Measurement of Nutritive Value and Phenolic Compounds in Forage Plants Used in Animal Production
Bibliographic record
Abstract
Secondary metabolites are important organic metabolites produced by plants. These metabolites include phenolic compounds, which have been of research interest because phenolics are considered an antinutritional factor for ruminants, compromise the bioavailability of nutrients. This study included a chemical composition analysis, an analysis of the condensed tannin content and the identification and quantification of the phenolic compounds present in the following plants cultivated with and without fertilisation: Coastcross-1 grass (G) and the legumes Stylosanthes guianensis cv. Mineirão (MS), Stylosanthes capitata × Stylosanthes macrocephala cv. Campo Grande (CGS), Arachis pintoi cv. Amarillo (AA) and Arachis pintoi cv. Belmonte (AB). High-performance liquid chromatography (HPLC) was used to analyse 13 phenolic compounds. The forage with the best nutritive value was Amarillo pinto peanut. The condensed tannin content was higher in the legumes than that in the grass. Vanillin and o-coumaric, m-coumaric, caffeic and ferulic acid were detected in all the cultivars. The cultivar with the largest variety of phenolic compounds was Coastcross-1 grass. Diversity existed in the occurrence of phenolic compounds, which indicated the presence of condensed tannins in the cultivars and possibly that the diversity does not affect the concentration of these compounds. The AA cultivar was the most interesting alternative for the establishment of pasture intercropped with Coastcross-1 grass.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 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".