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Predicting enteric methane production from cattle in the tropics
- R. S. Ribeiro, J. P. P. Rodrigues, R. M. Maurício, A. L. C. C. Borges, R. Reis e Silva, T. T. Berchielli, S. C. Valadares Filho, F. S. Machado, M. M. Campos, A. L. Ferreira, R. Guimarães Júnior, J. A. G. Azevêdo, R. D. Santos, T. R. Tomich, L. G. R. Pereira
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Accurate estimates of methane (CH4) production by cattle in different contexts are essential to developing mitigation strategies in different regions. We aimed to: (i) compile a database of CH4 emissions from Brazilian cattle studies, (ii) evaluate prediction precision and accuracy of extant proposed equations for cattle and (iii) develop specialized equations for predicting CH4 emissions from cattle in tropical conditions. Data of nutrient intake, diet composition and CH4 emissions were compiled from in vivo studies using open-circuit respiratory chambers, SF6 technique or the GreenFeed® system. A final dataset containing intake, diet composition, digestibility and CH4 emissions (677 individual animal observations, 40 treatment means) obtained from 38 studies conducted in Brazil was used. The dataset was divided into three groups: all animals (GEN), lactating dairy cows (LAC) and growing cattle and non-lactating dairy cows (GCNL). A total of 54 prediction equations available in the literature were evaluated. A total of 96 multiple linear models were developed for predicting CH4 production (MJ/day). The predictor variables were DM intake (DMI), gross energy (GE) intake, BW, DMI as proportion of BW, NDF concentration, ether extract (EE) concentration, dietary proportion of concentrate and GE digestibility. Model selection criteria were significance (P < 0.05) and variance inflation factor lower than three for all predictors. Each model performance was evaluated by leave-one-out cross-validation. The Intergovernmental Panel on Climate Change (2006) Tier 2 method performed better for GEN and GCNL than LAC and overpredicted CH4 production for all datasets. Increasing complexity of the newly developed models resulted in greater performance. The GCNL had a greater number of equations with expanded possibilities to correct for diet characteristics such as EE and NDF concentrations and dietary proportion of concentrate. For the LAC dataset, equations based on intake and animal characteristics were developed. The equations developed in the present study can be useful for accurate and precise estimation of CH4 emissions from cattle in tropical conditions. These equations could improve accuracy of greenhouse gas inventories for tropical countries. The results provide a better understanding of the dietary and animal characteristics that influence the production of enteric CH4 in tropical production systems.
Effect of recovery period of mixture pasture on cattle behaviour, pasture biomass production and pasture nutritional value
- F. C. Pereira, L. C. P. Machado Filho, D. C. S. Kazama, R. Guimarães Júnior, L. G. R. Pereira, D. Enríquez-Hidalgo
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Pasture management that considers pasture growth dynamics remains an open question. Conceptually, such management must allow for grazing only after the recuperation of the pasture between two separate timely grazing periods when pasture reaches optimum recovery, as per the first law of Voisin’s rational grazing system. The optimum recovery period not only implies a pasture with better nutritional value and higher biomass yield but one that also reduces the production of enteric methane (CH4) to improve the grazing efficiency of cattle. Therefore, this study aimed to evaluate three different recovery periods (RP) of mixed grasses on the grazing behaviour of heifers, as well as herbage selectivity, herbage yield and nutritional value, in vitro degradability and CH4 production. Based on these criteria, three pasture RPs of 24 (RP24), 35 (RP3) and 46 (RP46) days were evaluated in six blocks using a randomized block design. At each predetermined RP, samples of the pasture were taken before the animals were allowed to graze. Right after collecting the pasture samples, heifers accessed the pasture during 4 h consecutively for grazing simulation and behavioural observations. We also measured the bite rate of each animal. The pasture growing for 24 days had the highest biomass production, best nutritional value, best efficiency of in vitro CH4 relative emission (ml) per DM degraded (g) and bite rate of the three RPs. Heifers all selected their herbage, irrespective of RP, but with different nutritional value and higher in vitro degradability. However, this did not change the production of in vitro CH4. Considering the growth conditions of the area where the study was performed, we recommend the shorter RP24 as the most suitable during the summer season. The study’s findings support the idea of management intervention to increase the quality of grazing systems.