Field Evaluation of a Pneumatic Prototype Machine Designed to Control the Colorado Potato Beetle in Potato Crops
Bibliographic record
Abstract
The Colorado Potato Beetle (CPB), Leptinotarsa decemlineata Say, 1824, is a major insect pest of potato plants. It can greatly reduce potato yields if left uncontrolled. The most effective method of controlling the CPB is to apply chemical insecticides during its life cycle. However, the CPB tends to develop resistance to chemicals. Therefore, its control is difficult. This has prompted researchers to explore alternatives to insecticides. The use of pneumatic methods to control the CPB could considerably reduce the environmental impacts of insecticide applications and the need for farmers to handle toxic products. The objective of this study was to investigate the impact of a CPB pneumatic prototype machine on potato plant growth and tuber yield as well as its efficacy in controlling the CPB. Three airflow velocities (45, 50, and 55 m/s) and two travel speeds (5 and 6 km/h) were tested. The measured variables in organic and pneumatic control plots were CPB populations at different life stages, potato plant height, dry matter, Leaf Area Index (LAI), and tuber yield. The results indicated that the use of the pneumatic prototype machine to control the CPB had no significant negative impact on potato plant growth (height, dry matter, and LAI). Tuber yields were comparable to those obtained in the control plots and the prototype machine was highly effective in dislodging the CPB. These results confirm those obtained in 2018 and suggest that this innovative prototype pneumatic machine could efficiently control the CPB and significantly contribute to reducing the use of chemical insecticides.
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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".