Adhesion of decay-causing fungal conidia in wounds of<i>Malus</i>×<i>domestica</i>'Golden Delicious' apple fruit is influenced by wound age
Bibliographic record
Abstract
Wounds are the primary site in apple fruit for infection by conidia of Botrytis cinerea Pers.:Fr. and Penicil lium expansum Link & Thom. The effects of wound shape, wound age, and chemical properties of the wound on conidial adhesion in wounds of Malus ×domestica Borkh. 'Golden Delicious' fruit were investigated. Adhesion was measured after dislodging conidia from wounds using a sonication probe above the wound. In all experiments, conidial adhesion responses were similar for both fungi. Conidial adhesion in puncture wounds was not different from adhesion in slice wounds. Wound age, however, profoundly affected conidial adhesion. Conidia of both fungi exhibited 78.1%91.9% adhesion in freshly made wounds of both shapes compared with 37.7%56.6% in 1-d-old wounds. Conidial adhesion increased as wound age increased from 1 to 5 d. Exposure of 1- and 2-d-old wounds to butyl acetate, a volatile constituent of apple fruit, increased conidial adhesion compared with nonexposed wounds. This finding, in addition to results from the histochemical analyses of wounds, the quantification of sugars and total phenolics in water diffusates from wounds, and the measurement of conidial adhesion to wound diffusates, suggested that conidial adhesion in wounds was influenced by altered surface chemistry of wounds as they aged.Key words: apple fruit wounds, decay-causing fungi, fungal spore adhesion, mycoactive acetate esters, wound aging, wound decay.
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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 | 0.001 |
| 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".