Genetic Relationship among Common Bean Cultivars with Enhanced Accumulation of Bioactive Compounds
Bibliographic record
Abstract
Common bean (Phaseolus vulgaris L.) is now considered as a nutritive food containing bioactive compounds for human health. Studies are necessary to understand genetic and environmental influence over yield and the accumulation of bioactive compounds in seeds. Days to flowering, disease reaction, maturity, seed yield, 100 seed weight, flavonoid content and genetic relationships were evaluated in eight common bean cultivars in spring and summer cropping seasons. Flowering was registered between 36 and 54 days after planting, values between 1 and 7 were observed for CBB (Common Bacterial Blight) and maturity showed values between 88 and 98 days. Similar seed yields were registered between growing seasons and significant differences (p ≤ 0.05) among cultivars were obtained in spring (484 kg ha-1 to 1 544 kg ha-1) and summer (1 042 kg ha-1 to 1 573 kg ha-1). Highly significant differences (p ≤ 0.01) were observed among cultivars for myricetin, quercetin and kaempferol content. High values for seed yield and flavonoid content were observed in Negro Pacífico (1 500 kg ha-1; myr = 68.6 µg g-1), Negro Nayarit (1 417 kg ha-1; myr = 31.8 µg g-1) and Negro Sahuatoba (1 396 kg ha-1; myr = 70.7 µg g-1; quer = 183.5 µg g-1; kaemp = 7.2 µg g-1). Seven SSR loci were used to establish genetic relationships among breed cultivars derived from parents collected in Southern México and Central America. Agronomic, laboratory and molecular markers allowed generating important information to find gene sources for genetic breeding programs in order to improve seed yield and bioactive compounds accumulation in common bean seeds.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".