Relationship between feed efficiency and resilience in dairy ewes subjected to acute underfeeding

Selection of dairy sheep based on production levels has caused a loss of rusticity, which might compromise their future resilience to nutritional challenges. Although refocusing breeding programs toward improved feed efficiency (FE) is expected, more-efficient ewes also seem to be more productive. As a first step to examine the relationship between FE and resilience in dairy sheep, in this study we explored the variation in the response to and the recovery from an acute nutritional challenge in high-yielding Assaf ewes phenotypically divergent for FE. First, feed intake, milk yield and composition, and body weight changes were recorded individually over a 3-wk period in a total of 40 sheep fed a total mixed ration (TMR) ad libitum. Data were used to calculate their FE index (FEI, defined as the difference between the actual and predicted intake estimated through net energy requirements for maintenance, production, and weight change). The highest and lowest FE ewes (H-FE and L-FE groups, respectively; 10 animals/group) were selected and then subjected to the nutritional challenge (i.e., withdrawing the TMR and limiting their diet only to the consumption of straw for 3 d). Afterward, sheep were fed again the TMR ad libitum. Temporal patterns of variation in performance traits, and ruminal fermentation and blood parameters were examined. A good consistency between FEI, residual feed intake, and feed conversion ratio was observed. Results supported that H-FE were more productive than L-FE sheep at similar intake level. Average time trends of milk yield generated by a piecewise model suggest that temporal patterns of variation in this trait would be related to prechallenge production level (i.e., H-FE presented quicker response and recovery than L-FE). Considering all studied traits, the overall response to and recovery from underfeeding was apparently similar or even better in H-FE than in L-FE. This would refute the initial hypothesis of a poorer resilience of more-efficient sheep to an acute underfeeding. However, the question remains whether a longer term feed restriction might impair the ability of H-FE ewes to maintain or revert to a high-production status, which would require further research.

Plasma and milk metabolomics in lactating sheep divergent for feed efficiency

Enhancing the ability of animals to convert feed into meat or milk by optimizing feed efficiency (FE) has become a priority in livestock research. Although untargeted metabolomics is increasingly used in this field and may improve our understanding of FE, no information in this regard is available in dairy ewes. This study was conducted to (1) discriminate sheep divergent for FE and (2) provide insights into the physiological mechanisms contributing to FE through high-throughput metabolomics. The ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q/TOF-MS) technique was applied to easily accessible animal fluids (plasma and milk) to assess whether their metabolome differs between high- and low-feed efficient lactating ewes (H-FE and L-FE groups, respectively; 8 animals/group). Blood and milk samples were collected on the last day of the 3-wk period used for FE estimation. A total of 793 features were detected in plasma and 334 in milk, with 100 and 38 of them, respectively, showing differences between H-FE and L-FE. The partial least-squares discriminant analysis separated both groups of animals regardless of the type of sample. Plasma allowed the detection of a greater number of differential features; however, results also supported the usefulness of milk, more easily accessible, to discriminate dairy sheep divergent for FE. Regarding pathway analysis, nitrogen metabolism (either anabolism or catabolism) seemed to play a central role in FE, with plasma and milk consistently indicating a great impact of AA metabolism. A potential influence of pathways related to energy/lipid metabolism on FE was also observed. The variable importance in the projection plot revealed 15 differential features in each matrix that contributed the most for the separation in H-FE and L-FE, such as l-proline and phosphatidylcholine 20:4e in plasma or l-pipecolic acid and phosphatidylethanolamine (18:2) in milk. Overall, untargeted metabolomics provided valuable information into metabolic pathways that may underlie FE in dairy ewes, with a special relevance of AA metabolism in determining this complex phenotype in the ovine. Further research is warranted to validate these findings.

An evaluation of detailed animal characteristics influencing the lactation production efficiency of spring-calving, pasture-based dairy cattle

