-individual variability on reticulorumen digesta passage rate in goats

Identifying factors that influence an individual's ability to utilize nutrients is a strategy for enhancing livestock sustainability. Digesta passage rate (kp) is one of the most important determinants that influence nutrient utilization. However, there is limited knowledge regarding the individual's variability on kp. The objective of this study was to investigate between-individual variability of reticulorumen (RR) kp of solutes and particles in goats, and its relationship to total NDF digestibility (NDFd). A dataset consisting of 103 individual records from two studies of castrated male (n = 36), female (n = 34), and intact male (n = 33) growing Saanen goats fed ad libitum and slaughtered at around 16.62 ± 0.96 (n = 21), 23.09 ± 1.33 (n = 19), 30.67 ± 2.25 kg (n = 29), 38.02 ± 1.61 (n = 16), and 44.12 ± 1.95 (n = 18) kg BW was used. The RR kp of solutes and particles were measured using Cr-EDTA and indigestible NDF (iNDF), respectively. Using mixed-effect models, considering sex and BW as fixed effects and study as random effect, we aimed to identify meaningful between-individual variance of RR kp of solutes and particles. Given the characteristic of our dataset (i.e., one observation per individual), our approach focused on exploring the variance between individuals described by the residuals of our fitted models. The RR kp of solutes and particles showed significant (P < 0.05) between-individual variation (CV ≈ 27%). Only 10% of RR kp of solutes variance was explained by DM intake (DMI) (g/d and g/d and g/kg BW) and NDF intake (NDFI); g/d), while 51.8% of the variance in RR kp of particles was explained by DMI and NDFI (g/d and g/kg BW), RR wet pool size, and iNDF:NDF intake ratio. The between-individual variation of RR kp of particles explained 19.5% of the between-individual variation in NDFd (P < 0.001). However, the nutritional and individual traits cited above (i.e., DMI, NDFI, RR wet pool size, and iNDF:NDF intake ratio) explained only 51.8% of the between-individual variation of RR kp of particles, while the remaining 48.2% was attributed to the individual's inherent characteristics, which in turn explained only 1.24% of the between-individual variation of NDFd (P = 0.146). The RR kp of particles and solutes showed meaningful between-individuals variance, which was partially related to both individual inherent characteristics and nutritional and animal traits. However, the NDFd was found to be unrelated to the inherent characteristics of RR kp of particles.

Social interactions, feeding patterns, and feed efficiency of same- and mixed-parity groups of lactating cows

Social dynamics in group-housed animals can have important effects on their welfare, feed efficiency, and production potential. Our objectives were to: (1) evaluate the effects of parity and social grouping on competition behavior, feeding patterns, and feed efficiency, and (2) investigate cow-level relationships between competition and feeding behavior, production, and feed efficiency. Fifty-nine Holstein cows (144.5 ± 21.8 starting days in milk, mean ± SD) were housed in a freestall pen with 30 Roughage Intake Control (RIC) bins. We evaluated the effects of parity (primiparous [PR, n = 29] vs. multiparous [MU, n = 30]) and group composition at the feed bunk (same-parity [SM, n = 39] vs. mixed-parity [MX, n = 20, 50% of each parity]) with a 2 × 2 factorial design (SM-MU: n = 20; SM-PR: n = 19; MX-MU: n = 10; MX-PR: n = 10) on competition behavior, feeding patterns, and feed efficiency. Within the pen, groups of 9 to 10 cows were considered subgroups and assigned to treatments defined by sets of 5 assigned bins (2:1 stocking density). Feed bunk competition and feeding patterns were recorded via continuous video in the first hour after morning feed delivery and 24-h RIC data, respectively. Residual feed intake (RFI) was calculated as the difference between predicted and observed dry matter intake (DMI) after accounting for known energy sinks. Linear models were used to evaluate the effects and interactions of parity and group composition on competition, feeding behavior, and feed efficiency. Within-cow correlations were performed between competition, feeding behavior, and RFI. Cows in MX, compared with SM, were involved in more competitive interactions [mean (95% CI): competitive contacts: 11.5 (8.1, 16.3) vs. 7.2 (5.5, 9.3) events; displacements: 4.0 (3.0, 5.3) vs. 2.1 (1.7, 2.7) events, and replacements: 3.5 (2.6, 4.7) vs. 1.9 (1.5, 2.5) events]. Cows in MX vs. those in SM had more bunk visits/meal ( 4.3 [3.9, 4.8] vs. 3.7 [3.4, 3.9] visits/meal) and longer meals (31.2 vs. 27.4 ± 0.9 min/meal) and tended to have higher RFI (0.41 ± 0.3 vs. -0.21 ± 0.2) and were therefore less feed efficient. Multiparous versus PR cows had greater DMI per day (29.3 ± 0.6 vs. 25.5 ± 0.4 kg/d) and per meal (4.2 [4.0, 4.4] vs. 3.4 [3.2, 3.6] kg/meal), faster eating rates (0.14 [0.13, 0.15] vs. 0.12 [0.11, 0.13] kg/min), and fewer bunk visits/d (26.6 [24.0, 29.4] vs. 32.8 [29.7, 35.9]). Regardless of grouping or parity, cows with shorter latencies to first visit the bunk after feed delivery were involved in more competition and tended to be less feed efficient. Overall, individual cow- and group-level relationships among competition, feeding behavior, and feed efficiency play an important role in feed bunk social dynamics. At a competitive 2:1 stocking density, mixed-parity groups for lactating cows may have potentially negative animal welfare and feed efficiency implications that should be considered when selecting grouping strategies on the farm.

