Yield Loss Assessment in Canola: Effects of Brown Girdling Root Rot and Maggot Damage on Single Plant Yield
Bibliographic record
Abstract
Single plant yield loss due to brown girdling root rot (Rhizoctonia solani) and cabbage root maggot (Delia spp.) damage was assessed in canola (Brassica rapa cvs. Reward and Tobin) to quantify the effects of root rot on yield and determine whether yield losses due to root rot are compounded by maggot damage. At crop ripening during 1998 and 1999, 2,000 plants from six growers' fields were scored for both root rot and maggot injury. The assessed roots were separated into eight categories constructed by crossing four classes of root rot severity based on degree of girdling and two classes of maggot damage based on percentage of the root surface with maggot tunnels. A ninth category was defined for partially to completely decayed roots for which it was not possible to determine maggot damage. There was no root rot by maggot injury interaction on any of the yield parameters measured. Furthermore, maggots had no adverse effects on yield at the observed damage levels. In contrast, plant weight, seed yield, harvest index, seed size, but not oil content were reduced on plants with completely decayed roots. On average, seed yield was not reduced on plants with roots with nongirdling lesions and superficial nonsinking girdling lesions, but was reduced by 17% on plants with roots with girdling and sinking lesions, and by 65% on plants with decayed taproots. Over 2 years, yield losses in growers' fields ranged from 1 to 5%.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".