Selection for feed efficiency, the ratio of output (e.g., milk yield) to feed intake, has traditionally been limited on commercial dairy farms by the necessity for detailed individual animal intake and performance data within large animal populations. The objective of the experiment was to evaluate the effects of individual animal characteristics (animal breed, genetic potential, milk production, body weight (BW), daily total dry matter intake (TDMI), and energy balance) on a cost-effective production efficiency parameter calculated as the annual fat and protein (milk solids) production per unit of mid-lactation BW (MSperBW_lact). A total of 1,788 individual animal intake records measured at various stages of lactation (early, mid, and late lactation) from 207 Holstein-Friesian and 200 Jersey × Holstein-Friesian cows were used. The derived efficiency traits included daily kilograms of milk solids produced per 100 kg of BW (dMSperBW_int) and daily kilograms of milk solids produced per kilogram of TDMI (dMSperTDMI). The TDMI per 100 kg of BW was also calculated (TDMI/BW_int) at each stage of lactation. Animals were subsequently either ranked as the top 25% (Heff) or bottom 25% (Leff) based on their lactation production efficiency (MSperBW_lact). Dairy cow breed significantly affected animal characteristics over the entire lactation and during specific periods of intake measurements. Jersey crossbred animals produced more milk, based on a lower TDMI, and achieved an increased intake per kilogram of BW. Similarly, Heff produced more milk over longer lactations, weighed less, were older, and achieved a higher TDMI compared with the Leff animals. Both Jersey × Holstein-Friesian and Heff cows achieved superior production efficiency due to lower maintenance energy requirements, and consequentially increased milk solids production per kilogram of BW and per kilogram of TDMI at all stages of lactation. Indeed, within breed, Heff animals weighed 20 kg less and produced 15% more milk solids over the total lactation than Leff. In addition, Heff achieved increased daily milk solids yield (+0.16 kg) and milk solids yield per kilogram of TDMI (+ 0.23 kg/kg DM) during intake measurement periods. Moreover, the strong and consistently positive correlations between MSperBW_lact and detailed production efficiency traits (dMSperBW_int, dMSperTDMI) reported here demonstrate that MSperBW_lact is a robust measure that can be applied within commercial grazing dairy systems to increase the selection intensity for highly efficient animals.

Study of cattle microbiota in different regions of Kazakhstan using 16S metabarcoding analysis

Methane (CH₄) is an important greenhouse gas (GHG). Enteric methane emissions from farmed ruminant livestock account for approximately 15% of global GHG emissions, with approximately 44% of livestock emissions in the form of methane. The purpose of the research is to study the influence of feeding types and regional characteristics of Kazakhstan on the microbiota of feces and the number of methane-forming archaea of beef and meat-and-dairy cattle productivity. For this purpose, fecal samples were taken rectally from 37 cattle heads from four regions of Kazakhstan (Western, Southern, Northern and Southeast). The taxonomic composition of the community in all samples was determined by 16S metabarcoding; additionally alpha and beta diversities were calculated. The dominant phyla were: Firmicutes (57.30%), Bacteroidetes (17.00%), Verrucomicrobia (6.88%), Euryarchaeota (6.49%), Actinobacteria (4.77%) and Patescibacteria (3.38%). Significant differences with regard to methanogens bacteria were found: Euryarchaeota were less present in animals from Western Kazakhstan (2.40%), while Methanobacteriales and Methanobrevibacter were prevalent in Southeast, and less abundant in Western region. Western Kazakhstan differs from the other regions likely because animals are mainly grazed in the pasture. Thus, grazing animals has an impact on their microbiota thus leading to a decrease in methane emissions.

The potential for mitigation of methane emissions in ruminants through the application of metagenomics, metabolomics, and other -OMICS technologies

Ruminant supply chains contribute 5.7 gigatons of CO_2-eq per annum, which represents approximately 80% of the livestock sector emissions. One of the largest sources of emission in the ruminant sector is methane (CH₄), accounting for approximately 40% of the sectors total emissions. With climate change being a growing concern, emphasis is being put on reducing greenhouse gas emissions, including those from ruminant production. Various genetic and environmental factors influence cattle CH₄ production, such as breed, genetic makeup, diet, management practices, and physiological status of the host. The influence of genetic variability on CH₄ yield in ruminants indicates that genomic selection for reduced CH₄ emissions is possible. Although the microbiology of CH₄ production has been studied, further research is needed to identify key differences in the host and microbiome genomes and how they interact with one another. The advancement of “-omics” technologies, such as metabolomics and metagenomics, may provide valuable information in this regard. Improved understanding of genetic mechanisms associated with CH₄ production and the interaction between the microbiome profile and host genetics will increase the rate of genetic progress for reduced CH₄ emissions. Through a systems biology approach, various “-omics” technologies can be combined to unravel genomic regions and genetic markers associated with CH₄ production, which can then be used in selective breeding programs. This comprehensive review discusses current challenges in applying genomic selection for reduced CH₄ emissions, and the potential for “-omics” technologies, especially metabolomics and metagenomics, to minimize such challenges. The integration and evaluation of different levels of biological information using a systems biology approach is also discussed, which can assist in understanding the underlying genetic mechanisms and biology of CH₄ production traits in ruminants and aid in reducing agriculture’s overall environmental footprint.

