Introgression from local cultivars is a driver of agricultural adaptation in Argentinian weedy rice
Bibliographic record
Abstract
Abstract Weedy rice, a pervasive and troublesome weed found across the globe, has often evolved through fertilization of rice cultivars with little importance of crop‐weed gene flow. In Argentina, weedy rice has been reported as an important constraint since the early 1970s, and, in the last few years, strains with herbicide‐resistance are suspected to evolve. Despite their importance, the origin and genetic composition of Argentinian weedy rice as well its adaptation to agricultural environments has not been explored so far. To study this, we conducted genotyping‐by‐sequencing on samples of Argentinian weedy and cultivated rice and compared them with published data from weedy, cultivated and wild rice accessions distributed worldwide. In addition, we conducted a phenotypic characterization for weedy‐related traits, a herbicide resistance screening and genotyped accessions for known mutations in the acetolactate synthase ( ALS ) gene, which confers herbicide resistance. Our results revealed large phenotypic variability in Argentinian weedy rice. Most strains were resistant to ALS‐inhibiting herbicides with a high frequency of the ALS mutation (A 122 T) present in Argentinian rice cultivars. Argentinian cultivars belonged to the three major genetic groups of rice: japonica , indica and aus while weeds were mostly aus or aus‐indica admixed, resembling weedy rice strains from the Southern Cone region. Phylogenetic analysis supports a single origin for aus‐like South American weeds, likely as seed contaminants from the United States, and then admixture with local indica cultivars. Our findings demonstrate that crop to weed introgression can facilitate rapid adaptation to agriculture environments.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".