Damage Assessment of Melanagromyza sojae (Diptera: Agromyzidae) on Soybean in Brazil
Bibliographic record
Abstract
Soybean stem fly, Melanagromyza sojae Zehntner (Diptera: Agromyzidae), is an important soybean (Glycine max) pest in Eastern Asia that has recently colonized South America. The region colonized by M. sojae includes Brazil and several other major soybean growing countries. Management strategies for this pest remain largely undeveloped due to lack of information regarding its potential to injury soybeans. The objective of this study was to quantify soybean yield reduction caused by M. sojae injury. One experiment was carried out during two summer crop seasons (2020 and 2021) at Santa Maria, RS state, Brazil. Soybean was planted during late-season to ensure that high pressure of M. sojae adults were present in the fields. The number of seeds, 1,000-seed weight, seed yield and number of pods were quantified for the lower, middle and upper canopy, and plant height was compared to the amount of stem injured to determine percentage of injured stem. Each 1% of injured stem in the lower, middle and upper canopy segments significantly reduced the number of seeds per plant, 1,000-seed weight, and yield. Across all canopy segments, yield reduction reached 0.9 g per plant for every 1% of injured stem. Treatments where insecticide applications started during the vegetative phase presented the lowest damage by M. sojae. These data suggest that M. sojae is an economically important herbivore of soybeans under Brazilian growing conditions and highlight the need to develop efficient and sustainable management strategies for this pest.
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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 | 0.001 | 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".