The effects of residual energy intake on nutrient use, methane emissions and microbial composition in dairy cows.

For sustainable food production selection and breeding of feed efficient animals is crucial. The objective of this study was to evaluate whether multiparous dairy cows, ranked during their first lactation based on residual energy intake (REI) as efficient (low; L-REI) or inefficient (high; H-REI), differ in terms of nutrient use efficiency, methane emissions, rumen fermentation, and gut microbiota composition. Six L-REI and 6 H-REI cows were offered two diets with either a low or high proportion of concentrates (30 vs. 50% of DM) on two consecutive periods of 21 d. Gas exchanges, milk yield, feces and urine excretions were measured in open-circuit respiratory chambers. The results indicated that L-REI cows had higher methane yields (22.6 vs. 20.4 g/kg DM intake) and derived more energy (energy balance - 36.6 vs. - 16.9 MJ/d) and protein (N balance - 6.6 vs. 18.8 g/d) from the tissues to support similar milk yields compared to H-REI cows. Nutrient intake and digestibility were not affected by REI, and there were no interactions between REI and diet. Milk yield, milk production efficiency, and milk composition were not affected by REI except for milk urea concentration that was higher for L-REI cows (14.1 vs. 10.8 mg/100 ml). The rumen and fecal microbiota community structure and function were associated with both the diet and REI, but the diet effect was more pronounced. The current study identified several physiological mechanisms underlying the differences between high and low REI cows, but further studies are needed to distinguish the quantitative role of each mechanism.

Short communication: Predicting blood plasma non-esterified fatty acid and beta-hydroxybutyrate concentrations from cow milk-addressing systematic issues in modelling.

Negative energy status in early lactation is linked to a variety of metabolic disorders, reduced fertility, and decreased milk production. To improve the energy status of cows by breeding and management, the identification of negative energy status is crucial. While biomarkers such as non-esterified fatty acid (NEFA) concentration and beta-hydroxybutyrate (BHB) in blood plasma could be used to identify a negative energy state, measuring them directly from blood is both invasive and expensive. In this work, we developed prediction equations for blood plasma NEFA and BHB levels based on mid-IR spectral measurements of milk. The models were fitted using partial least squares regression and evaluated using both cross-validation and independent-herd validation. A total of 3 183 spectral records from 606 lactations originating from three different herds were utilised. R2 values of 0.53 (RMSE = 0.206 mmol/l, RMSE of cross-validation (RMSECV) 0.217 mmol/l) for NEFA and 0.63 (RMSE = 0.326 mmol/l, RMSECV = 0.353 mmol/l) for BHB were obtained. Furthermore, relatively similar prediction accuracies were found for BHB (RMSE of prediction (RMSEP) 0.411 mmol/l and 0.422 mmol/l) and NEFA (RMSEP = 0.186 mmol/l and 0.221 mmol/l) when model training was done using two herds and validated on the third herd. The results from the model fits confirm that it is possible to build blood plasma BHB and NEFA models based on mid-IR spectra that are sufficiently accurate for practical use.

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 (rtest = 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.

Long-term effects of early-life rumen microbiota modulation on dairy cow production performance and methane emissions.

Rumen microbiota modulation during the pre-weaning period has been suggested as means to affect animal performance later in life. In this follow-up study, we examined the post-weaning rumen microbiota development differences in monozygotic twin-heifers that were inoculated (T-group) or not inoculated (C-group) (n = 4 each) with fresh adult rumen liquid during their pre-weaning period. We also assessed the treatment effect on production parameters and methane emissions of cows during their 1st lactation period. The rumen microbiota was determined by the 16S rRNA gene, 18S rRNA gene, and ITS1 amplicon sequencing. Animal weight gain and rumen fermentation parameters were monitored from 2 to 12 months of age. The weight gain was not affected by treatment, but butyrate proportion was higher in T-group in month 3 (p = 0.04). Apart from archaea (p = 0.084), the richness of bacteria (p < 0.0001) and ciliate protozoa increased until month 7 (p = 0.004) and anaerobic fungi until month 11 (p = 0.005). The microbiota structure, measured as Bray-Curtis distances, continued to develop until months 3, 6, 7, and 10, in archaea, ciliate protozoa, bacteria, and anaerobic fungi, respectively (for all: p = 0.001). Treatment or age × treatment interaction had a significant (p < 0.05) effect on 18 bacterial, 2 archaeal, and 6 ciliate protozoan taxonomic groups, with differences occurring mostly before month 4 in bacteria, and month 3 in archaea and ciliate protozoa. Treatment stimulated earlier maturation of prokaryote community in T-group before month 4 and earlier maturation of ciliate protozoa at month 2 (Random Forest: 0.75 month for bacteria and 1.5 month for protozoa). No treatment effect on the maturity of anaerobic fungi was observed. The milk production and quality, feed efficiency, and methane emissions were monitored during cow's 1st lactation. The T-group had lower variation in energy-corrected milk yield (p < 0.001), tended to differ in pattern of residual energy intake over time (p = 0.069), and had numerically lower somatic cell count throughout their 1st lactation period (p = 0.081), but no differences between the groups in methane emissions (g/d, g/kg DMI, or g/kg milk) were observed. Our results demonstrated that the orally administered microbial inoculant induced transient changes in early rumen microbiome maturation. In addition, the treatment may influence the later production performance, although the mechanisms that mediate these effects need to be further explored.

