Invited review: Improving feed efficiency in dairy production: challenges and possibilities

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

Large datasets allow estimation of 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 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 DIM, age-parity subclass, trial date, management group, and BW 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, respectively) 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 ECM 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, whereas the sire genomic regressions indicated approximately 35% more DMI for fat than protein. Estimates of annual maintenance in kilograms DMI/kilograms BW per 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 the National Academies for Science, Engineering, and Medicine 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 BW 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.

Milk transcriptome biomarker identification to enhance feed efficiency and reduce nutritional costs in dairy ewes

In recent years, rising prices for high-quality protein-based feeds have significantly increased nutrition costs. Consequently, investigating strategies to reduce these expenses and improve feed efficiency (FE) have become increasingly important for the dairy sheep industry. This research investigates the impact of nutritional protein restriction (NPR) during prepuberty and FE on the milk transcriptome of dairy Assaf ewes (sampled during the first lactation). To this end, we first compared transcriptomic differences between NPR and control ewes. Subsequently, we evaluated gene expression differences between ewes with divergent FE, using feed conversion ratio (FCR), residual feed intake (RFI), and consensus classifications of high- and low-FE animals for both indices. Lastly, we assess milk gene expression as a predictor of FE phenotype using random forest. No effect was found for the prepubertal NPR on milk performance or FE. Moreover, at the milk transcriptome level, only one gene, HBB, was differentially expressed between the NPR (n = 14) and the control group (n = 14). Further, the transcriptomic analysis between divergent FE sheep revealed 114 differentially expressed genes (DEGs) for RFI index (high-FERFI = 10 vs low-FERFI = 10), 244 for FCR (high-FEFCR = 10 vs low-FEFCR = 10), and 1 016 DEGs between divergent consensus ewes for both indices (high-FEconsensus = 8 vs low-FEconsensus = 8). These results underscore the critical role of selected FE indices for RNA-Seq analyses, revealing that consensus divergent animals for both indices maximise differences in transcriptomic responses. Genes overexpressed in high-FEconsensus ewes were associated with milk production and mammary gland development, while low-FEconsensus genes were linked to higher metabolic expenditure for tissue organisation and repair. The best prediction accuracy for FE phenotype using random forest was obtained for a set of 44 genes consistently differentially expressed across lactations, with Spearman correlations of 0.37 and 0.22 for FCR and RFI, respectively. These findings provide insights into potential sustainability strategies for dairy sheep, highlighting the utility of transcriptomic markers as FE proxies.

The oral microbiome as a proxy for feed intake in dairy cattle

Genetic material from rumen microorganisms can be found within the oral cavity, and hence there is potential in using the oral microbiome as a proxy of the ruminal microbiome. Feed intake (FI) influences the composition of rumen microbiota and might directly influence the oral microbiome in dairy cattle. Ruminal content samples (RS) from 29 cows were collected at the beginning of the study and also 42 d later (RS0 and RS42, respectively). Additionally, 18 oral samples were collected through buccal swabbing at d 42 (OS42) from randomly selected cows. Samples were used to characterize and compare the taxonomy and functionality of the oral microbiome using nanopore sequencing and to evaluate the feasibility of using the oral microbiome to estimate FI. Up to 186 taxonomical features were found differentially abundant (DA) between RS and OS42. Similar results were observed when comparing OS42 to RS collected on different days. Microorganisms associated with the liquid fraction of the rumen were less abundant in OS42 because these were probably swallowed after regurgitation. Up to 1,102 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were found to be DA between RS and OS42, and these results differed when comparing time of collection, but DA KEGG pathways were mainly associated with metabolism in both situations. Models based on the oral microbiome and rumen microbiome differed in their selection of microbial groups and biological pathways to predict FI. In the rumen, fiber-associated microorganisms are considered suitable indicators of FI. In contrast, biofilm formers like Gammaproteobacteria or Bacteroidia classes are deemed appropriate proxies for predicting FI from oral samples. Models from RS exhibited some predictive ability to estimate FI, but oral samples substantially outperformed them. The best lineal model to estimate FI was obtained with the relative abundance of taxonomical feature at genera level, achieving an average R2 = 0.88 within the training data, and a root mean square error of 3.46 ± 0.83 (±SD) kg of DM, as well as a Pearson correlation coefficient between observed and estimated FI of 0.48 ± 0.30 in the test data. The results from this study suggest that oral microbiome has potential to predict FI in dairy cattle, and it encourages validating this potential in other populations.

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.

Feed Efficiency Estimation from Stochastic Feed Requirement Frontier

Feed accounts 40 to 70 percent of livestock production cost. Therefore, improving feed efficiency of production animals will promote farm profitability. To this end, precise estimation of animal level feed efficiency is important. Considering some limitations of residual feed intake (RFI) as indicator of animal level feed efficiency, an alternative approach is suggested. The approach involves estimation of a stochastic feed requirement frontier (SFRF), which explicitly allows for feed efficiency and statistical noise in the same specification. As a result, a SFRF naturally leads to feed efficiency indicator free from statistical noise. Furthermore, the feed efficiency indicator it generates is nonnegative and it can easily be expressed in terms of surplus feed intake (SFI) caused by feed inefficiency. Simulation experiment was used to illustrate the problems that arise from RFI-based feed efficiency estimation and the improvements that can be expected from the alternative approach. The experimental results showed that RFI tends to overestimate feed efficiency of animals. The overestimation gets worse as the contribution of feed inefficiency to feed intake variation increases. The results from the experiment also showed SFRF provides consistent feed efficiency estimates and associated SFI. Finally, further benefits of the alternative approach in feed efficiency estimation at animal level are presented.

Supplementing a Bacillus-based direct-fed microbial improves feed efficiency in lactating dairy cows

This experiment was conducted to evaluate the effects of feeding a Bacillus-based direct-fed microbial (DFM) on performance and nutrient digestibility of lactating dairy cows. Seventy-six lactating (42 ± 6 days in milk [DIM]) Holstein-Friesian primiparous and multiparous cows were enrolled to a 16-wk experiment. Cows were blocked by lactation number and DIM and within blocks, assigned to 1 of the 2 treatments: 1) basal partial-mixed ration (PMR) without DFM addition (n = 38; CON) or 2) basal PMR with the addition of 3 g/head/d of a DFM containing B. licheniformis 809 and B. subtilis 810 (n = 38; BOVACILLUS, Chr. Hansen A/S, Hørsholm, Denmark; DFM). The DFM was mixed in a protein-based pellet, whereas the CON group was fed the same pellet without DFM (0.6 kg/cow/d). The PMR contained (dry matter [DM] basis) 50% of forage and 48% of a concentrate feed based on corn meal, soybean meal, wheat meal, wheat middlings, and a mineral-vitamin premix, with the remaining part of the diet being represented by the pellet used as a carrier for the treatments (CON and DFM). Dry matter intake (DMI), milk yield, and production efficiency were recorded daily, whereas milk protein and fat concentrations were recorded using electronic milk meters. An additional milk sample was collected every second week of the study for milk composition. On week 15 of the study, fecal samples were collected from each cow for apparent nutrient digestibility calculation. All data were analyzed using the MIXED procedure of SAS (version 9.4; SAS Inst. Inc., Cary, NC). No treatment effects were observed on cow final body weight, daily DMI, milk yield, energy-corrected milk (ECM), ECM efficiency, milk composition (yield or content), and somatic cell count (SCC) (P ≥ 0.12). However, cows fed DFM had a greater feed and N efficiency (P ≤ 0.03) compared to cows fed CON. Moreover, DM digestibility tended to be greater for DFM-fed cows when compared to CON (P = 0.10), whereas no further nutrient digestibility differences were observed (P ≥ 0.24). In summary, supplementing a DFM containing Bacillus licheniformis and B. subtilis benefited feed efficiency of lactating dairy cows fed a PMR, while also tending to improve the digestibility of DM.

