Bibliographic record
Abstract
The systematic literature review investigates Nomuraea rileyi's semi-solid fermentative process, which functions as an entomopathogenic fungus in Lepidopteran pest biocontrol applications. This review combines research conducted from 2020 to 2025 that focuses on maximizing conidia production for commercial use. A systematic review was conducted following PRISMA guidelines, through which researchers retrieved articles using Boolean operators within Scopus, Google Scholar, PubMed, and Web of Science databases. Studies using semi-solid fermentation, which reported quantitative data about conidia yield and viability along with controlled laboratory conditions, met all inclusion criteria. An evaluation process using the Newcastle-Ottawa Scale evaluated the studies to counteract potential biases. The production of conidia reaches its highest levels when scientists use rice materials as their substrate, especially when they work with broken rice and rice bran. The addition of yeast extract boosts conidial production, but implementation faces significant economic barriers due to supplement costs. The optimal conditions for obtaining viable conidial production involved maintaining temperatures between 25-30°C while keeping above 70% relative humidity. The review examines difficulties in large-scale conidial production because of expensive substrates and proposes implementing agricultural waste products to decrease manufacturing expenses. The study further advocates the research work into sustainable fermentation systems by utilizing various substrates, thus developing N. rileyi production at industrial scales for integrated pest management (IPM) applications.
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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.172 | 0.019 |
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".