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Record W2066122220 · doi:10.1139/g99-119

Biodiversity of Asian rice gall midge (<i>Orseolia oryzae </i>Wood Mason) from five countries examined by AFLP analysis

2000· article· en· W2066122220 on OpenAlexvenueno aff
S. K. Katiyar, Girish Chandel, Yen Y. Tan, Y Zhang, Biao Huang, L. Nugaliyadde, Kumudu Fernando, J. S. Bentur, S. Inthavong, S. V. Constantino, J. Bennett

Bibliographic record

VenueGenome · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect Resistance and Genetics
Canadian institutionsnot available
Fundersnot available
KeywordsAmplified fragment length polymorphismBiologyUPGMAMidgeGallDNA profilingPopulationGenetic diversityRAPDVeterinary medicineBotanyGenetic variationGeneticsDNAGene

Abstract

fetched live from OpenAlex

Amplified fragment length polymorphism (AFLP) analysis was used to assess the biodiversity of one of the most important dipteran pests of cereals, the Asian rice gall midge (Orseolia oryzae Wood Mason). Larvae and pupae were collected at 15 locations in five Asian countries and preserved in 95% ethanol for storage, shipment, and DNA extraction using cetyltrimethylammonium bromide (CTAB). Although only approximately 1 microg of DNA was extracted from a single pupa or larva, the use of several AFLP primers in various combinations meant that this amount of DNA was sufficient to allow many DNA fingerprints to be made per individual. Fingerprints were sufficiently reproducible, especially during selective amplification, to allow the genetic diversity within a field population to be characterized. Extraction of DNA from a pool of 20 insects yielded AFLP fingerprints in which variation among individuals was sacrificed in favor of detecting differences among populations. For each location, pooled DNA was amplified with three primer pairs. A total of 261 distinct AFLP bands were identified for the 45 fingerprints. Cluster analysis, performed by the unweighted pair-group method (UPGMA), separated the populations into two distinct groups. Group I included two populations from Guangdong province of southern China and one each from Laos and Imphal in northeastern India, while group II was comprised of eleven populations from elsewhere in India (Assam, Orissa, Madhya Pradesh, Andhra Pradesh, and Kerala) and from Nepal and Sri Lanka. AFLP analysis provided insight into the origins of gall midge biotypes. In 1992, the prevailing biotype in Imphal changed from Indian biotype 3 to a new biotype 3M. Our data show that biotype 3M belongs to group I and did not arise by a recent mutation from biotype 3, which belongs to group II. By contrast, Indian biotypes 2 and 4 are likely to have diverged through recent mutation and selection, as are Chinese biotypes 1 and 4. The almost simultaneous emergence of new biotypes in Kerala and Sri Lanka during 1985-1988 was most probably coincidental, because these biotypes are not closely related. AFLP fingerprints were also able to detect sexual dimorphism in the DNA of adult gall midges and to distinguish gall midge from its major parasite Platygaster oryzae.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.687
Threshold uncertainty score0.894

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.003
GPT teacher head0.185
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations31
Published2000
Admission routes1
Has abstractyes

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