The dispersal of wheat curl mites (Acari: Eriophyidae) and kernel streaking in maize (Zea mays L.)
Bibliographic record
Abstract
The wheat curl mite (WCM, 'Aceria tosichella' Keifer), a pest of corn, is suggested to be associated with kernel streaking in corn (KSC). KSC is a physiological disorder that seriously affects the quality of food grade corn, but little is known about the factor/factors causing the expression of KSC or the dispersal characteristics of WCM into corn from winter wheat. These projects were conducted from 1999 to 2002 at Ridgetown College and the University of Guelph, Ontario, Canada, to study the dispersal characteristics of WCM from their source into corn fields, and the effects of WCM, low temperature during grain filling phase of corn, and sunlight and corn genotype on the expression of KSC. Corn fields adjacent to winter wheat, soybean or grasses were chosen to clarify the main source of WCM. Corn fields with wheat to the north, east, south and west were selected to study the critical distances for WCM dispersal in corn fields and the dispersal period of WCM. The influence of WCM, cool nights during the grain filling phase of corn, stronger sunlight on kernels when without husk protection, and corn hybrids on the expression of KSC was studied. The main source of WCM in corn in the summer was winter wheat; the critical distances to isolation planting of corn were 90 m when wheat was to the west of corn and 60 m when wheat was in the north or south; WCM dispersal started in late June, peaked in the first three weeks of July and stopped when winter wheat was harvested; The presence of WCM, cool night temperatures and intensity of sunlight were factors that influenced the incidence and severity of KSC, but their effects largely depended on the susceptibility of corn hybrids. Therefore, plant breeding may be a more logical approach to managing KRS in food grade corn.
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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) | 0.000 | 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".