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Record W2350887701

Effect of Pb,Hg Pollution on Germination and Antioxidant Activity of Three Kinds of Wheat Seeds

2012· article· en· W2350887701 on OpenAlexvenueno aff
Aoen Boli-ge

Bibliographic record

VenueSeed · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsnot available
Fundersnot available
KeywordsGerminationAntioxidantChemistryHorticultureAgronomyBiologyBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

In this paper,three kinds of wheat seeds were used as experimental material to study the effects of different concentrations of Hg+ and Pb2+ Pollution on the germination rate,germination vigor,the length of bud,antioxidant activity of them by the method of water culture.The results showed that the germination rate,germination vigor,the length of bud,antioxidant activity of three wheat were all inhibitied by Pb2+ polution.With the increasing of Pb2+ concentration,the inhibition gradually increased.Germination rate,germination vigor,the length of bud,antioxidant activity of agricultural wheat No.3 seed were all inhibitied by Hg+ pollution.and with the Hg+ concentration increasing,the inhibition gradually increased,but to agricultural wheat No.2 seed and new spring No.23,when Hg+ concentration were less than 50 mg/L,germination vigor had a little increasing,but had no effect on both the average length of bud and germination rate of the seeds.And when Hg+ concentration were higher than 100 mg/L,the germination rate,germination vigor,the length of bud,antioxidant activity of them were all inhibitied,and the higher of the concentration,the inhibition was the stronger.Antioxidant activity of three kinds of wheat seeds were all decreased in different concentrations of Hg+ pollution,and the higher of the concentration,the antioxidant activity of seedlings was the lower.When the Hg+ concentration was 300 mg/L,Pb2+ concentration was 500 mg/L,the germination of three wheat seeds were affected seriously.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score0.086

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.015
GPT teacher head0.238
Teacher spread0.224 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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