Stand establishment in processing carrots – Effects of various temperature regimes on germination and the role of salicylates in promoting germination at low temperatures
Bibliographic record
Abstract
The effects of various temperature regimes on carrot seed germination and the possibility of hastening germination at a low temperature using salicylates were studied. Seeds were incubated at various temperatures viz., 25, 20, 15, 10, 5 and 2°C. Salicylates such as, 2,6-dihydoxybenzoic acid (DHBA), acetylsalicylic acid (ASA), salicylic acid (SA) were supplied at 0, 1, 10, 100 and 1000 mg L-1 continually to the seeds incubated at 25 and 5°C until germination. Data on germination percentage were collected, and vigor value was calculated. Incubating seeds at various low temperature regimes significantly and proportionately reduced germination percentage and vigor value. The highest cumulative germination and vigor value was observed at 25°C. Critical threshold temperature for germination (GT50) was 5°C. Seed treatment using salicylates hastened germination at 5°C. 2,6-dihydoxybenzoic acid 1, ASA 100 and SA 1 mg L-1 all were effective in hastening germination at 5°C. Among all the salicylates, ASA 100 mg L-1 was the most effective in advancing germination at 5°C. Salicylates at the highest concentration of 1000 mg L-1 inhibited germination significantly both at 25 and 5°C. Key words: Acetylsalicylic acid, carrot, 2,6-dihydoxybenzoic acid, germination percentage, rate of germination, salicylates, SA, temperature, thermogenesis, vigor value
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.002 | 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".