Optimal Vegetable Selection in Urban and Rural Areas Using Artificial Bee Colony Algorithm: Heavy Metal Assessment and Health Risk

Abstract

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, T & uuml;rkiye. 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 mu g/kg) exceeded permissible limits in all vegetables, Al (898.9-210,706.2 mu g/kg) in most, while Fe (11.2-298.4 mu g/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.