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Record W2557307483 · doi:10.1139/cjm-2016-0369

The effects of <i>Pantoea</i> sp. strain Y4-4 on alfalfa in the remediation of heavy-metal-contaminated soil, and auxiliary impacts of plant residues on the remediation of saline–alkali soils

2016· article· en· W2557307483 on OpenAlexvenueno aff
Shuhuan Li, Jie Wang, Nanxiong Gao, Lizhu Liu, Yahua Chen

Bibliographic record

VenueCanadian Journal of Microbiology · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant-Microbe Interactions and Immunity
Canadian institutionsnot available
FundersPriority Academic Program Development of Jiangsu Higher Education InstitutionsGovernment of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsEnvironmental remediationShootRhizosphereDry weightAgronomyChemistryPhytoremediationHorticultureInoculationSoil contaminationStrain (injury)PantoeaContaminationBiologyEnvironmental chemistryBacteria16S ribosomal RNAHeavy metals

Abstract

fetched live from OpenAlex

The plant-growth-promoting rhizobacterium (PGPR) Y4-4 was isolated from plant rhizosphere soil and identified as Pantoea sp. by 16S rRNA sequence analysis. The effects of strain Y4-4 on alfalfa grown in heavy-metals-contaminated soil was investigated using a pot experiment. In a Cu-rich environment, the shoot dry mass and total dry mass of plants inoculated with strain Y4-4 increased by 22.6% and 21%, and Cu accumulation increased by 15%. In a Pb-Zn-rich environment, the shoot dry mass and total dry mass of plants inoculated with strain Y4-4 increased by 23.4% and 22%, and Zn accumulation increased by 30.3%. In addition, the salt tolerance and biomass of wheat seedlings could be improved by applying strain Y4-4 mixed with plant residue as a result of the Cu-rich plant residues providing copper nutrition to wheat. This study offers an efficient PGPR with strong salt tolerance and a safe strategy for the post-treatment of plant residue.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.010
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 source (direct Gemma or distilled Codex), 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

Citations16
Published2016
Admission routes1
Has abstractyes

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