Review: Breeding common bean for resistance to insect pests and nematodes
Bibliographic record
Abstract
Singh, S. P. and Schwartz, H. F. 2011. Review: Breeding common bean for resistance to insect pests and nematodes. Can. J. Plant Sci. 91: 239–250. Various insect pests and nematodes cause severe losses (35–100%) globally to the yield and quality of dry and green common bean (Phaseolus vulgaris L.). The objectives of this review are to briefly describe major insect pests and nematodes in the Americas, breeding strategies and methods used, and research progress achieved. We also describe integrated genetic improvement for resistance to multiple insect pests and nematodes and cultivar development. Breeding for resistance to one insect pest or nematode at a time has been practiced in most instances. Backcross, pedigree, and bulk-pedigree breeding methods have been used. Considerable progress has been made in genetics and germplasm enhancement for resistance to bean pod weevil (Apion godmani Wagner), tropical bruchid (Zabrotes subfasciatus Boheman), leafhoppers (Empoasca kraemeri Ross and Moore), and root- knot nematode (Meloidogyne species). However, improvement in resistance to Acanthoscelides obtectus (Say), lesion (Pratylenchus species) and soybean cyst (Heterodera glycines) nematodes, and other regional insect pests has been minimal or non-existent. Furthermore, dry or green common bean cultivars with high levels of resistance to one or more insect pests and nematodes are rare. Breeding strategies for integrated and simultaneous genetic improvement of multiple qualitatively and quantitatively inherited resistances for cultivar development are briefly described.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".