Thermal processing induced changes on molecular structure spectral profile of carbohydrates and ruminal degradation and intestinal digestion characteristics of oat grains (<i>Avena sativa</i>) in dairy cows: comparison among dry heating vs. moisture heating vs. microwave irradiation
Bibliographic record
Abstract
In this study, the objectives were to ( i) identify the magnitude of differences between dry heating, moisture heating, microwave irradiation, and no-heated treatments on chemical profiles, energy values, the Cornell Net Carbohydrate and Protein System fractions, rumen degradation, and intestinal digestion of newly developed oat ( Avena sativa) varieties; ( ii) investigate heating induced changes in the molecular structure of the grains with the use of vibrational attenuated total reflectance–Fourier transform infrared (ATR-FTIR) spectroscopy; and ( iii) predict rumen degradability of the nutrients based on the molecular spectral profile obtained from ATR-FTIR. Duration and temperature for each processing treatment were established based on previous studies. Results showed that heat processing treatments altered CHO fractions with undegradable CHO fraction (CC) increased by moisture heating. The ATR-FTIR spectroscopy was successful in detecting the processing induced CHO molecular structure changes in oat grain. The CHO molecular profiles were correlated to chemical profile and in situ rumen degradation characteristics. Lastly, multiple regressions with best model variable selection for prediction of nutritional value were obtained. In conclusion, heat processing methods tended to affect both energy values and rumen degradation features. The CHO molecular structure spectral profiles could be used as potential predictors for heated oat grain degradation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".