Dairy cow nutritional programs are a major determinant of the profitability of dairy farms. Despite this, the sustainability of the dairy enterprise is beyond just cow nutrition. For almost 50 yr, the NC-2042 project (Management Systems to Improve the Economic and Environmental Sustainability of Dairy Enterprises) has been addressing most of these components as individual research units and in integrated ways. This review has the objective to report the body of research developed by members of the group in connection with the existing literature on dietary formulation and feeding management during the dry period, peripartal period, and early postpartum (fresh) period. Peak disease incidence (shortly after parturition) corresponds with the time of greatest negative energy balance (NEB), the peak in blood concentrations of nonesterified fatty acids, and the greatest acceleration of milk yield. Decreased fertility in the face of increasing milk production may be attributable to greater severity of postpartal NEB resulting from inadequate transition management or increased rates of disease. The depth and duration of NEB is highly related to dry matter intake. Periparturient diseases can result from adverse ruminal conditions caused by excessive grain in the precalving or fresh cow diet, perhaps aggravated by overcrowding, heat stress, or other stressors. Others have also implicated inflammatory responses in alterations of metabolism, occurrence of health problems, and impaired reproduction. Providing controlled-energy and negative dietary cation-anion difference diets prepartum may improve dairy cow performance during the transition period. A major area of concern in the fresh cow period is a sudden increase in dietary energy density leading to subacute ruminal acidosis, which can decrease dry matter intake and digestibility of nutrients. Adequate physical form of the diet, derived from either forage neutral detergent fiber content or a mixing strategy of different ingredients in a total mixed ration, must be present to stimulate ruminal activity and chewing behavior. In conclusion, formulation and delivery of appropriate diets that limit total energy intake to requirements but also provide proper intakes of all other nutrients (including the most limiting amino acids Met and Lys) before calving can help lessen the extent of NEB after calving. Effects of such diets on indicators of metabolic health are generally positive, suggesting the potential to lessen effects of periparturient disease on fertility.

The gastrointestinal tracts of ruminants harbor a diverse microbial community that coevolved symbiotically with the host, influencing its nutrition, health, and performance. While the influence of environmental factors on rumen microbes is well documented, the process by which host genetics influences the establishment and colonization of the rumen microbiota still needs to be elucidated. This knowledge gap is due largely to our inability to easily sample the rumen microbiota. There are three common methods for rumen sampling but all of them present at least one disadvantage, including animal welfare, sample quality, labor, and scalability. The development and validation of noninvasive methods, such as buccal swabbing, for large-scale rumen sampling is needed to support studies that require large sample sizes to generate reliable results. The validation of buccal swabbing will also support the development of molecular tools for the early diagnosis of metabolic disorders associated with microbial changes in large herds.

The effects of different ruminal protozoa (RP) on CH₄ emissions from ruminants were evaluated in a meta-analysis, using 64 publications reporting data from 79 in vivo experiments. Experiments included in the database reported CH₄ emissions (g/d) and total RP (TRP, log₁₀ cells/mL) from the same group of animals. The relationship between CH₄ emissions and RP (TRP, entodiniomorphids, and isotrichids), and TRP-, entodiniomorphid-, and isotrichid-based CH₄ emission prediction models, were evaluated as mixed models with experiment as a random effect and weighted by the reciprocal of the standard error of the mean and centered around one. Positive associations existed between TRP and isotrichids with CH₄ emissions but not between entodiniomorphids and CH₄ emissions. A reduction in CH₄ emissions was observed, averaging 7.96 and 4.25 g/d, per log unit reduction in TRP and isotrichid concentrations, respectively. Total RP and isotrichids were important variables in predicting CH₄ emissions from ruminants. Isotrichid CH₄ prediction model was more robust than the TRP, evidenciated by lower predicted sigma hat study (%), and error (%), and with higher concordance correlation coefficient. Both TRP and isotrichid models can accurately predict CH₄ emissions across different ruminant types, as shown by the low square root of the mean square prediction error, with 6.59 and 4.08% of the mean of root of the mean square prediction error in the TRP and isotrichid models, respectively. Our results confirm that isotrichids are more important than entodiniomorphids in methanogenesis. Distinguishing these 2 populations yielded a more robust CH₄ prediction model than combining them as total protozoa.

