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Record W7126088494 · doi:10.18280/ijdne.201214

Valorization of Winery By-Products: Comprehensive Profiling of Bioactive Compounds in Peels of Three Azerbaijani Pomegranate (Punica granatum L.) Cultivars

2025· article· W7126088494 on OpenAlexvenueno aff
Umide Majnunlu, Vugar Mikayilov, Vugar Salimov, Güven Özdemir

Bibliographic record

VenueInternational Journal of Design & Nature and Ecodynamics · 2025
Typearticle
Language
FieldNursing
TopicPomegranate: compositions and health benefits
Canadian institutionsnot available
Fundersnot available
KeywordsWineryCultivarProfiling (computer programming)Punica

Abstract

fetched live from OpenAlex

The aim of this study is to scientifically evaluate the bioactive composition of peel samples of Bala Mursal, Azerbaijan Guloyshe, and Nazik Gabig pomegranate varieties generated during processing, with particular emphasis on vitamins, minerals, and fatty acids, in order to assess their potential use as promising raw materials for functional food additives and high-value biotechnological products.This investigation is conducted to obtain bioactive compounds from the peels of the Bala Mursal (Aghsu), Azerbaijan Guloyshe (Aghsu), and Nazik Gabig (Goychay) pomegranate varieties obtained during processing from winemaking factories located in the Aghsu and Goychay districts of the Nagorno Shirvan economic region, and to study their health benefits for the purpose of food supplement applications.Peel samples were collected in October from processing facilities in the Aghsu and Goychay districts at full commercial maturity to minimize seasonal variability.Pomegranate peels contain many bioactive compounds such as vitamins, fatty acids, and mineral elements.The antioxidant properties of these compounds further contribute to their functions, such as protection against oxidative stress and reducing the risk of chronic diseases, including anti-cancer, antibacterial, and cardiovascular protection.For this purpose, the chemical and nutritional composition of the research samples was analyzed using modern equipment in accordance with the appropriate methodology.All compositional analyses were conducted on a dry-weight basis.When determining the fatty acid profile, minerals, proximate composition, and vitamins, it was revealed that the moisture level varied in the range of 7% (Nazik Gabig) -9% (Azerbaijan Guloyshe).The crude fiber amount varied from 18.89% in Bala Mursal 18.93% in Azerbaijan Guloyshe.The crude ash content ranged from 3.74% in Azerbaijan Guloyshe to 3.77% in Nazik Gabıg, while the crude protein content varied from 2.96% in Nazik Gabıg to 2.99% in Bala Mursal.The crude fat content ranged from 1.34% in Bala Mursal to 1.38% in Azerbaijan Guloyshe.The vitamin A content showed a wider variation, ranging from 0.176 mg/100 g in Bala Mursal to 13.26 mg/100 g in Azerbaijan Guloyshe.The results on mineral content were wider, with iron in Bala Mursal being 5 mg/100 g and potassium in Azerbaijan Guloyshe being 338 mg/100 g. 19 fatty acids were found in pomegranate peels, with the highest fatty acid amount being oleic acid, which was found in Azerbaijan Guloyshe -20.98883%.The least fatty acids were pentadecanoic, myristic, palmitoleic, arachidic, gamma-linolenic, behenic, docosadienoic, lignoceric, eicosapentaenoic, nervonic, and docosahexaenoic, varying in the range of 0.31912-2.98725%.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.296
Teacher spread0.278 · 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 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".

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Citations0
Published2025
Admission routes1
Has abstractno

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