Selenium and Trace Element Distribution in Astragalus Plants: Developing a Differential Pulse Polarographic Method for Their Determination
Bibliographic record
Abstract
Astragalus plants have a wide range of applications in pharmaceuticals (gum tragacanth), as thickening agents in foods, and may have applications in controlling cancer cells. They are used as feed for animals and they are indicator plants for selenium. Because of their use in health-related areas it is very important to determine their selenium and trace element content with high accuracy. A new differential pulse polarographic method was established for trace element determination (10 elements) and their distribution in these plants. The Astragalus plants investigated in this work are Astragalus microcephalus and Astragalus lusitanicus, which grow almost everywhere. Their roots, stems, and leaves were analyzed separately. Since some Astragalus plants are known to accumulate selenium, the most emphasis was given to its determination. The Astragalus plants were wet digested and their DPP polarograms were taken in various media. In pH 2 acetate buffer, Se, Mo, Cd, Pb, Cr, Zn, and As peaks, and in pH 4 acetate buffer, Cu, Se, Mo, As, and Zn peaks could be separated and determined. In the presence of EDTA at pH 4, Cu, Ti, Se, and As peaks, and at pH 6, Fe, Cu, Ti, and As peaks could be separated and determined. Thus, by adjusting the pH and medium, it was possible to determine 10 trace elements in the same solution. While in Astragalus microcephalus plants the Se content was 183 \\pm 15 m g/g, another plant, Elymus (Gramineae), which was taken from the same soil had no selenium, which indicates that selenium is accumulated in this kind of astragalus plant. On the other hand, no selenium was found in Astragalus lusitanicus plants. The types of Astragalus plants that accumulate selenium to the greatest degree are known to grow in Canada, USA, Russia, Afghanistan, Spain, and Turkey. According to the results, most of the elements are accumulated in the roots, but selenium was also distributed in the stems and leaves. Although large quantities of Cr were present in the roots, it was under the detection level in the stems and leaves. On the other hand, there was a level of iron present in both the roots and leaves. The proposed method is simple, fast, and cheap, does not require any preconcentration or separation procedure, and can be safely used with many biological materials.
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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 | 0.000 |
| 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 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".