Novel genetic parameters for genetic residual feed intake in dairy cattle using time series data from multiple parities and countries in North America and Europe

Residual feed intake is viewed as an important trait in breeding programs that could be used to enhance genetic progress in feed efficiency. In particular, improving feed efficiency could improve both economic and environmental sustainability in the dairy cattle industry. However, data remain sparse, limiting the development of reliable genomic evaluations across lactation and parity for residual feed intake. Here, we estimated novel genetic parameters for genetic residual feed intake (gRFI) across the first, second, and third parity, using a random regression model. Research data on the measured feed intake, milk production, and body weight of 7,379 cows (271,080 records) from 6 countries in 2 continents were shared through the Horizon 2020 project Genomic Management Tools to Optimise Resilience and Efficiency, and the Resilient Dairy Genome Project. The countries included Canada (1,053 cows with 47,130 weekly records), Denmark (1,045 cows with 72,760 weekly records), France (329 cows with 16,888 weekly records), Germany (938 cows with 32,614 weekly records), the Netherlands (2,051 cows with 57,830 weekly records), and United States (1,963 cows with 43,858 weekly records). Each trait had variance components estimated from first to third parity, using a random regression model across countries. Genetic residual feed intake was found to be heritable in all 3 parities, with first parity being predominant (range: 22-34%). Genetic residual feed intake was highly correlated across parities for mid- to late lactation; however, genetic correlation across parities was lower during early lactation, especially when comparing first and third parity. We estimated a genetic correlation of 0.77 ± 0.37 between North America and Europe for dry matter intake at first parity. Published literature on genetic correlations between high input countries/continents for dry matter intake support a high genetic correlation for dry matter intake. In conclusion, our results demonstrate the feasibility of estimating variance components for gRFI across parities, and the value of sharing data on scarce phenotypes across countries. These results can potentially be implemented in genetic evaluations for gRFI in dairy cattle.

N-3 Polyunsaturated Fatty Acids as a Nutritional Support of the Reproductive and Immune System of Cattle-A Review

This paper focuses on the role of n-3 fatty acids as a nutrient crucial to the proper functioning of reproductive and immune systems in cattle. Emphasis was placed on the connection between maternal and offspring immunity. The summarized results confirm the importance and beneficial effect of n-3 family fatty acids on ruminant organisms. Meanwhile, dietary n-3 fatty acids supplementation, especially during the critical first week for dairy cows experiencing their peripartum period, in general, is expected to enhance reproductive performance, and the impact of its supplementation appears to be dependent on body condition scores of cows during the drying period, the severity of the negative energy balance, and the amount of fat in the basic feed ration. An unbalanced, insufficient, or excessive fatty acid supplementation of cows' diets in the early stages of pregnancy (during fetus development) may affect both the metabolic and nutritional programming of the offspring. The presence of the polyunsaturated fatty acids of the n-3 family in the calves' ration affects not only the performance of calves but also the immune response, antioxidant status, and overall metabolism of the future adult cow.

Genomic evaluation of feed efficiency in US Holstein heifers

There is growing interest in improving feed efficiency traits in dairy cattle. The objectives of this study were to estimate the genetic parameters of residual feed intake (RFI) and its component traits [dry matter intake (DMI), metabolic body weight (MBW), and average daily gain (ADG)] in Holstein heifers, and to develop a system for genomic evaluation for RFI in Holstein dairy calves. The RFI data were collected from 6,563 growing Holstein heifers (initial body weight = 261 ± 52 kg; initial age = 266 ± 42 d) for 70 d, across 182 trials conducted between 2014 and 2022 at the STgenetics Ohio Heifer Center (South Charleston, OH) as part of the EcoFeed program, which aims to improve feed efficiency by genetic selection. The RFI was estimated as the difference between a heifer's actual feed intake and expected feed intake, which was determined by regression of DMI against midpoint MBW, age, and ADG across each trial. A total of 61,283 SNPs were used in genomic analyses. Animals with phenotypes and genotypes were used as training population, and 4 groups of prediction population, each with 2,000 animals, were selected from a pool of Holstein animals with genotypes, based on their relationship with the training population. All traits were analyzed using univariate animal model in DMU version 6 software. Pedigree information and genomic information were used to specify genetic relationships to estimate the variance components and genomic estimated breeding values (GEBV), respectively. Breeding values of the prediction population were estimated by using the 2-step approach: deriving the prediction equation of GEBV from the training population for estimation of GEBV of prediction population with only genotypes. Reliability of breeding values was obtained by approximation based on partitioning a function of the accuracy of training population GEBV and magnitudes of genomic relationships between individuals in the training and prediction population. Heifers had DMI (mean ± SD) of 8.11 ± 1.59 kg over the trial period, with growth rate of 1.08 ± 0.25 kg/d. The heritability estimates (mean ± SE) of RFI, MBW, DMI, and growth rate were 0.24 ± 0.02, 0.23 ± 0.02, 0.27 ± 0.02, and 0.19 ± 0.02, respectively. The range of genomic predicted transmitted abilities (gPTA) of the training population (-0.94 to 0.75) was higher compared with the range of gPTA (-0.82 to 0.73) of different groups of prediction population. Average reliability of breeding values from the training population was 58%, and that of prediction population was 39%. The genomic prediction of RFI provides new tools to select for feed efficiency of heifers. Future research should be directed to find the relationship between RFI of heifers and cows, to select individuals based on their lifetime production efficiencies.

Liver and Muscle Transcriptomes Differ in Mid-Lactation Cows Divergent in Feed Efficiency in the Presence or Absence of Supplemental Rumen-Protected Choline

Improving dairy cow feed efficiency is critical to the sustainability and profitability of dairy production, yet the underlying mechanisms that contribute to individual cow variation in feed efficiency are not fully understood. The objectives of this study were to (1) identify genes and associated pathways that are altered in cows with high- or low-residual feed intake (RFI) using RNA sequencing, and (2) determine if rumen-protected choline supplementation during mid-lactation would influence performance or feed efficiency. Mid-lactation (134 ± 20 days in milk) multiparous Holstein cows were randomly assigned to either supplementation of 0 g/d supplementation (CTL; n = 32) or 30 g/d of a rumen-protected choline product (RPC; 13.2 g choline ion; n = 32; Balchem Corp., New Hampton, NY, USA). Residual feed intake was determined as dry matter intake regressed on milk energy output, days in milk, body weight change, metabolic body weight, and dietary treatment. The 12 cows with the highest RFI (low feed efficient; LE) and 12 cows with the lowest RFI (high feed efficient; HE), balanced by dietary treatment, were selected for blood, liver, and muscle analysis. No differences in production or feed efficiency were detected with RPC supplementation, although albumin was greater and arachidonic acid tended to be greater in RPC cows. Concentrations of β-hydroxybutyrate were greater in HE cows. Between HE and LE, 268 and 315 differentially expressed genes in liver and muscle tissue, respectively, were identified through RNA sequencing. Pathway analysis indicated differences in cell cycling, oxidative stress, and immunity in liver and differences in glucose and fatty acid pathways in muscle. The current work indicates that unique differences in liver and muscle post-absorptive nutrient metabolism contribute to sources of variation in feed efficiency and that differences in amino acid and fatty acid oxidation, cell cycling, and immune function should be further examined.

