Development of a DNA Macroarray for Detection and Monitoring of Economically Important Apple Diseases
Bibliographic record
Abstract
Short DNA gene sequences (oligonucleotides) from the ribosomal spacer regions of bacterial and fungal pathogens were used to identify and monitor economically important apple diseases. The oligonucleotides or probes were attached to a nylon membrane by an amine modified linker arm and arranged in a precise pattern to form an array for detecting five pathogens corresponding to five apple diseases. Initially the specificity of the probes was determined by hybridizing pure cultures of the pathogens to the probes. The DNA array correctly identified Botrytis cinerea, Penicillium expansum, Podosphaera leucotricha, Venturia inaequalis, and Erwinia amylovora and eliminated closely related species. When the array was used to monitor V. inaequalis ascospores collected from spore traps located in orchards, it confirmed the presence of ascospores as predicted by the disease forecasting model. Preliminary tests to quantify P. leucotricha populations using grayscale values was effective to 20 conidia per leaf disk. The DNA array is a promising new detection system for accurate identification of several pathogens in a single test with the potential for being a new tool for epidemiological studies.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".