Improvements in forage nutritive value can reduce methane emission intensity in grazing ruminants. This study was designed to evaluate how the legume rhizoma peanut (Arachis glabrata; RP) inclusion into bahiagrass (Paspalum notatum) hay diets would affect intake and CH4 production in beef steers. We also assessed the potential to estimate the proportion of RP contribution to CH4 emissions using δ13C from enteric CH4. Twenty-five Angus-crossbred steers were randomly allocated to one of five treatments (five steers per treatment blocked by bodyweight): 1) 100% bahiagrass hay (0%RP); 2) 25% RP hay + 75% bahiagrass hay (25%RP); 3) 50% RP hay + 50% bahiagrass hay (50%RP); 4) 75% RP hay + 25% bahiagrass hay (75%RP); 5) 100% RP hay (100%RP). The study was laid out using a randomized complete block design, and the statistical model included fixed effect of treatment, and random effect of block. Methane emissions were collected using sulfur hexafluoride (SF6) technique, and apparent total tract digestibility was estimated utilizing indigestible neutral detergent fiber as an internal marker. A two-pool mixing model was used to predict diet source utilizing CH4 δ13C. Inclusion of RP did not affect intake or CH4 production (P > 0.05). Methane production per animal averaged 250 g CH4/d and 33 g CH4/kg dry matter intake, across treatments. The CH4 δ13C were -55.5, -60.3, -63.25, -63.35, and -68.7 for 0%RP, 25%RP, 50%RP, 75%RP, and 100%RP, respectively, falling within the reported ranges for C3 or C4 forage diets. Moreover, there was a quadratic effect (P = 0.04) on the CH4 δ13C, becoming more depleted (e.g., more negative) as the diet proportion of RP hay increased, appearing to plateau at 75%RP. Regression between predicted and observed proportions of RP in bahiagrass hay diets based on δ13C from CH4 indicate δ13C to be useful (Adj. R2 = 0.89) for predicting the contribution of RP in C3-C4 binary diets. Data from this study indicate that, while CH4 production may not always be reduced with legume inclusion into C4 hay diets, the δ13C technique is indeed useful for tracking the effect of dietary sources on CH4 emissions.
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