Physiochemical Characteristics and Molecular Structures for Digestible Carbohydrates of Silages
Bibliographic record
Abstract
The main objectives of this study were (1) to assess the magnitude of differences among new barley silage varieties (BS) selected for varying rates of in vitro neutral detergent fiber (NDF) digestibility (ivNDFD; Cowboy BS with higher ivNDFD, Copeland BS with intermediate ivNDFD, and Xena BS with lower ivNDFD) with regard to their carbohydrate (CHO) molecular makeup, CHO chemical fractions, and rumen degradability in dairy cows in comparison with a new corn silage hybrid (Pioneer 7213R) and (2) to quantify the strength and pattern of association between the molecular structures and digestibility of carbohydrates. The carbohydrate-related molecular structure spectral data was measured using advanced vibrational molecular spectroscopy (FT/IR). In comparison to BS, corn silage showed a significantly (P < 0.05) higher level of starch and energy content and higher degradation of dry matter (DM). Cowboy BS had lower feeding value (higher indigestible fiber content and lower starch content) and lower DM degradation in the rumen compared to other BS varieties (P < 0.05). The spectral intensities of carbohydrates were significantly (P < 0.05) correlated with digestible carbohydrate content of the silages. In conclusion, the univariate approach with only one-factor consideration (ivNDFD) might not be a satisfactory method for evaluating and ranking BS quality. FT/IR molecular spectroscopy can be used to evaluate silage quality rapidly, particularly the digestible fiber content.
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 | 0.000 |
| 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".