Efficient and Direct Identification of Ditylenchus destructor and D. dipsaci in Soil and Plant Tissues Using a Species-Specific PCR Assay
Bibliographic record
Abstract
Ditylenchus destructor and D. dipsaci are important nematodes that have a significant economic impact on agronomic and horticultural plants worldwide. Microscopic observation alone may not distinguish between D. destructor and D. dipsaci. Accurate and rapid identification of these two species is essential for effective pest management. In the present study, a species-specific PCR assay was developed to detect and differentiate D. destructor and D. dipsaci based on the rDNA-ITS sequences. The primers developed in this study can specifically amplify fragments of DNA from D. destructor and D. dipsaci in the target population, without amplifying DNA from other non-target nematodes within the genus Ditylenchus. The sensitivity test revealed that this procedure has the ability to detect single second-stage juveniles (J2) of D. dipsaci at a dilution of 1/128 and D. destructor at a dilution of 1/64. Additionally, it can detect genomic DNA (gDNA) at concentrations of 10 pg/µL for D. dipsaci and 1 ng/µL for D. destructor. These results align with previously reported results obtained through RPA and LAMP methods. Furthermore, the primers developed in this study for D. destructor not only were able to amplify six different haplotypes of nematodes but also successfully detected it in infested plant roots and soil samples, thereby shortening the time and reducing the number of steps required for detection. Thus, this assay, which does not necessitate taxonomic or morphological expertise, significantly enhances the diagnosis of D. destructor and D. dipsaci in infested fields. This advancement aids in the early control of these nematodes.
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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 | 0.001 |
| 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 | 0.000 | 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".