Evaluation of Biorational Insecticides as Stand-alone Treatments for the Management of the Pigweed Flea Beetle, Disonycha glabrata (Coleoptera: Chrysomelidae), in Organic Production of Amaranthus spp.
Bibliographic record
Abstract
The pigweed flea beetle, Disonycha glabrata, is the most damaging insect pest on Amaranthus spp. in the Piedmont zone of North Carolina (NC), United States. It is capable of causing severe yield loss on amaranth greens if uncontrolled. Field experiments were conducted over two growing seasons (Summer 2017 and 2018) in Greensboro, NC, to evaluate OMRI-approved biorational insecticides against D. glabrata in organic amaranth production. Insecticides evaluated included Azatin® O (azadiractin), Ecotec® (oils: rosemary, peppermint and geraniol), Entrust® (spinosad) and PyGanic® (pyrethrins) as stand-alone threshold-driven treatments applied at recommended label rates. Insecticide treatment action threshold (AT) was 2 (on a scale of 5) representing 20-40% leaf damage. The efficacy of the insecticides against D. glabrata population differed significantly within the amaranth varieties in comparison to their respective controls: treatments with Entrust® and PyGanic® on Green Callaloo and Red Leaf recorded 80% reduction in beetle population while Ecotec® gave only a 15% beetle reduction. The Azatin® O treatments recorded the highest D. glabrata population, sometimes greater than the control. Marketable fresh leaf yield from both Green Callaloo and Red Leaf amaranth was highest in the Entrust® and PyGanic® treatments. Hopi Red-Dye and Molten Fire amaranths showed some resistance to beetle damage; they are also intrinsically low yielding. These findings provide information that would make organic amaranth production possible with only limited and safe insecticide input using OMRI-approved insecticides in a threshold-driven manner, an important step towards the sustainable management of D. glabrata and amaranth production.
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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 | 0.001 | 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".