(71) Comparison of Phytophthora Disease Incidence in Composted Pine Bark Mixes to Chemical and Biological Controls
Bibliographic record
Abstract
Phytophthora diseases are economically important, requiring the use of chemical fungicides and, more recently, biological controls. Recent research suggests that composted bark products may lessen the impact of the disease, even in the absence of these chemicals. An experiment was conducted to compare chemical and biological fungicides to untreated pine bark compost. Impatiens wallerana plugs were transplanted from 288 trays into 1801 trays. All plants were planted into Berger BM-7, 35% composted bark mix (Berger Horticulture, Quebec, Canada). Media was prepared by premixing one of the five following fungicide treatments: 1) Control, 2) Banrot at 0.6 g/L, 3) Root Shield at 1.6 g/L, 4) Actino-Fe at 5.1 g/Ll, or 5) SoilGard at 1.6 g/L. Plants received no fertilizer. Three strains of Phytophthora were grown in 25 °C on clarified V8 media. Pathogenic inoculum was made by macerating the growth media and fungi in 100 ml H 2 O. Mixture was pulse-blended for 1 min, and an additional 200 mL dH 2 O was added. Inoculation was 5 ml per plant. Flats were kept on a misting bench, and misted twice daily for 15 min. The experiment was set up using a RBD repeated six times with three plants per rep. Plants were rated weekly for 5 weeks using a damage scale of 0 to 5, with 0 indicating no sign of disease and 5 being dead. Statistical analysis was conducted using a Chi-Square. Disease incidence between the biological, chemical, and composted bark treatments did not differ, with all treatments providing complete control. At least in this study, the use of composted pine bark media provided Phytophthora control equivalent to current chemical and biological fungicides.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".