Shining Light on the Differences in Molecular Structural Chemical Makeup and the Cause of Distinct Degradation Behavior between Malting- and Feed-Type Barley Using Synchrotron FTIR Microspectroscopy: A Novel Approach
Bibliographic record
Abstract
The objective of this study was to use advanced synchrotron-sourced FTIR microspectroscopy (SFTIRM) as a novel approach to identify the differences in protein and carbohydrate molecular structure (chemical makeup) between these two varieties of barley and illustrate the exact causes for their significantly different degradation kinetics. Items assessed included (1) molecular structural differences in protein amide I to amide II intensities and their ratio within cellular dimensions, (2) molecular structural differences in protein secondary structure profile and their ratios, and (3) molecular structural differences in carbohydrate component peak profile. Our hypothesis was that molecular structure (chemical makeup) affects barley quality, fermentation, and degradation behavior in both humans and animals. Using SFTIRM, the protein and carbohydrate molecular structural chemical makeup of barley was revealed and identified. The protein molecular structural chemical makeup differed significantly between the two varieties of barleys. No difference in carbohydrate molecular structural chemical makeup was detected. Harrington was lower than Valier in protein amide I, amide II, and protein amide I to amide II ratio, while Harrington was relatively higher in model-fitted protein alpha-helix and beta-sheet, but lower in the others (beta-turn and random coil). These results indicated that it is the molecular structure of protein (chemical makeup) that may play a major role in the different degradation kinetics between the two varieties of barleys (not the molecular structure of carbohydrate). It is believed that use of the advanced synchrotron technology will make a significant step and an important contribution to research in examining the molecular structure (chemical makeup) of plant, feed, and seeds.
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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 | 0.000 |
| 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 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".