19. Improving the Prediction of Methane Production Determined by in Vitro Gas Production Technique for Ruminants

Abstract Twelve feedstuffs (cereals, fibrous byproducts, protein-rich byproducts and forages) were determined for methane (CH4) production by the in vitro gas production technique (IVGPT) and were correlated with their chemical compositions to predict enteric CH4 originating from these feedstuffs in ruminants. Corn, soybean hull, soybean meal and corn silage generated the highest CH4 production from their respective categories. The average CH4 production of fibrous byproducts (44.6 ml/g DM incubated) was significantly higher than that of cereals (40.3 ml/g DM incubated), forages (33.3 ml/g DM incubated) and protein-rich byproducts (31.0 ml/g DM incubated) after the 48-h incubation (P≤0.05). The highest average total volatile fatty acid (VFA) concentration was determined in cereals (53.6 mM). The acetate to propionate ratio was significantly lower in cereals when compared with other categories of feedstuff (P≤0.05). The correlation analysis showed that in vitro true digestibility (IVTD) positively correlated with the CH4 production in all four categories of feedstuffs (P≤0.05). The neutral detergent fiber (NDF) and acid detergent fiber (ADF) content positively correlated with CH4 production in every category of feedstuffs except cereals. The starch content negatively correlated with CH4 production for fibrous and protein-rich byproducts (P≤0.05), but it positively correlated with CH4 production for forages (P≤0.05). The CH4 production was predicted more accurately by the equations proposed for each category (R2=0.944, 0.876, 0.942 and 0.915 for cereals, fibrous and protein-rich byproducts and forages, respectively) than for the unclassified feedstuffs (R2=0.715). In conclusion, the contribution of individual chemical composition to CH4 production differed depending on the category of feedstuffs. The precision of CH4 prediction could be substantially improved by classifying feedstuffs into categories according to their chemical composition, and selecting the appropriate predictors for each category. Information about the CH4 output of these feedstuffs will be useful in formulating low CH4-producing diets for ruminants.

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