Analysis of the Allelic Structure of Photoperiodism Genes E1–E4 in Soybean Collections and Its Impact on the Timing and Duration of Flowering under the Growing Conditions of the Omsk Oblast
Bibliographic record
Abstract
Abstract Soybean is a strategically important agricultural crop that serves as a source of vegetable fat and protein. The processed products derived from soybean are utilized in the food, livestock, and various other industries. To expand soybean production in Russia, it is essential to develop varieties that are adapted to the agroclimatic conditions of northern latitudes, including Western Siberia, which is characterized by a relatively short growing season and long daylight period. To effectively develop adaptive early-flowering and early-maturing soybean varieties, it is essential to evaluate the impact of the E1, E2, E3, and E4 genes on the photoperiodic response of soybean and their influence on plant development timing under local conditions. A total of 102 accessions from the Omsk Agricultural Scientific Center’s collection were analyzed, including original varieties from the center, varieties from other domestic breeding centers, and foreign varieties and breeding accessions from Poland, Sweden, Belarus, Ukraine, Canada, and other countries. Data on flowering dates were collected from a field experiment conducted in the Omsk oblast between 2021 and 2023. Genotyping was performed using both classical PCR-based markers and next-generation markers based on competitive allele-specific PCR. The analysis revealed that the recessive alleles of the E loci, which produce a photoperiodically neutral phenotype (e1-as, e1-fs, e2-ns, e3-tr, e3-fs, e4-kes, e4-kes+e4-SORE-1), are predominant in the collection. Furthermore, it was determined that the E2 and E4 loci exert the most significant influence on the full flowering date, while the E3 locus has the greatest effect on the end date of flowering and the overall duration of flowering. The findings can be utilized in marker-assisted selection to develop early-flowering varieties of the Siberian ecotype.
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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 | 0.000 | 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".