Enhancing sustainability through resource efficiency in beef production systems using a sliding time window-based approach and frame scores

The food needs of the increasing global population, inefficiencies in supply chains, customer expectations and environmental concerns are the challenges to meeting resource-intensive protein needs sustainably. Collectively, this increases the need to enhance sustainability in the beef sector. This study proposes a sliding time-window-based multi-period livestock production model using mixed-integer linear programming (MILP) to simultaneously balance economic and environmental losses. It identifies the optimal finishing time using frame score (FS) and feed conversion ratio (FCR), targeting flexibility by allowing variable growth periods to reduce food/nutritional losses while meeting the variability in demands with minimum inventory levels. Furthermore, sequencing and assigning animals to facilities with optimum separation time is applied to avoid bad handling of animals and ensure quality meat with hygienic standards for longer shelf life. The system boundary of the proposed model includes beef farms and processing facilities. Compared to the recently proposed batch processing models over seven months with a herd size of 1980 animals, the findings reduce the average forage needed by ∼126.90 kips and methane emissions by ∼2560 kg, with a significant benefit in terms of the live animals' weight gain by ∼10,276 lbs.

Impact of parity differences on residual feed intake estimation in Holstein cows

Residual feed intake (RFI) has been used as a measure of feed efficiency in farm animals. In lactating dairy cattle, RFI is typically obtained as the difference between dry matter intake observations and predictions from regression on known energy sinks, and effects of parity, days in milk, and cohort. The impact of parity (lactation number) on the estimation of RFI is not well understood, so the objectives of this study were to (1) evaluate alternative RFI models in which the energy sinks (metabolic body weight, body weight change, and secreted milk energy) were nested or not nested within parity, and (2) estimate variance components and genetic correlations for RFI across parities. Data consisted of 72,474 weekly RFI records of 5,813 lactating Holstein cows collected from 2007 to 2022 in 5 research stations across the United States. Estimates of heritability, repeatability, and genetic correlations between weekly RFI for parities 1, 2, and 3 were obtained using bivariate repeatability animal models. The nested RFI model showed better goodness of fit than the nonnested model, and some partial regression coefficients of dry matter intake on energy sinks were heterogeneous between parities. However, the Spearman's rank correlation between RFI values calculated from nested and nonnested models was equal to 0.99. Similarly, Spearman's rank correlation between the RFI breeding values from these 2 models was equal to 0.98. Heritability estimates for RFI were equal to 0.16 for parity 1, 0.19 for parity 2, and 0.22 for parity 3. Repeatability estimates for RFI across weeks within parities were high, ranging from 0.51 to 0.57. Spearman's rank correlations of sires' breeding values were 0.99 between parities 1 and 2, 0.91 between parities 1 and 3, and 0.92 between parities 2 and 3. We conclude that nesting energy sinks within parity when computing RFI improves model goodness of fit, but the impact on the estimated breading values appears to be minimal.

Development of nutrigenomic based precision management model for Hanwoo steers

Focusing high marble deposition, Hanwoo feedlot system uses high-energy diet over the prolonged fattening period. However, due to the individual genetic variation, around 40% of them are graded into inferior quality grades (QG), despite they utilized the same resources. Therefore, focusing on development of a nutrigenomic based precision management model, this study was to evaluated the response to the divergent selection on genetic merit for marbling score (MS), under different dietary total digestible nutrient (TDN) levels. Total of 111 calves were genotyped and initially grouped according to estimated breeding value (high and low) for marbling score (MS-EBV). Subsequently, managed under two levels of feed TDN%, over the calf period, early, middle, and final fattening periods following 2 × 2 factorial arrangement. Carcasses were evaluated for MS, Back fat thickness (BFT) and Korean beef quality grading standard. As the direct response to the selection was significant, the results confirmed the importance of initial genetic grouping of Hanwoo steers for MS-EBV. However, dietary TDN level did not show an effect (p > 0.05) on the MS. Furthermore, no genetic-by-nutrition interaction for MS (p > 0.05) was also observed. The present results showed no correlation response on BFT (p > 0.05), which indicates that the selection based on MS-EBV can be used to enhance the MS without undesirable effect on BFT. Ultimate turnover of the Hanwoo feedlot operation is primarily determined by the QGs. The present model shows that the initial grouping for MS-EBV increased the proportion of carcasses graded for higher QGs (QG1⁺⁺ and QG1⁺) by approximately 20%. Moreover, there appear to be a potential to increase the proportion of QG 1⁺⁺ animals among the high-genetic group by further increasing the dietary energy content. Overall, this precision management strategy suggests the importance of adopting an MS based initial genetic grouping system for Hanwoo steers with a subsequent divergent management based on dietary energy level.

Genetic Analysis of Methane Emission Traits in Holstein Dairy Cattle

Genetic selection can be a feasible method to help mitigate enteric methane emissions from dairy cattle, as methane emission-related traits are heritable and genetic gains are persistent and cumulative over time. The objective of this study was to estimate heritability of methane emission phenotypes and the genetic and phenotypic correlations between them in Holstein cattle. We used 1765 individual records of methane emission obtained from 330 Holstein cattle from two Canadian herds. Methane emissions were measured using the GreenFeed system, and three methane traits were analyzed: the amount of daily methane produced (g/d), methane yield (g methane/kg dry matter intake), and methane intensity (g methane/kg milk). Genetic parameters were estimated using univariate and bivariate repeatability animal models. Heritability estimates (±SE) of 0.16 (±0.10), 0.27 (±0.12), and 0.21 (±0.14) were obtained for daily methane production, methane yield, and methane intensity, respectively. A high genetic correlation (rg = 0.94 ± 0.23) between daily methane production and methane intensity indicates that selecting for daily methane production would result in lower methane per unit of milk produced. This study provides preliminary estimates of genetic parameters for methane emission traits, suggesting that there is potential to mitigate methane emission in Holstein cattle through genetic selection.

