Genetic diversity and association analysis of leafminer (<i>Liriomyza langei</i>) resistance in spinach (<i>Spinacia oleracea</i>)
Bibliographic record
Abstract
Leafminer (Liriomyza langei) is a major insect pest of many important agricultural crops, including spinach (Spinacia oleracea). Use of genetic resistance is an efficient, economic, and environment-friendly method to control this pest. The objective of this research was to conduct association analysis and identify single nucleotide polymorphism (SNP) markers associated with leafminer resistance in spinach germplasm. A total of 300 USDA spinach germplasm accessions were used for the association analysis of leafminer resistance. Genotyping by sequencing (GBS) was used for genotyping and 783 SNPs from GBS were used for association analysis. The leafminer resistance showed a near normal distribution with a wide range from 1.1 to 11.7 stings per square centimeter leaf area, suggesting that the leafminer resistance in spinach is a complex trait controlled by multiple genes with minor effect in this spinach panel. Association analysis indicated that five SNP markers, AYZV02040968_7171, AYZV02076752_412, AYZV02098618_4615, AYZV02147304_383, and AYZV02271373_398, were associated with the leafminer resistance with LOD 2.5 or higher. The SNP markers may be useful for breeders to select plants and lines for leafminer resistance in spinach breeding programs through marker-assisted selection.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.000 |
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".