Abundance and diversity of fungal endophytes isolated from monk fruit (<i>Siraitia grosvenorii</i>) grown in a Canadian research greenhouse
Bibliographic record
Abstract
Monk fruit (Siraitia grosvenorii) is an herbaceous perennial vine of the Cucurbitaceae family native to the southern parts of China. In 2020 and 2021, monk fruit plants were grown from seeds in a research greenhouse at Kwantlen Polytechnic University in British Columbia, Canada. Fungal endophytes were isolated from seeds, seedlings, mature monk fruit plants, and fruits on potato dextrose agar and water agar media. At least 150 species of fungal endophytes representing approximately 60 genera and 20 orders were recovered in culture from the monk fruit tissues. Isolates were identified by microscopic examination and BLAST comparison of ITS sequences to published sequences in GenBank. Non-metric multidimensional scaling (NMDS) was carried out to explore the similarity of fungal communities among different plant parts. Our study showed that monk fruit plants are a rich source of fungal endophytes with the greatest abundance and diversity in leaves. This work has deepened our understanding of the intricate interactions between plants and fungi that sustain ecosystems and underpin plant health and resilience. This knowledge can inform strategies for developing climate-resilient crops and restoring ecosystems in the face of climate challenges and developing more sustainable and eco-friendly strategies for plant health management.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".