Effects of variety on chemical composition, <i>in situ</i> nutrient disappearance and <i>in vitro</i> gas production of spineless cacti
Bibliographic record
Abstract
Abstract This study determined the chemical composition, in situ ruminal nutrient disappearance and in vitro gas production kinetics of three cactus varieties grown in northeastern Brazil. The varieties were Gigante, IPA‐20 and Miúda. Results of the chemical analysis showed no significant differences in ash, ether extract, crude protein (CP) and neutral detergent fibre (NDF) between the cactus varieties. However, acid detergent fibre was highest (P < 0.05) for IPA‐20, intermediate (P < 0.05) for Gigante, and lowest (P < 0.05) for Miúda. Fractionation of carbohydrate and true protein based on rates of ruminal degradation indicated that the main carbohydrate component was the rapidly degradable fraction, whereas the main true protein component was the intermediately degradable fraction. No differences in carbohydrate or protein fractions were observed between the cactus varieties. Results of the in situ experiment showed no differences in ruminal dry matter (DM, average 803 g kg−1 of DM), CP (900 g kg−1 of CP) and NDF (611 g kg−1 of NDF) disappearance between the three cactus varieties after 48 h of ruminal incubation. Potential gas production at the end of 48 h of incubation was higher (P < 0.05) for Gigante than for the Miúda or IPA‐20 variety. However, rate of gas production and lag time in gas production were similar for the three cactus varieties at 6.8% h−1 and 0.6 h respectively. Our results showed little or no differences in chemical composition or ruminal nutrient degradabilities between the three cactus varieties. Copyright © 2003 Society of Chemical Industry
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".