This is a prospective observational study that evaluates the effects of body condition score (BCS) changes in primiparous Holstein cows during peripartum on their NEFA and BHBA concentrations, hormone levels, postpartum health, and production performance. The cows under study (n = 213) were assessed to determine their BCS (5-point scale; 0.25-point increment) once a week during the whole peripartum by the same researchers; backfat was used for corrections. Blood samples were collected 21 and 7 days before calving and 7, 21, and 35 days after calving, and were assayed for NEFA, BHBA, growth hormone (GH), insulin, leptin, and adiponectin concentrations. The incidence of disease and milk yield were recorded until 84 days after calving. Cows were classified according to their BCS changes during peripartum as follows: Those that gained BCS (G; ΔBCS ≥ 0.25), maintained BCS (M; ΔBCS = 0–0.25), or lost BCS (L; ΔBCS ≥ 0.5). The BCS at −21 days and at 7, 14, and 21 days were different (p < 0.01), but trended toward uniformity in all groups at calving. The L group had higher NEFA and BHBA concentrations and hormone levels (p < 0.01) than the M and G groups at 21 and 35 days after calving, and had a higher incidence of uterine and metabolic diseases; however, there were no differences in production performance between the various groups. In conclusion, a lower BCS in primiparous cows during peripartum influences the NEFA and BHBA concentrations, hormone levels, and occurrence of health problems postpartum. The postpartum effects of BCS changes appear prior to calving.

N-carbamylglutamate (NCG), a structural analog of N-acetylglutamate, improves nitrogen utilization in dairy cows. However, the effects of NCG on bulls are unknown. The purpose of the current research was to investigate the effects of adding different amounts of NCG on growth performance, nutrient digestibility, nitrogen metabolism and plasma metabolites of fattening Holstein bulls. Twenty-four Holstein bulls with similar body weights (BW, 408 ± 21.9 kg) and ages (450 ± 6.1 d; all mean ± SD) were selected for the feeding trial. After 2 weeks of adaptation, bulls were blocked by BW and age and subsequently randomly assigned to 1 of 4 groups: (1) CON group (control diet), (2) L group (supplementation with 20 mg/kg BW NCG), (3) M group (supplementation with 40 mg/kg BW NCG), or (4) H group (supplementation with 80 mg/kg BW NCG). The addition of NCG linearly and quadratically increased the average daily gain (CON vs. L vs. M vs. H = 1.03 vs. 1.19 vs. 1.40 vs. 1.26 kg/d) (p < 0.05), feed conversion ratio (CON vs. L vs. M vs. H = 11.92 vs. 9.22 vs. 7.76 vs. 8.62) (p < 0.05), crude protein digestibility (CON vs. L vs. M vs. H = 64.3 vs. 63.8 vs. 67.7 vs. 65.8%) (0.05 < p < 0.10), N retention (p < 0.05) and N utilization (p < 0.05) of bulls, whereas the contents of fecal N (0.05 < p < 0.10) and urinary N (0.05 < p < 0.10) in NCG-fed bulls linearly decreased compared with those in CON bulls. Bulls fed NCG showed a quadratic increased plasma nitric oxide (p < 0.05) concentration. Furthermore, Arg (p < 0.05), Ile (p < 0.05), Val (p < 0.05), Ala (p < 0.05), Glu (p < 0.05), Ser (p < 0.05), total essential amino acid (p < 0.05) and total nonessential amino acid (p < 0.05) concentrations linearly and quadratically increased with increasing doses of NCG. In contrast, plasma urea (p < 0.05) and ammonia (p < 0.05) concentration linearly and quadratically decreased with increasing doses of NCG. Overall, the addition of NCG increased plasma Arg, Ile, Val, TEAA and TNEAA concentration, which in turn resulted in a higher N utilization and, therefore, higher average daily gain in NCG-fed bulls, providing baseline data for the widespread application of NCG in beef cattle production.

Volatile fatty acids (VFAs) and methane are the main products of rumen fermentation. Quantitative studies of rumen fermentation parameters can be performed using in vitro techniques and machine learning methods. The currently proposed models suffer from poor generalization ability due to the small number of samples. In this study, a prediction model for rumen fermentation parameters (methane, acetic acid (AA), and propionic acid (PA)) of dairy cows is established using the stacking ensemble learning method and in vitro techniques. Four factors related to the nutrient level of total mixed rations (TMRs) are selected as inputs to the model: neutral detergent fiber (NDF), acid detergent fiber (ADF), crude protein (CP), and dry matter (DM). The comparison of the prediction results of the stacking model and base learners shows that the stacking ensemble learning method has better prediction results for rumen methane (coefficient of determination ($R^2$) = 0.928, root mean square error (RMSE) = 0.968 mL/g), AA ($R^2$ = 0.888, RMSE = 1.975 mmol/L) and PA ($R^2$ = 0.924, RMSE = 0.74 mmol/L). And the stacking model simulates the variation of methane and VFAs in relation to the dietary fiber content. To demonstrate the robustness of the model in the case of small samples, an independent validation experiment was conducted. The stacking model successfully simulated the transition of rumen fermentation type and the change of methane content under different concentrate-to-forage (C:F) ratios of TMR. These results suggest that the rumen fermentation parameter prediction model can be used as a decision-making basis for the optimization of dairy cow diet compositions, rapid screening of methane emission reduction, feed beneficial to dairy cow health, and improvement of feed utilization.

