Effects of urea plus nitrate pretreated rice straw and corn oil supplementation on fiber digestibility, nitrogen balance, rumen fermentation, microbiota and methane emissions in goats
Bibliographic record
Abstract
Urea pretreatment is an efficient strategy to improve fiber digestibility of low quality roughages for ruminants. Nitrate and oil are usually used to inhibit enteric methane (CH 4 ) emissions from ruminants. The objective of this study was to examine the combined effects of urea plus nitrate pretreated rice straw and corn oil supplementation to the diet on nutrient digestibility, nitrogen (N) balance, CH 4 emissions, ruminal fermentation characteristics and microbiota in goats. Nine female goats were used in a triple 3 × 3 Latin Square design (27 d periods). The treatments were: control (untreated rice straw, no added corn oil), rice straw pretreated with urea and nitrate (34 and 4.7 g/kg of rice straw on a dry matter [DM] basis, respectively, UN), and UN diet supplemented with corn oil (15 g/kg soybean and 15 g/kg corn were replaced by 30 g/kg corn oil, DM basis, UNCO). Compared with control, UN increased neutral detergent fiber (NDF) digestibility ( P < 0.001) and copies of protozoa ( P < 0.001) and R. albus ( P < 0.05) in the rumen, but decreased N retention (−21.2%, P < 0.001), dissolved hydrogen concentration (−22.8%, P < 0.001), molar proportion of butyrate (−18.2%, P < 0.05), (acetate + butyrate) to propionate ratio ( P < 0.05) and enteric CH 4 emissions (−10.2%, P < 0.05). In comparison with UN, UNCO increased N retention (+34.9%, P < 0.001) and decreased copies of protozoa ( P < 0.001) and methanogens ( P < 0.001). Compared with control, UNCO increased NDF digestibility (+8.3%, P < 0.001), reduced ruminal dissolved CH 4 concentration (−24.4%, P < 0.001) and enteric CH 4 emissions (−12.6%, P < 0.05). A combination of rice straw pretreated with urea plus nitrate and corn oil supplementation of the diet improved fiber digestibility and lowered enteric CH 4 emissions without negative effects on N retention. These strategies improved the utilization of rice straw by goats.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".