MétaCan
Menu
Back to cohort
Record W4287010098 · doi:10.3390/foods11152195

Phytochemical Enhancement in Broccoli Florets after Harvest by Controlled Doses of Ozone

2022· article· en· W4287010098 on OpenAlexafffund
Arturo Duarte‐Sierra, Charles F. Forney, Minty Thomas, Paul Angers, Joseph Arul

Bibliographic record

VenueFoods · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLight effects on plants
Canadian institutionsAgriculture and Agri-Food CanadaUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaConsejo Nacional de Ciencia y Tecnología
KeywordsPhytochemicalGlucosinolatePostharvestChemistryHorticultureGlucoraphaninAntioxidant capacityMethyl jasmonateFumigationAntioxidantFood scienceBiologyBiochemistry

Abstract

fetched live from OpenAlex

The objective of this work was to examine the effect of controlled doses of O3 (0, 5 µL L−1 of O3 for 60 min, and 5 µL L−1 of O3 for 720 min) on the quality and phytochemical content of broccoli florets during postharvest storage. The optimal dose was found at 5 µL L−1 of O3 for 60 min, from the color retention of broccoli florets exposed to the gas treatment. Overall, the antioxidant capacity of the florets was significantly affected by both doses of O3 compared to the non-exposed florets. The profile of glucosinolates was determined for up to 14 days in broccoli florets stored at 4 °C by LC-MS. The amount of total glucobrassicins and total hydroxy-cinnamates in florets significantly (p ≤ 0.05) improved by the application of 5 µL L−1 of O3 for 60 min compared to non-treated florets. The up-regulation of genes of the tryptophan-derived glucosinolate pathway was observed immediately after both treatments. The gene expression of CYP79A2 and CYP79B3 in broccoli was significantly higher in broccoli florets exposed to 5 µL L−1 of O3 for 720 min compared to non-exposed florets. Although enhancement of secondary metabolites can be achieved by the fumigation of broccoli florets with low doses of ozone, quality parameters, particularly weight loss, can be compromised.

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 categoriesInsufficient payload (model declined to judge)
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 score0.229
Threshold uncertainty score0.999

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)0.0020.000

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 head0.006
GPT teacher head0.195
Teacher spread0.190 · 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.

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

Citations2
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueFoodsSame topicLight effects on plantsFrench-language works237,207