Dairy Cows Are Limited in Their Ability to Increase Glucose Availability for Immune Function during Disease

Shortages of energy and glucose have been hypothesized to play a key role in the development of and responses to production diseases in dairy cows during early lactation. Given the importance of glucose for immune functions, we used a recently established method for the estimation of glucose balance (GB) to evaluate glucose availability during disease phases. A dataset comprising ration analyses as well as individual daily milk yields (MY), dry matter intake (DMI), body weights, and health records of 417 lactations (298 cows) was used to calculate individual daily GB and energy balance (EB). The magnitude and dynamics of MY, DMI, GB, and EB were evaluated in the weeks before, at, and after diagnoses of inflammatory diseases in different stages of early lactation from week in milk 1 to 15. Diagnoses were categorized as mastitis, claw and leg diseases, and other inflammatory diseases. Mixed linear models with a random intercept and slope term for each lactation were used to evaluate the effect of diagnosis on MY, DMI, GB, and EB while accounting for the background effects of week in milk, parity, season, and year. When unaffected by disease, in general, the GB of cows was close to zero in the first weeks of lactation and increased as lactation progressed. Weekly means of EB were negative throughout all lactation stages investigated. Disease decreased both the input of glucose precursors due to a reduced DMI as well as the output of glucose via milk due to a reduced MY. On average, the decrease in DMI was −1.5 (−1.9 to −1.1) kg and was proportionally higher than the decrease in MY, which averaged −1.0 (−1.4 to −0.6) kg. Mastitis reduced yield less than claw and leg disease or other diseases. On average, GB and EB were reduced by −3.8 (−5.6 to −2.1) mol C and −7.5 (−10.2 to −4.9) MJ in the week of diagnosis. This indicates the need to investigate strategies to increase the availability of glucogenic carbon for immune function during disease in dairy cows.

Effects of genomic estimated breeding value and dietary energy to protein ratio on growth performance, carcass trait, and lipogenic gene expression in Hanwoo steer

"Genome-based precision feeding" is a concept that involves the application of customised diets to different genetic groups of cattle. We investigated the effects of the genomic estimated breeding value (gEBV) and dietary energy to protein ratio (DEP) on growth performance, carcass traits, and lipogenic gene expression in Hanwoo (Korean cattle) steers. Forty-four Hanwoo steers (BW = 636 kg, age = 26.9 months) were genotyped using the Illumina Bovine 50 K BeadChip. The gEBV was calculated using genomic best linear unbiased prediction. Animals were separated into high gEBV of marbling score or low-gMS groups based on the upper and lower 50% groupings of the reference population, respectively. Animals were assigned to one of four groups in a 2 × 2 factorial arrangement: high gMS/high DEP (0.084 MJ/g), high gMS/low DEP (0.079 MJ/g), low gMS/high DEP, and low gMS/low DEP. Steers were fed concentrate with a high or low DEP for 31 weeks. The BW tended to be higher (0.05 < P < 0.1) in the high-gMS groups compared to the low-gMS groups at 0, 4, 8, 12, and 20 weeks. The average daily gain (ADG) tended to be lower (P = 0.08) in the high-gMS group than in the low-gMS group. Final BW and measured carcass weight (CW) were positively correlated with the gEBV of carcass weight (gCW). The DEP did not affect ADG. Neither the gMS nor the DEP affected the MS and beef quality grade. The intramuscular fat (IMF) content in the longissimus thoracis (LT) tended to be higher (P = 0.08) in the high-gMS groups than in the low-gMS groups. The mRNA levels of lipogenic acetyl-CoA carboxylase and fatty acid binding protein 4 genes in the LT were higher (P < 0.05) in the high-gMS group than in the low-gMS group. Overall, the IMF content tended to be affected by the gMS, and the genetic potential (i.e., gMS) was associated with the functional activity of lipogenic gene expression. The gCW was associated with the measured BW and CW. The results demonstrated that the gMS and the gCW may be used as early prediction indexes for meat quality and growth potential of beef cattle.

Genetic analysis of production traits and body size measurements and their relationships with metabolic diseases in German Holstein cattle

This study sheds light on the genetic complexity and interplay of production, body size, and metabolic health in dairy cattle. Phenotypes for body size-related traits from conformation classification (130,166 animals) and production (101,562 animals) of primiparous German Holstein cows were available. Additionally, 21,992, 16,641, and 7,096 animals were from herds with recordings of the metabolic diseases ketosis, displaced abomasum, and milk fever in first, second, and third lactation. Moreover, all animals were genotyped. Heritabilities of traits and genetic correlations between all traits were estimated and GWAS were performed. Heritability was between 0.240 and 0.333 for production and between 0.149 and 0.368 for body size traits. Metabolic diseases were lowly heritable, with estimates ranging from 0.011 to 0.029 in primiparous cows, from 0.008 to 0.031 in second lactation, and from 0.037 to 0.052 in third lactation. Production was found to have negative genetic correlations with body condition score (BCS; -0.279 to -0.343) and udder depth (-0.348 to -0.419). Positive correlations were observed for production and body depth (0.138-0.228), dairy character (DCH) (0.334-0.422), and stature (STAT) (0.084-0.158). In first parity cows, metabolic disease traits were unfavorably correlated with production, with genetic correlations varying from 0.111 to 0.224, implying that higher yielding cows have more metabolic problems. Genetic correlations of disease traits in second and third lactation with production in primiparous cows were low to moderate and in most cases unfavorable. While BCS was negatively correlated with metabolic diseases (-0.255 to -0.470), positive correlations were found between disease traits and DCH (0.269-0.469) as well as STAT (0.172-0.242). Thus, the results indicate that larger and sharper animals with low BCS are more susceptible to metabolic disorders. Genome-wide association studies revealed several significantly associated SNPs for production and conformation traits, confirming previous findings from literature. Moreover, for production and conformation traits, shared significant signals on Bos taurus autosome (BTA) 5 (88.36 Mb) and BTA 6 (86.40 to 87.27 Mb) were found, implying pleiotropy. Additionally, significant SNPs were observed for metabolic diseases on BTA 3, 10, 14, 17, and 26 in first lactation and on BTA 2, 6, 8, 17, and 23 in third lactation. Overall, this study provides important insights into the genetic basis and interrelations of relevant traits in today's Holstein cattle breeding programs, and findings may help to improve selection decisions.

