Estimating enteric methane emissions from Chilean beef fattening systems using a mechanistic model
Bibliographic record
Abstract
SUMMARY A mechanistic model (COWPOLL) was used to estimate enteric methane (CH 4 ) emissions from beef production systems in Chile. The results expressed as a proportion of gross energy intake (GEI) were compared with enteric fermentation data reported in the last Chilean greenhouse gases inventory, which utilized an earlier the Intergovernmental Panel on Climate Change Tier 2 approach. The simulation analysis was based on information from feedstuffs, dry matter intake (DMI), body weight (BW) and average daily gain (ADG) of steers raised and finished at two research facilities located in Central and Southern Chile, as well as three simulated scenarios for grass-based finishing systems in Southern Chile. Data for feedlot production systems in the central region were assessed by considering steers fed a forage : concentrate ratio of 23 : 77 using maize silage and wheat straw as roughage sources during the stages of backgrounding and fattening. Average DMI were 7·3±0·62 and 9·2±0·55 kg/day per steer for backgrounding and fattening, respectively, whereas ADG were 1·1±0·22 and 1·3±0·37 kg/day for backgrounding and fattening. For the Southern Chilean fattening production systems, the forage : concentrate ratio was 56 : 44 with ryegrass pasture as the sole forage source. In this case, average DMI was 9·97±0·51 and ADG was 1·1±0·24 kg/day per steer. Two of the grass-based scenarios used the same initial BW information as that used for the Central and Southern Chilean systems, but feedlot diets were replaced by ryegrass pasture. The third grass-based scenario used an initial BW of 390 kg. In all the grass-based scenarios an ADG of 0·90 kg/day, with maximum DMI estimated as a proportion of BW (0·01 of NDF, kg/kg BW), was assumed. The results of the simulation analysis showed that emission factors ( Y m ; fraction of GEI) ranged from 0·062 to 0·079 of GEI. Smaller values were associated with finishing systems that included a lower proportion of forage in the diet due to higher propionate production, which serves as a sink for hydrogen in the rumen. Cattle finished in feedlot systems had an average of 0·062 of GEI lost as CH 4 , whereas grass-based cattle had losses of 0·079 of GEI. Enteric CH 4 emissions for the systems using grass-based and concentrate diets were 261 and 159 g/kg weight gain, respectively. The Chilean CH 4 inventory employs a fixed Y m of 0·060 to estimate enteric fermentation for all cattle. This value is lower than the average Y m obtained in the current simulation analysis (0·071 of GEI), which results in underestimation of enteric CH 4 emissions from beef cattle. However, these results need to be checked against field measurements of CH 4 emissions. Implementation of mechanistic models in the preparation of national greenhouse gas inventories is feasible if appropriate information is provided, allowing dietary characteristics and regional particularities to be taken into consideration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".