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Record W1686906155 · doi:10.1007/s10535-015-0554-6

Sufficient sulfur supply promotes seedling growth, alleviates oxidation stress, and regulates iron uptake and translocation in rice

2015· article· en· W1686906155 on OpenAlexfundno aff
Zonghan Wu, C. Zhang, Chen Dai, Ying Ge

Bibliographic record

VenueBiologia Plantarum · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Micronutrient Interactions and Effects
Canadian institutionsnot available
FundersSpecialized Research Fund for the Doctoral Program of Higher Education of ChinaState Key Laboratory of Soil and Sustainable AgricultureInstitute of Soil Science, Chinese Academy of SciencesNational Natural Science Foundation of ChinaMcGill University
KeywordsOryza sativaTBARSSeedlingShootChemistryOxidative stressSulfurChromosomal translocationHorticultureRice plantHydroponicsAgronomyFood scienceBiologyLipid peroxidationBiochemistry

Abstract

fetched live from OpenAlex

We investigated the effect of sulfur (S) supply on growth, oxidative stress, and iron uptake and transport in rice (Oryza sativa L.) seedlings using a hydroponic culture with four S concentrations (0, 1.75, 3.5, and 7.0 mM). The length and fresh mass of seedlings were enhanced with the increased S concentration. In addition, the content of thiobarbituric acid reactive substances (TBARS) in rice leaves was the highest when no S was added to the nutrition solution and gradually declined with the increasing S supply. The higher S nutrition reduced the amount of Fe plaque on rice roots and increased Fe content in roots and leaves. The content of nicotianamine was significantly higher in rice roots under the S deficiency, whereas the reverse trend was observed in rice shoots. Taken together, the sufficient S nutrition promoted growth of rice, reduced oxidative stress, and ensured normal Fe uptake and distribution.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.710
Threshold uncertainty score0.230

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 head0.018
GPT teacher head0.206
Teacher spread0.188 · 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

Citations17
Published2015
Admission routes1
Has abstractyes

Explore more

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