Animal board invited review: Genomic-based improvement of cattle in response to climate change

Climate change brings challenges to cattle production, such as the need to adapt to new climates and pressure to reduce greenhouse emissions (GHG). In general, the improvement of traits in current breeding goals is favourably correlated with the reduction of GHG. Current breeding goals and tools for increasing cattle production efficiency have reduced GHG. The same amount of production can be achieved by a much smaller number of animals. Genomic selection (GS) may offer a cost-effective way of using an efficient breeding approach, even in low- and middle-income countries. As climate change increases the intensity of heatwaves, adaptation to heat stress leads to lower efficiency of production and, thus, is unfavourable to the goal of reducing GHG. Furthermore, there is evidence that heat stress during cow pregnancy can have many generation-long lowering effects on milk production. Both adaptation and reduction of GHG are among the difficult-to-measure traits for which GS is more efficient and suitable than the traditional non-genomic breeding evaluation approach. Nevertheless, the commonly used within-breed selection may be insufficient to meet the new challenges; thus, cross-breeding based on selecting highly efficient and highly adaptive breeds may be needed. Genomic introgression offers an efficient approach for cross-breeding that is expected to provide high genetic progress with a low rate of inbreeding. However, well-adapted breeds may have a small number of animals, which is a source of concern from a genetic biodiversity point of view. Furthermore, low animal numbers also limit the efficiency of genomic introgression. Sustainable cattle production in countries that have already intensified production is likely to emphasise better health, reproduction, feed efficiency, heat stress and other adaptation traits instead of higher production. This may require the application of innovative technologies for phenotyping and further use of new big data techniques to extract information for breeding.

Prediction of dry matter intake and gross feed efficiency using milk production and live weight in first-parity Holstein cows

Direct measurement of dry matter intake (DMI) presents a major challenge in estimating gross feed efficiency (GFE) in dairy cattle. This challenge can, however, be resolved through the prediction of DMI and GFE from easy-to-measure traits such as milk production (i.e. milk yield, energy-corrected milk (ECM), butterfat, protein, lactose) and live weight (LW). The main objective of this study was, therefore, to investigate the feasibility of predicting dry matter intake and gross feed efficiency for first-parity Holstein cows using milk production traits and LW. Data comprised of 30 daily measurements of DMI and milk production traits, and 25 daily LW records of a group of 100 first-parity Holstein cows, fed a total mixed ration. Gross feed efficiency was calculated as kg ECM divided by kg DMI. The initial step was to estimate correlations of milk production traits and LW with DMI and GFE, to identify the best potential predictors of DMI and GFE. Subsequently, a forward stepwise regression analysis was used to develop models to predict DMI and GFE from LW and milk production traits, followed by within-herd validations. Means for DMI, butterfat yield (BFY) and LW were 21.91 ± 2.77 kg/day, 0.95 ± 0.14 kg/day and 572 ± 15.58 kg/day, respectively. Mean GFE was 1.32 ± 0.22. Dry matter intake had positive correlations with milk yield (MY) (r = 0.32, p < 0.001) and LW (r = 0.76, p < 0.0001) and an antagonistic association with butterfat percent (BFP) (r =  - 0.55, p < 0.001). On the other hand, GFE was positively associated with MY (r = 0.36, p < 0.001), BFP (r = 0.53, p < 0.001) and BFY (r = 0.83, p < 0.0001), and negatively correlated with LW (r =  - 0.23, p > 0.05). Dry matter intake was predicted reliably by a model comprising of only LW and MY (R² = 0.79; root mean squared error (RMSE) = 1.05 kg/day). A model that included BFY, MY and LW had the highest ability to predict GFE (R² = 0.98; RMSE = 0.05). Live weight and BFY were the main predictor traits for DMI and GFE, respectively. The best models for predicting DMI and GFE were as follows: DMI (kg/day) =  - 54.21 - 0.192 × MY (kg/day) + 0.146 × LW (kg/day) and GFE (kg/day) = 4.120 + 0.024 × MY (kg/day) + 1.000 × BFY (kg/day) - 0.008 × LW (kg/day). Thus, daily DMI (kg/day) and GFE can be reliably predicted from LW and milk production traits using these developed models in first-parity Holstein cows. This presents a big promise to generate large quantities of data of individual cow DMI and GFE, which can be used to implement genetic improvement of feed efficiency.

Full-lactation performance of multiparous dairy cows with differing residual feed intake

Residual feed intake (RFI) is an efficiency trait underpinning profitability and environmental sustainability in dairy production. This study compared performance during a complete lactation of 36 multiparous dairy cows divided into three equal-sized groups with high (HRFI), intermediate (IRFI) or low RFI (LRFI). Residual feed intake was determined by two different equations. Residual feed intake according to the NorFor system was calculated as (RFI_NorFor) = (NE_intake)–(NE_maintenance + NE_gestation + NE_milk—NE_mobilisation + NE_deposition). Residual feed intake according to the USA National Research Council (NRC) (RFI_NRC) was calculated as: RFI = DMI − predicted DMI where predicted_s DMI = [(0.372× ECM)+(0.0968×BW^0.75)]×(1−e^{−0.192×(DIM/7+3.67)}). Cows in the HRFI_NorFor group showed higher daily CH₄ production, CH₄/ECM and CH₄ yield (g/kg DMI) than IRFI_NorFor and LRFI_NorFor cows. Cows characterized by high efficiency (LRFI_NorFor) according to the NorFor system had lower body weight. Dry matter intake and apparent dry matter digestibility were not affected by efficiency group but milk yield was lower in the low efficiency, HRFI_NorFor, group. Cows characterized by high efficiency according to the NRC system (LRFI_NRC) had lower dry matter intake while yield of CH₄ was higher. Daily CH₄ production and CH₄ g/kg ECM did not differ between RFI_NRC groups. Dairy cows characterized by high efficiency (both LRFI_NorFor and LRFI_NRC cows) over a complete lactation mobilized more of their body reserves in early lactation as well as during the complete lactation. The results also indicated great phenotypic variation in RFI between different stages the lactation.