Review: Improving residual feed intake modelling in the context of nutritional- and genetic studies for dairy cattle

The residual feed intake (RFI) model has recently gained popularity for ranking dairy cows for feed efficiency. The RFI model ranks the cows based on their expected feed intake compared to the observed feed intake, where a negative phenotype (eating less than expected) is favourable. Yet interpreting the biological implications of the regression coefficients derived from RFI models has proven challenging. In addition, multitrait modelling of RFI has been proposed as an alternative to the least square RFI in nutrition and genetic studies. To solve the challenge with the biological interpretation of RFI regression coefficients and suggest ways to improve the modelling of RFI, an interdisciplinary effort was required between nutritionists and geneticists. Therefore, this paper aimed to explore the challenges with the traditional least square RFI model and propose solutions to improve the modelling of RFI. In the traditional least square RFI model, one set of fixed effects is used to solve systematic effects (e.g., seasonal effects and age at calving) for traits with different means and variances. Thereby, measurement and model fitting errors can accumulate in the phenotype, resulting in undesirable effects. A multivariate RFI model will likely reduce this problem, as trait-specific fixed effects are used. In addition, regression coefficients for DM intake on milk energy tend to have more biologically meaningful estimates in multitrait RFI models, which indicates a confounding effect between the fixed effects and regression coefficients in the least square RFI model. However, defining precise expectations for regression coefficients from RFI models or sourcing for accurate feed norm coefficients seems difficult, especially if the coefficients are applied to a wide cattle population with varying diets or management systems, for example. To improve multitrait modelling of RFI, we suggest improving the modelling of changes in energy status. Furthermore, a novel method to derive the energy density of the diet and individual digestive efficiency is proposed. Digestive efficiency is defined as the part of the efficiency associated with digestive processes, which primarily reflects the conversion from gross energy to metabolisable energy. We show the model was insensitive to prior values of energy density in feed and that there was individual variation in digestive efficiency. The proposed method needs further development and validation. In summary, using multitrait RFI can improve the accuracy of the ranking of dairy cows' feed efficiency, consequently improving economic and environmental sustainability on dairy farms.

How much can performance measures explain of the between-cow variation in enteric methane?

Enteric CH4 produced from dairy cows contributes to the emission of greenhouse gases from anthropogenic sources. Recent studies have shown that the selection of lower CH4-emitting cows is possible, but doing so would be simpler if performance measures already recorded on farm could be used, instead of measuring gas emissions from individual cows. These performance measures could be used for selection of low emitting cows. The aim of this analysis was to quantify how much of the between-cow variation in CH4 production can be explained by variation in performance measures. A dataset with 3 experiments and a total of 149 lactating dairy cows with repeated measures was used to estimate the between-cow variation (the variation between cow estimates) for performance and gas measures from GreenFeed (C-Lock, Rapid City, SD). The cow estimates were obtained with a linear mixed model with the diet within period effect as a fixed effect and the cow within experiment as a random effect. The cow estimates for CH4 production were first regressed on the performance and gas measures individually, and then performance and CO2 production measures were grouped in 3 subsets for principal component analysis and principal component regression. The variables that explained most of the between-cow variation in CH4 production were DMI (R2 = 0.44), among the performance measures, and CO2 production (R2 = 0.61), among gas measures. Grouping the measures increased the R2 to 0.53 when only performance measures were used, and to 0.66 when CO2 production was added to the significant performance measures. We found the marginal improvement to be insufficient to justify the use of grouped measures rather than an individual measure because the latter simplifies the model and avoids over-fitting. Investigation of other measures that can be explored to increase explanatory power of between-cow variation in CH4 production is briefly discussed. Finally, the use of residual CH4 as a measure for CH4 efficiency could be considered by using either DMI or CO2 production as the sole predicting variables.

Assessment of milk metabolites as biomarkers for predicting feed efficiency in dairy sheep

Estimating feed efficiency (FE) in dairy sheep is challenging due to the high cost of systems that measure individual feed intake. Identifying proxies that can serve as effective predictors of FE could make it possible to introduce FE into breeding programs. Here, 39 Assaf ewes in first lactation were evaluated regarding their FE by 2 metrics, residual feed intake (RFI) and feed conversion ratio (FCR). The ewes were classified into high, medium and low groups for each metric. Milk samples of the 39 ewes were subjected to untargeted metabolomics analysis. The complete milk metabolomic signature was used to discriminate the FE groups using partial least squares discriminant analysis. A total of 41 and 26 features were selected as the most relevant features for the discrimination of RFI and FCR groups, respectively. The predictive ability when utilizing the complete milk metabolomic signature and the reduced data sets were investigated using 4 machine learning (ML) algorithms and a multivariate regression method. The orthogonal partial least squares algorithm outperformed other ML algorithms for FCR prediction in the scenarios using the complete milk metabolite signature (R2 = 0.62 ± 0.06) and the 26 selected features (R2 = 0.62 ± 0.15). Regarding RFI predictions, the scenarios using the 41 selected features outperformed the scenario with the complete milk metabolite signature, where the multilayer feedforward artificial neural network (R2 = 0.18 ± 0.14) and extreme gradient boosting (R2 = 0.17 ± 0.15) outperformed other algorithms. The functionality of the selected metabolites implied that the metabolism of glucose, galactose, fructose, sphingolipids, amino acids, insulin, and thyroid hormones was at play. Compared with the use of traditional methods, practical applications of these biomarkers might simplify and reduce costs in selecting feed-efficient ewes.

Genetic relationships between behavioral traits and feed efficiency traits in lactating Holstein cows

The evaluation of dairy cow feed efficiency using residual feed intake accounts for known energy sinks. However, behavioral traits may also contribute to the variation in feed efficiency. Our objective was to estimate the heritability and repeatability of behavioral traits and their genetic correlations with feed efficiency and its components in lactating Holstein cows. The first data set consisted of 36,075 daily rumination and lying time records collected using a SMARTBOW ear tag accelerometer (Zoetis, Parsippany, NJ) and 6,371 weekly feed efficiency records of 728 cows from the University of Wisconsin-Madison. The second data set consisted of 59,155 daily activity records, measured as number of steps, recorded by pedometers (AfiAct; S.A.E. Afikim, Kibbutz Afikim, Israel), and 8,626 weekly feed efficiency records of 635 cows from the University of Florida. Feed efficiency and its components included dry matter intake, change in body weight, metabolic body weight, secreted milk energy, and residual feed intake. The statistical models included the fixed effect of cohort, lactation number, and days in milk, and the random effects of animal and permanent environment. Heritability estimates for behavioral traits using daily records were 0.19 ± 0.06 for rumination and activity, and 0.37 ± 0.07 for lying time. Repeatability estimates for behavioral traits using daily data ranged from 0.56 ± 0.02 for activity to 0.62 ± 0.01 for lying time. Both heritability and repeatability estimates were larger when weekly records instead of daily records were used. Rumination and activity had positive genetic correlations with residual feed intake (0.40 ± 0.19 and 0.31 ± 0.22, respectively) while lying time had a negative genetic correlation with this residual feed intake (-0.27 ± 0.11). These results indicate that more efficient cows tend to spend more time lying and less time active. Additionally, less efficient cows tend to eat more and therefore also tend to ruminate longer. Overall, sensor-based behavioral traits are heritable and genetically correlated with feed efficiency and its components and, therefore, they could be used as indicators to identify feed efficient cows within the herd.

