Distribution of micronutrients in Arborg oat (Avena sativa L.) using synchrotron X-ray fluorescence imaging
Bibliographic record
Abstract
It is important to know the mineral distribution in cereal grains for nutritional improvement or genetic biofortification. Distributions and intensities of micro-elements (Mn, Fe, Cu, and Zn) and macro-elements (P, S, K and Ca) in Arborg oat were investigated using synchrotron-based on X-ray fluorescence imaging (XFI). Arborg oat provided by the Crop Development Center (CDC, Aaron Beattie) of the University of Saskatchewan for 2D X-ray fluorescence scans were measured at the BioXAS-Imaging beamline at the Canadian Light Source. The results show that the Ca and Mn were mainly localized in the aleurone layer and scutellum. P, K, Fe, Cu, and Zn were mainly accumulated in the aleurone layer and embryo. Particularly the intensities of P, K, Cu, and Zn in the scutellum were higher compared to other areas. S was also distributed in each tissue and its abundance in the sub-aleurone was the highest. In addition, the intensities of S and Cu were highest in the nucellar projection of the crease region. All these elements were also found in the pericarp but they were at lower levels than other tissues. Overall, the details of these experimental results can provide important information for micronutrient biofortification and processing strategies on oat through elemental mapping in Arborg oat.
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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".