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Record W4402565180 · doi:10.1139/cjb-2024-0070

Germination responses of carob (<i>Ceratonia siliqua</i> L.) seeds to salinity and water stresses: implications for the restoration of Mediterranean marginal lands

2024· article· en· W4402565180 on OpenAlexvenueno aff
Mohammed Dadach, Arvind Bhatt, Sanjay Gairola, Attiat Elnaggar, Ali El‐Keblawy

Bibliographic record

VenueBotany · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPolysaccharides Composition and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsCeratonia siliquaGerminationSalinityBiologyMediterranean climateSeedlingHorticultureBotanyOsmotic pressureAridAbiotic componentEcology

Abstract

fetched live from OpenAlex

The iconic Mediterranean tree, Ceratonia siliqua L., holds substantial potential for restoring arid and semi-arid marginal lands. However, there is limited knowledge about the interaction of various abiotic factors and environmental stressors on seed germination of C. siliqua. Therefore, we examined the influence of salinity levels (0, 75, 150, 225 mmol/L) and water stress using (polyethylene glycol (PEG) 6000 ) (−0.4, −0.8, −1.2 MPa) on C. siliqua seed germination under varying thermoperiods (15/25 and 25/35 °C) and photoperiods (12 h of light and complete darkness). Our findings indicate that higher temperatures (25/35 °C) significantly reduced germination of seeds compared to lower temperatures (15/25 °C). However, the photoperiods showed no significant impact, especially under minimal salinity stress and low osmotic potentials (75 mmol/L NaCl and −0.4 MPa PEG). In general, C. siliqua seeds exhibited enhanced performance in darkness at higher osmotic potentials, while increased stress prolonged the germination period. The dry weight of seedlings decreased with higher osmotic potential, although 75 mmol/L NaCl promoted seedling biomass production. Our results confirm C. siliqua resilience to high salinity and moderate drought, offering practical applications for its successful reintroduction and cultivation in challenging Mediterranean environmental conditions.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.685
Threshold uncertainty score0.105

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 head0.035
GPT teacher head0.291
Teacher spread0.257 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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