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.

Contribution of genetic variability to phenotypic differences in on-farm efficiency metrics of dairy cows based on body weight and milk solids yield

Milk solids per kilogram of body weight (BW) is growing in popularity as a measure of dairy cow lactation efficiency. Little is known on the extent of genetic variability that exist in this trait but also the direction and strength of genetic correlations with other performance traits. Such genetic correlations are important to know if producers are to consider actively selecting cows excelling in milk solids per kilogram of BW. The objective of the present study was to use a large data set of commercial Irish dairy cows to quantify the extent of genetic variability in milk solids per kilogram of BW and related traits but also their genetic and phenotypic inter-relationships. Mid-lactation BW and body condition score (BCS), along with 305-d milk solids yield (i.e., fat plus protein yield) were available on 12,413 lactations from 11,062 cows in 85 different commercial dairy herds. (Co)variance components were estimated using repeatability animal linear mixed models. The genetic correlation between milk solids and body weight was only 0.05, which when coupled with the observed large genetic variability in both traits, indicate massive potential to select for both traits in opposite directions. The genetic correlations between both milk solids and BW with BCS; however, need to be considered in any breeding strategy. The genetic standard deviation, heritability, and repeatability of milk solids per kilogram of BW was 0.08, 0.37, and 0.57, respectively. The genetic correlation between milk solids per kilogram of BW with milk solids, BW, and BCS was 0.62, -0.75, and -0.41, respectively. Therefore, based on genetic regression, each increase of 0.10 units in genetic merit for milk solids per kilogram of BW is expected to result in, on average, an increase in 16.1 kg 305-d milk solids yield, a reduction of 25.6 kg of BW and a reduction of 0.05 BCS units (scale of 1-5 where 1 is emaciated). The genetic standard deviation (heritability) for 305-d milk solids yield adjusted phenotypically to a common BW was 27.3 kg (0.22). The genetic correlation between this adjusted milk solids trait with milk solids, BW, and BCS was 0.91, -0.12, and -0.26, respectively. Once also adjusted phenotypically to a common BCS, the genetic standard deviation (heritability) for milk solids adjusted phenotypically to a common BW was 26.8 kg (0.22) where the genetic correlation with milk solids, BW and BCS was 0.91, -0.21, and -0.07, respectively. The genetic standard deviation (heritability) of BW adjusted phenotypically for differences in milk solids was 35.3 kg (0.61), which reduced to 33.2 kg when also phenotypically adjusted for differences in BCS. Results suggest considerable opportunity exists to change milk solids yield independent of BW, and vice versa. The opportunity is reduced slightly once also corrected for differences in BCS. Inter-animal BCS differences should be considered if selection on such metrics is contemplated.

Effect of Dietary Supplementation with Lipids of Different Unsaturation Degree on Feed Efficiency and Milk Fatty Acid Profile in Dairy Sheep

Lipids of different unsaturation degree were added to dairy ewe diet to test the hypothesis that unsaturated oils would modulate milk fatty acid (FA) profile without impairing or even improving feed efficiency. To this aim, we examined milk FA profile and efficiency metrics (feed conversion ratio (FCR), energy conversion ratio (ECR), residual feed intake (RFI), and residual energy intake (REI)) in 40 lactating ewes fed a diet with no lipid supplementation (Control) or supplemented with 3 fats rich in saturated, monounsaturated and polyunsaturated FA (i.e., purified palmitic acid (PA), olive oil (OO), and soybean oil (SBO)). Compared with PA, addition of OO decreased milk medium-chain saturated FA and improved the concentration of potentially health-promoting FA, such as cis-9 18:1, trans-11 18:1, cis-9 trans-11 CLA, and 4:0, with no impact on feed efficiency metrics. Nevertheless, FA analysis and decreases in FCR and ECR suggested that SBO supplementation would be a better nutritional strategy to further improve milk FA profile and feed efficiency in dairy ewes. The paradox of differences observed depending on the metric used to estimate feed efficiency (i.e., the lack of variation in RFI and REI vs. changes in FCR and ECR) does not allow solid conclusions to be drawn in this regard.