Clostridium butyricum (C. butyricum) is currently widely used to improve the body health and productive performance of monogastric animals. However, there have been few reports on the effects and specific mechanism of action of Clostridium butyricum in ruminants. This study aimed to investigate the effects of Clostridium butyricum supplementation on the growth performance and digestive microbiota of fattening goats. Twenty-four healthy male Albas goats (body weight = 22 ± 2.03 kg) were randomly divided into 3 treatment groups with eight goats in each group. The treatments were as follows: control group (CON) (basal diet, concentrate to forage ratio = 65:35); low-dose Clostridium butyricum (LCB) (basal diet plus 2.0 × 10⁸ CFU/kg Clostridium butyricum); and high-dose Clostridium butyricum (HCB) (basal diet plus 1.0 × 10⁹ CFU/kg Clostridium butyricum). The experiment lasted for 8 weeks after a 2-week adaptation period. Therefore, growth performance and rumen and rectum microbiota were evaluated in goats supplemented with Clostridium butyricum and its metabolites. The results showed that dietary supplementation with Clostridium butyricum significantly increased the pH (P < 0.05), but had no significant effect on growth performance (P > 0.05). Compared with the control group, dietary Clostridium butyricum supplementation significantly increased the relative abundance of Prevotella_1, Christensenellaceae AE_R-7_Group and Prevotellaceae AE_UCG-003 (P < 0.05), and significantly decreased Succiniclasticum and Muribaculaceae_unclassified (P < 0.05). The relative abundance of Clostridium in the rumen was <1.0%. Moreover, 16S rDNA analysis showed that the fecal Clostridium or Clostridium butyricum count was significantly decreased (P < 0.05), and the relative abundance of Alistipes and Akkermansia was increased (P < 0.10) in the low-dose group compared with the control group. Supplementing Clostridium butyricum in a high-concentrate diet did not significantly affect the performance of goats, while regulation of the gastrointestinal microbiota and related metabolites was associated with rumen fermentation.

Clostridium butyricum, as a probiotic with a variety of active products, has been widely used to improve the intestinal health of humans and animals. Previous studies had demonstrated that Clostridium butyricum exhibited potential protective and positive effects in human disease research and animal production by producing a variety of beneficial substances, such as intestinal inflammation, the intestinal epithelial barrier, metabolic diseases, and regulation of the gut microbiota. Therefore, we hypothesized that dietary Clostridium butyricum supplementation could improve gut health in fattening goats by modulating gut microbiota. However, it is unclear whether Clostridium butyricum can reach the intestine through the rumen, so 15 healthy Albas goats were selected and randomly divided into 3 treatments with 5 replicates in each group. The groups were divided as follows: control group (CON: basal diet), rumen-protected Clostridium butyricum group (RPCB: basal diet plus 1.0 × 10⁹ CFU/kg Clostridium butyricum coated with hydrogenated fat), and Clostridium butyricum group (CB: basal diet plus 1.0 × 10⁹ CFU/kg Clostridium butyricum). The experiment was slaughtered after a 70-day growth test, and the jejunal mucosa and intestinal contents of the goats were collected to determine tight junction proteins related genes expression and 16S rDNA microbial sequencing analysis to evaluate the intestine health. The results showed that dietary supplementation with Clostridium butyricum significantly increased the expression of the Claudin-4 gene of the jejunal mucosa (P < 0.05) and had a trend toward a significant increase in the Occludin gene (0.05 < P < 0.10). However, Clostridium butyricum had no significant effect on the expression of intestinal inflammatory factors (P > 0.10). In addition, the relative fractionation of Clostridium and Clostridiaceae_unclassified in the gut microbiota at the genus level decreased significantly compared with controls (P < 0.05). The results of the analysis of the level of Clostridium species showed that Clostridium butyricum only existed in the treatment group. And the correlation results showed that Occludin and Claudin-4 genes were positively correlated with Sharppea and Clostridium butyricum, and negatively correlated with Clostridium (P < 0.05). Supplementing Clostridium butyricum in the diet did not significantly affect the intestinal immune function of goats, while regulation of the intestinal microbiota was associated with improving the intestinal epithelial barrier.

The management of body condition score (BCS) during the dry period is associated with the postpartum health outcomes of dairy cows. However, the difference between the actual BCS and the fixed ideal value is not able to accurately predict the occurrence of postpartum diseases. This study aimed to use statistical process control (SPC) technology to monitor the BCS of dry cows, to evaluate the effect of control charts on nutritional strategies, and to explore the utility of SPC in predicting the incidence of postpartum subclinical ketosis (SCK). The BCS and SCK data of 286 cows from the dry off period to 60 days postpartum were collected to set up the early warning function. Three control charts, including a control chart for the average BCS of the herds, for the BCS of each dry cow, and for individual BCS, were established. The early warning signs for postpartum SCK development were: (1) an individual BCS more than 3.5 that remained unchanged for six weeks; (2) a capability index (CPK), an SPC tool, greater than −0.52. Using these parameters, the early warning signs of SCK development were verified in 429 dry cows. The results showed that the accuracy of early warning signal was 0.64 and the precision was 0.26. The control chart showed that the average BCS of dry cows was consistently higher than the expected upper limit of BCS during the experimental period, and that the addition of new cows to the herds increased the average BCS. In summary, the application of SPC technology to monitor the BCS of dry cows was not a good tool for the prediction of postpartum SCK occurrence but was an appropriate tool for guiding positive nutrition strategies.