Performance and Establishment of a Commercial Mycorrhizal Inoculant in Viticulture
Bibliographic record
Abstract
(1) Background: Arbuscular mycorrhizal (AM) fungi are symbiotic organisms that help plants acquire nutrients from the soil in exchange for photosynthetic carbon. Commercial AM fungal inoculants are widely available and are used extensively in agriculture including wine grape production. However, positive growth responses from inoculants are more consistent in the greenhouse compared to the field. (2) Methods: We grew three grapevine rootstocks with and without an AM fungal inoculant in the greenhouse for one year, then they were transplanted to the field for two years. To quantify the establishment of the inoculant, we analyzed root samples with a digital PCR assay. (3) Results: We show that AM fungal inoculation increased biomass production only in the greenhouse. After two growing seasons in the field, the commercial inoculant colonized roots but did not increase biomass production compared to uninoculated rootstocks. (4) Conclusions: This study highlights that AM fungal inoculants do not always promote growth of grapevines in the field. Future research should focus on inoculant strains designed for viticulture applications and take rootstock into consideration to maximize their efficacy.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".