Development of a Loop-Mediated Isothermal Amplification (LAMP) Method to Detect the Potato Zebra Chip Pathogen ‘<i>Candidatus</i> Liberibacter solanacearum’ (Lso) and Differentiate Haplotypes A and B
Bibliographic record
Abstract
), which can significantly reduce potato yield. In this study, a loop-mediated isothermal amplification (LAMP) method for the detection of Lso haplotypes A and B was developed and evaluated. Two sets of LAMP primers named LAMP-A and LAMP-B were designed and tested for specificity and sensitivity. Both LAMP-A and LAMP-B were specific to Lso in in silico analysis using the Primer-Blast tool. The LAMP-A and LAMP-B could only produce positive signals from DNA mixtures of Lso-infected tomato but not from the genomic DNA of 37 nontarget plant pathogens. The sensitivity of LAMP-A and LAMP-B on Lso haplotypes A and B were tested on gBlocks and genomic DNA from Lso-infected tomato. On the genomic DNA for LAMP-A, the lowest amount of template DNA for a positive LAMP reaction was 2 to 20 ng on four haplotype A strains and 20 to 80 ng on four haplotype B strains; for LAMP-B, the lowest amount of template DNA for a positive LAMP reaction was 0.02 to 2 ng on four haplotype B strains and 20 ng to no amplification on four haplotype A strains. On gBlocks for LAMP-A, the lowest number of copies for a positive LAMP reaction was 60 on haplotype A and 600 on haplotype B; for LAMP-B, the lowest number of copies for a positive LAMP reaction was 60 on haplotype B and 600 on haplotype A. Therefore, considering the convenience of the LAMP technique, as well as the high specificity and sensitivity, the LAMP-A and LAMP-B primers can be used together to test the probable Lso-infected plant or psyllid samples to rapidly, accurately, and directly differentiate haplotypes A and B. We highly recommend this LAMP system to plant pathology practitioners and diagnostic labs for routine detection of Lso and confirmation of zebra chip disease on potato or tomato.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".