Retained energy in lactating beef cows; effects on maintenance energy requirement and voluntary feed intake

The objectives of these experiments were to determine the relationship between maintenance requirements and energy partitioned to maternal tissue or milk production in limit-fed Angus cows and to determine the relationship between retained energy during the lactation period to dry-period voluntary forage intake (VDMI). Twenty-four mature fall-calving Angus cows were used in a 79-d study during late lactation to establish daily metabolizable energy required for maintenance (ME_m). Cows were individually fed daily a mixed diet (2.62 Mcal MEl/kg, 18.2% crude protein) to meet energy and protein requirements of 505 kg beef cows producing 8.2 kg milk daily. If cow BW changed by ±9 kg from initial BW, daily feed intake was adjusted to slow BW loss or reduce BW gain. Milk yield and composition were determined on 3 occasions throughout the study. Maintenance was computed as metabolizable energy intake minus retained energy assigned to average daily maternal tissue energy change, average daily milk energy yield, and average daily energy required for pregnancy. After calves were weaned, cows were fed a low-quality grass hay diet (8.2% crude protein, 65% NDF) and VDMI was measured for 21 days. Lactation maintenance energy was 83% the default value recommended by NASEM (2016. Nutrient Requirements of Beef Cattle: Eighth Revised Edition.) for lactating Angus cows. Increasing lactation-period retained energy (decreasing BW loss and increasing milk energy yield) was associated with lower maintenance energy requirements (P < 0.01; R² = 0.92). Increased residual daily gain during lactation was associated with lower lactation maintenance energy requirements (P = 0.05; R² = 0.17). Post-weaning VDMI was not related to late-lactation milk energy production, although sensitive to lactation period BCS and BW loss. These results contradict previous reports, suggesting that maintenance requirements increase with increasing milk yield.

Maladaptation to the transition period and consequences on fertility of dairy cows

After parturition, dairy cows undergo a plethora of metabolic, inflammatory, and immunologic changes to adapt to the onset of lactation. These changes are mainly due to the homeorhetic shift to support milk production when nutrient demand exceeds dietary intake, resulting in a state of negative energy balance. Negative energy balance in postpartum dairy cows is characterized by upregulated adipose tissue modelling, insulin resistance, and systemic inflammation. However, half of the postpartum cows fail to adapt to these changes and develop one or more types of clinical and subclinical disease within 5 weeks after calving, and this is escorted by impaired reproductive performance in the same lactation. Maladaptation to the transition period exerts molecular and structural changes in the follicular and reproductive tract fluids, the microenvironment in which oocyte maturation, fertilization, and embryo development occur. Although the negative effects of transition diseases on fertility are well-known, the involved pathways are only partially understood. This review reconstructs the mechanism of maladaptation to lactation in the transition period, explores their key (patho)physiological effects on reproductive organs, and briefly describes potential carryover effects on fertility in the same lactation.

Plasma essential amino acid concentration and profile are associated with performance of lactating dairy cows as revealed through meta-analysis and hierarchical clustering

Our aim was to explore whether changes in plasma essential AA (EAA) concentration ([EAA]_p) or profile (defined here as the molar proportion of individual [EAA]_p relative to the total [EAA]_p) may serve as an indicator of the EAA status of a cow. We undertook a meta-analysis with the objectives to determine if different plasma EAA profiles exist among cows and to explore the association of [EAA]_p or the profile of EAA with lactating cow performance and measures of N utilization. We hypothesized the existence of differences in [EAA]_p and different plasma EAA profile for cows with greater milk output, feed efficiency, and greater N use efficiency (NUE; milk true protein-N:N intake) compared with cows with lower milk output, feed efficiency, and lower NUE. The data set included 22 feeding trials and 96 dietary treatments. First, a mixed-effect model analysis was used to predict [EAA]_p in response to the categorical fixed effect of EAA, continuous fixed effect of National Research Council model-predicted metabolizable protein (MP) supply, continuous fixed effect of body weight, the fixed effect of EAA and MP supply interaction, the fixed effect of EAA and body weight interaction, and the random effect of study. Then, residuals of the model were standardized based on Z-score and clustered using the hierarchical method (Euclidean distance and Ward's minimum variance method) resulting in 2 clusters. Finally, a fixed-effect model was used to evaluate the significance with which clusters were associated with [EAA]_p, cow performance, feed efficiency, and NUE. The total concentration of [EAA]_p was lower (784 vs. 983 µM) and the concentration of each EAA was on average 22 µM lower for cows in cluster 1 compared with cluster 2 with the smallest and greatest difference found for Met (4 µM) and Val (59 µM), respectively. The percentage difference in [EAA]_p was the smallest for Thr (-5.3%) and the greatest for Leu (-37.1%). There was no difference between clusters for Arg, His, and Met molar proportions; however, cows in cluster 1 had a lower molar proportion of Leu and a tendency for lower molar proportion of Val compared with cows in cluster 2. Additionally, cows in cluster 1 had greater molar proportions of Ile, Lys, and Thr and a tendency for greater molar proportion of Phe compared with cows in cluster 2. The fixed-effect model analysis indicated that cows in cluster 1 had higher milk energy output (+3.2 Mcal/d), true protein yield (+87 g/d) and fat yield (+236 g/d), feed efficiency (milk Mcal:dry matter intake; +8% unit), and a tendency for greater MP efficiency (Milk true protein/MP supply; +2.3% unit) than cows in cluster 2. These results suggested greater use of EAA by the mammary gland (as reflected by greater milk protein synthesis) and lower hepatic catabolism of AA (as reflected by a tendency to greater MP efficiency) in cows of cluster 1 compared with cluster 2. Our findings should be evaluated further, including whether the relative molar proportions of plasma EAA might serve as a holistic indicator of the EAA status of cows as related to their productivity, feed efficiency and N utilization.

Association of Residual Feed Intake With Blood Metabolites and Reproduction in Holstein Cows

The objectives of this study were to evaluate the associations between residual dry matter (DM) intake or residual feed intake (RFI) from 1 to 15 weeks postpartum and concentrations of metabolites in plasma in early lactation and reproduction in Holstein cows. Data from 9 experiments, including 851 cows, were used. Intake of DM, milk yield, and body weight were evaluated daily, whereas milk composition and body condition were evaluated twice weekly for the first 105 days postpartum. Blood was sampled on the day of calving and again on days 7, 14, and 21 postpartum and analyzed for concentrations of non-esterified fatty acids (FA), β-hydroxybutyrate (BHB), and glucose. Reproduction was evaluated for the first 300 days postpartum. Residual DM intake was calculated as the observed minus the predicted intake, with intake predicted based on a model that accounted for major energy sinks. Cows were ranked and categorized into RFI quartiles, from the smallest (Q1) to the largest (Q4) RFI (−1.87, −0.46, 0.39, and 1.90 kg/day). Increasing efficiency (i.e., from Q4 to Q1) resulted in linear decreases in DM intake (Q1 to Q4; 18.9, 20.4, 21.3, and 22.7 kg/day), and median days open (132, 125, 135, and 147 d). Conversely, improving efficiency was associated with a linear increase in pregnancy per artificial insemination (AI, 31.4, 30.6, 31.2, and 24.5%) and quadratic increases in the 21-day cycle pregnancy rate (21.2, 21.1, 22.0, and 16.6%) and the proportion of pregnant cows (79.0, 80.7, 82.4, and 71.5%). The estimated net energy for lactation (NEL) content of diets increased linearly with improved RFI (1.88, 1.76, 1.71, and 1.58 Mcal/kg), resulting in no association between RFI and energy-corrected milk yield or body energy change. Nevertheless, increased feed efficiency was associated with a linear increase in concentrations of blood FA (0.68, 0.63, 0.60, and 0.59 mM), but a quadratic association with BHB (0.75, 0.64, 0.64, and 0.65 mM), with no association with glucose. Collectively, the most feed efficient cows ate 3.8 kg/day less DM, produced the same amount of energy-corrected milk, and had improved reproductive performance compared with the least efficient cows, thus suggesting that the underlying mechanisms responsible for improved feed efficiency might also be linked with improvements in reproduction.

