Characterizing Resistance to Soybean Aphid (Hemiptera: Aphididae): Antibiosis and Antixenosis Assessment
Bibliographic record
Abstract
Host-plant resistance (HPR) remains a vital tool to manage soybean aphid (Aphis glycines Matsumura), a major pest of soybean in Midwestern United States and southern Canada. HPR can be overcome by virulent biotypes of A. glycines; thus, in order to increase the durability of resistant cultivars, HPR needs to be deployed strategically. To improve the strategic deployment, a complete understanding of HPR in existing resistant germplasm will help ensure HPR success. In this study, we characterized HPR soybean to determine antibiosis and antixenosis categories of resistance to different biotypes of A. glycines. No-choice and free-choice tests were performed on 11 previously reported plant introductions (PIs) possessing resistance to at least one A. glycines biotype (1, 2, and 3). Overall, we found that the PIs manifested differences of a particular resistance category in response to infestation by different biotypes. Our data from no-choice tests indicate that all tested PIs possess antibiosis-based resistance to three biotypes. However, the strength of antibiosis was variable as some PIs showed stronger antibiosis toward a given biotype than others. All tested PIs manifested antixenosis, in addition to antibiosis. Furthermore, detached leaf assays revealed that resistance to A. glycines was not retained in excised soybean leaves. Characterization of resistance in this study can contribute to develop strategies for future deployment of resistant cultivars developed from these PIs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".