Effects of peripartal yeast culture supplementation on lactation performance, blood biomarkers, rumen fermentation, and rumen bacteria species in dairy cows.

Feeding yeast culture fermentation products has been associated with improved feed intake and milk yield in transition dairy cows. These improvements in performance have been further described in terms of rumen characteristics, metabolic profile, and immune response. The objective of this study was to evaluate the effects of a commercial yeast culture product (YC; Culture Classic HD, Phibro Animal Health) on performance, blood biomarkers, rumen fermentation, and rumen bacterial population in dairy cows from -30 to 50 d in milk (DIM). Forty Holstein dairy cows were enrolled in a randomized complete block design from -30 to 50 DIM and blocked according to expected calving day, parity, previous milk yield, and genetic merit. At -30 DIM, cows were assigned to either a basal diet plus 114 g/d of ground corn (control; n = 20) or a basal diet plus 100 g/d of ground corn and 14 g/d of YC (n = 20), fed as a top-dress. Cows received the same close-up diet from 30 d prepartum until calving [1.39 Mcal/kg of dry matter (DM) and 12.3% crude protein (CP)] and lactation diet from calving to 50 DIM (1.60 Mcal/kg of DM and 15.6% CP). Blood samples and rumen fluid were collected at various time points from -30 to 50 d relative to calving. Cows fed YC compared with control showed a trend for increased energy-corrected milk (+3.2 kg/d). Lower somatic cell counts were observed in YC cows than in control. We detected a treatment × time interaction in nonesterified fatty acids (NEFA) that could be attributed to a trend for greater NEFA in YC cows than control at 7 DIM, followed by lower NEFA in YC cows than control at 14 and 30 DIM. In the rumen, YC contributed to mild changes in rumen fermentation, mainly increasing postpartal valerate while decreasing prepartal isovalerate. This was accompanied by alterations in rumen microbiota, including a greater abundance of cellulolytic (Fibrobacter succinogenes) and lactate-utilizing bacteria (Megasphaera elsdenii). These results describe the potential benefits of supplementing yeast culture during the late pregnancy through early lactation, at least in terms of rumen environment and performance.

Technical note: A novel approach to estimate dry matter intake of lactating dairy cows through multiple on-cow accelerometers.

The objective of this study was to evaluate the feasibility of using multiple 3-dimensional accelerometers to estimated individual dry matter intake (DMI) of lactating dairy cows. Twenty-four Holstein cows in late lactation were assigned into 2 groups, a calibration group (n = 12) and a validation group (n = 12). All cows were fitted with 3 sensors that recorded 3-dimensional acceleration (i.e., x, y, and z) at 10-s intervals, 1 on the lateral side of the left hind leg and 2 attached directly to a halter over the nose and jaw area on the left side. Then, 3 accelerations were generated from each accelerometer (e.g., Leg-X, Leg-Y, and Leg-Z). Six new variables were created based on the change in acceleration in the nose and jaw accelerometers between 2 consecutive time points (e.g., LagJaw-X). For both groups (i.e., calibration and validation), cows were continuously video recorded while data on acceleration and intake of total mixed ration were collected for 10 consecutive days. Cows were fed once daily using an individual gate system, and individual refusals were recorded next day before morning feeding. Cows were fed a common lactating cow diet (17.9% crude protein; 1.70 Mcal/kg of dry matter). In the calibration group, individual eating bouts were obtained based on video recordings and merged with the corresponding accelerometer data. Then, a stepwise regression analysis was conducted using the REG procedure of SAS (SAS Institute, Cary, NC) to determine the ranges in acceleration that accounted for the highest variation in DMI (highest R2) in each acceleration variable. All 32,767 potential acceleration combinations were tested in the validation group using the acceleration ranges predetermined in the calibration group. The CORR procedure of SAS was used to test the Pearson correlation coefficient (r) between the type of DMI [i.e., based on accelerations (DMIaccel) or actual DMI (DMIactual)]. The MIXED procedure of SAS was used to perform a repeated-measures analysis with type (DMIaccel vs. DMIactual), day, and their interaction (T × D) in the model. From this analysis, 8 candidate acceleration models were selected based on high r and similarity (P > 0.15) in terms of T and T × D between DMIaccel and DMIactual. A simulated effect on DMIactual was artificially created in the validation group by dividing this group (n = 12) into high and low intake cows (n = 6/group; DMI of 24.1 vs. 18.7 kg/d), and the candidate models were tested to determine whether they were sensitive enough to detect this effect. From these candidate models, AEN (Leg-X + Jaw-Z + LagJaw-Z) showed a weak correlation (r = 0.36) between DMIaccel and DMIactual, but DMIaccel and DMIactual were highly similar (21.2 vs. 21.4 kg/d of DMI). In addition, this was the only model that could detect the simulated effect on DMIactual (22.1 vs. 20.3 kg/d of DMI) in the validation group. The fact that the simulated effect on DMIactual was detected based only on accelerations is highly significant, and models such as AEN could be substantially improved if they were derived from a greater sample size and included different physiological stages in dairy cows.