The genetic improvement of protein quality in common bean (Phaseolus vulgaris L.)
Bibliographic record
Abstract
Abstract\nThe common bean (Phaseolus vulgaris L.) has a high seed protein content, between 20 and 30%. The protein quality in common is considered low because of the suboptimal levels of methionine and cysteine in the seed. Phaseolin, the main seed storage protein, accounts for 30-50% of the total seed protein content. Phaseolin only contains about 0.5 to 0.80% methionine. The suggested nutritional requirements for methionine-cysteine in the human diet are between 2.5 and 2.6 %. Previous studies on the germplasm SMARC1N-PN1 showed that deficiency in phaseolin and lectins leads to increased methionine-cysteine up to 2.6% in the bean seed. Dr. Hou, the bean breeder in Manitoba, made a cross between SMARC1N-PN1 and Morden-003. One Hundred and eighty-five recombinant inbred lines (RILs) F2:8 were obtained of this cross through eight generations of inbreeding. In this study I used SDS-PAGE to assess the protein profiles of the RILs according to the phenotypic expression for phaseolin and lectins. The RILs deficient in phaseolin and lectins increased their total methionine-cysteine seed content up to 3.4%. Field trials were conducted to assess the impact of the protein deficiency on the RILs’ agronomic traits. The RILs deficient in phaseolin and lectins had a similar agronomic performance as Morden-003 thus can be considered Canadian elite germplasm to develop common bean cultivars with improved protein. Key-words: Phaseolus vulgaris, SDS-PAGE, phaseolin, methionine, cysteine, recombinant inbreed lines
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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) | 0.000 | 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".