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Record W2518929498 · doi:10.1614/ws-d-16-00058.1

Influence of Soil Moisture Stress on Vegetative Growth and Mycorrhizal Colonization in Hound’s-tongue (<i>Cynoglossum officinale</i>)

2016· article· en· W2518929498 on OpenAlexafffund
Mina Momayyezi, Mahesh K. Upadhyaya

Bibliographic record

VenueWeed Science · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyWeedPetiole (insect anatomy)Dry weightAgronomyShootWater contentMoisture stressHorticultureSeedlingBiomass (ecology)Botany

Abstract

fetched live from OpenAlex

Hound’s-tongue is an invasive, biennial weed that thrives in dry rangelands of British Columbia. Rosette formation in the first year of growth and a deep root system offer this weed a competitive advantage against associated grasses under dry conditions. To study effects of water stress on seedling growth and mycorrhizal colonization in hound’s-tongue, seedlings of this weed were grown in pots in a greenhouse and subjected to four (100, 80, 60, and 40% of field capacity) soil moisture treatments. Effects of soil moisture stress (SMS) on several growth parameters as well as mycorrhizal colonization of roots were studied. The total biomass, shoot and root fresh and dry weights, leaf number, petiole length, leaf area, and specific leaf weight (leaf dry weight per unit leaf area) decreased with increasing SMS; shoot and root water content was not affected. Because of a greater effect of SMS on root compared with the shoot biomass, shoot:root ratio increased as the moisture stress increased. Water stress decreased mycorrhizal colonization and arbuscule and vesicle abundance. A reduction in total biomass, leaf number and leaf area per plant, petiole length, and mycorrhizal colonization may reduce the competitive advantage of hound’s-tongue over its neighbors under drought conditions. The effect on plant size may also influence herbivory, by biocontrol agents and other herbivores, and fecundity of this weed.

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)0.001
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 score0.740
Threshold uncertainty score0.715

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.006
GPT teacher head0.205
Teacher spread0.199 · 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

Citations6
Published2016
Admission routes2
Has abstractyes

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