Evaluation of the antagonistic activity of black soldier fly frass extracts against plant pathogens using single- and double-layer agar bioassays
Bibliographic record
Abstract
Abstract Larval frass from insects which consists of larval excrement, exoskeleton, and undigested diet, is a rich source of organic material and microorganisms. Despite its potential value, research on frass valorisation in agriculture is limited. In this study, single-layer agar (SLA) and double-layer agar (DLA) in vitro bioassays were conducted to evaluate the effect of water-based black soldier fly larvae (BSFL) frass extracts from two different diets on the growth of six plant pathogens: Alternaria solani, Botrytis cinerea, Fusarium oxysporum, Phytophthora capsici, Rhizoctonia solani and Sclerotinia sclerotiorum. The results showed that frass extract from Gainesville house fly diet strongly or completely inhibited the growth of all tested plant pathogens in both SLA and DLA bioassays, while frass extract from fruit/vegetable/bakery/brewery diet strongly inhibited the mycelial growth of A. solani, B. cinerea, and S. sclerotiorum, and moderately inhibited the mycelial growth of P. capsici in both bioassays. For both diets and bioassays, 0.22 μm microfiltered frass extracts which are free of microorganisms showed generally no effect on the growth of the pathogens indicating that growth inhibition is caused by frass-inhabiting microorganisms. Both SLA and DLA bioassays revealed strong antagonistic effect of microorganisms inhabiting BSFL frass against the plant pathogens B. cinerea, A. solani, R. solani, P. capsici, F. oxysporum and S. sclerotiorum. Moreover, the study showed the impact of the BSFL diet on the antagonistic effect of frass extract. In future work, the antagonistic effect of frass extracts against the above-mentioned pathogens will be tested in vivo. BSFL frass could eventually find applications for the control of plant diseases.
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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) | 0.001 | 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 | 0.000 |
| 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".