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Record W2529835607 · doi:10.1139/cjb-2016-0098

Ecotype-correlated variations in germination and seedling growth of <i>Zataria multiflora</i>

2016· article· en· W2529835607 on OpenAlexvenueno aff
Hossein Sadeghi, Zahra Robati

Bibliographic record

VenueBotany · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeed Germination and Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsEcotypeGerminationSeedlingBiologyAltitude (triangle)HorticultureThreatened speciesBotanyAgronomyEcology

Abstract

fetched live from OpenAlex

Zataria multiflora Boiss. is a rare aromatic species endemic to the southern and southwestern regions of Iran. It is a species that is not under cultivation anywhere else in the world and is only gathered from the wild by amateur collectors. Its cultivation and domestication is very limited. Hence, we investigated the seed germination behaviour and seedling growth of different ecotypes of Z. multiflora collected from 6 sites in Iran (Jam, Ab-garm, Layzangan, Dashte-khak, Kooh-namak, and Chehel-cheshmeh) in late spring. The experiment was carried out at College of Agriculture, Shiraz University, Shiraz, Iran, in 2012. The statistical differences among the ecotypes were determined through variance analysis (ANOVA). The results of the pot experiment showed that ecotype had a significant difference for the total germination percentage, number of leaves per plant, plant height, fresh mass, dry mass, relative water content, and antioxidant enzyme activity. Differences in growth performance were also noted in relation to the altitude of the six test populations: ecotypes at a higher altitude exhibited lower germination rates and plant height. This study is significant for land managers and conservation agencies with an interest in optimizing the germination of arid-zone seeds for rehabilitation of this threatened species.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.217
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2016
Admission routes1
Has abstractyes

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