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

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

Effects of 3-nitrooxypropanol and varying concentrate feed proportions in the ration on methane emission, rumen fermentation and performance of periparturient dairy cows

The climate-relevant enteric methane (CH₄) formation represents a loss of feed energy that is potentially meaningful for energetically undersupplied peripartal dairy cows. Higher concentrate feed proportions (CFP) are known to reduce CH₄ emissions in cows. The same applies to the feed additive 3-nitrooxypropanol (3-NOP), albeit through different mechanisms. It was hypothesised that the hydrogen not utilised for CH₄ formation through the inhibition by 3-NOP would be sequestered by propionate formation triggered by higher CFP so that it could thereby give rise to a synergistically reduced CH₄ emission. In a 2 × 2-factorial design, low (LC) or high (HC) CFP were either tested without supplements (CON_LC, CON_HC) or combined with 3-NOP (NOP_LC, 48.4 mg/kg dry matter (DM); NOP_HC, 51.2 mg 3-NOP/kg DM). These four rations were fed to a total of 55 Holstein cows from d 28 ante partum until d 120 post partum. DM intake (DMI) was not affected by 3-NOP but increased with CFP (CFP; p < 0.001). CH₄/DMI and CH₄/energy-corrected milk (ECM) were mitigated by 3-NOP (23% NOP_LC, 33% NOP_HC) (p < 0.001) and high CFP (12% CON, 22% 3-NOP groups) (CFP × TIME p < 0.001). Under the conditions of the present experiment, the CH₄ emissions of NOP_LC increased to the level of the CON groups from week 8 until the end of trial (3-NOP × CFP × TIME; p < 0.01). CO₂ yield decreased by 3-NOP and high CFP (3-NOP × CFP; p < 0.001). The reduced body weight loss and feed efficiency in HC groups paralleled a more positive energy balance being most obvious in NOP_HC (3-NOP × CFP; p < 0.001). ECM was lower for NOP_HC compared to CON_HC (3-NOP × CFP; p < 0.05), whereas LC groups did not differ. A decreased fat to protein ratio was observed in HC groups and, until week 6 post partum, in NOP_LC. Milk lactose and urea increased by 3-NOP (3-NOP; p < 0.05). 3-NOP and high CFP changed rumen fermentation to a more propionic-metabolic profile (3-NOP; CFP; p < 0.01) but did not affect rumen pH. In conclusion, CH₄ emission was synergistically reduced when high CFP was combined with 3-NOP while the CH₄ mitigating 3-NOP effect decreased with progressing time when the supplement was added to the high-forage ration. The nature of these interactions needs to be clarified.

Genetic mechanisms underlying feed utilization and implementation of genomic selection for improved feed efficiency in dairy cattle

The economic importance of genetically improving feed efficiency has been recognized by cattle producers worldwide. It has the potential to considerably reduce costs, minimize environmental impact, optimize land and resource use efficiency, and improve the overall cattle industry’s profitability. Feed efficiency is a genetically complex trait that can be described as units of product output (e.g., milk yield) per unit of feed input. The main objective of this review paper is to present an overview of the main genetic and physiological mechanisms underlying feed utilization in ruminants and the process towards implementation of genomic selection for feed efficiency in dairy cattle. In summary, feed efficiency can be improved via numerous metabolic pathways and biological mechanisms through genetic selection. Various studies have indicated that feed efficiency is heritable, and genomic selection can be successfully implemented in dairy cattle with a large enough training population. In this context, some organizations have worked collaboratively to do research and develop training populations for successful implementation of joint international genomic evaluations. The integration of “-omics” technologies, further investments in high-throughput phenotyping, and identification of novel indicator traits will also be paramount in maximizing the rates of genetic progress for feed efficiency in dairy cattle worldwide.

Mitochondrial protein gene expression and the oxidative phosphorylation pathway associated with feed efficiency and energy balance in dairy cattle

