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
Dr. Öğr. Üyesi Mukaddes Kılıç Bayraktar Karabük Üniversitesi, Türkiye
Prof. Dr. Hakan ŞEVİK Kastamonu Üniversitesi, Türkiye
Prof. Dr. Mehmet Çetin Kastamonu Üniversitesi, Türkiye
Dr. Öğr. Üyesi 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 (Q1) | ||
| Dergi ISSN | 0889-1575 Dergi Bilgileri (2025) | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | Türkçe | Basım Tarihi | 03-2025 |
| Kabul Tarihi | – | Yayınlanma Tarihi | 01-03-2025 |
| 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
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| 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
Optimal vegetable selection in urban and rural areas using artificial bee colony algorithm: Heavy metal assessment and health risk
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 14 |
| Scopus | 15 |
| Google Scholar | 30 |