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Record W2503518375 · doi:10.1139/cjb-2016-0130

Germination associated ROS production and glutathione redox capacity in two recalcitrant-seeded species differing in seed longevity

2016· article· en· W2503518375 on OpenAlexvenueno aff
Anushka Moothoo-Padayachie, Boby Varghese, N.W. Pammenter, Patrick Govender

Bibliographic record

VenueBotany · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeed Germination and Physiology
Canadian institutionsnot available
FundersInyuvesi Yakwazulu-NataliNational Research Foundation
KeywordsGerminationReactive oxygen speciesRecalcitrant seedBiologyLongevityGlutathioneBotanyAntioxidantHorticultureBiochemistryEnzyme

Abstract

fetched live from OpenAlex

This study investigated the relationship between germination rate and storage lifespan in two recalcitrant-seeded species, Avicennia marina (Forssk.) Vierh. and Trichilia dregeana Sond., in relation to water uptake and oxidative metabolism. Seeds of A. marina had a higher germination rate and shorter hydrated storage lifespan than T. dregeana. Rapid germination of A. marina seeds was associated with high water uptake rates and an early increase in reactive oxygen species (ROS) production and decline in GSH:GSSG ratio. Slower germination in T. dregeana seeds was associated with lower water uptake rates, delayed onset of the ROS-based trigger for germination, and high GSH:GSSG ratio. Positive correlations (p < 0.05) between ROS production and percent water uptake, and inhibition of germination by ROS scavenging agents confirmed the requirement for heightened ROS levels for germination in both species. Germination rate in recalcitrant seeds appears to be governed by the rate of water uptake and ROS production; the latter being dependent on antioxidant activity. We propose that poor longevity in recalcitrant seeds, such as those of A. marina, is based on high rates of water uptake and low levels of ROS scavenging activity that promote the ROS-based trigger for germination during hydrated storage.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.937
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.036
GPT teacher head0.242
Teacher spread0.206 · 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 designObservational
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

Citations29
Published2016
Admission routes1
Has abstractyes

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