Methane emissions and δ13C composition from beef steers consuming increasing proportions of sericea lespedeza hay on bermudagrass hay diets

Abstract

Abstract An experiment was conducted to evaluate the effects of different proportions of ‘Au Grazer’ sericea lespedeza [SL, Lespedeza cuneata (Dum. Cours.) G. Don], a legume rich in condensed tannins (CT), on nutrient intake and digestibility, and to estimate methane (CH4) emissions and 13C isotopic composition (δ13CCH4) from beef steers consuming a forage-based diet. Twenty-five Angus-crossbred steers were distributed in a randomized complete block design (344 ± 48 kg initial BW), and randomly assigned to one of five treatments: 0SL, 25SL, 50SL, 75SL, and 100SL, diets containing 0%, 25%, 50%, 75%, and 100% of SL hay, respectively, mixed with ‘Tifton-85’ bermudagrass hay (Cynodon spp.). The study was carried out for two experimental periods of 21-d each. The statistical model included the fixed effect of treatment and random effects of block, experimental period, and their interaction. Apparent total tract digestibility of crude protein, neutral detergent fiber, and acid detergent fiber was linearly decreased (P < 0.001) by the inclusion of SL. No effects were observed for total CH4 emissions per day, nor for CH4 relative to organic matter intake or digestible organic matter with the inclusion of SL. However, emission of CH4 in relation to intake of CT was affected by treatment (P < 0.001). A linear (P < 0.001) decrease and a quadratic effect (P < 0.001) were observed for δ13C of diets and gas, respectively, in which diets and enteric CH4 with greater inclusion of SL were more depleted in 13C. Moreover, the difference in δ13C between diets and gas (Δδ13C) had a linear decrease (P = 0.001) with the inclusion of SL. The model developed to predict the C3 proportions in the enteric CH4 fitted to predicted values (P < 0.0001). Therefore, greater proportions of SL resulted in lesser CH4 emission when CT intake was considered and the isotopic composition from enteric CH4 was able to predict the contribution of SL in the emissions.