Pre-Screening of Banana Genotypes for Fusarium Wilt Resistance by Using an In Vitro Bioassay
Bibliographic record
Abstract
Abstract In the process of breeding and selection of banana for resistance to Fusarium wilt, it is important to conduct an efficient resistance screening test by artificial inoculation with Fusarium oxysporum f. sp. cubense (Foc) Tropical Race 4. So far, there are two types of early bioassays for screening Musa genotypes against Foc: a greenhouse and an in vitro bioassay. The most commonly used greenhouse bioassay is a pot-based system followed by a hydroponic system. Here we describe an in vitro bioassay characterized by in vitro inoculation of rooted banana plantlets grown on medium consisting of half-strength MS macronutrients and MS micronutrients. The disease response and evaluation results obtained through this in vitro bioassay correlates with that from a greenhouse screen and/or field evaluation. Given the importance of in vitro cell and tissue culture techniques for banana (mutation) breeding, promising resistant clones could be screened directly. This in vitro bioassay is a totally contained system compared with greenhouse methods and does not require an acclimatization step, thereby improving banana breeding efficiency. The in vitro pre-screening protocol and bioassay for Fusarium wilt resistance presented here is fast, space-effective, and accurate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.002 | 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 teacher head, 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".