A meta-analysis was conducted to compare the effects of feeding dairy cows conventional sorghum silage (CSS) or conventional corn silage (CCS) compared with brown midrib sorghum silage (BMRSS) diets on dry matter intake (DMI), milk production, and milk composition. Data from 9 published articles (1984 to 2015) were used to contrast diets with CSS (7 means comparisons; 104 cows) or CCS (13 means comparisons; 204 cows) versus BMRSS diets. Statistical analysis was performed using fixed or random effects models with the Metafor package of R (https://www.R-project.org). The degree of heterogeneity was measured with the I2 statistic, and publication bias was determined with funnel plots and Egger's regression test. Other sources of heterogeneity of response were analyzed through meta-regression. Estimated effect size was calculated for DMI, milk production, and milk composition. No evidence of publication bias was observed for any variable tested. The highest degree of heterogeneity (I2 = 41.5 and 72.6%) was observed for DMI among dependent variables tested in both comparisons, indicating that intake responses to silage type are rather inconsistent; in contrast, milk production had the lowest degree of heterogeneity (I2 = 0%), supporting the idea that the responses of this variable to silage type were very consistent across studies. Compared with BMRSS diets, cows fed CSS diets exhibited decreased milk production (1.64 kg/d), milk fat concentration (0.09%), milk fat yield (0.08 kg/d), milk protein yield (0.04 kg/d), and milk lactose yield (0.16 kg/d) and tended to decrease DMI (0.83 kg/d). Compared with CCS diets, cows fed BMRSS diets increased milk fat concentration (0.10%), but decreased milk protein concentration (0.06%) and tended to increase lactose yield (0.08 kg/d). Meta-regression indicated that days in milk affected DMI and milk production when CSS diets were compared with BMRSS diets, and DMI when CCS diets were compared with BMRSS diets. Additionally, the inclusion rate of silage in the diet and dietary neutral detergent fiber affected yields of milk fat and lactose, respectively, when CCS and BMRSS diets were compared. Overall, lactation performance improved when cows were fed diets formulated with BMRSS compared with CSS, but performance was not different for cows fed BMRSS and CCS diets. However, the small sample size may have influenced these results by increasing the margin of the error and, concurrently, the power of the meta-analysis. Results of this analysis suggest that additional research is needed to explore the effects of days in milk and the inclusion rates of silages in the diets when comparing BMRSS with CSS or CCS.

The objective of this study was to investigate the effects on plasma metabolites and rumen traits when butyrate was infused into the rumen or abomasum of lactating cows. Jugular catheters were inserted into 5 ruminally fistulated Holstein cows [94.2 ± 26.3 DIM; 717 ± 45 kg of body weight (BW); mean ± SD] in a 5 × 5 Latin square with 3-d periods. Cows were infused for 24 h with 1 of 5 treatments: water (CON), 1 g/kg of BW of butyrate infused into either the abomasum (A1) or rumen (R1), or 2 g/kg of BW of butyrate infused into either the abomasum or rumen. Sodium butyrate was the source of butyrate and NaCl was added to the CON, A1, and R1 treatments to provide the same amount of sodium as supplied by the sodium butyrate treatment in the 2-g treatments. Plastisol flanges were inserted into the abomasum to allow infusion to the abomasum and peristaltic pumps provided continuous infusion at 9.3 mL/min for all treatments. The concentration of NaCl and sodium butyrate was varied in the infusate to provide the correct infusion amount. Rumen fluid samples were collected at -2, -1, 0, 1, 2, 3, 4, 6, 8, 12, 18, 24, 28, and 32 h relative to start of infusion. Serial blood samples were collected at -2, -1, 0, 0.5, 1, 2, 3, 4, 6, 8, 12, 18, 24, 26, 28, and 32 h relative to start of infusion. Compared with CON, infusing butyrate increased both plasma butyrate and plasma β-hydroxybutyrate (BHB), whereas plasma glucose decreased. Increasing butyrate infusion from 1 to 2 g increased plasma butyrate, tended to decrease plasma glucose, and tended to increase plasma BHB. Compared with abomasal infusion, rumen infusion of butyrate increased rumen butyrate, did not affect plasma glucose, and tended to increase plasma BHB. Treatment had no effect on plasma insulin. Results demonstrated that site of infusion and amount of butyrate affected several plasma metabolites when butyrate was infused in lactating dairy cows over a period of 24 h.

Dairy cattle are globally important agricultural animals. Central to their biology is the rumen, which houses an essential microbial community, or microbiome, important for providing nutrition from otherwise host-inaccessible dietary components. The rumen environment is noted for its substantial spatial heterogeneity, as illustrated by the stratification into ruminal solid and liquid phases. A third microbiota found directly attached to the ruminal epithelium (the epimural microbiota) also exists but is less well understood because of challenges in sampling the ruminal epithelium. As a result, our understanding of the epimural microbiota is based on analyses of cannulated animals sampled at a single location-the ventral sac-and does not account for other ruminal locations, which may have importance for overall rumen function. To address this knowledge gap, we hypothesize that the epimural microbiota at different ruminal locations differs due to known morphological, physiological, and functional differences across the geographic spread of the rumen epithelium. Here, we characterized bacterial epimural communities at different sites within 8 lactating Holstein dairy cows using 16S rRNA gene sequencing. Four different sites were sampled via rumen tissue biopsy: cranial sac (CS), ventral sac (VS), caudodorsal blind sac (CDBS), and caudoventral blind sac (CVBS). We found that locations differed in both epimural bacterial community structure and composition, with the CDBS community displaying the greatest diversity. Across all sampling sites, epimural bacterial communities were dominated by members of the phyla Bacteroidetes, Firmicutes, and Proteobacteria. Bacteria within Prevotellaceae, Butyrivibrio, Campylobacter, Mogibacterium, and Desulfobulbus all showed high relative sequence abundance and differential distributions according to sample location. There appears to be a core epimural microbiota present across all locations in all cows, although relative abundance was highly variable. The difference in relative abundance in epimural microbial communities, perhaps influenced by host physiology and the diversity within rumen contents, likely has important consequences for nutrition acquisition and general health. To the best of our knowledge, this work represents the first characterization of the ruminal epimural microbiota across different epithelial locations for any bovine ruminant.