Canola Nutrition and Variety Affect Oviposition and Offspring Performance in the Generalist Herbivore, Mamestra configurata (Lepidoptera: Noctuidae)
Bibliographic record
Abstract
Bertha armyworm Mamestra configurata Walker (Lepidoptera: Noctuidae) is a generalist herbivore that feeds on several crops in different plant families. Canola Brassica napus L. (Capparales: Brassicaceae) is one of the most favored host plants making the bertha armyworm a significant insect pest in the Canadian Prairie Provinces. The performance of the bertha armyworm on canola may vary with the quality of the canola plant. We tested the impact of plant nutrition and canola variety on oviposition and subsequent larval development of the bertha armyworm. A range of fertilization levels (0.0, 1.0, 3.0, and 5.0 g/pot) were applied to three different canola varieties: Clearfield 5535 CL, Roundup Ready hybrid 6060RR, and Q2. The total number of eggs laid on plants in a no-choice experiment increased with fertilizer level but a similar number of eggs were laid on plants that received moderate and high fertilizer treatments. Larvae reared on plants that received the moderate fertilizer application yielded heavier pupae than those reared on plants with low and high fertilizer treatments. Most eggs were laid on the Q2 variety when compared to Clearfield 5535 CL and Roundup Ready 6060 RR. Bertha armyworm females preferred to lay eggs on plants that received moderate or high fertilization over plants with the low fertilizer treatment. Plant leaf tissue nutrient content and plant growth were highest in plants that received moderate and high fertilizer treatment. We conclude that bertha armyworm oviposition behavior and larval performance are influenced by fertilizer treatment and canola variety.
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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".