Positive Yield Impact of Predacious Mites in Tea Production Areas of Kenya
Bibliographic record
Abstract
Tea agro ecosystems are least disturbed in comparison to other crop systems due to the plant canopy type. A survey on predacious mites’ abundance and impact on leaf yield in different tea production areas was carried out in 2014-2015 in Kenya. Major pest species were the red spider mite Oligonychus coffeae and the yellow thrip, Scirtothrips dorsalis. The red crevice mite, Brevipalpus phoenicis was found in few areas and in low numbers. Predacious mites of Phytoseiidae Family were highest at 5.8 and 6.8 mites per sample during dry and wet seasons, respectively. Phytoseiid abundance during the dry and wet seasons did not differ much within most sample sites. Presence of phytoseiid mites in combination with NPK-fertilizer-high altitude led to the strongest correlation to leaf yield than any other combination variable. High phytoseiid density- high altitude was third with positive impact to yield increase after high altitude combined with NPK-fertilizer. The findings here show contributory positive impact of phytoseiids in tea leaf yield in an agro eco-system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".