Optimal vegetable selection in urban and rural areas using artificial bee colony algorithm: Heavy metal assessment and health risk
Yazarlar (5)
Doç. Dr. Yücel Gültekin Institute Of Natural Sciences, Türkiye
Mukaddes Kılıç Bayraktar Karabük Üniversitesi, Türkiye
Prof. Dr. Hakan ŞEVİK Kastamonu Üniversitesi, Türkiye
Prof. Dr. Mehmet Çetin Kastamonu Üniversitesi, Türkiye
Tuğrul Bayraktar Karabük Üniversitesi, Türkiye
Makale Türü Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
Dergi Adı Journal of Food Composition and Analysis (Q2)
Dergi ISSN 0889-1575 Wos Dergi Scopus Dergi
Dergi Tarandığı Indeksler SCI-Expanded
Makale Dili Türkçe Basım Tarihi 03-2025
Cilt / Sayı / Sayfa 139 / 1 / – DOI 10.1016/j.jfca.2024.107169
Makale Linki https://doi.org/10.1016/j.jfca.2024.107169
UAK Araştırma Alanları
Silvikültür Orman Botaniği
Özet
Industrial 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 …
Anahtar Kelimeler
Artificial bee colony algorithm | Food safety | Health risk assessment | Heavy metal accumulation | Traffic density | Vegetables
Science Direct
BM Sürdürülebilir Kalkınma Amaçları
Atıf Sayıları
Web of Science 12
Scopus 13
Google Scholar 25
Optimal vegetable selection in urban and rural areas using artificial bee colony algorithm: Heavy metal assessment and health risk

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