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Record W2089427733 · doi:10.1002/jpln.201100217

Verte and Romaine lettuce varieties (<i>Lactuca sativa</i>) show differential responses to high NaCl concentrations

2012· article· en· W2089427733 on OpenAlexafffund
Héla Mahmoudi, Olfa Baâtour, Jun Huang, Nawel Nasri, Imen Ben Salah, Imen Tarchoun, Maha Zaghdoudi, Margaret Y. Gruber, Mokhtar Lachaâl, Zeineb Ouerghi, Abdelali Hannoufa

Bibliographic record

VenueJournal of Plant Nutrition and Soil Science · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Stress Responses and Tolerance
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsLactucaSeedlingCarotenoidGerminationSalinityChlorogenic acidHorticultureBiologyFlavonoidPolyphenolBotanyChemistryAntioxidantBiochemistry

Abstract

fetched live from OpenAlex

Abstract In this study, we report on the relationship between individual antioxidant carotenoids, phenolic fractions, and flavonoids and attenuating NaCl toxicity in two contrasting varieties of lettuce ( Lactuca sativa L., var. Verte and Romaine), as a means of developing more precise targets for lettuce breeding. In seedling leaves, carotenoid levels increased under NaCl stress in Verte, but remained unchanged in Romaine. Chlorogenic acid (CGA), a soluble polyphenol abundantly present in leaves, was the only phenolic acid that accumulated significantly in both varieties and was predominant under salinity. Remarkably, CGA was more prominent in Verte than Romaine at moderate salinity levels (100 mM). Foliar flavonoid levels were also differentially increased in both seedling types grown under 100 mM NaCl, but dropped significantly in both varieties under 200 mM NaCl. Germination, which was overall more salt‐resistant in Romaine, was significantly increased under salt stress by application of low dosage (10 –6 to10 –5 M) of CGA to Verte, but not to Romaine. These results suggest that CGA is involved in modulating NaCl‐induced oxidative‐stress responses during seed germination in Verte.

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 score0.953
Threshold uncertainty score0.321

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 head0.016
GPT teacher head0.224
Teacher spread0.208 · 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

Citations4
Published2012
Admission routes2
Has abstractyes

Explore more

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