Allele Mining of Major Gall Midge Resistance Genes <em>gm3, Gm4,</em> Gm8 and Gm11 in Selected Sri Lankan Rice Germplasm
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Bibliographic record
Abstract
Breeding ri ce varieties carrying resistance to rice gall midge (RGM), Orseolia oryzae is a key strategy to reduce yield losses incurred as a result of RGM infestations, globally. Using associated DNA-markers, the study evaluated 55 Sri Lankan ric e accessions (23 traditional (TAs) and 32 newly improved rice varieties (NIVs)) based on their breeding potential t o identify rice accessions carrying resistance alleles at four major RGM resistance genes: gm3, Gm4, Gm8, and Gm11. The allele profiling revealed that none of the rice accessions carried resistance alleles for all four genes and five access ions carried only susceptible alleles at the target loci. Eleven accessions carried resistance alleles at gene combinations Gm4, Gm8 and Gm11 (7), gm3, Gm8 and Gm11 (3), and gm 3, Gm4 and Gm11 (1). Twenty-four accessions reported combinations of any two resistance alleles from the four target genes, and 15 rice accessions carried only one resistance allele for the three target genes gm3, Gm8 and Gm11. The resistance alleles of Gm11 (56%) and gm3 (49%) were the most common in the study panel, and the resistance allele of Gm 4 was the least prevalent (33%). Considering all four resistance genes, TAs carried the resistance alleles mostly com pared to the NIVs, except in the gene gm3. The RGM resistance allele profiling conducted herewith will facilitate taking informative decisions at parental and donor selection for crosses and gene pyramiding, in rice breeding programs. The study must be further expanded with a field evaluation of rice accessions for resistance to RGM and discovering novel resistance genes in the local germplasm to broaden the understanding of RGM resistance in rice.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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 it