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Record W2836454729 · doi:10.5539/jas.v10n8p245

Antioxidant Enzymes Activity in the Elaeis guineensis Jacq. Submitted to Drought

2018· article· en· W2836454729 on OpenAlexvenueno aff
Cândido O. Neto, Maria Eliane Merlin Rocha, Mayra Taniely Ribeiro Abade, Glauco André dos Santos Nogueira, Vitor Resende do Nascimento, Kerolém Prícila Sousa Cardoso, Ana Ecídia de Araújo Brito, Liliane Corrêa Machado, Jéssica Taynara da Silva Martins, Thays Corrêa Costa, Ricardo Shigueru Okumura

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicOil Palm Production and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsElaeis guineensisAntioxidantCatalaseSuperoxide dismutaseAscorbic acidBiologyFood scienceGlutathione peroxidaseBotanyHorticultureBiochemistryPalm oil

Abstract

fetched live from OpenAlex

Oil palm is a very responsive culture in relation to climate change that intensifies or lowers its productivity. Thus, the objective of this study is to evaluate the activity of antioxidant enzymes in two genotypes of E. guineensis, both under water deficiency. The experiment conducted in a greenhouse at UFRA used genotypes 2528 and 2501 of E. guineensis submitted to water deficiency from the 10th day. The biochemical analysis was evaluated at the 5% level of significance by the Tukey test. The antioxidant variables analyzed were superoxide dismutase, catalase activity, ascorbate peroxidase activity, Malondialdeído (MDA), Glutathione and ascorbic acid content. In view of the obtained results, it was observed increases of the antioxidant enzymes when the genotypes were submitted to the water deficiency, presented significance for the results. Therefore, the study suggests that oil palm had a good use and adaptation when submitted to water deficit and that genotype 2528 was more responsive to maintain its vital biochemical activities.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.824
Threshold uncertainty score0.249

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.008
GPT teacher head0.244
Teacher spread0.235 · 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

Citations3
Published2018
Admission routes1
Has abstractyes

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