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Record W1978013867 · doi:10.4141/p00-083

Effect of <i>Penicillium bilaii</i> inoculation and phosphorus fertilisation on root and shoot parameters of field-grown pea

2001· article· en· W1978013867 on OpenAlexvenueaboutno aff
J. Kevin Vessey, Krista G Heisinger

Bibliographic record

VenueCanadian Journal of Plant Science · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLegume Nitrogen Fixing Symbiosis
Canadian institutionsnot available
Fundersnot available
KeywordsSativumShootPisumBiologyInoculationMicrobial inoculantField peaPhosphorusAgronomyDry matterHorticultureDry weightCropChemistry

Abstract

fetched live from OpenAlex

The mechanisms underlying the stimulating effect of Penicillium bilaii inoculation on the growth of crop plants are not clear. The effect of P. bilaii inoculation on root morphology [dry weight (DW), length and specific root length) and other root and shoot parameters of pea were investigated at two field sites in western Canada in 1996. Pea (Pisum sativum L.) was grown at three levels of P fertilization (0, 6.4 and 19.3 kg ha –1 ) at Ellerslie, AB, and Outlook, SK. Shoot dry matter, P concentrations, P content and nodulation were also measured in pea plants harvested at the seven- to nine-node stage. Soil cores were used to sample roots. Although plants were responsive to P fertiliser at both sites, P. bilaii inoculation affected pea growth at the Ellerslie site only. At this site, P. bilaii inoculation increased root length by 48%, specific root length (m g –1 root DW) by 21%, root DW by 13%, and shoot P concentration by 13% in treatments that received no P fertiliser. We suggest that the stimulating effect of P. bilaii inoculation on crop P nutrition is partly explained by increases in root absorptive capacity in the presence of the fungus. However, this effect was only significant under P-limited conditions. Key words: Microbial inoculants, Pisum sativum, Penicillium bilaii, phosphorus, root length, root morphology

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.804

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 head0.010
GPT teacher head0.199
Teacher spread0.189 · 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

Citations61
Published2001
Admission routes2
Has abstractyes

Explore more

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