Characterization of Trichoderma isolates from southern Italy, and their potential biocontrol activity against grapevine trunk disease fungi
Bibliographic record
Abstract
Grapevine trunk diseases (GTDs) are one of the most economically important diseases of grapevines, causing yield reductions and limiting vineyard lifespans. Fungal pathogens responsible for GTDs primarily infect grapevines through pruning wounds. The lack of systemic fungicides to stop the advance of fungi in vine vascular systems makes the use of pruning wound protection with either synthetic chemicals or biological control agents (BCAs) the main available GTD control strategy. Demands for sustainable grape production and increasing limitations on pesticide usage have raised interest in potential use of BCAs as pruning wound protectants against GTDs. The objectives of this study were to characterize 16 Trichoderma isolates from southern Italy using molecular methods, and to evaluate their potential activity as BCAs in vitro against the GTD canker-causing fungi Diplodia seriata, Eutypa lata and Neofusicoccum parvum. Molecular studies along with phylogenetic analyses identified eight species, including Trichoderma atroviride, T. guizhouense, T. harzianum, T. koningiopsis, T. longibrachiatum, T. paratroviride, T. paraviridescens, T. spirale, and one unidentified Trichoderma sp. All these species had optimum mycelium growth between 25 and 35°C. In vitro dual culture experiments assessed antagonistic capabilities of all the Trichoderma isolates against D. seriata, E. lata and N. parvum, and showed that the isolates inhibited mycelial growth of the pathogens by up to 70%. The most inhibitory isolates were tested in planta for capability to protect pruning wounds against D. seriata and N. parvum in a detached cane assay. All the selected Trichoderma isolates gave >80% control of D. seriata and 60% control of N. parvum, and protected pruning wounds for up to 21 d after treatment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".