Comparing proteins and carbohydrates molecular structures in different sorghum cultivars using fourier transform infrared spectroscopy (FTIR) and multivariate analyses
Bibliographic record
Abstract
This study was carried out to determine the protein and carbohydrate molecular structure of sorghum cultivars using Fourier Transform Infrared Spectroscopy (FTIR) with multivariate molecular spectroscopy analyses. Sorghum cultivars included: 1- Kimia, 2- Sepideh, 3- M2 and 4- M8. Protein and carbohydrate molecular functional groups studied included: peak area and height amide I, amide II, α-helix, β-sheet, 860 (non-structure carbohydrate), 928 (non-structure carbohydrate), total carbohydrate (CHO) with three major component peaks in this region, cellulosic compounds and different ratio of molecular structure. FTIR results showed that there were significant differences between sorghum cultivars in terms of proteins and carbohydrates molecular structures. Kimia had the greatest peak area and height amide I, II, α-helix, β-sheet, total carbohydrate and cellulosic compounds. Sepideh, M2 and M8 had similar proteins and carbohydrates molecular structures. Differences in protein and carbohydrate molecular structures can influence the availability of proteins and carbohydrates in ruminant and monogastric. Further studies needed to understand the effect of variety on protein and carbohydrate structure of sorghum and the relationship between protein and carbohydrate structure of a feed with nutrient availability in ruminant and monogastric
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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 | 0.001 | 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) | 0.001 | 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".