Effects of Temperature and Wetness on Components of the Infection Cycle of<i>Valdensia heterodoxa</i>in Lowbush Blueberry
Bibliographic record
Abstract
, is a serious disease of lowbush blueberry. The disease may develop rapidly, resulting in extensive defoliation of fields. The purpose of this study was to examine the effects of temperature and wetness duration on various components of the infection cycle to gain a better understanding of epidemic development that might lead to improved management practices. Lesions on leaves appeared 6 h after inoculation at 20°C and were larger on young 3-week-old leaves compared with 8-week-old leaves. Incidence of infection on 3-week-old leaves was lowest at 5°C, highest at 15 and 20°C, and failed to occur at 30°C. Defoliation began 48 h after inoculation at 20 and 25°C but was slower at higher and lower temperatures. Conidia production and release from colonized leaves began 48 h after inoculation at 15 and 19°C. Total conidia production was lowest at 7°C, highest at 15°C, and progressively declined at 19 and 23°C. Production of conidia lasted 2 to 3 days. Sclerotia formed mainly along the midveins and were similar in size at 5 to 15°C, largest at 20°C, and smallest at 25°C. Conidia formed directly on sclerotia that were overwintered outdoors and then incubated on moist filter paper. Conidia production began after 48 h at 10, 15, and 20°C. Total production was lowest at 5°C, highest at 20°C, failed to occur at 25°C, and ceased after 10 days at all temperatures. These data show that at optimal temperatures, relatively short wet periods are required for conidia production on overwintered sclerotia, infection of leaves, and subsequent conidia production on diseased leaves that may account for the sudden and rapid spread of disease in fields. The data will be useful for helping growers identify weather conditions favorable for disease development.
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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".