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Record W2789934496 · doi:10.1002/jsfa.8965

The effect of greenhouse covering materials on phytochemical composition and antioxidant capacity of tomato cultivars

2018· article· en· W2789934496 on OpenAlexafffund
Latifeh Ahmadi, Xiuming Hao, Rong Tsao

Bibliographic record

VenueJournal of the Science of Food and Agriculture · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLight effects on plants
Canadian institutionsAgriculture and Agri-Food CanadaWestern University
FundersAgriculture and Agri-Food Canada
KeywordsCultivarCaffeic acidChemistryFerulic acidMyricetinPhytochemicalRutinFood scienceQuercetinChlorogenic acidLuteinFlavonoidFlavonolsLycopeneCarotenoidHorticultureAntioxidantBiochemistryBiologyKaempferol

Abstract

fetched live from OpenAlex

BACKGROUND: The effect of light transmission (direct and diffuse) on the phenolic compounds of five tomato cultivars was investigated under controlled conditions in greenhouses covered with different covering materials. RESULTS: The type of covering material and type of diffusion of light simultaneously affected the reducing power of cultivars. Two-way analysis of variance showed statistically significant differences in total phenolic content for the different cultivars (P < 0.05) but not for the covering materials. Analysis by ultrahigh-performance liquid chromatography with diode array detection and liquid chromatography/tandem mass spectrometry showed the presence of major phenolic acid compounds such as chlorogenic acid, hydroxycinnamic acid/rutin, caffeic acid, ferulic acid and coumaric acid as well as flavonoid compounds such as myricetin, quercetin and naringenin. Most of the identified compounds showed a significant difference in different treatments due to both cultivar and covering material (P < 0.05). Statistical analysis showed that the type of covering material used influenced the total carotenoid and lycopene content (P < 0.05); however, the amount of lutein was not influenced by the type of covering material (P > 0.05). CONCLUSION: This study showed that the use of solar energy transmission could positively affect the reducing power of cultivars and alter the biosynthesis of certain phytochemicals that are health-beneficial. Further study could lead to applications for producing greenhouse vegetables with greater health attributes. © 2018 Society of Chemical Industry.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score0.233

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.007
GPT teacher head0.202
Teacher spread0.195 · 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

Citations13
Published2018
Admission routes2
Has abstractyes

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