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Record W2166633101 · doi:10.4141/p01-016

Stand establishment in processing carrots – Effects of various temperature regimes on germination and the role of salicylates in promoting germination at low temperatures

2002· article· en· W2166633101 on OpenAlexvenueno aff
Lada R. Rajasekaran, Claude Azure Stiles, Doug L. Caldwell

Bibliographic record

VenueCanadian Journal of Plant Science · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeed Germination and Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsGerminationSalicylic acidHorticultureChemistryBiologyAgronomyBiochemistry

Abstract

fetched live from OpenAlex

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 (GT 50 ) 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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.749
Threshold uncertainty score0.202

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.192
Teacher spread0.187 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations51
Published2002
Admission routes1
Has abstractyes

Explore more

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