A Characterization of a Cool-Climate Organic Vineyard’s Microbiome
Bibliographic record
Abstract
The microbiome, an influential factor affecting plant health and growth, is attracting increasing interest with respect to wine grape production. The purpose of this study was to characterize the microbiome (fungi and bacteria) of the soil, cover crop roots, and grape (Vitis spp.) roots across rootstock and depth in a cool-climate, organic vineyard. The cover crop consisted of a fescue (Festuca sp.) grass, while grape roots were sampled from New York Muscat, a cool-climate hybrid, across three root types (ungrafted, 3309C and Riparia Gloire) at three root depths (0 to 15, 15 to 30, and 30 to 50 cm). The grape root microbiome was more specialized, with fewer observed amplicon sequence variants for both bacteria (16S) and fungi (internal transcribe spacer) than found in the cover crop and the surrounding soil. Grape roots were dominated by bacterial genera Pseudomonas, Niastella, and Rhizobium; most prominent fungal genera were Plectosphaerella, Trichosporon, and Ilyonectria. Although no correlations were found between α-diversity metrics and soil parameters, Pseudaleuria relative abundance was correlated with Mn, Fe, and Na levels. Soil depth explained a small portion of bacterial but not fungal variance and taxonomic composition. Rootstock type explained a portion of both bacterial and fungal variance and taxonomic composition, substantiating the role of host plant genetics in the development of the grape root microbiome. This is the first characterization of the grape root microbiome in a cool-climate Canadian vineyard.
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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 | 0.001 | 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) | 0.001 | 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".