Effects of heat stress on feed intake, milk yield, milk composition, and feed efficiency in dairy cows: A meta-analysis

Heat stress compromises dairy production by decreasing feed intake and milk yield, and it may also alter milk composition and feed efficiency. However, little information is available for evaluating such effects across different levels of heat stress and cows enrolled in heat stress studies. The objectives of this study were to evaluate the effects of heat stress on dry matter intake (DMI), energy-corrected milk (ECM), milk composition, and feed efficiency (kg ECM/kg DMI) and to investigate the relationship between such effects and heat stress intervention and animal characteristics by using meta-analytical approaches. Data from 31 studies (34 trials) fulfilled the inclusion criteria and were used for analysis. Results showed that heat stress decreased DMI, ECM, and milk protein concentration, but did not alter milk fat concentration or feed efficiency. Meta-regression confirmed that such reductions in DMI and ECM were significantly associated with increasing temperature-humidity index (THI). Over the period of heat stress, for each unit increase in THI, DMI and ECM decreased by 4.13% and 3.25%, respectively, in mid-lactation cows. Regression models further revealed the existence of a strong interaction between THI and lactation stage, which partially explained the large heterogeneity in effect sizes of DMI and ECM. The results indicated a need for more research on the relationship between the effect of heat stress and animal characteristics. This study calls for the implementation of mitigation strategies in heat-stressed herds due to the substantial decrease in productivity.

Estimation of genetic parameters for feed efficiency traits using random regression models in dairy cattle

Feed efficiency has become an increasingly important research topic in recent years. As feed costs rise and the environmental impacts of agriculture become more apparent, improving the efficiency with which dairy cows convert feed to milk is increasingly important. However, feed intake is expensive to measure accurately on large populations, making the inclusion of this trait in breeding programs difficult. Understanding how the genetic parameters of feed efficiency and traits related to feed efficiency vary throughout the lactation period is valuable to gain understanding into the genetic nature of feed efficiency. This study used 121,226 dry matter intake (DMI) records, 120,500 energy-corrected milk (ECM) records, and 98,975 metabolic body weight (MBW) records, collected on 7,440 first-lactation Holstein cows from 6 countries (Canada, Denmark, Germany, Spain, Switzerland, and the United States), from January 2003 to February 2022. Genetic parameters were estimated using a multiple-trait random regression model with a fourth-order Legendre polynomial for all traits. Weekly phenotypes for DMI were re-parameterized using linear regressions of DMI on ECM and MBW, creating a measure of feed efficiency that was genetically corrected for ECM and MBW, referred to as genomic residual feed intake (gRFI). Heritability (SE) estimates varied from 0.15 (0.03) to 0.29 (0.02) for DMI, 0.24 (0.01) to 0.29 (0.03) for ECM, 0.55 (0.03) to 0.83 (0.05) for MBW, and 0.12 (0.03) to 0.22 (0.06) for gRFI. In general, heritability estimates were lower in the first stage of lactation compared with the later stages of lactation. Additive genetic correlations between weeks of lactation varied, with stronger correlations between weeks of lactation that were close together. The results of this study contribute to a better understanding of the change in genetic parameters across the first lactation, providing insight into potential selection strategies to include feed efficiency in breeding programs.

Analyzing long-term dynamics of agricultural greenhouse gas emissions in Austria, 1830-2018

Agriculture is an important contributor to greenhouse gas (GHG) emissions. While the development of agricultural GHG emissions on national and global scales is well studied for the last three to six decades, little is known about their trajectory and drivers over longer periods. In this article, we address this research gap by calculating and analyzing GHG emissions related to agriculture in Austria from 1830 to 2018. We calculate territorial emissions on an annual basis and include all GHG emissions from the processes directly involved in agricultural production. Based on this time series, we quantify the relative importance of major drivers of changes in GHG emissions across time and agricultural product categories, applying a structural decomposition analysis. We find that agricultural GHG emissions in Austria increased by 69 % over the total study period, from 4.6 Mt. CO2e/yr in 1830 to 7.7 Mt. CO2e/yr in 2018. While emissions increased only moderately from 1830 to 1945 (+22 % overall), with strong fluctuations between 1914 and 1945, they doubled from 1945 to 1985. In the most recent period from 1985 to 2018, emissions fell by one third, with decreases leveling off over time. Our decomposition analysis reveals that increases in agricultural production per capita most importantly contributed to the high growth in GHG emissions from 1945 to 1985. Conversely, decreasing emission intensities of products and a more climate friendly product mix were key drivers in the emissions reduction observed after 1985. We also contribute to the discussion around the global warming potential star (GWP*), by calculating GHG emissions based on this alternative metric, and contextualize our data within total socio-economic GHG emission trends. By providing insights into the historical trends and drivers of agricultural GHG emissions, our findings enhance the understanding of their long-term historical dynamics and adds to the knowledge base for future mitigation efforts.

Effects of feeding an inoculated corn silage with or without a direct-fed microbial on dry matter intake, milk production, and nutrient digestibility of high-producing lactating Holstein cows

This study evaluated the effects of inoculating corn silage and/or feeding a direct-fed microbial (PRO) on performance and nutrient digestibility of lactating dairy cows. At harvesting, corn silage was treated either with water (culated or not [CON]) or Lactococcus lactis and Lentilactobacillus buchneri (INC; SiloSolve FC) at 1.5 × 105 cfu/g of corn silage. Ten mini silos and one farm-scale silo bunker per treatment were prepared for the laboratory and the lactating dairy cow trial, respectively. Five mini silos per treatment were opened on days 2 or 90 post-ensiling for pH measurement, as well as chemical analysis and aerobic stability, respectively. The farm-scale silo bunkers were opened 77 d post-ensiling for the beginning of the lactating cow trial. Eighty lactating Holstein cows were assigned in a 2 × 2 factorial design to: (1) CON silage without PRO (CON-CON; n = 20), (2) CON silage with PRO at 14 g/head/d (CON-PRO; n = 20), (3) INC silage without PRO (INC-CON; n = 20), and (4) INC silage with PRO at 14 g/head/d (INC-PRO; n = 20). Concurrently with the feeding trial, eight cows per treatment were chosen for nutrient digestibility. The pH of the corn silage was not affected by the silage inoculant (P ≥ 0.29), but INC yielded greater concentration of acetic acid and longer aerobic stability (P < 0.01). Dairy cows fed INC had a lower mean total dry matter intake (DMI), milk protein content, and somatic cell counts vs. CON (P ≤ 0.02). On the other hand, milk and fat- and protein-corrected milk (FPCM) production efficiency, milk urea-N, DM, crude protein, and starch digestibility were greater for INC-fed cows (P ≤ 0.03). Feeding direct-fed microbials (DFM) improved mean body weight, milk yield, and FPCM, as well as milk protein and lactose yield (P ≤ 0.05), but reduced milk fat and protein content (P = 0.02). A silage inoculant × DFM interaction was observed for milk production efficiency, milk protein and lactose content, and somatic cell count (P ≤ 0.05). Dairy cows fed INC-CON had a greater milk production efficiency and milk lactose content (P ≤ 0.04), but INC-PRO had lower milk protein content and SCC (P ≤ 0.03). In summary, inoculating L. lactis and L. buchneri increased acetic acid content and aerobic stability of corn silage, reduced DMI, but improved milk production efficiency and nutrient digestibility of lactating Holstein dairy cows. On the other hand, feeding PRO improved milk, protein, and lactose yield. Additionally, combining the feeding of an inoculated corn silage with PRO reduced milk somatic cell count.

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.

