Occurrence and molecular identification of an invasive rice strain of fall armyworm Spodoptera frugiperda (Lepidoptera: Noctuidae) from Sindh, Pakistan, using mitochondrial cytochrome c oxidase I gene sequences
Bibliographic record
Abstract
Abstract The fall armyworm (FAW), an invasive pest of maize, is an emerging threat in Southern Asia after America and Europe. Recently, this notorious pest has also been found in different areas of Pakistan. To assess its presence in Pakistan, a survey was carried out in the provinces of Punjab, Sindh, and Khyber Pakhtunkhwa during May–October 2019. We observed the highest incidence of FAW in Sindh with maximum impact in districts Tando-Allahyar and Hyderabad. These samples were identified as Spodoptera frugiperda on the morphological and taxonomical bases. However, morphological identification of this pest is very difficult at early larval instars. Here, we use the mitochondrial cytochrome c oxidase I (COI) gene region for the precise identification of larva of this invasive pest at species level. Two different regions of COI gene (COI-5′ and COI-3′) were used as molecular markers for the identification of this species. DNA sequence similarity searches of the obtained COI gene sequences (NCBI GenBank Accession Nos. MW241537, MW241538, MW349515, MW349516, MW349493 and MW349494) revealed that genetically it is more than 99% identical to S. frugiperda . The phylogenetic analysis indicated it as the rice-strain (R-strain). Both 3′- and 5′-fragment tree topologies showed that the collected samples of the FAW species belong to the R-strain. To the best of our knowledge, this is the first report providing molecular evidence for the existence of R-strain of S. frugiperda that was found feeding on maize crop in Sindh, Pakistan, using COI gene sequences as a marker.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 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".