Research on Biological Control Technologies and Mechanism Analysis of Common Pests and Diseases in Chrysanthemum morifolium (Hangbaiju)
Bibliographic record
Abstract
Chrysanthemum morifolium pest and disease control is ushering in a green transformation, and biological control technology has become a key solution due to its environmentally friendly characteristics. This study comprehensively sorted out the current mainstream biological control systems, covering multiple dimensions such as microbial antagonism, natural enemy regulation, botanical pesticides and ecological management, deeply analyzed their mechanisms of action and evaluated their application prospects. In the field of microbial control, Bacillus subtilis and Trichoderma harzianum have shown excellent disease inhibition capabilities. These beneficial microorganisms work through a dual mechanism: on the one hand, they secrete antimicrobial active substances to directly inhibit pathogens, and on the other hand, they activate the plant's own immune defense system. Natural enemy insects such as ladybugs and lacewings have built a natural pest control network, which has a significant control effect on common pests such as aphids and red spiders. In terms of botanical pesticides, natural ingredients such as matrine and tea tree essential oil have attracted much attention due to their broad-spectrum antibacterial and insect repellent properties. Field practice has confirmed that the integration of multiple biological control methods can produce a synergistic effect and achieve a win-win situation of economic benefits and ecological protection. This study not only provides a systematic solution for the green production of chrysanthemum, but also provides a practical example for promoting sustainable agricultural development.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".