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Effect of peat on mycorrhizal colonization and effectiveness of the arbuscular mycorrhizal fungus<i>Gigaspora margarita</i>

2007· article· en· W2105450896 on OpenAlexaboutno aff
Ning Ma, Kazuhira Yokoyama, Takuya Marumoto

Bibliographic record

VenueSoil Science & Plant Nutrition · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsPeatColonizationSporeBiologyMycorrhizaInoculationArbuscular mycorrhizalBotanyAgronomySymbiosisHorticultureEcologyBacteria

Abstract

fetched live from OpenAlex

Abstract The influence of the addition of Chinese peat and Canadian peat on arbuscular mycorrhizal colonization, mycorrhizal effectiveness and host-plant growth was investigated in a pot experiment. Chinese peat or Canadian peat was mixed with Masa soil (weathered granite soil) at different levels (0, 25, 50, 100, 150 or 200 g kg−1) into which an arbuscular mycorrhizal fungus (AMF) Gigaspora margarita Becker & Hall was inoculated, and seedlings of Miscanthus sinensis Anderess were planted. There was a significant increase in plant growth with increasing amounts of Chinese peat. The growth-promoting effect of the AMF on the host was enhanced when the addition of Chinese peat was increased from 25 to 100 g kg−1. Root colonization and the number of spores proliferating increased with increases at low levels of Chinese peat (from 25 to 100 g kg−1), and decreased gradually with higher Chinese peat increments. Although plant growth and root colonization with the addition of Canadian peat increased slightly, Canadian peat suppressed mycorrhizal effectiveness. In contrast to Canadian peat, the addition of Chinese peat improved considerably the physical and chemical properties of the soil, which might result in the promotion of AM formation and mycorrhizal effectiveness.

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)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.263

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.004
GPT teacher head0.202
Teacher spread0.198 · 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

Citations24
Published2007
Admission routes1
Has abstractyes

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