Mid-infrared spectroscopic analysis of raw milk to predict the blood nonesterified fatty acid concentrations in dairy cows.

In high-yielding dairy cattle, severe postpartum negative energy balance is often associated with metabolic and infectious disorders that negatively affect production, fertility, and welfare. Mobilization of adipose tissue associated with negative energy balance is reflected through an increased level of nonesterified fatty acids (NEFA) in the blood plasma. Earlier, identification of negative energy balance through detection of increased blood plasma NEFA concentration required laborious and stressful blood sampling. More recently, attempts have been made to predict blood NEFA concentration from milk samples. In this study, we aimed to develop and validate a model to predict blood plasma NEFA concentration using the milk mid-infrared (MIR) spectra that are routinely measured in the context of milk recording. To this end, blood plasma and milk samples were collected in wk 2, 3, and 20 postpartum for 192 lactations in 3 herds. The blood plasma samples were taken in the morning, and representative milk samples were collected during the morning and evening milk sessions on the same day. To predict plasma NEFA concentration from the milk MIR spectra, partial least squares regression models were trained on part of the observations from the first herd. The models were then thoroughly validated on all other observations of the first herd and on the observations of the 2 independent herds to explore their robustness and wide applicability. The final model could accurately predict blood plasma NEFA concentrations <0.6 mmol/L with a root mean square error of prediction of <0.143 mmol/L. However, for blood plasma with >1.2 mmol/L NEFA, the model clearly underestimated the true level. Additionally, we found that morning blood plasma NEFA levels were predicted with significantly higher accuracy using MIR spectra of evening milk samples compared with MIR spectra of morning samples, with root mean square error of prediction values of, respectively, 0.182 and 0.197 mmol/L, and R2 values of 0.613 and 0.502. These results suggest a time delay between variations in blood plasma NEFA and related milk biomarkers. Based on the MIR spectra of evening milk samples, cows at risk for negative energy status, indicated by detrimental morning blood plasma NEFA levels (>0.6 mmol/L), could be identified with a sensitivity and specificity of, respectively, 0.831 and 0.800. As this model can be applied to millions of historical and future milk MIR spectra, it opens an opportunity for regular metabolic screening and improved resilience phenotyping.

Effect of dietary protein on embryo recovery rate and quality in superovulated heifers.

For almost 3 decades, superovulation and embryo transfer have been used in cattle breeding to increase the number of offspring from genetically superior female animals. Several factors including nutrition affect the number of transferable embryos recovered. We compared the effects of two different dietary protein levels easily achieved in practical conditions on embryo number and quality in superovulated heifers. Finnish Ayrshire heifers (n = 37) were allocated to isoenergic diets containing either 14% (D14) or 18% (D18) crude protein (CP). Estruses were synchronized, and the heifers were subsequently superovulated and inseminated using a standard FSH-protocol. Embryos were collected 7 days after inseminations (71-72 days after the beginning of the treatment period) by uterine flushing. The number of corpora lutea, and the number and quality of embryos were determined. Protein feeding did not affect superovulatory response, the number of embryos or the number of transferable embryos recovered. Proportionally more poor-quality embryos were found in group D14 than in group D18 (20.2% versus 13.2%, respectively, P = 0.053). It is concluded that a long-term moderate increase in the content of crude protein fed to energy-adequate heifers does not seem to affect superovulatory response and the number of embryos recovered, but it may be advantageous to the quality of embryos.