Dry heating, moist heating, and microwave irradiation of cold‐climate‐adapted barley grain—Effects on ruminant‐relevant carbohydrate and molecular structural spectral profiles
Bibliographic record
Abstract
Different feed processing techniques affect barley digestibility and nutrient utilization in ruminants. To our knowledge, there are few studies on the interactive relationship between carbohydrate molecular structure profiles of cool-season-adapted barley grain and nutritional characteristics for ruminants. The objectives of this study were: (1) to investigate the effect of different technological processing methods on carbohydrate chemical profiles, Cornell Net Carbohydrate and Protein System-carbohydrate subfractions, ruminal and intestinal carbohydrate digestion of barley grain in dairy cows; (2) to study the effect of heat processing on carbohydrate molecular structure of barley grain using advanced molecular spectroscopy; and (3) to associate processing-induced changes in carbohydrate molecular structure with changes in carbohydrate metabolic profiles in dairy cows. Barley grain samples collected from Crop Research Field in Western Canada underwent four different processing treatments: control, dry heating (120°C for 60 min in an air-ventilated oven), moist heating (120°C for 60 min in an autoclave), and microwave irradiation (900 W and 2450 MHz for 5 min in a microwave). The heating conditions used in the current study induced some changes in rumen-degradable and -undegradable digestible fibre (CB3) fraction. Intestinally digestible CB3 was decreased after moist heating. Moist heating decreased starch digestibility compared to the other three treatments. The processing-induced carbohydrate molecular structure changes, which was revealed by advanced vibrational molecular spectroscopic technique (attenuated total reflectance-Fourier transform infrared), could be used to predict carbohydrate nutritional value.
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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) | 0.001 | 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".