Multiphase diets may improve feed efficiency in fattening crossbreed Holstein bulls: a retrospective simulation of the economic and environmental impact

Beef industry needs alternative feeding strategies to enhance both economic and environmental sustainability. Among these strategies, adjusting the diet dynamically according to the change of nutritional requirements (multiphase diet) has demonstrated its economic and environmental benefits in pig production systems. Therefore, this retrospective study aims to assess, through simulation, the theoretical economic and environmental benefits of introducing a multiphase diet for crossbreed bulls feeding (one or more diet changes). For this, individual data of BW, BW gain, and daily intake were recorded from 342 bulls during the last fattening period (112 days). These data were used to estimate individual trajectory of energy and protein requirements, which were subsequently divided by individual intake to calculate the required dietary energy and protein concentrations. The area between two functions (i.e., ƒ1: constant protein concentration in the original diet during fattening and ƒ2: estimated protein concentration requirements) was minimised to identify the optimal moments to adjust the dietary concentration of energy and protein. The results indicated that both energy and protein intake exceeded requirements on average (+16% and +28% respectively, P < 0.001), justifying the adoption of a multiphase diet. Modelling the individual trajectories of required metabolisable protein (MP, g/kg DM) during the fattening period resulted in exponential decay model in relation to BW [32120 × exp(-0.026 × BW) + 59.9], while the dietary net energy concentration followed a slightly quadratic model [2.26-0.0026 × BW + 0.000003 × BW2]. Minimisation of the area between curves showed two optimal moments to adjust the diet: at 312 kg and 385 kg of BW, indicating three diet phases: (a) <312 kg, (b) 312-385 kg, and (c) 385-600 kg. For the second and third phases, the dietary energy and protein concentration should be 70 g MP/kg DM and 1.70 Mcal/kg DM and 61 g MP/kg DM and 1.65 Mcal/kg DM, respectively. These diet adjustments might improve economic profitability by 29 €/animal, reduce estimated nitrogen excretions by 16% (P < 0.001), and maintain similar weight gain (P > 0.16) compared to the commercial diet. However, the decrease in dietary energy concentration led to increased fibre concentration, which in turn increased the estimated CH4 emissions of animals with the multiphase diet (+44%, P < 0.001). Hence, multiphase diet could theoretically reduce feeding cost and nitrogen excretion from fattening cattle. Further in vivo studies should confirm these results and find optimal nutritional strategies to improve economic profitability and environmental impact.

Genetic parameter estimates for daily predicted gross feed efficiency and its association with energy-corrected milk in South African Holstein cattle

Genetic parameters for daily predicted gross feed efficiency (pGFE) and energy corrected milk (ECM) in the first three parities of South African Holstein cattle were estimated by repeatability animal models. Data comprised of 11,068 test-day milk production records of 1,575 Holstein cows that calved between 2009 and 2019. Heritability estimates for pGFE were 0.12 ± 0.06, 0.09 ± 0.04 and 0.18 ± 0.05 in early, mid and late lactation, respectively. Estimates were moderate for primiparous (0.21 ± 0.05) and low for multiparous (0.10 ± 0.04) cows. Heritability and repeatability across all lactations were 0.14 ± 0.03 and 0.37 ± 0.03, respectively. Genetic correlations between pGFE in different stages of lactation ranged from 0.87 ± 0.24 (early and mid) to 0.97 ± 0.28 (early and late), while a strong genetic correlation (0.90 ± 0.03) was found between pGFE and ECM, across all lactations. The low to moderate heritability estimates for pGFE suggest potential for genetic improvement of the trait through selection, albeit with a modest accuracy of selection. The high genetic correlation of pGFE with ECM may, however, assist to improve accuracy of selection for feed efficiency by including both traits in multi-trait analyses. These genetic parameters may be used to estimate breeding values for pGFE, which will enable the trait to be incorporated in the breeding objective for South African Holstein cattle.

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.

Epigenetic regulation of functional candidate genes for milk production traits in dairy sheep subjected to protein restriction in the prepubertal stage

BACKGROUND

As the prepubertal stage is a crucial point for the proper development of the mammary gland and milk production, this study aims to evaluate how protein restriction at this stage can affect methylation marks in milk somatic cells. Here, 28 Assaf ewes were subjected to 42.3% nutritional protein restriction (14 animals, NPR) or fed standard diets (14 animals, C) during the prepubertal stage. During the second lactation, the milk somatic cells of these ewes were sampled, and the extracted DNA was subjected to whole-genome bisulfite sequencing.

RESULTS

A total of 1154 differentially methylated regions (DMRs) were identified between the NPR and C groups. Indeed, the results of functional enrichment analyses of the genes harboring these DMRs suggested their relevant effects on the development of the mammary gland and lipid metabolism in sheep. The additional analysis of the correlations of the mean methylation levels within these DMRs with fat, protein, and dry extract percentages in the milk and milk somatic cell counts suggested associations between several DMRs and milk production traits. However, there were no phenotypic differences in these traits between the NPR and C groups.

CONCLUSION

In light of the above, the results obtained in the current study might suggest potential candidate genes for the regulation of milk production traits in the sheep mammary gland. Further studies focusing on elucidating the genetic mechanisms affected by the identified DMRs may help to better understand the biological mechanisms modified in the mammary gland of dairy sheep as a response to nutritional challenges and their potential effects on milk production.

Residual Feed Intake as an Efficiency Metric for Pre-Weaning Dairy Calves: What Do We Know?

Dairy cattle systems have targeted improvements in feed efficiency by selecting animals that can convert less feed into more products. Residual feed intake (RFI) has been the index of choice when selecting dairy cattle for feed efficiency. Nonetheless, RFI studies have focused on lactating cows, and the crucial importance of pre-weaning efficiency on farm profitability and cow productivity has been mostly neglected. This review discusses the current knowledge of how RFI divergence relates to nutrient metabolism in pre-weaning dairy calves, including the advantages and limitations of evaluating RFI in this phase. Existing literature indicates that nutrient utilization, energy metabolism, protein metabolism, vitamin metabolism, intestinal development, and hindgut bacterial populations may be implicated in RFI divergence between pre-weaning calves. Techniques developed to date to evaluate RFI in this phase are still evolving to better adapt to the unique characteristics of this phase, and more research is needed to fill in the gaps in our current understanding of early-life feed efficiency divergence in cattle. However, current results suggest great potential for selecting high-efficiency calves while in pre-weaning to accelerate the progress of genetic selection in dairy cattle.

Feed Conversion Ratio (FCR) and Performance Group Estimation Based on Predicted Feed Intake for the Optimisation of Beef Production

This paper reports on the use of estimates of individual animal feed intake (made using time spent feeding measurements) to predict the Feed Conversion Ratio (FCR), a measure of the amount of feed consumed to produce 1 kg of body mass, for an individual animal. Reported research to date has evaluated the ability of statistical methods to predict daily feed intake based on measurements of time spent feeding measured using electronic feeding systems. The study collated data of the time spent eating for 80 beef animals over a 56-day period as the basis for the prediction of feed intake. A Support Vector Regression (SVR) model was trained to predict feed intake and the performance of the approach was quantified. Here, feed intake predictions are used to estimate individual FCR and use this information to categorise animals into three groups based on the estimated Feed Conversion Ratio value. Results provide evidence of the feasibility of utilising the 'time spent eating' data to estimate feed intake and in turn Feed Conversion Ratio (FCR), the latter providing insights that guide farmer decisions on the optimisation of production costs.