Feed efficiency and energy balance are important traits underpinning profitability and environmental sustainability in animal production. They are complex traits, and our understanding of their underlying biology is currently limited. One measure of feed efficiency is residual feed intake (RFI), which is the difference between actual and predicted intake. Variation in RFI among individuals is attributable to the metabolic efficiency of energy utilization. High RFI (H_RFI) animals require more energy per unit of weight gain or milk produced compared with low RFI (L_RFI) animals. Energy balance (EB) is a closely related trait calculated very similarly to RFI. Cellular energy metabolism in mitochondria involves mitochondrial protein (MiP) encoded by both nuclear (NuMiP) and mitochondrial (MtMiP) genomes. We hypothesized that MiP genes are differentially expressed (DE) between H_RFI and L_RFI animal groups and similarly between negative and positive EB groups. Our study aimed to characterize MiP gene expression in white blood cells of H_RFI and L_RFI cows using RNA sequencing to identify genes and biological pathways associated with feed efficiency in dairy cattle. We used the top and bottom 14 cows ranked for RFI and EB out of 109 animals as H_RFI and L_RFI, and positive and negative EB groups, respectively. The gene expression counts across all nuclear and mitochondrial genes for animals in each group were used for differential gene expression analyses, weighted gene correlation network analysis, functional enrichment, and identification of hub genes. Out of 244 DE genes between RFI groups, 38 were MiP genes. The DE genes were enriched for the oxidative phosphorylation (OXPHOS) and ribosome pathways. The DE MiP genes were underexpressed in L_RFI (and negative EB) compared with the H_RFI (and positive EB) groups, suggestive of reduced mitochondrial activity in the L_RFI group. None of the MtMiP genes were among the DE MiP genes between the groups, which suggests a non-rate limiting role of MtMiP genes in feed efficiency and warrants further investigation. The role of MiP, particularly the NuMiP and OXPHOS pathways in RFI, was also supported by our gene correlation network analysis and the hub gene identification. We validated the findings in an independent data set. Overall, our study suggested that differences in feed efficiency in dairy cows may be linked to differences in cellular energy demand. This study broadens our knowledge of the biology of feed efficiency in dairy cattle.

The effects of energy metabolism variables on feed efficiency in respiration chamber studies with lactating dairy cows

The objective of the present study was to investigate factors related to variation in feed efficiency (FE) among cows. Data included 841 cow/period observations from 31 energy metabolism studies assembled across 3 research stations. The cows were categorized into low-, medium-, and high-FE groups according to residual feed intake (RFI), residual energy-corrected milk (RECM), and feed conversion efficiency (FCE). Mixed model regression was conducted to identify differences among the efficiency groups in animal and energy metabolism traits. Partial regression coefficients of both RFI and RECM agreed with published energy requirements more closely than cofficients derived from production experiments. Within RFI groups, efficient (Low-RFI) cows ate less, had a higher digestibility, produced less methane (CH₄) and heat, and had a higher efficiency of metabolizable energy (ME) utilization for milk production. High-RECM (most efficient) cows produced 6.0 kg/d more of energy-corrected milk (ECM) than their Low-RECM (least efficient) contemporaries at the same feed intake. They had a higher digestibility, produced less CH₄ and heat, and had a higher efficiency of ME utilization for milk production. The contributions of improved digestibility, reduced CH₄, and reduced urinary energy losses to increased ME intake at the same feed intake were 84, 12, and 4%, respectively. For both RFI and RECM analysis, increased metabolizability contributed to approximately 35% improved FE, with the remaining 65% attributed to the greater efficiency of utilization of ME. The analysis within RECM groups suggested that the difference in ME utilization was mainly due to the higher maintenance requirement of Low-RECM cows compared with Medium- and High-RECM cows, whereas the difference between Medium- and High-RECM cows resulted mainly from the higher efficiency of ME utilization for milk production in High-RECM cows. The main difference within FCE (ECM/DMI) categories was a greater (8.2 kg/d) ECM yield at the expense of mobilization in High-FCE cows compared with Low-FCE cows. Methane intensity (CH₄/ECM) was lower for efficient cows than for inefficient cows. The results indicated that RFI and RECM are different traits. We concluded that there is considerable variation in FE among cows that is not related to dilution of maintenance requirement or nutrient partitioning. Improving FE is a sustainable approach to reduce CH₄ production per unit of product, and at the same time improve the economics of milk production.

Effects of a Dietary L-Carnitine Supplementation on Performance, Energy Metabolism and Recovery from Calving in Dairy Cows

Simple Summary

Dairy cows develop metabolic diseases especially in the transition period due to high energy requirements for the process of calving, beginning milk production and, simultaneously, restricted feed intake capacity. L-carnitine is endogenously synthesised as an obligatory, quaternary amine for the initial step of ß-oxidation, but with the onset of lactation it is also excreted with milk, whereby its availability for other metabolic pathways might be limited. Supplemental L-carnitine might be able to fill in this apparent gap and to enhance the efficiency of ß-oxidation, whereby the magnitude of negative energy balance would be decreased. The present experiment mainly focused on the energy-consuming process of calving itself and on the energy metabolism during the first weeks of lactation.

