Diversity of soil fungi in the vineyards of Changli region in China
Bibliographic record
Abstract
This study aimed to elucidate the fungal diversity of Changli vineyard soil in China. High-throughput sequencing technology was used to investigate the diversity and composition of soil fungi in five vineyards from different geographical locations in Changli. Although the five vineyards had similar fungal communities, the diversity, composition, and distribution of the high-abundance species differed. Ascomycota, Basidiomycota, and Mortierellomycota were dominant phyla. Among the 14 high-abundance genera of fungi, Odiodendron, Pleotrichocladium, and Plectosephalella have rarely been reported in other vineyards and are unique to the Changli region. In addition, Solicoccozyma aeria and Solicoccozyma terrea were the dominant species in the five vineyards and have rarely been reported in domestic vineyards. Additionally, Rhizophagus, Wardomyces, Mortierella, Volutella, and Cryptococcus were significantly different among the five vineyard soils. Among these species, Mortierella was highly abundant in each vineyard, but its contents were significantly different across vineyards. These findings enrich the information on the composition and diversity of soil fungi in the vineyard of the Changli region, which helps to explore the regional or distinctive sensorial attributes of wine from the perspective of microbial biogeography.
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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".