Selection of Tomato Hybrids With Zingiberene Concentration for Breeding Programs to Pest Resistance
Bibliographic record
Abstract
The zingiberene is a sesquiterpene that is present in tomato leaves. This compound is known to promote resistance to pests and diseases. The Brazil has a germplasm bank of vegetable at Universidade Federal de Viçosa (HGB-UFV) crops with over 8 million accesses. One technique that helps in the choice of progenitors with favorable concentrations of zingiberene is the diallel crosses. The diallel crosses allow the estimation of general combining ability (GCA) and specific combining ability (SCA). Thus, the aim of this study was to find out tomato hybrids with high zingiberene concentrations. The genitors were divided into two contrasting groups for resistance to pests. The characterization and quantification spectrophotometric of zingiberene was performed, obtaining absorbance values at 270 nm. To determine the content of zingiberene in hybrids those were coming from the diallel cross. The analysis from the spectrophotometric method was performed. The estimates of GCA and SCA of these hybrids at combinations HGB 2119 x LA716, HGB 2119 x PI 12786, HGB 2214 x HGB 674, HGB 2064 x HGB 674, HGB 2214 x PI 127826, HGB 985 x LA 716 and Santa Clara x HGB 674 have high potential in tomato plant breeding aiming of resistance to pests and diseases.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".