The Effect of Manure from Cattle Fed Barley- vs. Corn-Based Diets on Greenhouse Gas Emissions Depends on Soil Type
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Bibliographic record
Abstract
Efforts to reduce greenhouse gas (GHG) emissions from cattle production have led to modifications of livestock diet composition aimed at reducing CH4 emissions from enteric fermentation. These diet modifications can result in varied manure types that may differentially affect GHG emissions when applied to soil. The purpose of this experiment was to examine the effect of different manure types on GHG emissions. We conducted an incubation experiment, comparing the manure from livestock fed a corn-based diet (CM) to that from livestock fed a traditional barley-based diet (BM). The manures were applied to three soil types (with varied soil fertility and pH) and compared to a control (without manure application). Carbon dioxide (CO2) emissions were greater from CM than from BM across all soil types (29.1 and 14.7 mg CO2-C kg−1, respectively). However, CM resulted in lower N2O emissions relative to BM in the low fertility soil (4.21 and 72.67 μg N2O-N kg−1, respectively) and in lower CH4 emissions relative to BM in the two acidic soils (0.5 and 2.5 μg CH4-C kg−1, respectively). Total GHG emissions (sum of CO2, N2O, and CH4) were similar between CM and BM across all soil types, but CM (unlike BM) had 52–66% lower emissions in the low fertility soil relative to both CM and BM in the high fertility soil. Our study shows that manure and soil type interact to affect GHG emissions and that CM may mitigate N2O emissions relative to BM when applied to low fertility soils.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it