Positional Effects of Bottle-Baited Traps in Reducing Infestation Level of Coffee Berry Borer Hypothenemus Hampei Ferrari in Kilimanjaro Region, Tanzania
Bibliographic record
Abstract
Coffee berry borer (CBB) is among the key insect pests of coffee worldwide. The use of bottle-baited traps has been in practice in several coffee-growing areas including Tanzania. However, there is limited information about the influence of height and spacing of commonly used bottle-baited traps in managing CBB in coffee-growing areas in the country. Therefore, the objective of this research was to evaluate the effect of height where traps were placed (0.6, 1.2, and 1.6 m) on the reduction of infestation level of coffee berry borers at different developmental stages of coffee fruit (green and red fruit) under field conditions. The experiment followed a completely randomized block design with a factorial arrangement and four replications, three (lower, middle, and upper) levels of height and spacing were placed for 7 months. The number of captured CBB and damaged berries percentage was evaluated. The data were analyzed by R Software (2021) through an analysis of variance and means were separated by Turkey’s (0.05). A significant minimum berries damage (0.26%) as an implication of the lowest CBB infestation level was shown at the height of 0.6 m (for all stages of berries). On the other hand, at the red berries stage, the lowest damage (11.12%) was observed at the height of 1.6 m. Generally, this study deduced that the lower the height from which the traps are placed, the lower the infestation level of CBB hence reducing crop damage by the 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 | 0.000 | 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) | 0.001 | 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".