Abstract

Dairy cows are metabolically challenged during the transition period. Furthermore, the process of parturition represents an energy-consuming process. The degree of negative energy balance and recovery from calving also depends on the efficiency of mitochondrial energy generation. At this point, L-carnitine plays an important role for the transfer of fatty acids to the site of their mitochondrial utilisation. A control (n = 30) and an L-carnitine group (n = 29, 25 g rumen-protected L-carnitine per cow and day) were created and blood samples were taken from day 42 ante partum (ap) until day 110 post-partum (pp) to clarify the impact of L-carnitine supplementation on dairy cows, especially during the transition period and early puerperium. Blood and clinical parameters were recorded in high resolution from 0.5 h to 72 h pp. L-carnitine-supplemented cows had higher amounts of milk fat in early lactation and higher triacylglyceride concentrations in plasma ap, indicating increased efficiency of fat oxidation. However, neither recovery from calving nor energy balance and lipomobilisation were influenced by L-carnitine.

Characterizing the metabotype and its persistency in lactating Holstein cows: An approach toward metabolic efficiency measures

The variation in feed efficiency among dairy cows is due to differences in fermentation and digestion characteristics, but recent studies have suggested that various aspects of postabsorptive metabolic processes including heat production or the metabolizable energy for maintenance are more crucial. Thus, metabolic efficiency largely determines feed efficiency, but whether divergent feed efficient cows differ in O₂ consumption and metabolic CO₂ production, directly determining the metabolic rate has not been investigated. Therefore, the objective of the present study was to determine whether variation in ME intake (MEI), O₂ consumption, and metabolic CO₂ production account for the variation in metabolic efficiency of dairy cows and whether this effect persists across the lactation cycle. Eighteen cows with different German breeding value functional herd life were kept in freestalls with ad libitum access to a total mixed ration that was kept constant in composition throughout the first lactation. Cows were blood sampled and weighed at wk 5, 13, and 42 postpartum (pp) and transferred into respiration chambers. Animals were retrospectively clustered according to MEI, O₂ consumption, and metabolic CO₂ production, each normalized to metabolic body weight (mBW). Cluster analysis revealed 9 high metabolically efficient (high-Meff) and 9 low metabolically efficient cows. The high-Meff cows had greater MEI and feed conversion efficiency, produced less metabolic CO₂ and methane, had a stronger negative energy balance, and tended to have a lower metabolic respiratory quotient. Further, high-Meff cows had lower residual MEI, less heat energy loss, and lower plasma glucose concentrations, but used a greater portion of body reserves instead of feed energy for milk synthesis, particularly at wk 5 and 13 pp. However, these group differences did not persist by wk 42 pp. Cow groups were not different in O₂ consumption, milk yield, metabolizable energy for maintenance, or the efficiency of tissue utilization for milk synthesis, but high-Meff cows tended to have the lower German relative breeding value functional herd life, indicating a link between metabolic performance and productive lifespan. In conclusion, the use of a clustering approach involving MEI/mBW, O₂/mBW, and CO₂/mBW seems to be a promising method to differentiate cows with divergent metabolic efficiency but does not allow identifying an individual metabotype that persists across the whole lactation cycle.

Effects of Body Condition and Concentrate Proportion of the Ration on Mobilization of Fat Depots and Energetic Condition in Dairy Cows during Early Lactation Based on Ultrasonic Measurements

Simple Summary

During early lactation, cows face metabolic challenges. They experience a negative energy balance as energy intake increases more slowly than energy output with milk rises. To compensate for that energy deficit, higher amounts of concentrate are offered. Additionally, cows are able to extract energy from body fat by lipid mobilization. Excessive body fat mobilization, however, leads to metabolic disorders. Therefore, high-conditioned cows are suggested to have a more pronounced lipid mobilization. The intention of the present study was to examine the change of various fat depots during the transition period depending on body condition and energy supply with ultrasonic measurements. Body condition loss after calving usually interpreted as mobilization of subcutaneous adipose tissue was not different between cows with a higher or lower body condition score. However, ultrasonic measurements detected a more pronounced mobilization of subcutaneous adipose tissue in higher conditioned animals. In contrast, inner fat depots were mobilized similarly between cows. Higher concentrate feed proportions led to a less pronounced negative energy balance. A less pronounced negative energy balance would have been expected to decrease lipid mobilization. However, this relation could not be verified in the present study. This demonstrates that sonography-based methods provide a clearer picture of metabolic conditions.

