Fitness, Competitive Ability, and Mutation Stability of Isolates of <i>Colletotrichum acutatum</i> from Strawberry Resistant to QoI Fungicides
Bibliographic record
Abstract
Quinone-outside inhibitor (QoI) fungicides are used to manage anthracnose of strawberry, caused by Colletotrichum acutatum. However, selection for resistance to QoI fungicides was first reported in 2013 in Florida and, subsequently, in strawberry nurseries and production areas across the United States and Canada. C. acutatum resistance to QoIs is associated with the G143A point mutation in the cytochrome b gene. This mutation is known to be associated with field resistance even at high rates of QoI. In this study, we investigated the relative fitness and competitive ability of QoI-resistant and -sensitive C. acutatum isolates. A fitness comparison did not indicate any difference between resistant and sensitive isolates in aggressiveness, spore production, and mycelial growth at different temperatures. Additionally, in the absence of selection pressure, resistant and sensitive isolates were equally competitive. Cultivation of QoI-resistant and QoI-sensitive isolates for four culture cycles in vitro in the absence of azoxystrobin showed that QoI resistance was stable. The observed lack of fitness penalties and stability of the G143A mutation in QoI-resistant C. acutatum populations suggest that the interruption and further reintroduction of QoI fungicides might not be an option for strawberry nurseries and fruit production areas. Further investigation of alternative chemical and nonchemical C. acutatum control practices, in addition to the integration of multisite fungicides, is needed to reduce the occurrence and distribution of QoI-resistant populations in strawberry fields.
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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 | 0.000 |
| 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".