Evaluation of Tactics for Management of Sugarcane Aphid (Hemiptera: Aphididae) in Grain Sorghum
Bibliographic record
Abstract
The invasive sugarcane aphid, Melanaphis sacchari (Zehntner), is a devastating new pest of grain sorghum. Studies were conducted utilizing an integrated approach of four management tactics: planting date, insecticidal seed treatment, a foliar-applied insecticide, and plant resistance. Experiments were conducted in 2016 and 2017 at Griffin, Tifton, and Plains Georgia, and in 2016 in Texas, Alabama, and Oklahoma, United States. Early planting was effective in reducing damage and increasing yields when compared to the late planting. Use of a resistant variety reduced cumulative aphid-days, plant injury and usually prevented significant yield loss. Foliar application of flupyradifurone when aphids reached an economic threshold, was an effective management tactic preventing aphid injury and yield loss. Use of clothianidin seed treatment also reduced aphid injury and yield loss of the susceptible hybrid but generally did not prevent injury and yield loss of the resistant hybrid. We conclude that an earlier planting date coupled with a resistant variety and judicious use of an efficacious foliar-applied insecticide can effectively manage sugarcane aphid on grain sorghum. An insecticide seed treatment also may be useful to reduce the risk of sugarcane aphid damage to seedlings of susceptible hybrids.
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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) | 0.000 | 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".