0490 Effect of steam flaking and seed type on carbohydrate molecular structure features associated with nutrient availability of legume seed in ruminants
Bibliographic record
Abstract
The objectives of this study were to evaluate the effect of steam flaking processing and different seed type on carbohydrate spectroscopic features in relation to degradation kinetics. Six different sources of peas from Duck Lake and COOP were processed at Canadian Feed Research Center (CFRC, University of Saskatchewan, North Battleford, Canada). The carbohydrate molecular structure makeup was detected using attenuated total reflectance-Fourier transform infrared spectroscopy instrument at molecular spectroscopy lab, Department of Animal and Poultry Science, University of Saskatchewan. Three rumen-cannulated lactating Holstein cows were used to determine the in situ rumen degradation kinetics of DM and starch at Rayner Dairy Teaching and Research Facility (RDTRF). Statistical analyses were performed using the PROC MIXED procedure of SAS 9.3. The Tukey method was used for multi-treatment comparison. Difference was declared at P < 0.05. The results of univariate molecular spectral analyses showed that the whole pea seed had a significantly higher ratio of structural carbohydrate to total carbohydrate area than split pea seed (0.313 vs. 0.307; P < 0.05). The spectral ratio of cellulosic compound to structure carbohydrate area was significantly affected by steam flaking treatment, which was higher in flaking pea seed than the control (0.153 vs. 0.135; P < 0.05). Additionally, steam flaking treated pea seed also had a significant higher spectral ratio of cellulosic compound to total carbohydrate area than control untreated pea seed as a control (0.047 vs. 0.042; P < 0.05). In conclusion, steam flaking affected the inner molecular makeup of pea seed, which may be highly associated with the nutrient utilization.
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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".