Moist and dry heating-induced changes in protein molecular structure, protein subfractions, and nutrient profiles in camelina seeds
Bibliographic record
Abstract
The objectives of the present study were to investigate the nutritive value of camelina seeds (Camelina sativa L. Crantz) in ruminant nutrition and to use molecular spectroscopy as a novel technique to quantify the heat-induced changes in protein molecular structures in relation to protein digestive behavior in the rumen and intestine of dairy cattle. In this study, camelina seeds were used as a model for feed protein. The seeds were kept as raw (control) or heated in an autoclave (moist heating) or in an air-draft oven (dry heating) at 120°C for 60 min. The parameters evaluated were (1) chemical profiles, (2) Cornell Net Protein and Carbohydrate System protein subfractions, (3) nutrient digestibilities and estimated energy values, (4) in situ rumen degradation and intestinal digestibility, and (5) protein molecular structures. Compared with raw seeds, moist heating markedly decreased (52.73 to 20.41%) the content of soluble protein and increased (2.00 to 9.01%) the content of neutral detergent insoluble protein in total crude protein (CP). Subsequently, the rapidly degradable Cornell Net Protein and Carbohydrate System CP fraction markedly decreased (45.06 to 16.69% CP), with a concomitant increase in the intermediately degradable (45.28 to 74.02% CP) and slowly degradable (1.13 to 8.02% CP) fractions, demonstrating a decrease in overall protein degradability in the rumen. The in situ rumen incubation study revealed that moist heating decreased (75.45 to 57.92%) rumen-degradable protein and increased (43.90 to 82.95%) intestinal digestibility of rumen-undegradable protein. The molecular spectroscopy study revealed that moist heating increased the amide I-to-amide II ratio and decreased α-helix and α-helix-to-β-sheet ratio. In contrast, dry heating did not significantly change CP solubility, rumen degradability, intestinal digestibility, and protein molecular structures compared with the raw seeds. Our results indicated that, compared with dry heating, moist heating markedly changed protein chemical profiles, protein subfractions, rumen protein degradability, and intestinal digestibility, which were associated with changes in protein molecular structures (amide I-to-amid II ratio and α-helix-to-β-sheet ratio). Moist heating improved the nutritive value and utilization of protein in camelina seeds compared with dry heating.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".