Development of Screening Assays for Pathogen Virulence and Resistance to Phytophthora Root Rot and Wilting Complex in Raspberry
Bibliographic record
Abstract
Phytophthora root rot and wilting complex (PRRW) of red raspberry, caused primarily by Phytophthora rubi, is an economically important disease in British Columbia (BC) and in raspberry producing regions globally. Reliable, rapid, and efficient screening methods are lacking for evaluating germplasm for potential disease resistance in raspberry breeding programs as well as for screening pathogen isolates for virulence. The objective of this study was to compare various screening methods for efficiency and rapidity in inducing symptoms of disease to identify the most suitable approach. We compared several intact plant root inoculation (IPRI) assays, detached stem assays, and an intact plant stem inoculation (IPSI) assay. A virulent isolate of P. rubi was inoculated in two commercial cultivars: ‘Chemainus’ (susceptible to PRRW) and ‘Cascade Bounty’ (moderately resistant to PRRW). For IPRI assays, days to first symptom development, plant wilt progression, and root assessment were recorded. For detached stem tissue and IPSI assays, days to first visible lesions and lesion size were assessed. Experiments were arranged in a completely randomized design with three replications in each experiment. Three IPRI assays produced reliable symptoms in both cultivars. Among the detached stem assays, a node inoculation method performed better than other methods. Detached stem assays are useful for rapid pathogenicity testing of P. rubi, whereas IPRI assays are better for screening germplasm for disease resistance. Overall, this study identified several assays that can be used for conducting studies on pathogen phenotypic diversity (pathogenicity and virulence tests) and screening raspberry cultivars, germplasm, and breeding materials for response to PRRW.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".