Rapid Method to Screen Resistance of Potato Plants Against Myzus persicae (Homoptera: Aphididae) in the Laboratory
Bibliographic record
Abstract
With the objective to develop a potato, Solanum tuberosum L., resistance program against aphids, we propose a rapid screening method with Myzus persicae (Sulzer) in the laboratory. We aimed to optimize the duration of the whole procedure and to decrease the frequency of measurements. In a first experiment, intrinsic rate of natural increase (r(m)) values were compared between adult aphids reared throughout their entire life and adults reared only during a period equivalent to their prereproductive period. No significant differences were observed. In a second experiment, four groups of aphids were distinguished according to the sampling frequency, i.e., those whose biological parameters were evaluated every single, second, third, and fourth day. Except for the fourth-day experiment, the r(m) values estimated on aphids reared on the three potato lines were not significantly different whatever sampling frequency of single, second, or third day used to check aphids. Thus, screening efforts in laboratory can be largely optimized by evaluating adult aphids only during a period equivalent to their prereproductive period and assessing M. persicae populations every third day. Our method is reliable and adapted to screen a large number of potato plants against M. persicae because it allows an average 70% reduction in the time required for the whole experimental process.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".