Body and milk production traits as indicators of energy requirements and efficiency of purebred Holstein and 3-breed rotational crossbred cows from Viking Red, Montbéliarde, and Holstein sires

This study aimed to compare rotational 3-breed crossbred cows of Viking Red, Montbéliarde, and Holstein breeds with purebred Holstein cows for a range of body measurements, as well as different metrics of the cows' productivity and production efficiency. The study involved 791 cows (440 crossbreds and 351 purebreds), that were managed across 2 herds. Within each herd, crossbreds and purebreds were reared and milked together, fed the same diets, and managed as one group. The heart girth, height at withers, and body length were measured, and body condition score (BCS) was determined on all the cows on a single test day. The body weight (BW) of 225 cows were used to develop an equation to predict BW from body size traits, parity, and days in milk, which was then used to estimate the BW of all the cows. Equations from the literature were used to estimate body protein and lipid contents using the predicted BW and BCS. Evidence suggests that maintenance energy requirements may be closely related to body protein mass, and Holstein and crossbred cows may be different in body composition. Therefore, we computed the requirements of net energy for maintenance (NE_M) on the basis either of the metabolic weight (NE_M-MW: 0.418 MJ/kg of metabolic BW) or of the estimated body protein mass according to a coefficient (NE_M-PM: 0.631 MJ/kg body protein mass) computed on the subset comprising the purebred Holstein. On the same day when body measurements were collected, individual test-day milk yield and fat and protein contents were retrieved once from the official Italian milk recording system, and milk was sampled to determine fresh cheese yield. Measures of NE_M were used to scale the production traits. Statistical analyses of all variables included the fixed effects of herd, days in milk, parity, and genetic group (purebred Holstein and crossbred), and the herd × genetic group interaction. External validation of the equation predicting BW yielded a correlation coefficient of 0.94 and an average bias of -4.95 ± 36.81 kg. The crossbreds had similar predicted BW and NE_M-MW compared with the Holsteins. However, NE_M-PM of crossbreds was 3.8% lower than that of the Holsteins, due to their 11% greater BCS and different estimated body composition. The crossbred cows yielded 4.8% less milk and 3.4% less milk energy than the purebred Holsteins. However, the differences between genetic groups were no longer significant when the production traits were scaled on NE_M-PM, suggesting that the crossbreds and purebreds have the same productive ability and efficiency per unit of body protein mass. In conclusion, measures of productivity and efficiency that combine the cows' production capability with traits related to body composition and the energy cost of production seem to be more effective criteria for comparing crossbred and purebred Holstein cows than just milk, fat, and protein yields.

Rumen Microbiota Predicts Feed Efficiency of Primiparous Nordic Red Dairy Cows

Efficient feed utilization in dairy cows is crucial for economic and environmental reasons. The rumen microbiota plays a significant role in feed efficiency, but studies utilizing microbial data to predict host phenotype are limited. In this study, 87 primiparous Nordic Red dairy cows were ranked for feed efficiency during their early lactation based on residual energy intake, and the rumen liquid microbial ecosystem was subsequently evaluated using 16S rRNA amplicon and metagenome sequencing. The study used amplicon data to build an extreme gradient boosting model, demonstrating that taxonomic microbial variation can predict efficiency (r_test = 0.55). Prediction interpreters and microbial network revealed that predictions were based on microbial consortia and the efficient animals had more of the highly interacting microbes and consortia. Rumen metagenome data was used to evaluate carbohydrate-active enzymes and metabolic pathway differences between efficiency phenotypes. The study showed that an efficient rumen had a higher abundance of glycoside hydrolases, while an inefficient rumen had more glycosyl transferases. Enrichment of metabolic pathways was observed in the inefficient group, while efficient animals emphasized bacterial environmental sensing and motility over microbial growth. The results suggest that inter-kingdom interactions should be further analyzed to understand their association with the feed efficiency of animals.

Implementation of Feed Efficiency in Iranian Holstein Breeding Program

This study aimed to evaluate the economic impact of improving feed efficiency on breeding objectives for Iranian Holsteins. Production and economic data from seven dairy herds were used to estimate the economic values of different traits, and a meta-analysis was conducted to analyze the genetic relationships between feed efficiency and other traits. Economic weights were calculated for various traits, with mean values per cow and per year across herds estimated at USD 0.34/kg for milk yield, USD 6.93/kg for fat yield, USD 5.53/kg for protein yield, USD −1.68/kg for dry matter intake, USD −1.70/kg for residual feed intake, USD 0.47/month for productive life, and USD −2.71/day for days open. The Iranian selection index was revised to improve feed efficiency, and the feed efficiency sub-index (FE$) introduced by the Holstein Association of the United States of America was adopted to reflect Iran’s economic and production systems. However, there were discrepancies between Iranian and US genetic coefficients in the sub-index, which could be attributed to differences in genetic and phenotypic parameters, as well as the economic value of each trait. More accurate estimates of economic values for each trait in FE$ could be obtained by collecting dry matter intake from Iranian herds and conducting genetic evaluations for residual feed intake.

Intergenerational impact of dietary protein restriction in dairy ewes on epigenetic marks in the perirenal fat of their suckling lambs

In sheep, nutrition during the prepubertal stage is essential for growth performance and mammary gland development. However, the potential effects of nutrient restriction in a prepuberal stage over the progeny still need to be better understood. Here, the intergenerational effect of maternal protein restriction at prepubertal age (2 months of age) on methylation patterns was evaluated in the perirenal fat of Assaf suckling lambs. In total, 17 lambs from ewes subjected to dietary protein restriction (NPR group, 44% less protein) and 17 lambs from control ewes (C group) were analyzed. These lambs were ranked based on their carcass proportion of perirenal and cavitary fat and classified into HighPCF and LowPCF groups. The perirenal tissue from 4 NPR-LowPCF, 4 NPR-HighPCF, 4 C-LowPCF, and 4 C-HighPCF lambs was subjected to whole-genome bisulfite sequencing and differentially methylated regions (DMRs) were identified. Among other relevant processes, these DMRs were mapped in genes responsible for regulating the transition of brown to white adipose tissue and nonshivering thermoregulation, which might be associated with better adaptation/survival of lambs in the perinatal stage. The current study provides important biological insights about the intergenerational effect on the methylation pattern of an NPR in replacement ewes.

Fermented Total Mixed Ration Alters Rumen Fermentation Parameters and Microbiota in Dairy Cows

This study aimed to determine changes and interactions of ruminal microbiota and chemical parameters in dairy cows fed FTMR. Twelve multiparous Holstein dairy cows (Body weight = 616 ± 13.4 kg; day in milk = 106 ± 7.55 d; and parity = 2.31 ± 0.49; mean ± standard deviation) were divided randomly into two treatments depending on the day in milk, milk production, and parity. The two treatments were: (1) total mixed ration (TMR) and (2) FTMR. Illumina MiSeq sequencing was used to explore the changes in the ruminal microbiota. The results revealed that the bacterial and fungal diversity of the FTMR group were significantly higher than the TMR group. The predominant microbiota phyla in the bacteria and fungi showed significant differences between TMR and FTMR, as follows: Verrucomicrobia (p = 0.03) and Tenericutes (p = 0.01), Ascomycota (p = 0.04) and Basidiomycota (p = 0.04). The dominant bacterial genera in the bacteria, fungi, protozoan, and archaea that showed significant differences between TMR and FTMR were Unclassified_Bacteroidales (p = 0.02), Unclassified_RFP12 (p = 0.03), Candida (p = 0.0005), Bullera (p = 0.002), Cryptococcus (p = 0.007), and Ostracodinium (p = 0.01). LefSe analysis was performed to reveal the biomarker genera of the rumen microbiota community (bacteria, fungi, protozoan, and archaea) in the TMR and FTMR were the genera Shuttleworthia, Ruminococcus, Cryptococcus, Mycosphaerella, Bullera, Candida, and Ostracodinium. NH3-N concentration (p < 0.0001), total VFA concentration (p = 0.003), and molar proportion in total VFA of acetate (p = 0.01) were higher for the cows fed FTMR compared with the cows fed the TMR. Several bacterial genera showed significant correlations with rumen fermentation parameters. The genus Unclassified_Bacteroidales and Bullera were positively correlated with total volatile fatty acids (VFA) and acetate, whereas Candida and Ostracodinium showed negative correlations. Meanwhile, propionate was positively correlated with Candida and negatively correlated with Bullera. The PICRUSt functional profile prediction indicated that the xenobiotics biodegradation and metabolism, the lipid, amino acid, terpenoids, and polyketides metabolisms of the FTMR group were significantly higher than that of the TMR group. The results imply that FTMR can increase lipid and amino acid metabolism, and modulate the rumen microbiome and improve ruminal fermentation.