Abstract

The aim of this study was to evaluate energy metabolism and lipid mobilization via ultrasonic measurements (USM), considering inner fat depots, in lactating dairy cows differing in body condition score (BCS) and fed rations with low (35% at dry matter basis; C₃₅) or high (60% at dry matter basis; C₆₀) concentrate feed proportions postpartum. Sixty pluriparous German Holstein cows were arranged in a 2 × 2 factorial design from d 42 antepartum (relative to calculated calving) until d 120 postpartum. Animals were divided into a group with a lower (initial BCS = 3.1 ± 0.38 SD; BCS_L) and a group with a higher (initial BCS = 3.83 ± 0.41 SD; BCS_H) BCS. Due to higher dry matter intake C₆₀ groups reached the positive energy balance earlier, whereas C₃₅ groups had a more pronounced negative energy balance. Although this would suggest a more pronounced mobilization of C₃₅ groups the USM revealed no differences between feeding groups. Differences in BCS between both BCS groups remained almost the same over the trial. This was not reflected in ultrasonic data, as lipid mobilization was higher in higher conditioned cows. These findings demonstrate the extended possibilities of USM to depict metabolic processes.

Whole rumen metagenome sequencing allows classifying and predicting feed efficiency and intake levels in cattle

The current research was carried out to determine the associations between the rumen microbiota and traits related with feed efficiency in a Holstein cattle population (n = 30) using whole metagenome sequencing. Improving feed efficiency (FE) is important for a more sustainable livestock production. The variability for the efficiency of feed utilization in ruminants is partially controlled by the gastrointestinal microbiota. Modulating the microbiota composition can promote a more sustainable and efficient livestock. This study revealed that most efficient cows had larger relative abundance of Bacteroidetes (P = 0.041) and Prevotella (P = 0.003), while lower, but non-significant (P = 0.119), relative abundance of Firmicutes. Methanobacteria (P = 0.004) and Methanobrevibacter (P = 0.003) were also less abundant in the high-efficiency cows. A de novo metagenome assembly was carried out using de Bruijn graphs in MEGAHIT resulting in 496,375 contigs. An agnostic pre-selection of microbial contigs allowed high classification accuracy for FE and intake levels using hierarchical classification. These microbial contigs were also able to predict FE and intake levels with accuracy of 0.19 and 0.39, respectively, in an independent population (n = 31). Nonetheless, a larger potential accuracy up to 0.69 was foreseen in this study for datasets that allowed a larger statistical power. Enrichment analyses showed that genes within these contigs were mainly involved in fatty acids and cellulose degradation pathways. The findings indicated that there are differences between the microbiota compositions of high and low-efficiency animals both at the taxonomical and gene levels. These differences are even more evident in terms of intake levels. Some of these differences remain even between populations under different diets and environments, and can provide information on the feed utilization performance without information on the individual intake level.

The rumen microbiome: a crucial consideration when optimising milk and meat production and nitrogen utilisation efficiency

Methane is generated in the foregut of all ruminant animals by the microorganisms present. Dietary manipulation is regarded as the most effective and most convenient way to reduce methane emissions (and in turn energy loss in the animal) and increase nitrogen utilization efficiency. This review examines the impact of diet on bovine rumen function and outlines what is known about the rumen microbiome. Our understanding of this area has increased significantly in recent years due to the application of omics technologies to determine microbial composition and functionality patterns in the rumen. This information can be combined with data on nutrition, rumen physiology, nitrogen excretion and/or methane emission to provide comprehensive insights into the relationship between rumen microbial activity, nitrogen utilisation efficiency and methane emission, with an ultimate view to the development of new and improved intervention strategies.

Statistical properties of proportional residual energy intake as a new measure of energetic efficiency

Traditional ratio measures of efficiency, including feed conversion ratio (FCR), gross milk efficiency (GME), gross energy efficiency (GEE) and net energy efficiency (NEE) may have some statistical problems including high correlations with milk yield. Residual energy intake (REI) or residual feed intake (RFI) is another criterion, proposed to overcome the problems attributed to the traditional ratio criteria, but it does not account for production or intake levels. For example, the same REI value could be considerable for low producing and negligible for high producing cows. The aim of this study was to propose a new measure of efficiency to overcome the problems attributed to the previous criteria. A total of 1478 monthly records of 268 lactating Holstein cows were used for this study. In addition to FCR, GME, GEE, NEE and REI, a new criterion called proportional residual energy intake (PREI) was calculated as REI to net energy intake ratio and defined as proportion of net energy intake lost as REI. The PREI had an average of -0·02 and range of -0·36 to 0·27, meaning that the least efficient cow lost 0·27 of her net energy intake as REI, while the most efficient animal saved 0·36 of her net energy intake as less REI. Traditional ratio criteria (FCR, GME, GEE and NEE) had high correlations with milk and fat corrected milk yields (absolute values from 0·469 to 0·816), while the REI and PREI had low correlations (0·000 to 0·069) with milk production. The results showed that the traditional ratio criteria (FCR, GME, GEE and NEE) are highly influenced by production traits, while the REI and PREI are independent of production level. Moreover, the PREI adjusts the REI magnitude for intake level. It seems that the PREI could be considered as a worthwhile measure of efficiency for future studies.

