Comparative Study Between ATOMES Novels, NOVOSECT SC21®, ATO BED BUG® and NEO-BOOST® as a Bio-organic Solution in Managing Tomato Open Field Plantation in Hrajel Area in Lebanon
Bibliographic record
Abstract
The increasing use of chemical insecticides has adversely effected the environment and increased insect resistance. Biopesticides have been noticed the potential to be an excellent alternative to chemicals to reduce the negative impacts to human health and the environment. Tomato (Lycopersicon esculentum) is the second most important vegetable crop worldwide due to its nutritional importance. The effect of NOVOSECT SC21® (0.5 L/200 L), ATO BED BUGS® (1 L/200 L) and NEO-BOOST® (1 kg/200 L) against Tuta absoluta, Liriomyza trifolii and Alternaria solani was studied. A complete randomized block design (CRBD) was used with three replications, three treatments and one control in Hrajel area in Lebanon in the summer of 2020. We evaluated the level of infestation and larval mortality level of Tuta absoluta, Liriomyza trifolii and Alternaria solani infection 24, 48 and 72 hr after the application. Results showed that NOVOSECT SC21® (Mix of metabolites of the Bacillus F.D. 777) was the most efficient in decreasing the infestation and inducing larval mortality level of T. absoluta and L. trifolii and the fungal infection induced by A. solani with significant difference with time, followed respectively by ATO BED BUGS® and finally NEO-BOOST®.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 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".