Establishment of a rapeseed meal fermentation model for iturin A production by <i>Bacillus amyloliquefaciens</i> <scp>CX</scp> ‐20
Bibliographic record
Abstract
Summary Iturin A is an important broad‐spectrum antifungal cyclic lipopeptide used as an ideal potential biological control agent. However, its application is limited mainly due to the producer strains’ low productivity and the high production costs. Here, a potentially industrial strain Bacillus amyloliquefaciens CX ‐20 was proved to use low‐cost rapeseed meal ( RSM ) as the sole source of all nutrients except the carbon source for the high productivity of iturin A. A fermentation model was first established to analyse the specific roles of different RSM components on iturin A production. Proteins and minerals in RSM were confirmed to play positive role, whereas fibre had negative effect. And the maximal concentration of iturin A was predicted to be more than 1.64 g l −1 by the established evaluation model. Moreover, submerged fermentation of B. amyloliquefaciens CX ‐20 demonstrated a strong ability to hydrolyse RSM and release water‐soluble nutrients. This fermentation broth, a mixture of Bacillus , iturin A and RSM hydrolysate, could simultaneously combat clubroot disease and promote the growth of Brassica napus . In conclusion, this study provides a promising strategy to achieve full utilization of RSM for the production of a combination of value‐added biological control agent and biofertilizer.
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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 | 0.001 |
| 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) | 0.000 | 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 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".