Translational multi-omics microbiome research for strategies to improve cattle production and health

Cattle microbiome plays a vital role in cattle growth and performance and affects many economically important traits such as feed efficiency, milk/meat yield and quality, methane emission, immunity and health. To date, most cattle microbiome research has focused on metataxonomic and metagenomic characterization to reveal who are there and what they may do, preventing the determination of the active functional dynamics in vivo and their causal relationships with the traits. Therefore, there is an urgent need to combine other advanced omics approaches to improve microbiome analysis to determine their mode of actions and host-microbiome interactions in vivo. This review will critically discuss the current multi-omics microbiome research in beef and dairy cattle, aiming to provide insights on how the information generated can be applied to future strategies to improve production efficiency, health and welfare, and environment-friendliness in cattle production through microbiome manipulations.

Emerging Roles of Non-Coding RNAs in the Feed Efficiency of Livestock Species

A global population of already more than seven billion people has led to an increased demand for food and water, and especially the demand for meat. Moreover, the cost of feed used in animal production has also increased dramatically, which requires animal breeders to find alternatives to reduce feed consumption. Understanding the biology underlying feed efficiency (FE) allows for a better selection of feed-efficient animals. Non-coding RNAs (ncRNAs), especially micro RNAs (miRNAs) and long non-coding RNAs (lncRNAs), play important roles in the regulation of bio-logical processes and disease development. The functions of ncRNAs in the biology of FE have emerged as they participate in the regulation of many genes and pathways related to the major FE indicators, such as residual feed intake and feed conversion ratio. This review provides the state of the art studies related to the ncRNAs associated with FE in livestock species. The contribution of ncRNAs to FE in the liver, muscle, and adipose tissues were summarized. The research gap of the function of ncRNAs in key processes for improved FE, such as the nutrition, heat stress, and gut–brain axis, was examined. Finally, the potential uses of ncRNAs for the improvement of FE were discussed.

Evaluation of Ingestive Behavior, Ruminal and Blood Parameters, Performance, and Thermography as a Phenotypic Divergence Markers of Residual Feed Intake in Rearing Dairy Heifers

Simple Summary

The selection of highly efficient animals will support meeting the world’s future demand for products and food of animal origin. Thus, the identification of efficient animals and an understanding of the mechanisms inherent to this efficiency is fundamental for the progress of breeding systems. In the present study, we identify highly efficient animals for residual feed intake in dairy heifers. This animal category is unexplored in relation to this index. We utilized the classical parameters evaluated in cattle of different ages to carry out the study on these animals.

Abstract

The objectives of this study were: (1) to identify and rank phenotypically divergent animals for residual feed intake (RFI) regarding their efficiency (high: HE or low: LE); (2) to evaluate their relationships with ingestive behavior, ruminal and blood parameters, performance, and infrared thermography; and (3) to determine if such measurements can be used as feed efficiency markers in rearing dairy heifers. Thirty-eight heifers, 143 d ± 4 (Mean ± SD) of age and 108.7 kg ± 17.9 of body weight were used. The animals were fed with a total mixed ration during the 91 d of the trial. A phenotypic divergence of DMI for RFI was observed between −0.358 and 0.337 kg/d for HE and LE, respectively. Dry matter intake (DMI) was lower in the HE (2.5 kg DMI/d vs. 3.1 kg DMI/d), as was the number of visits to the feed bin with consumption (59 vs. 71). Feed intake was the best predictor of said divergence. Water intake and number of visits to the feed bin were presented moderate correlations with RFI. The ruminal fermentation variables, blood metabolites, blood hormones (such as the other ingestive behavior variables), and infrared thermography were not able to accurately predict HE or LE animals.

Genetic parameters for body weight and milk production of dairy Gyr herds

The aim of this study was to estimate genetic parameters for cow weight at calving (CW) and cumulative 305-day milk yield (MY305) in dairy Gyr cattle by two-trait analysis. The study used 1,847 CW records, in which 418 females presented more than one measure, and 4,048 MY305 records, wherein 1068 females provided repeated measures, from 2,339 females belonging to three herds, which calved between 1986 and 2019. Variance components were estimated by the restricted maximum likelihood method (REML) using a two-trait animal model. The model included direct additive genetic, permanent environmental and residual effects as random effects and the fixed effects of contemporary group, formed by animals that had calved on the same farm year and season, and age of cow at calving as covariates (fitted as linear and quadratic effect). The heritability estimates for CW and MY305 were 0.21 ± 0.06 and 0.29 ± 0.04, respectively, and repeatability estimates were 0.49 ± 0.03 and 0.49 ± 0.02. The genetic correlation between CW and MY305 was positive and of low magnitude (0.33 ± 0.18), indicating that selection for MY305 will cause little genetic change in the weights of dairy Gyr animals. The genetic trends of breeding values of analyzed traits showed marked genetic gains in MY305, with little changes in CW of dairy Gyr cows over the years in the herds studied, which is an important result considering the production systems adopted in the tropics.

