Development of a method to determine carotenoid composition of fresh forages
Bibliographic record
Abstract
Due to the limited interest in carotenoids in ruminant diets until recently, analyses of forages are often incomplete, focusing mainly on β-carotene and lutein. Carotenoid composition of green forage from middle mountain meadow was analyzed by HPLC after extraction and elimination of chlorophylls by mild saponification. This method of analysis uses two C18 columns in series with a quaternary gradient system. Our method allowed, for the first time, the identification and quantification of several xanthophylls other than lutein (i.e., violaxanthin, antheraxanthin, epilutein) in chlorophyll-free extracts from carotenoid-rich forage. The intra-day (3.5–7.5 %) and inter-day (1.2–3.5 %) coefficients of variation are suitable for routine determination of carotenoids in green forage. This method could also be used in metabolic studies of these micronutrients in ruminants. Key words: Xanthophylls, carotenoids, fresh forage, HPLC
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".