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.

Life cycle assessment of Parmigiano Reggiano PDO cheese with product environmental footprint method: A case study implementing improved slurry management strategies

The environmental impact of Parmigiano Reggiano PDO cheese was quantified using the Product Environmental Footprint Category Rules (PEFCRs) in a Traditional System (TS) and in an Improved Management System (IMS). The TS differs from IMS with respect to slurry management (raw slurry storage vs anaerobic digestion and storage of the liquid fraction of digestate) and application of nutrients to the field (by slurry tanker with a diverter plate vs soil injection at pre-sowing and side dressing). Two additional scenarios were evaluated by considering the possible environmental enhancement achievable by reducing enteric methane production and by using soybean grain produced in Italy as the protein source for animals' diets. The environmental impact was quantified both for 1 kg of fat and protein corrected milk (FPCM) and for the production of 10 g dry matter equivalent of cheese as single score. For the first assessment, the environmental impact results were 124 and 112 μPt kg FPCM^-1 for TS and IMS, respectively. In the second case, it was 10.8 μPt and 9.9 μPt 10 g dry matter equivalent^-1 of cheese, for TS and IMS, respectively. The specific cost for reducing the GHG emissions in this production chain was equal to 34 € Mg^-1 milk produced. Finally, although specific studies should consider the reduction of enteric methane emissions and the use of soybean grain nationally produced as feed source, the scenarios evaluated in this study highlighted some potential for environmental improvements. Even small environmental improvements to the Parmigiano Reggiano PDO cheese supply chain can bring substantial improvements to the sustainability of the food market, because of the widespread demand on the global market of Parmigiano Reggiano and of its chance of attracting consumers who are sensitive to environmental problems.

Unraveling feed and nutrient use efficiencies in grassland-based dairy farms

Grassland-based dairy farms are important for the provisioning of milk and ecosystem services. However, the key factors and interactions that influence the feed use efficiency of grassland-based dairy farms in practice are not well known and understood, and as a consequence no well-targeted recommendations can be provided. This paper addresses the question ‘what are the main factors that determine the variations in calculated feed efficiency and N and P use efficiencies on dairy farms subjected to agri-environmental regulations’. Monitoring and modeling data from ~12000 grassland-based dairy farms in The Netherlands over a 4 year period (2017–2020), collected through the KringloopWijzer model, were analyzed and the data from 2020 were statistically analyzed in detail. Farms greatly differed in milk production intensity (range &lt; 10 to &gt;25 Mg per ha per yr) and in the amount of purchased feed. The 5 and 95 percentile values of frequency distribution of the calculated annual mean feed efficiency at herd level were 0.9 and 1.3 kg milk per kg feed dry matter, respectively. Feed efficiency was statistically related to milk yield and number of young stock per cow, the share of concentrates and silage maize in the ration, and the net energy content of silage grass. At herd level, the 5 and 95 percentile values of the calculated annual mean N use efficiency increased with feed efficiency from 21 to 28%, and those of the annual mean P use efficiency from 32 to 40%. Contrary to expectations, mean surpluses of N and P at farm level remained more or less constant with feed efficiency and the intensity of milk production, but the amounts of purchased feed and manure export strongly increased with the intensity of milk production. The N and P surpluses and use efficiencies at farm level were sensitive to accounting for the externalization of feed production and manure utilization. The modeled ammonia and methane emissions per kg milk produced were relatively low on farms with high feed efficiency. In conclusion, feed use and N and P use efficiencies are key indicator for the profitability and environmental performance of dairy farms. Differences between farms in these key indicators were large, and these differences were related to a limited number of explanatory variables. Our study provides lessons for improving the profitability and environmental performance of grassland-based dairy farms.

Feed efficiency of lactating Holstein cows is repeatable within diet but less reproducible when changing dietary starch and forage concentrations

Improving feed efficiency has become an important target for dairy farmers to produce more milk with fewer feed resources. With decreasing availability of arable land to produce feeds that are edible for human consumption, it will be important to increase the proportion of feeds in the diets for dairy cattle that are less edible for human consumption. The current research analyzed the ability of lactating dairy cows to maintain their feed efficiency when switching between a high starch diet (HS diet: 27% starch, 29% NDF, 47.1% forages on a DM basis) and a low starch diet (LS diet: 13% starch, 37% NDF, 66.4% forages on a DM basis). Sixty-two lactating Holstein cows (137 ± 23 days in milk (DIM) at the start of experiment), of which 29 were primiparous cows, were utilized in a crossover design with two 70-d experimental periods, including a 14-d adaption period for each. Feed efficiency was estimated as the individual deviation from the population average intercept in a mixed model predicting DM intake (DMI) with net energy in milk, maintenance and BW gain and loss. Repeatability was estimated within each diet by comparing feed efficiency estimated over the first 28-day period and the second 28-day period within each diet, using Pearson's and intraclass correlations, and the estimation of error of repeatability. Similarly, reproducibility was estimated by comparing the second 28-day period of one diet with the first 28-day period of the other diet. Feed efficiency was less reproducible across diets than repeatable within the same diet. This was shown by lower intraclass correlations (0.399) across diets compared to that in the HS diet (0.587) and LS diet (0.806), as well as a lower Pearson's correlation coefficient (0.418) across diets compared to that in the HS diet (0.630) and LS diet (0.809). In addition, the estimation of error of repeatability was higher (0.830 kg DM/d) across diets compared to that in the HS diet (0.761 kg DM/d) and LS diet (0.504 kg DM/d). This means that the feed efficiency of dairy cows is more likely to change after a diet change than over subsequent lactation stages. Other determinants, such as digestive processes, need to be further investigated to determine its effects on estimating feed efficiency.

Challenges and opportunities for manureshed management across U.S. dairy systems: Case studies from four regions

The manureshed represents cropland needed to safely assimilate manure nutrients from an animal feeding operation. Dairy manuresheds can be contained on-farm but may need to involve additional farms that can assimilate excess nutrients. We present case studies reviewing challenges and opportunities to manureshed management in four major dairy-producing states using available information on local manuresheds. Additionally, geographic information system software was used with data from regulated Minnesota dairies to assess cropland assimilative capacities and transport needs surrounding large dairies. Manureshed requirements vary across regions, but increased import of feed and soil phosphorus accumulation constrain on-farm manure utilization across the United States. In Minnesota, a growing proportion of Jersey cattle and differences in continuous corn (Zea mays L.) vs. corn-alfafa (Medicago sativa L.) rotations contribute to the amount of land needed to absorb dairy manure nutrients. Farm-gate budgets reveal that N-based manuresheds can be contained within Idaho dairies, but P-based manuresheds extend beyond the farm. In New Mexico, relocation of surplus manure nutrients off the farm is common via informal networks, but incentives to strengthen these networks could ensure sustainable manureshed management. Evaluation of manureshed requirements in Pennsylvania is often complicated by the need for additional nutrient management planning and greater understanding of nutrient balances on the preponderance of small dairies. Nutrient imbalances with highly concentrated dairy production often lead to the need for manure transport off-farm. However, advances in herd and cropland management offer opportunities to improve on-farm nutrient efficiencies, and emerging networks and technologies promise to facilitate manure export when needed.

