Univariate and multi‐variate comparisons of protein and carbohydrate molecular structural conformations and their associations with nutritive factors in typical by‐products
Bibliographic record
Abstract
BACKGROUND: Little attention has been paid on the inherent molecular structural effects among agricultural by-products. In this study, soybean meal (SM), wheat bran (WB), corn distillers dried grains with soluble (DDGS), dry brewer's grain (DBG), wet brewer's grain (WBG), and apple pomace (AP), which are widely used in the animal industry were selected to explore protein and carbohydrate molecular structural conformations. RESULTS: All the protein peak heights (including α-helix and β-sheet) and areas were exhibited highest values in SM and lowest in AP. The SM had the highest peak area intensity of cellulosic compounds (CELC), while the remaining varieties showed the lowest absorbance level. The TSCHO (sum of structural carbohydrate (SCHO) and CELC area exhibited variations among the samples. Multivariate comparisons showed AP had no molecular structural association with other by-products within the protein amide region. Protein amides I, II and (I+II) areas, α-helix, β-sheet and area ratio of protein amide and (TSCHO + TCHO) had strong relationships with CP, NDF, ADF, ADL, SCP, starch, PC, CA, CC and TDN contents. CONCLUSION: Inherent molecular structures varied among the selected by-product types and they might be used as potential predictors of nutritive factors, especially for protein structural information. © 2016 Society of Chemical Industry.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".