The potential of Fourier transform infrared spectroscopy of milk samples to predict energy intake and efficiency in dairy cows

Knowledge of animal-level and herd-level energy intake, energy balance, and feed efficiency affect day-to-day herd management strategies; information on these traits at an individual animal level is also useful in animal breeding programs. A paucity of data (especially at the individual cow level), of feed intake in particular, hinders the inclusion of such attributes in herd management decision-support tools and breeding programs. Dairy producers have access to an individual cow milk sample at least once daily during lactation, and consequently any low-cost phenotyping strategy should consider exploiting measureable properties in this biological sample, reflecting the physiological status and performance of the cow. Infrared spectroscopy is the study of the interaction of an electromagnetic wave with matter and it is used globally to predict milk quality parameters on routinely acquired individual cow milk samples and bulk tank samples. Thus, exploiting infrared spectroscopy in next-generation phenotyping will ensure potentially rapid application globally with a negligible additional implementation cost as the infrastructure already exists. Fourier-transform infrared spectroscopy (FTIRS) analysis is already used to predict milk fat and protein concentrations, the ratio of which has been proposed as an indicator of energy balance. Milk FTIRS is also able to predict the concentration of various fatty acids in milk, the composition of which is known to change when body tissue is mobilized; that is, when the cow is in negative energy balance. Energy balance is mathematically very similar to residual energy intake (REI), a suggested measure of feed efficiency. Therefore, the prediction of energy intake, energy balance, and feed efficiency (i.e., REI) from milk FTIRS seems logical. In fact, the accuracy of predicting (i.e., correlation between predicted and actual values; root mean square error in parentheses) energy intake, energy balance, and REI from milk FTIRS in dairy cows was 0.88 (20.0MJ), 0.78 (18.6MJ), and 0.63 (22.0MJ), respectively, based on cross-validation. These studies, however, are limited to results from one research group based on data from 2 contrasting production systems in the United Kingdom and Ireland and would need to be replicated, especially in a range of production systems because the prediction equations are not accurate when the variability used in validation is not represented in the calibration data set. Heritable genetic variation exists for all predicted traits. Phenotypic differences in energy intake also exists among animals stratified based on genetic merit for energy intake predicted from milk FTIRS, substantiating the usefulness of such FTIR-predicted phenotypes not only for day-to-day herd management, but also as part of a breeding strategy to improve cow performance.

Haematological, clinical-chemical and immunological consequences of feeding Fusarium toxin contaminated diets to early lactating dairy cows

Dairy cows experience a negative energy balance at the onset of lactation which results in an enhanced vulnerability for infectious diseases. Any dietary imbalances, including Fusarium toxin contamination, might therefore exacerbate this situation. The aim of the present investigations was to study the effects of increasing dietary concentrations of deoxynivalenol (DON) and zearalenone (ZEN) on clinical-chemical, haematological and immunological traits up to week 14 of lactation. For this purpose, ten cows each were assigned to a control group (CON; 0.02 mg ZEN and 0.06 mg DON per kg diet at 88 % DM), toxin level 1 (TOX-1; 0.29 mg ZEN and 2.31 mg DON per kg diet at 88 % DM) and toxin level 2 (TOX-2; 0.58 mg ZEN and 4.61 mg DON per kg diet at 88 % DM). The measured values of most parameters were affected by parturition but only a few of them were further modified by dietary treatment. For example, the time-dependent decrease in haemoglobin concentration, haematocrit and erythrocyte counts occurred at a significantly higher level for group TOX-2 while a serum glucose increase was missing in this group. Proportions of CD4+ and CD8+ cells decreased significantly over time solely in group TOX-2 while the CD4+/CD8+ ratio remained uninfluenced. Ability of granulocytes to mount an oxidative burst tended to increase at the end of the study in groups TOX-1 and TOX-2 while the opposite was observed in group CON. The results of this time-limited study indicate that feeding of Fusarium-toxin contaminated diets in early lactation affects health related parameters without compromising milking performance. However, long-term consequences of the observed effects on health need to be addressed in further studies.