Seed damage and sources of yield loss by <i>Sitodiplosis mosellana</i> (Diptera: Cecidomyiidae) in resistant wheat varietal blends relative to susceptible wheat cultivars in western Canada
Bibliographic record
Abstract
Abstract Spring wheat varieties with the Sm1 gene for resistance to wheat midge, Sitodiplosis mosellana (Géhin) (Diptera: Cecidomyiidae), were compared with susceptible wheat (Triticum Linnaeus; Poaceae) with respect to sources of yield loss and reduction in market value from wheat midge feeding damage. Four resistant varietal blends (90% Sm1 wheat plus 10% susceptible refuge) and four susceptible cultivars were grown in replicated experiments at eight locations in western Canada. Frequencies and 1000-kernel weights of undamaged and midge-damaged seeds were assessed before harvest by dissecting samples of ripe spikes, and after harvest in samples of cleaned grain. Spike data were used to estimate yield losses from reduced weight of damaged seeds and loss of severely damaged seeds (⩽8 mg) at harvest. Among midge-damaged seeds in spikes, few were severely damaged in resistant varietal blends, whereas most were severely damaged in susceptible cultivars. Cleaned, harvested grain of resistant varietal blends and susceptible cultivars had similar frequencies of midge damage and were assessed similar market grades. The primary benefit of midge-resistant wheat was reduced yield loss due to seed damage by wheat midge larvae. Resistant wheat did not protect against loss of market grade, but market value could increase due to larger yields.
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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 | 0.001 | 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".