Opportunities to Harness High-Throughput and Novel Sensing Phenotypes to Improve Feed Efficiency in Dairy Cattle

Simple Summary

Sensors, routinely collected on-farm tests, and other repeatable, high-throughput measurements can provide novel phenotype information on a frequent basis. Information from these sensors and high-throughput measurements could be harnessed to monitor or predict individual dairy cow feed intake. Predictive algorithms would allow for genetic selection of animals that consume less feed while producing the same amount of milk. Improved monitoring of feed intake could reduce the cost of milk production, improve animal health, and reduce the environmental impact of the dairy industry. Moreover, data from these information sources could aid in animal management (e.g., precision feeding and health detection). In order to implement tools, the relationship of measurements with feed intake needs to be established and prediction equations developed. Lastly, consideration should be given to the frequency of data collection, the need for standardization of data and other potential limitations of tools in the prediction of feed intake. This review summarizes measurements of feed efficiency, factors that may impact the efficiency and feed consumption of an animal, tools that have been researched and new traits that could be utilized for the prediction of feed intake and efficiency, and prediction equations for feed intake and efficiency presented in the literature to date.

Abstract

Feed for dairy cattle has a major impact on profitability and the environmental impact of farms. Sustainable dairy production relies on continued improvement in feed efficiency as a way to reduce costs and nutrient loss from feed. Advances in breeding, feeding and management have led to the dilution of maintenance energy and thus more efficient dairy cattle. Still, many additional opportunities are available to improve individual animal feed efficiency. Sensing technologies such as wearable sensors, image-based and high-throughput phenotyping technologies (e.g., milk testing) are becoming more available on commercial farm. The application of these technologies as indicator traits for feed intake and efficiency related traits would be advantageous to provide additional information to predict and manage feed efficiency. This review focuses on precision livestock technologies and high-throughput phenotyping in use today as well as those that could be developed in the future as possible indicators of feed intake. Several technologies such as milk spectral data, activity, rumen measures, and image-based phenotypes have been associated with feed intake. Future applications will depend on the ability to repeatably measure and calibrate these data across locations, so that they can be integrated for use in predicting and managing feed intake and efficiency on farm.

The Potential of Using Temperate-Tropical Crossbreds and Agricultural by-Products, Associated with Heat Stress Management for Dairy Production in the Tropics: A Review

The demand and consumption of dairy products are expected to increase exponentially in developing countries, particularly in tropical regions. However, the intensification of dairy production to meet this increasing demand has its challenges. The challenges ranged from feed costs, resources, and their utilization, as well as the heat stress associated with rearing temperate-tropical crossbred cattle in the tropics. This article focused on key nutritional and environmental factors that should be considered when temperate-tropical crossbred cattle are used in the tropics. The article also describes measures to enhance the utilization of regional feed resources and efforts to overcome the impacts of heat stress. Heat stress is a major challenge in tropical dairy farming, as it leads to poor production, despite the genetic gains made through crossbreeding of high production temperate cattle with hardy tropical animals. The dependence on imported feed and animal-man competition for the same feed resources has escalated feed cost and food security concerns. The utilization of agricultural by-products and production of stable tropical crossbreds will be an asset to tropical countries in the future, more so when scarcity of feed resources and global warming becomes a closer reality. This initiative has far-reaching impacts in the tropics and increasingly warmer areas of traditional dairying regions in the future.

Circulating Metabolites Indicate Differences in High and Low Residual Feed Intake Holstein Dairy Cows

Selection for more feed efficient dairy cows is key to improving sustainability and profitability of dairy production; however, underlying mechanisms contributing to individual animal feed efficiency are not fully understood. The objective of this study was to identify circulating metabolites, and pathways associated with those metabolites, that differ between efficient and inefficient Holstein dairy cows using targeted metabolite quantification and untargeted metabolomics. The top and bottom fifteen percent of cows (n = 28/group) with the lowest and highest residual feed intake in mid-lactation feed efficiency trials were grouped retrospectively as high-efficient (HE) and low-efficient (LE). Blood samples were collected for quantification of energy metabolites, markers of hepatic function, and acylcarnitines, in addition to a broader investigation using untargeted metabolomics. Short-chain acylcarnitines, C3-acylcarnitine, and C4-acylcarntine were lower in HE cows (n = 18/group). Untargeted metabolomics and multivariate analysis identified thirty-nine differential metabolites between HE and LE (n = 8/group), of which twenty-five were lower and fourteen were higher in HE. Pathway enrichment analysis indicated differences in tryptophan metabolism. Combined results from targeted metabolite quantification and untargeted metabolomics indicate differences in fatty acid and amino acid metabolism between HE and LE cows. These differences may indicate post-absorptive nutrient use efficiency as a contributor to individual animal variation in feed efficiency.

Association of Feed Efficiency, Feeding Rate, and Behaviour with the Milk Performance of Dairy Cows

Identification of the associations of cow feed efficiency with feeding behaviour and milk production is important for supporting recommendations of strategies that optimise milk yield. The objective of this study was to identify associations between measures of feed efficiency, feed intake, feeding rate, rumination time, feeding time, and milk production using data collected from 26 dairy cows during a 3 month period in 2018. Cows averaged (mean ± standard deviation) 2.2 ± 1.7 lactations, 128 ± 40 days in milk, 27.5 ± 5.5 kg/day milk, 1.95 ± 0.69 kg feed/1 kg milk—the measure used to express feed conversion ratio (FCR), 575 ± 72 min/day rumination time, and 264 ± 67 min/day feeding time during the observation period. The coefficient of variation for rumination time (min/d) was 12.5%. A mixed linear model was selected for analyses. The most feed inefficient cows with the highest FCR (≥2.6 kg feed/1 kg milk) showed the lowest milk yield (24.8 kg/day), highest feed intake (78.8 kg), highest feeding rate (0.26 kg/min) and BCS (3.35 point). However, the relative milk yield (milk yield per 100 kg of body weight) was the highest (4.01 kg/day) in the most efficient group with the lowest FCR (≤1.4 kg feed/1 kg milk). Our study showed that the most efficient cows with the lowest FCR (≤1.4 kg feed/1 kg milk) had the highest rumination time (597 min/day; p < 0.05), feeding time (298 min/day; p < 0.05), rumination/activity ratio (4.39; p < 0.05) and rumination/feeding ratio (2.04; p < 0.05). Less active cows (activity time 164 min/day; p < 0.05) were the most efficient cows with the lowest FCR (≤1.4 kg feed/1 kg milk). The behavioural differences observed in this study provide new insight into the association of feed behaviour and feed efficiency with milk performance. Incorporating feeding behaviour into the dry matter intake model can improve its accuracy in the future and benefit breeding programmes.