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Record W2039279127 · doi:10.1021/jf304660d

Tomato Fruit Antioxidants in Relation to Salinity and Greenhouse Climate

2013· article· en· W2039279127 on OpenAlexaff
David L. Ehret, Kevin Usher, Tom Helmer, Glenn Block, Dan Steinke, Brenda Frey, Tallie Kuang, Moussa S. Diarra

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2013
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsGreenhouseSalinityClimate changeEnvironmental scienceHorticultureAgronomyBiologyEcology

Abstract

fetched live from OpenAlex

A two-year study of antioxidants in greenhouse tomato was conducted. Plants were treated continuously with nutrient solution electrical conductivities (EC) of 2, 4, or 6 dS m⁻¹. Increasing EC reduced yield per plant and fruit size. Oxygen radical absorbance capacity (ORAC), lutein, β-carotene, lycopene, and vitamin C concentrations were evaluated in harvested fruit. ORAC and all antioxidants with the exception of lutein increased with EC. None of the 10 genes involved in antioxidant metabolism were affected by salinity in ripe fruit, but the expression of three of them (ZDS, CrtR-b1, and NCED1) varied with the stage of fruit development. Antioxidant concentrations were related to greenhouse climatic conditions. β-Carotene, lycopene, lutein, and vitamin C responded negatively to light and positively to temperature, whereas ORAC was unresponsive. Multiple regressions of antioxidants in relation to EC and climatic factors showed that antioxidants responded more strongly to light and temperature than to EC.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
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 head0.011
GPT teacher head0.225
Teacher spread0.214 · 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 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

Citations44
Published2013
Admission routes1
Has abstractyes

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