Differential Response of Common Bean Genotypes to High Temperature
Bibliographic record
Abstract
Yield components of 24 common bean (Phaseolus vulgaris L.) genotypes were evaluated following exposure during reproductive development to four greenhouse day/night temperature treatments (24 °C/21 °C, 27 °C/24 °C, 30 °C/27 °C and 33 °C/30 °C). Genotypes included 12 snap beans, two wax beans, six dry beans, and four common bean accessions; 18 genotypes were previously described as heat-tolerant and three were heat-sensitive controls. The highest temperature treatment reduced seed number, pod number, mean seed weight and seeds/pod an average of 83%, 63%, 47%, and 73%, respectively. A heat susceptibility index (S) measuring yield stability under high temperatures indicated that `Brio', `Carson', `G122', `HB 1880', `HT 20', `HT 38', `Opus', and `Venture' were heat tolerant. Heat-tolerant genotypes displayed differential responses to high temperature, suggesting different genetic control of heat tolerance mechanisms. Genotypes with moderate heat tolerance, including `Barrier' and `Hystyle', showed stable yields in the 30 °C/27 °C treatment only, indicating this regime is optimal for screening common bean materials of unknown heat tolerance. `Haibushi', `Indeterminate Jamaica Red', and `Tío Canela-75' were previously described as heat tolerant but exhibited a heat-sensitive reaction in this study. Heat-sensitive genotypes `Haibushi' and `Labrador' maintained mean seed weight under high temperature. This data will help utilize nonallelic heat tolerance genes in development of bean varieties grown in high temperature environments.
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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".