Co-vectoring of Beauveria bassiana and Clonostachys rosea by bumble bees (Bombus impatiens) for control of insect pests and suppression of grey mould in greenhouse tomato and sweet pepper
Bibliographic record
Abstract
Greenhouse cage trials were conducted to assess the effectiveness of bumble bee pollinators for the co-vectoring of two fungi (Beauveria bassiana [Balsamo] Vuillemin [BotaniGard 22WP® formulation] and Clonostachys rosea Lnk: Fr. [Endofine®]), in greenhouse tomato and sweet pepper for control of insect pests (greenhouse whitefly, Trialeurodes vaporariorum Westwood; and tarnished plant bug, Lygus lineolaris [Palisot de Beauvois]), and grey mould (Botrytis cinerea Pers: Fr.). Three treatments were evaluated: 6.24 × 1010 conidia of B. bassiana + 1.38 × 107 conidia of C. rosea/g of inoculum vectored by bees (active inoculum); heat-inactivated inoculum vectored by bees; and a control with no inoculum and no bees. In each crop, the treatments were arranged in a completely randomized block design with four replications. When applied in the tomato crop, the active inoculum killed 49% of the T. vaporariorum and suppressed grey mould by 57% and 46%, respectively, on the flowers and leaves. In sweet pepper, mortality of L. lineolaris was 73% and grey mould was suppressed by 59% and 47%, respectively, on the flowers and leaves in the active inoculum treatment. The incidence of grey mould in sweet pepper and tomatoes treated with the heat-inactivated inoculum or no inoculum (control) was approximately 80% on the flowers and leaves. Thus, the combined inoculum of B. bassiana and C. rosea can potentially control T. vaporariorum and L. lineolaris, and suppress grey mould in greenhouse tomatoes and sweet peppers, when vectored simultaneously by bumble bees. Commercial greenhouse trials need to be conducted next to determine control efficacy under large scale production conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".