Rapid Detection of Pine Pathogens Lecanosticta acicola, Dothistroma pini and D. septosporum on Needles by Probe-Based LAMP Assays
Bibliographic record
Abstract
Needle blights are serious needle fungal diseases affecting pines both in natural and productive forests. Among needle blight agents, the ascomycetes Lecanosticta acicola, Dothistroma pini and D. septosporum are of particular concern. These pathogens need specific, fast and accurate diagnostics since they are regulated species in many countries and may require differential management measures. Due to the similarities in fungal morphology and the symptoms they elicit, these species are hard to distinguish using morphological characteristics. The symptoms can also be confused with those caused by insects or abiotic agents. DNA-based detection is therefore recommended. However, the specific PCR assays that have been produced to date for the differential diagnosis of these pathogens can be applied only in a well-furnished laboratory and the procedure takes a relatively long execution time. Surveillance and forest protection would benefit from a faster diagnostic method, such as a loop-mediated isothermal amplification (LAMP) assay, which requires less sophisticated equipment and can also be deployed directly on-site using portable devices. LAMP assays for the rapid and early detection of L. acicola, D. pini and D. septosporum were developed in this work. Species-specific LAMP primers and fluorescent assimilating probes were designed for each assay, targeting the beta tubulin (β-tub2) gene for the two Dothistroma species and the elongation factor (EF-1α) region for L. acicola. Each reaction detected its respective pathogen rapidly and with high specificity and sensitivity in DNA extracts from both pure fungal cultures and directly from infected pine needles. These qualities and the compatibility with inexpensive portable instrumentation position these LAMP assays as an effective method for routine phytosanitary control of plant material in real time, and they could profitably assist the management of L. acicola, D. pini and D. septosporum.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| 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".