Effect of Dried Distillers Grains With Solubles and Red Osier Dogwood Extract on Fermentation Pattern and Microbial Profiles of a High-Grain Diet in an Artificial Rumen System.

The objective of this study was to evaluate the effect of dried distillers grains with solubles (DDGS) and red-osier dogwood (ROD) extract on in vitro fermentation characteristics, nutrient disappearance, and microbial profiles using the rumen simulation technique. The experiment was a completely randomized design with a 2 × 2 factorial arrangement of treatments and four replicates per treatment. A basal diet [10% barley silage, 87% dry-rolled barley grain, and 3% vitamin and mineral supplement, dry matter (DM) basis] and a DDGS diet (as per basal diet with 25% of wheat DDGS replacing an equal portion of barley grain) were supplemented with ROD extract at 0 and 1% (DM basis), respectively. The experimental period was 17 d, consisting 10 days of adaptation and 7 days of data and sample collection. The substitution of wheat DDGS for barley grain did not affect gas production; disappearances of DM, organic matter, and crude protein; total volatile fatty acid (VFA) production; and microbial protein production. However, replacing barley grain with wheat DDGS increased (P = 0.01) fermenter pH and molar proportion of branched-chain VFA, switched (P = 0.06) the fermentation pattern to higher acetate production due to increased (P = 0.01) disappearance of neutral detergent fiber (NDF), and decreased (P = 0.08) methane (CH4) production. In the basal barley diet, the ROD extract increased the acetate to propionate (A:P) ratio (P = 0.08) and reduced the disappearance of starch (P = 0.06) with no effect on any other variables. No effects of ROD in the DDGS diet were observed. The number of operational taxonomic unit (OTUs) and the Shannon diversity index of the microbial community had little variation among treatments. Taxonomic analysis revealed no effect of adding the ROD extract on the relative abundance of bacteria at the phylum level with either the basal diet or DDGS diet, while at the genus level, the microbial community was affected by the addition of both DDGS and the ROD extract. Prevotella and Fibrobacter were the most abundant genera in the basal diet; however, Treponema became the most abundant genus with the addition of the ROD extract. These results indicated that the substitution of wheat DDGS for barley grain may mitigate enteric CH4 emissions. The trend of reduced starch fermentability and increased NDF disappearance with the addition of ROD extract suggests a reduced risk of rumen acidosis and an improvement in the utilization of fiber for cattle-fed high-grain diet.

Application of Meta-Analysis and Machine Learning Methods to the Prediction of Methane Production from In Vitro Mixed Ruminal Micro-Organism Fermentation.

In vitro gas production systems are utilized to screen feed ingredients for inclusion in ruminant diets. However, not all in vitro systems are set up to measure methane (CH4) production, nor do all publications report in vitro CH4. Therefore, the objective of this study was to develop models to predict in vitro CH4 production from total gas and volatile fatty acid (VFA) production data and to identify the major drivers of CH4 production in these systems. Meta-analysis and machine learning (ML) methodologies were applied to a database of 354 data points from 11 studies to predict CH4 production from total gas production, apparent DM digestibility (DMD), final pH, feed type (forage or concentrate), and acetate, propionate, butyrate and valerate production. Model evaluation was performed on an internal dataset of 107 data points. Meta-analysis results indicate that equations containing DMD, total VFA production, propionate, feed type and valerate resulted in best predictability of CH4 on the internal evaluation dataset. The ML models far exceeded the predictability achieved using meta-analysis, but further evaluation on an external database would be required to assess generalization ability on unrelated data. Between the ML methodologies assessed, artificial neural networks and support vector regression resulted in very similar predictability, but differed in fitting, as assessed by behaviour analysis. The models developed can be utilized to estimate CH4 emissions in vitro.

Effect of engineered biocarbon on rumen fermentation, microbial protein synthesis, and methane production in an artificial rumen (RUSITEC) fed a high forage diet.

The objective of this study was to investigate the effects of adding engineered biocarbon to a high-forage diet on ruminal fermentation, nutrient digestion, and enteric methane (CH4) production in a semi-continuous culture artificial rumen system (RUSITEC). The experiment was a completely randomized block design with four treatments assigned to sixteen fermentation vessels (four/treatment) in two RUSITEC apparatuses. The basal diet consisted of 60% barley silage, 27% barley grain, 10% canola meal, and 3% supplement (DM basis) with biocarbon added at 0, 0.5, 1, and 2% of substrate DM. The study period was 17 d, with a 10-d adaptation and 7-d sample collection period. Increasing biocarbon linearly increased (P < 0.05) disappearance of DM, OM, CP, ADF and NDF. Compared to control, increasing biocarbon enhanced (P < 0.01) production of total VFA, acetate, propionate, branch-chained VFAs, and tended to increase (P = 0.06) NH3-N. Microbial protein synthesis linearly increased (P = 0.01) with increasing biocarbon. Addition of biocarbon reduced overall CH4 production compared with the control (P ≤ 0.05). There were no differences (P > 0.05) in production of total gas, large or small peptides, or in the number of protozoa as a result of addition of biocarbon to the diet. Addition of biocarbon to a forage diet increased DM digestibility by up to 2%, while lowering enteric CH4 production and enhancing microbial protein synthesis in in vitro semi- continuous culture fermenters.

Water use intensity of Canadian beef production in 1981 as compared to 2011.

The amount of beef produced per animal in Canada increased significantly from 1981 to 2011, due to enhanced production efficiency and increased carcass weight. This study examined the impact of improvements in production efficiency on water use intensity over this period. Temporal and regional differences in cattle categories, water use for drinking, feed production and meat processing, feeding systems, average daily gains, and carcass weight were considered in the analysis. Potential evapotranspiration (PET) was estimated by the National Drought Model (NDM) from 679 weather stations across Canada using the Priestley and Taylor equation. To adjust PET estimates for each crop included in cattle diets, FAO crop coefficients were used to calculate total feed water demand. Estimates of drinking water consumed by a given class of cattle accounted for physiological status, body weight and dry matter intake as well as ambient temperature. In both years, drinking water accounted for less than 1% of total water use with precipitation (i.e., green water) included for feed and pasture production. With exclusion of green water, drinking water accounted for 24% and 21% of total water use for Canadian beef production in 1981 and 2011, respectively. The estimated intensity of blue water (surface and groundwater) use per kilogram of boneless beef was 577L in 1981 and 459 in 2011, a 20% decline. The observed reduction in water use intensity over the past three decades is attributed to an increase in average daily gain and slaughter weight, improved reproductive efficiency, reduced time to slaughter as well as improvements in crop yields and irrigation efficiency. Given that feed production accounts for the majority of water use in beef production, further advances may be achieved by improving feeding efficiencies and reducing water use per unit of feed crop and pasture production.