Conformation traits of Holstein cows and their association with a Canadian economic selection index

Pro$ is a Canadian economic selection index aimed to maximize profit by increasing production yields, while maintaining conformation and functional traits. Currently, there is an interest in understanding the individual contributions of conformation traits recorded in Canada to the overall economic value of a cow and whether they are equally important. We used multiple polynomial regression and principal component analysis to assess the association of 26 conformation traits with Pro$ using Relative Breeding Values (RBV) from 9,351 proven bulls. The best reduced regression model explained 72.5% of the Pro$ variance, with heel depth and body depth having the highest and lowest effect on Pro$ values, respectively. Four traits classified as intermediate optimum traits, e.g., teat length, showed significant linear association with Pro$ instead of quadratic, whereas bone quality was not significantly associated with the index. Principal component analysis indicated that highly profitable bulls share similar RBV, with a sub-clustering of bulls of daughters with better mammary system versus better dairy strength and feet and legs. These results provide understanding of the individual contributions of conformation traits to Pro$ and give information to guide the Canadian dairy industry on how to best consider these traits in recording and genetic evaluation programs.

Historical Evolution of Cattle Management and Herd Health of Dairy Farms in OECD Countries

This work aimed to review the important aspects of the dairy industry evolution at herd level, interrelating production with health management systems. Since the beginning of the industrialization of the dairy cattle sector (1950s), driven by the need to feed the rapidly growing urban areas, this industry has experienced several improvements, evolving in management and technology. These changes have been felt above all in the terms of milking, rearing, nutrition, reproductive management, and design of facilities. Shortage of labor, emphasis on increasing farm efficiency, and quality of life of the farmers were the driving factors for these changes. To achieve it, in many areas of the world, pasture production has been abandoned, moving to indoor production, which allows for greater nutritional and reproductive control of the animals. To keep pace with this paradigm in milk production, animal health management has also been improved. Prevention and biosecurity have become essential to control and prevent pathologies that cause great economic losses. As such, veterinary herd health management programs were created, allowing the management of health of the herd as a whole, through the common work of veterinarians and farmers. These programs address the farms holistically, from breeding to nutrition, from prevention to consultancy. In addition, farmers are now faced with a consumer more concerned on animal production, valuing certified products that respect animal health and welfare, as well as environmental sustainability.

Analysis of Chemical Composition, Amino Acid Content, and Rumen Degradation Characteristics of Six Organic Feeds

The current study was designed to investigate the chemical composition, amino acid content, and rumen degradation characteristics (nylon bag method) of six organic feeds to illustrate their feeding values. The feeds analyzed were: corn grain (CG), soybean cake (SC), wheat bran (WB), corn silage (CS), oat hay (OT), and alfalfa hay (AF). Our results showed that the contents of crude protein (CP) (47.46%) and ether extract (EE) (8.23%) in SC were highest. The contents of neutral detergent fiber (NDF) (65.00%) and acid detergent fiber (ADF) (39.16%) in OT were highest. The contents of total amino acid (TAA) (42.95%) and essential amino acid (EAA) (19.73%) in SC were highest. Among SC, WB, and CG, the effective degradation rate (ED) of dry matter (DM) is SC (87.89%) > WB (73.32%) > CG (64.25%); the ED value of CP is CG (82.37%) > WB (82.40%) > SC (60.47%). Among CS, OT, and AF, the effective degradation rate (ED) of DM is CS (72.68%) > OT (59.97%) > AF (58.89%); the ED value of CP is AF (76.46%) > CS (72.03%) > OT (71.99%). In conclusion, the chemical composition, amino acid content, and rumen degradation rate of SC and AF were better than those of the other four feeds.

Metagenomics reveals differences in microbial composition and metabolic functions in the rumen of dairy cows with different residual feed intake

Background

Rumen microbial composition and functions have vital roles in feed digestion and fermentation and are linked to feed efficiency in cattle. This study selected Holstein cows, which are high in both milk protein content and milk yield, to analyse the relationship between the rumen microbiota and residual feed intake (RFI). Eighteen multiparous lactating cows were divided into low RFI (LRFI, high efficiency, n = 9) and high RFI (HRFI, low efficiency, n = 9) groups to investigate the differences in microbial composition and functions.

Results

The relative abundances of butyrate producers, including the Clostridium, Butyrivibrio, Eubacterium and Blautia genera, were higher in HRFI cows than in LRFI cows (P < 0.05). Four carbohydrate metabolic pathways (glycolysis/gluconeogenesis, pentose phosphate pathway, fructose and mannose metabolism, and butanoate metabolism) and one energy metabolism pathway (methane metabolism), were more abundant in HRFI animals (P < 0.05). Quorum sensing and DNA replication pathways were more abundant in HRFI cows. For CAZyme profiles, 14 out of 19 genes encoding carbohydrates-deconstructing enzymes were more abundant in HRFI cows (P < 0.05). Seven Lachnospiraceae species associated with carbohydrate metabolism and quorum sensing may contribute to the difference in feed efficiency. Moreover, the LRFI cows had lower abundances of Methanosphaera (P < 0.01), Methanobrevibacter ruminantium (P = 0.09) and methanogenesis functions (P = 0.04).

Conclusions

The rumen microbiota of low-efficiency cows has stronger abilities to degrade carbohydrates and produce methane, and quorum sensing pathways could also be associated with differences in feed efficiency. This study provides a deeper understanding of the microbial ecology of dairy cows with different feed efficiencies and highlights the possibility of modulating the rumen microbiome or microbial functions to improve the feed efficiency of dairy cows.

Supplementary Information

The online version contains supplementary material available at 10.1186/s42523-022-00170-3.

Effects of butyrate− on ruminal Ca2+ transport: evidence for the involvement of apically expressed TRPV3 and TRPV4 channels

The ruminal epithelium absorbs large quantities of NH₄⁺ and Ca²⁺. A role for TRPV3 has emerged, but data on TRPV4 are lacking. Furthermore, short-chain fatty acids (SCFA) stimulate ruminal Ca²⁺ and NH₄⁺ uptake in vivo and in vitro, but the pathway is unclear. Sequencing of the bovine homologue (bTRPV4) revealed 96.79% homology to human TRPV4. Two commercial antibodies were tested using HEK-293 cells overexpressing bTRPV4, which in ruminal protein detected a weak band at the expected ~ 100 kDa and several bands ≤ 60 kDa. Immunofluorescence imaging revealed staining of the apical membrane of the stratum granulosum for bTRPV3 and bTRPV4, with cytosolic staining in other layers of the ruminal epithelium. A similar expression pattern was observed in a multilayered ruminal cell culture which developed resistances of > 700 Ω · cm² with expression of zonula occludens-1 and claudin-4. In Ussing chambers, 2-APB and the TRPV4 agonist GSK1016790A stimulated the short-circuit current across native bovine ruminal epithelia. In whole-cell patch-clamp recordings on HEK-293 cells, bTRPV4 was shown to be permeable to NH₄⁺, K⁺, and Na⁺ and highly sensitive to GSK1016790A, while effects of butyrate⁻ were insignificant. Conversely, bTRPV3 was strongly stimulated by 2-APB and by butyrate⁻ (pH 6.4 > pH 7.4), but not by GSK1016790A. Fluorescence calcium imaging experiments suggest that butyrate⁻ stimulates both bTRPV3 and bTRPV4. While expression of bTRPV4 appears to be weaker, both channels are candidates for the ruminal transport of NH₄⁺ and Ca²⁺. Stimulation by SCFA may involve cytosolic acidification (bTRPV3) and cell swelling (bTRPV4).

