Dose response of dairy cows to ammonium salts of volatile fatty acids

Isoacids supplementation improves growth performance and feed fiber digestibility associated with ruminal bacterial community in yaks

Introduction

This study was conducted to assess the effect of mixed isoacid (MI) supplementation on fermentation characteristics, nutrient apparent digestibility, growth performance, and rumen bacterial community in yaks.

Methods

A 72-h in vitro fermentation experiment was performed on an ANKOM RF gas production system. MI was added to five treatments at doses of 0, 0.1%, 0.2%, 0.3%, 0.4%, and 0.5% on the dry matter (DM) basis of substrates using a total of 26 bottles (4 bottles per treatment and 2 bottles as the blank). Cumulative gas production was measured at 4, 8, 16, 24, 36, 48, and 72 h. Fermentation characteristics including pH, the concentration of volatile fatty acids (VFAs), ammonia nitrogen (NH₃-N), microbial proteins (MCP), and the disappearance rate of dry matter (DMD), neutral detergent fiber (NDFD), and acid detergent fiber (ADFD) were measured after a 72-h in vitro fermentation to determine an optimal MI dose. Fourteen Maiwa male yaks (180-220 kg, 3-4 years old of age) were randomly assigned to the control group (without MI, n = 7) and the supplemented MI group (n = 7, supplemented with 0.3% MI on DM basis) for the 85-d animal experiment. Growth performance, nutrient apparent digestibility, rumen fermentation parameters, and rumen bacterial diversity were measured.

Results

Supplementation with 0.3% MI achieved the greatest propionate and butyrate content, NDFD and ADFD compared with other groups (P < 0.05). Therefore, 0.3% was used for the animal experiment. Supplementation with 0.3% MI significantly increased the apparent digestibility of NDF and ADF (P < 0.05), and the average daily weight gain of yaks (P < 0.05) without affecting the ruminal concentration of NH₃-N, MCP, and VFAs. 0.3% MI induced rumen bacteria to form significantly different communities when compared to the control group (P < 0.05). g__norank_f__Bacteroidales_BS11_gut_group, g__norank_f__Muribaculaceae, g__Veillonellaceae_UCG-001, g__Ruminococcus_gauvreauii_group, g__norank_f__norank_o__RF39 and g__Flexilinea were identified as the biomarker taxa in responding to supplementation with 0.3% MI. Meanwhile, the abundance of g__Flexilinea and g__norank_f__norank_o__RF39 were significantly positively correlated with the NDF digestibility (P < 0.05).

Conclusion

In conclusion, supplementation with 0.3% MI improved the in vitro rumen fermentation characteristics, feed fiber digestibility, and growth performance in yaks, which was associated with changes of the abundance of g__Flexilinea and g__norank_f__norank_o__RF39.

Assessing milk response to different combinations of branched-chain volatile fatty acids and valerate in Jersey cows

Some cellulolytic bacteria require 1 or more branched-chain volatile fatty acids (BCVFA) for the synthesis of branched-chain AA and branched-chain long-chain fatty acids because they are not able to uptake branched-chain AA or lack 1 or more enzymes to synthesize branched-chain AA de novo. Supplemental BCVFA and valerate were included previously as a feed additive that was later removed from the market; these older studies and more current studies have noted improvements in neutral detergent fiber digestibility and milk efficiency. However, most studies provided a single BCVFA or else isobutyrate (IB), 2-methylbutyrate (MB), isovalerate, and valerate altogether without exploring optimal combinations. Our objective was to determine a combination of isoacids that is optimal for milk production. Sixty (28 primiparous and 32 multiparous) lactating Jersey cows (106 ± 54 days in milk) were blocked and assigned randomly to either a control (CON) treatment without any isoacids, MB [12.3 mmol/kg dry matter (DM)], MB + IB (7.7 and 12.6 mmol/kg DM of MB and IB, respectively), or all 4 isoacids (6.2, 7.3, 4.2, and 5.1 mmol/kg DM of MB, IB, isovalerate, and valerate, respectively). Cattle were fed the CON treatment for a 2-wk period, then were assigned randomly within a block to treatments for 8 wk (n = 15). There was a trend for an interaction of supplement and parity for milk components. There were no differences in components for primiparous cows, whereas MB + IB tended to increase protein concentration by 0.04 and 0.08 percentage units in multiparous cows compared with the CON and MB treatments, respectively. Feeding MB + IB increased fat concentration by 0.23 to 0.31 percentage units compared with all other treatments in multiparous cows. Milk yield and dry matter intake (DMI) did not change with treatment. Treatment interacted with week for milk net energy for lactation/DMI; MB + IB tended to increase milk net energy of lactation/DMI by 0.10 Mcal/kg compared with MB and approached a trend for CON, mainly during the early weeks of the treatment period, whereas differences decreased during the last 2 wk of the treatment period. Cows fed MB had the highest 15:0 anteiso fatty acids in the total milk fatty acid profile, which was greater than that for CON or MB + IB cows, but not cows supplemented with isoacids. Cows fed MB alone had the numerically lowest milk net energy for lactation/DMI. The combination of MB + IB appeared optimal for increasing feed efficiency in our study and was not at the expense of average daily gain. Further research is needed for evaluating how potential changes in supplemental isoacid dosage should vary under differing dietary conditions.

Evaluation of equations based on animal factors to predict intake of lactating Holstein cows

The accuracy of seven DMI prediction equations based only on animal factors was evaluated with 11 independent data files. Mean square prediction error was used to compare equation accuracy, which was considered to be unsatisfactory when the square root of the mean square prediction error was greater than +/-20% of the observed mean DMI. Robust intake equations that have a tolerable level of prediction errors for most data files would be less risky for practical use than models that are highly accurate for some data files but highly inaccurate for others. The number of independent data files for which equation accuracy was unsatisfactory was used to measure lack of robustness. No equation evaluated was able to predict individual cow DMI with a prediction error that was consistently lower than +/-20% of the observed mean intake. The most robust equation in this study predicted intake unsatisfactorily for 3 of the 11 evaluation data files. Unsatisfactory accuracy for this equation was mainly due to mean bias.