Using Synchrotron Radiation-Based Infrared Microspectroscopy to Reveal Microchemical Structure Characterization: Frost Damaged Wheat vs. Normal Wheat
Bibliographic record
Abstract
This study was conducted to compare: (1) protein chemical characteristics, including the amide I and II region, as well as protein secondary structure; and (2) carbohydrate internal structure and functional groups spectral intensities between the frost damaged wheat and normal wheat using synchrotron radiation-based Fourier transform infrared microspectroscopy (SR-FTIRM). Fingerprint regions of specific interest in our study involved protein and carbohydrate functional group band assignments, including protein amide I and II (ca. 1774-1475 cm(-1)), structural carbohydrates (SCHO, ca. 1498-1176 cm(-1)), cellulosic compounds (CELC, ca. 1295-1176 cm(-1)), total carbohydrates (CHO, ca. 1191-906 cm(-1)) and non-structural carbohydrates (NSCHO, ca. 954-809 cm(-1)). The results showed that frost did cause variations in spectral profiles in wheat grains. Compared with healthy wheat grains, frost damaged wheat had significantly lower (p < 0.05) spectral intensities in height and area ratios of amide I to II and almost all the spectral parameters of carbohydrate-related functional groups, including SCHO, CHO and NSCHO. Furthermore, the height ratio of protein amide I to the third peak of CHO and the area ratios of protein amide (amide I + II) to carbohydrate compounds (CHO and SCHO) were also changed (p < 0.05) in damaged wheat grains. It was concluded that the SR-FTIR microspectroscopic technique was able to examine inherent molecular structure features at an ultra-spatial resolution (10 × 10 μm) between different wheat grains samples. The structural characterization of wheat was influenced by climate conditions, such as frost damage, and these structural variations might be a major reason for the decreases in nutritive values, nutrients availability and milling and baking quality in wheat grains.
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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".