Effect of spraying adjuvants with the biocontrol fungus<i>Microsphaeropsis ochracea</i>at different water volumes on the colonization of apple leaves
Bibliographic record
Abstract
In a previous study, it was observed that Microsphaeropsis ochracea was less efficacious as a biofungicide for apple scab when applied under field conditions as an unformulated spore suspension with an airblast spray using low water volumes as compared to a ground cover spray using high water volumes. The effect of spore concentration (109 to 1012 spores ha−1), water volume (250–1500 L ha−1), and 20 adjuvants were studied to improve colonization of apple leaves by M. ochracea. Using commercial-type spray equipment, the fungus was applied to excised apple leaves. Higher spores concentrations resulted in greater colonization. Water volume did not have a strong impact on colonization. Only a few adjuvants improved germination (glycerine) and mycelial growth (K-90, Agrimer, Ekol, and Tween 80) in some trials. When tested on apple trees, the adjuvant Assist provided the most consistent improvement in colonization in five out of eight trials. The use of oils, humectants, and surfactants could broaden the opportunities for using this biofungicide.
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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".