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Record W2939868938 · doi:10.1139/cjb-2018-0207

Factors controlling seed dormancy and germination response of <i>Brachypodium hybridum</i> growing in the hot arid mountains of the Arabian Desert

2019· article· en· W2939868938 on OpenAlexvenueno aff
Masarra Elgabra, Ali El‐Keblawy, Kareem A. Mosa, Sameh S. M. Soliman

Bibliographic record

VenueBotany · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeed Germination and Physiology
Canadian institutionsnot available
FundersAlexandria UniversityUniversity of Sharjah
KeywordsGerminationDormancyBiologyphotoperiodismAridBotanyBrachypodiumHorticultureSeed dormancyEcology

Abstract

fetched live from OpenAlex

Seed dormancy and germination have been studied in the genetic model Brachypodium species complex in cooler, moist higher latitudes. Studying environmental factors in arid mountains affecting dormancy and germination in Brachypodium complex could determine the factors controlling these processes. This study assesses the impacts of temperature during seed maturation, seed after-ripening, drought, photoperiod, and thermoperiod on final germination and germination rate index of B. hybridum in the Arabian Desert. Seeds were germinated under dark or light conditions and under different ratios of red:far-red light, with three diurnal thermoperiods. The final germination percentage was significantly greater at 15/25 °C and 20/30 °C than at 25/35 °C and in light rather than in darkness. Seeds that reached maturity at 15/25 °C attained greater germination rates and faster germination than those that reached maturity at 20/30 °C. One-year after-ripening enhanced the final germination percentage and reduced photoperiod requirements. Light quality did not affect final germination percentage. The seeds tolerated drought of up to –0.8 MPa polyethylene glycol. The tolerance of B. hybridum seeds produced at higher thermoperiods to moderate levels of osmotic stress and their higher dormancy indicate that this species has the potential to survive the projected global warming in its native and introduced ranges.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.901
Threshold uncertainty score0.087

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.227
Teacher spread0.209 · 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

Citations9
Published2019
Admission routes1
Has abstractyes

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