Optimal vegetable selection in urban and rural areas using artificial bee colony algorithm: Heavy metal assessment and health risk

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dc.authoridhttps://orcid.org/0000-0002-1974-1242
dc.authoridhttps://orcid.org/0000-0002-8871-8820
dc.authoridhttps://orcid.org/0000-0003-1662-4830
dc.authoridhttps://orcid.org/0000-0002-8992-0289
dc.authoridhttps://orcid.org/0000-0001-5620-5804
dc.contributor.authorGültekin, Yücel
dc.contributor.authorKılıç Bayraktar, Mukaddes
dc.contributor.authorSevik, Hakan
dc.contributor.authorCetin, Mehmet
dc.contributor.authorBayraktar, Tuğrul
dc.date.accessioned2025-01-13T13:07:36Z
dc.date.available2025-01-13T13:07:36Z
dc.date.issued2025-03
dc.departmentFakülteler, Sağlık Bilimleri Fakültesi, Beslenme ve Diyetetik Bölümü
dc.departmentFakülteler, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü
dc.description.abstractIndustrial and traffic activities have raised heavy metal (HM) pollution, increasing health risks from contaminated vegetables. The study aims to analyze HM concentrations of lead (Pb), iron (Fe), and aluminum (Al) in Solanum lycopersicum L. (tomato), Capsicum annuum L. (pepper), Phaseolus vulgaris L. (bean), and Zea mays L. (corn) plants grown in urban and rural areas of Ordu province, Türkiye. Variations in the HMs were evaluated based on species, organ, growing area, and washing status. The goal is to use the Artificial Bee Colony (ABC) algorithm to identify the best vegetable combination based on health risk assessment. Tomato and corn had the lowest HM levels, while pepper had the highest. Urban vegetables had high Pb levels, with urban-grown corn showing notably high Fe and Al levels. Pb levels (341.4–13,240.4 μg/kg) exceeded permissible limits in all vegetables, Al (898.9–210,706.2 μg/kg) in most, while Fe (11.2–298.4 μg/kg) stayed within safe limits. Health risk assessments (hazard quotient and hazard indices <1) show no risk of non-carcinogenic diseases. The recommended upper limits for HM concentrations constrain vegetable choices to minimize health risks, with the ABC algorithm advising washed pepper, tomato, and bean from urban areas and unwashed corn from rural areas.
dc.identifier.citationGültekin, Y., Bayraktar, M.K., Sevik, H., Çetin, M., & Bayraktar, T. (2024). Optimal Vegetable Selection in Urban and Rural Areas Using Artificial Bee Colony Algorithm: Heavy Metal Assessment and Health Risk. Journal of Food Composition and Analysis.
dc.identifier.doi10.1016/j.jfca.2024.107169
dc.identifier.issn0889-1575
dc.identifier.scopus2-s2.0-85213253124
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.jfca.2024.107169
dc.identifier.urihttps://hdl.handle.net/20.500.14619/14981
dc.identifier.volume139
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofJournal of Food Composition and Analysis
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectArtificial bee colony algorithm
dc.subjectFood safety
dc.subjectHealth risk assessment
dc.subjectHeavy metal accumulation
dc.subjectTraffic density
dc.subjectVegetables
dc.titleOptimal vegetable selection in urban and rural areas using artificial bee colony algorithm: Heavy metal assessment and health risk
dc.typeArticle
oaire.citation.volume139

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