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Record W2887858668 · doi:10.5539/jas.v10n9p87

Black Seed Oil Applications for the Preservation of Postharvest Quality of ‘Wonderful’ Pomegranate Under Modified Atmosphere Packaging

2018· article· en· W2887858668 on OpenAlexvenueno aff
İbrahim Kahramanoğlu

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typearticle
Languageen
FieldNursing
TopicPomegranate: compositions and health benefits
Canadian institutionsnot available
Fundersnot available
KeywordsPostharvestModified atmosphereShelf lifeHorticultureRelative humidityFood scienceBiologyGeography

Abstract

fetched live from OpenAlex

This study was conducted to determine the effects of black seed oil (0.1% and 0.5%) applications with and without modified atmosphere packaging (MAP), on the postharvest quality of pomegranate cv. ‘Wonderful’. Fruit samples were stored at 6.5±1 ºC with 90-95% relative humidity for 150 days and quality analysis done at 30-day intervals. Furthermore, after each storage period, fruits were removed and kept at 20 ºC for 7 days to simulate a period of shelf-life. MAP alone or in combination with black seed oil application found to have a significant influence on the maintaining of fruit weight. Percent reduction in the fruit weight 150 days after storage (DAS) was 4.7% and 8.8% for black seed oil (0.5%)+MAP and control+MAP applications, respectively, where it was 18.9% for the control without MAP. The juice content of pomegranate fruits was 31.4% at harvest and it decreased to 21.9% on the control treatment in 150 days. Furthermore, juice content of the fruits with control+MAP and propolis+MAP were determined as 25.8%, and 28.1%, respectively, at 150 DAS. Applications of 0.5% black seed oil especially when combined with MAP, have found to be effective in preventing weight loss, preventing juice content, controlling gray mould development and decelerate the occurrence of chilling injury.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.968
Threshold uncertainty score0.450

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.051
GPT teacher head0.340
Teacher spread0.290 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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