Effect of Marker Aided Pyramiding of Anthracnose and Pythium Root Rot Resistance Genes on Plant Agronomic Characters among Advanced Common Bean Genotypes
Bibliographic record
Abstract
One of the factors that accounts for the low yields in common bean is the simultaneous occurrence of diseases on the common bean crop. Bean root rots and anthracnose are the most important common bean diseases that simultaneously occur on the bean crop in Uganda. Moreover, Colletotrichum lindemuthianum, the pathogen that causes bean anthracnose, possesses a high genetic variability which makes it easily break down single gene resistance. Pyramiding resistance genes for both diseases in commercial varieties would ensure reduction of yield losses resulting from the two diseases. However, the effect of marker assisted gene pyramiding on plant agronomic characters is not well understood. Three-way crosses were made to pyramid three anthracnose and one Pythium root rot resistance genes in four susceptible market class varieties. Sequence characterized amplified regions (SCAR) markers were used to facilitate the pyramiding scheme. Correlation analysis and Path coefficient analysis were used to assess the association between number of pyramided genes and different plant agronomic characters. Number of pyramided genes was negatively correlated with number of pods per plant (-0.32), number of seeds per plant (-0.25), number of seeds per pod (-0.18), pod length (-0.17), days to 50% flowering (-0.09) and 100-seed weight (-0.02). Path coefficient analysis showed that number of pyramided genes, plant height, days to 50% flowering, number of seeds per pod and number of pods per plant had negative direct effects on seed weight per plant. Number of seeds per plant had the highest positive direct effects (0.98) followed by 100-seed weight (0.28) while days to maturity had the least positive direct effect (0.03) on seed weight per plant. Only number of seeds per plant had its correlation coefficient (0.94) almost equal to the direct path coefficient (0.97). Number of pyramided genes had significant (P < 0.05) negative indirect effect on seed weight per plant only through number of seeds per plant (-0.25). Therefore, pyramiding higher numbers of resistance genes may cause a grain yield reduction via number of seeds per plant. Therefore, it is important for breeders to simultaneously select for number of pyramided genes with number of seeds per plant and other highly associated traits.
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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".