Re-evaluating TiCl4 and UV assays for detection of vicine and convicine in high-throughput screening of immature and mature seeds of faba bean
Bibliographic record
Abstract
Genomic resources have just started to focus on the faba bean; the genes for synthesis of vicine and convicine (V-C) have not been determined, and recently developed genetic markers for these anti-nutritionals have not been used to examine these traits in very large scale in faba bean. Simple, rapid and cost-effective technologies are crucial in crop breeding programs, especially in the developing world, and in some cases, traditional methodologies are used in combination with genetic markers to assess agronomic traits and the value of gene markers. Here, two methodologies (TiCl4 assay and 274 nm absorption) are re-evaluated for their application in detection of V-C in faba beans. In comparison with TiCl4 assay, the method of 274 nm UV absorption without an HPLC analysis offers more reliable analysis for detection of V-C in immature and mature seeds of faba bean. Its application in high throughput screening by 60 min agitation of immature seeds or mature seed flour in 2% trichloroacetic acid (TCA) allows quick screening of low V-C faba beans. The level of V-C was maximum when seed moisture was 80% and V-C level was measured as 0.92% in CDC Fatima flour. Though V-C from 2% TCA extract of mature and immature seeds of CDC Fatima was detected by 274 wavelength in the TiCl4 assay reaction, a Ti-aglycone complex was not clearly detectible at 480 nm as previously suggested. Key words: Vicine, convicine, TiCl4 assay, UV assay, high throughput, seed, faba bean.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".