Preferences of European dairy stakeholders in breeding for resilient and efficient cattle: A best-worst scaling approach

Including resilience in the breeding objective of dairy cattle is gaining increasing attention, primarily as anticipated challenges to production systems, such as climate change, may make some perturbations more difficult to moderate at the farm level. Consequently, the underlying biological mechanisms by which resilience is achieved are likely to become an important part of the system itself, increasing value on the animal's ability to be unperturbed by variable production circumstances, or to quickly return to pre-perturbed levels of productivity and health. However, because the value of improving genetic traits to a system is usually based on known profit functions or bioeconomic models linked to current production conditions, it can be difficult to define longer-term value, especially under uncertain future production circumstances and where nonmonetary values may be progressively more important. We present the novel application of a discrete choice experiment, used to investigate potential antagonisms in the values of genetic improvements for 8 traits to dairy cattle system stakeholders in Europe when the production goal was either efficiency or resilience. A latent class model was used to identify heterogeneous preferences within each production goal, and postestimation was used to identify associations between these preferences and sociodemographic characteristics of respondents. Results suggested 3 distinct latent preference classes for each production goal. For the efficiency goal, yield and feed efficiency traits were generally highly valued, whereas for the resilience goal, health and robustness traits were generally highly valued. In both cases, these traits generally carried a low value in the other production scenario. Overall, in both scenarios, longevity was highly valued; however, the value of this trait in terms of resilience will depend on phenotyping across diverse environments to sufficiently capture performance under various anticipated system challenges. Additionally, results showed significant associations between membership of latent preference classes with education level and profession. In conclusion, as resilience becomes increasingly important, it is likely that a continued reliance on the short-term economic value of traits alone will lead decision makers to misrepresent the importance of some traits, including those with substantial contextual values in terms of resilience.

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.

Overview of Metabolomic Analysis and the Integration with Multi-Omics for Economic Traits in Cattle

Metabolomics has been applied to measure the dynamic metabolic responses, to understand the systematic biological networks, to reveal the potential genetic architecture, etc., for human diseases and livestock traits. For example, the current published results include the detected relevant candidate metabolites, identified metabolic pathways, potential systematic networks, etc., for different cattle traits that can be applied for further metabolomic and integrated omics studies. Therefore, summarizing the applications of metabolomics for economic traits is required in cattle. We here provide a comprehensive review about metabolomic analysis and its integration with other omics in five aspects: (1) characterization of the metabolomic profile of cattle; (2) metabolomic applications in cattle; (3) integrated metabolomic analysis with other omics; (4) methods and tools in metabolomic analysis; and (5) further potentialities. The review aims to investigate the existing metabolomic studies by highlighting the results in cattle, integrated with other omics studies, to understand the metabolic mechanisms underlying the economic traits and to provide useful information for further research and practical breeding programs in cattle.

Assessment of feed and economic efficiency of dairy farms based on multivariate aggregation of partial indicators measured on field

Many of the metrics used to evaluate farm performance are only partial indicators of farm operations, which are assumed to be best predictors of the whole farm efficiency. The main objective of this work was to identify aggregated multiple indexes of profitability using common partial indicators that are routinely available from individual farms to better support the short-term decision-making processes of the cattle-feeding process. Data were collected from face-to-face interviews with farmers from 90 dairy farms in Italy and used to calculate 16 partial indicators that covered almost all indicators currently used to target feeding and economic efficiency in dairy farms. These partial indicators described feed efficiency, energy utilization, feed costs, milk-to-feed price ratio, income over feed costs, income equal feed cost, money-corrected milk, and bargaining power for feed costs. Calculations of feeding costs were based on lactating cows or the whole herd, and income from milk deliveries was determined with or without considering the milk quality payment. Multivariate factor analysis was then applied to the 16 partial indicators to determine simplified and latent structures. The results indicated that 5 factors explained 70% of the variability. Each of the original partial indicator was associated with all factors in different proportions, as indicated by loading scores from the multivariate factor analysis. Based on the loading scores, we labeled these 5 factors as "economic efficiency," "energy utilization," "break-even point," "milk-to-feed price," and "bargaining power of the farm," in decreasing order of explained communality. The first 3 factors shared 83% of the total communality. Feed efficiency was similarly associated with factor 1 (53% loading) and factor 2 (66% loading). Only factor 4 was significantly affected by farm location. Milk production and herd size had significant effects on factor 1 and factor 2. Our multivariate approach eliminated the problem of multicollinearity of partial indicators, providing simple and effective descriptions of farm feeding economics. The proposed method allowed the evaluation, benchmarking, and ranking of dairy herd performance at the level of single farms and at territorial level with high opportunity to be used or replicated in other areas.

Residual energy intake, energy balance, and liability to diseases: Genetic parameters and relationships in German Holstein dairy cows

Residual energy intake (REI) is an often-suggested trait for direct selection of dairy cows for feed efficiency. Cows with lower REI seem to be more efficient but are also in a more severe negative energy balance (EB), especially in early lactation. A negative EB leads to a higher liability to diseases. Due to this fact, this study aims to investigate the genetic relationship between REI and liability to diseases. Health and production data were recorded from 1,370 German Holstein dairy cows from 8 research farms over a period of 2 yr. We calculated 2 phenotypes for REI that considered the following energy sinks: milk energy content, metabolic body weight, body weight change, body condition score, and body condition score change. Genetic parameters were estimated with threshold or linear random regression models from days in milk (DIM) 1 to 305. Heritabilities for REI, EB, and all diseases ranged from 0.12 to 0.39, 0.15 to 0.31, and 0.09 to 0.20, respectively. Genetic correlations between selected DIM for REI and EB were higher for adjacent DIM than for more distant DIM. Pearson correlation coefficients between estimated breeding values (EBV) for REI and EB varied between 0.47 and 0.81; they were highest in mid lactation. Correlations between EBV for all diseases and REI as well as EB were negative, with lowest values in early lactation. Within the first 50 DIM, proportions of diseased days for cows with lowest EBV for REI were almost twice as high as for cows with highest EBV for REI. In conclusion, selecting dairy cows for lower REI should be treated with caution because of an unfavorable relationship with liability to diseases, especially in early lactation.

In Vitro and In Vivo Assessment of Dietary Supplementation of Both Natural or Nano-Zeolite in Goat Diets: Effects on Ruminal Fermentation and Nutrients Digestibility

This study aimed to evaluate in vitro and in vivo dietary supplementation with different levels of natural or nano-zeolite forms on rumen fermentation patterns and nutrient digestibility. In the in vitro experiment, a basal diet (50% concentrate: 50% forage) was incubated without additives (control) and with natural zeolite (10, 20, 30 g/kg DM) or nano-zeolite (0.2, 0.3, 0.4, 0.5, 1.0 g/kg DM) for 24 h to assess their effect on ruminal fermentation, feed degradability, and gas and methane production using a semi-automatic system of in vitro gas production (GP). The most effective doses obtained from the in vitro experiment were evaluated in vivo using 30 Barki goats (26 ± 0.9 SE kg body weight). Goats were allocated into three dietary treatments (n = 10/treatment) as follows: control (basal diet without any supplementations), natural zeolite (20 g/kg DM diet), and nano-zeolite (0.40 g/kg DM diet). The in vitro results revealed that only the nano-zeolite supplementation form quadratically (p= 0.004) increased GP, and the level of 0.5 g/kg DM had the highest GP value compared to the control. Both zeolite forms affected the CH₄ production, linear, and quadratic reductions (p < 0.05) in CH₄ (mL/g DM), consistent with linear increases in truly degraded organic matter (TDOM) (p = 0.09), and propionate molar proportions (p = 0.007) were observed by nano zeolite treatment, while the natural form of zeolite resulted in a linear CH₄ reduction consistent with a linear decrease (p = 0.004) in NH₃-N, linear increases in TDOM (p = 0.09), and propionate molar proportions (p = 0.004). Results of the in vivo experiment demonstrated that the nutrient digestibility was similar among all treatments. Nano zeolite enhanced (p < 0.05) the total short-chain fatty acids and butyrate concentrations, while both zeolite forms decreased (p < 0.001) NH₃-N compared to the control. These results suggested that both zeolite supplementation forms favorably modified the rumen fermentation in different patterns.