Effect of patulin on the growth and nutrient composition of black soldier fly larvae
Bibliographic record
Abstract
Abstract Black solider fly (BSF, Hermetia illucens ) is a common insect in most part of North America, Europe, and Asia, and it is one of the most promising alternative protein sources for animal consumption. BSF can be fed on food waste and agricultural byproducts, which are usually contaminated with mycotoxins. Therefore, it is important to study the fate of mycotoxins in BSF and how mycotoxins will affect the growth and nutrient composition of BSF. Patulin is one of the major mycotoxins found in rotten fruits and consumption of patulin contaminated food can cause both long term and short-term health problems in both human and livestock. In this study clean and patulin spiked apple puree were provided to 50 three days old black soldier fly larvae (BSFL) for 3, 6, 9 and 17 days. Patulin bioaccumulation and degradation by BSFL, survival rate, weight gain and nutrient composition of BSFL were evaluated. During the treatment period, no patulin bioaccumulation was found in BSFL. BSFL was able to degrade patulin and convert patulin into (E)-ascladiol. By day 17, BSFL degraded 89.7% of patulin, 5.7% of patulin was converted into (E)-ascladiol, and 10.3% of patulin remained in its original form. While patulin treatment led to lower biomass and growth rate in BSFL, greater protein content and lower lipid content was observed in patulin treated BSFL. Thus, we conclude that BSFL do not accumulate patulin, and it is able to degrade patulin and converts patulin into its derivatives. The applied patulin negatively affects the development of BSLF resulting in lower biomass, growth rate and lipid content, but it induces higher protein content in BSFL.
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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".