Factors influencing colonization of cucumber roots by <i>Clonostachys</i> <i>rosea</i> f. <i>catenulata</i> , a biological disease control agent
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The biocontrol fungus Clonostachys rosea f. catenulata (Gliocladium catenulatum) strain J1446, commercially available as Prestop® (Verdera Oy, Finland), is an effective antagonist against several root and foliar greenhouse pathogens. The biocontrol agent forms dense networks of hyphae on plant roots, grows internally in root epidermal cells, and produces hydrolytic enzymes, all of which lead to a reduction in pathogen propagules. An understanding of the environmental and host factors that influence root colonization by C. rosea f. catenulata is important to maximize disease control efficacy. Cucumber roots grown in nutrient solution in containers were inoculated with conidia of a GUS-transformed strain of C. rosea f. catenulata. Population levels associated with roots over time were assessed by colony-plate counts, GUS staining and enzymatic assays to determine GUS activity. Variables such as pH, temperature and growing medium were major factors that influenced population levels, while cucumber cultivar, addition of nutrients, and wounding of roots did not appear to significantly affect colonization. Population density of C. rosea f. catenulata on roots was highest when the nutrient solution was maintained at pH 5, 6, or 7, and at temperatures of 18–22°C. Lowest colonization levels were observed on roots of plants grown in potting mix or in field soil. Measurement of GUS activity provided a slightly more accurate assessment of root colonization levels compared to colony-plate counts. These results illustrate the optimal environmental conditions which can ensure maximum root colonization by C. rosea f. catenulata and enhance disease control by the biocontrol agent.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it