PSXII-5 Feed processing-induced changes in protein molecular structure in relation to nutrient utilization and availability of warm-season Sorghum grain (Sorghum bicolor) in ruminants
Bibliographic record
Abstract
Abstract The objective of this study was reveal heat related processing (HP) induced changes in protein molecular structure in relation to nutrient utilization and availability of warm-season sorghum grain (Sorghum bicolor) in dairy cows. Three new warm-season genotypes of sorghum grain (Sorghum bicolor) were studied. The nutrient utilization and availability of sorghum grain (Sorghum bicolor) in dairy cows include: protein subfractions, energy values, rumen degradation, and intestinal digestibility of rumen undegraded protein. The protein structure change on molecular level were revealed with cutting edge non-invasive vibrational ATR-FTIR molecular spectroscopy. The warm-season sorghum grains were either maintained in their raw state (as control) or treated with for 80 min at 121°C with the Lindberg/Blue M™. The RCBD data were analyzed using SAS9.4 with Mixed model procedure. Tukey method was used for mean separation. The results showed that compared with the control, the HP treatment altered (P < 0.05) nutrient profiles and utilization and availability in dairy cows and increased (P < 0.05) metabolizable energy and net energy values in dairy cows. The HP treatment also altered (P < 0.05) the protein molecular structure profile of the warm-season sorghum grain. It increased (P < 0.05) the ratio of protein Amide I and Amide II height and decreased (P < 0.05) the ratio of α-helix to β-sheet. In conclusion, the HP treatment altered molecular structure and nutrient profiles without negatively affecting the nutritive value and digestion of warm-season sorghum grain. The molecular spectral profiles revealed by rapid and non-invasive ATR-FTIR molecular spectroscopy could be used as a fast predictor for the warm-season sorghum grain utilization and digestion in dairy cows.
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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".