Physiological and Biochemical Characterization of Quinclorac Resistance in a False Cleavers (<i>Galium spurium </i>L.) Biotype
Bibliographic record
Abstract
The physiological and biochemical basis for quinclorac resistance in a false cleavers (Galium spurium L.) biotype was investigated. There was no difference between herbicide resistant (R) and susceptible (S) false cleavers biotypes in response to 2,4-D, clopyralid, glyphosate, glufosinate-ammonium, or bentazon. On the basis of GR(50) (growth reduction of 50%) or LD(50) (lethal dose to 50% of tested plants) values, the R biotype was highly resistant to the acetolactate synthase (ALS) inhibitor, thifensulfuron-methyl (GR(50) resistance ratio R/S = 57), and quinolinecarboxylic acids (quinclorac R/S = 46), resistant to MCPA (R/S = 12), and moderately resistant to the auxinic herbicides picloram (R/S = 3), dicamba (R/S = 3), fluroxypyr (R/S = 3), and triclopyr (R/S = 2). The mechanism of quinclorac resistance was not due to differences in [(14)C]quinclorac absorption, translocation, root exudation, or metabolism. Seventy-two hours after root application of quinclorac, ethylene increased ca. 3-fold in S but not R plants when compared to controls, while ABA increased ca. 14-fold in S as opposed to ca. 3-fold in R plants suggesting an alteration in the auxin signal transduction pathway, or altered target site causes resistance in false cleavers. The R false cleavers biotype may be an excellent model system to further examine the auxin signal transduction pathway and the mechanism of quinclorac and auxinic herbicide action.
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 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 | 0.000 | 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 | 0.001 |
| 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".