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Comparative study of two modeling approaches for predicting heavy metals contaminant migration from polyethylene bags

TitleComparative study of two modeling approaches for predicting heavy metals contaminant migration from polyethylene bags
Publication TypeJournal Article
Year of Publication2016
AuthorsBanadda, N, Lule, F, Sempala, C, Kigozi, J
JournalInt J Agric & Biol Eng
Volume9
Issue3
Date PublishedMay 2016
Keywordsheavy metals, mathematical models, migration, polyethylene bags
Abstract
Plasto-Foam brand, medium size of 30 mm thickness (black and green) commonly used polyethylene bags for preparing foods were selected from those available in local markets. The polyethylene bag samples were crushed into pieces, ashed and then acid digested to determine the concentrations of heavy metals selected (Pb, Cr, Co and Cd) using Atomic Absorption spectrophotometer. All the polyethylene samples were tested positive for heavy metals. Concentrations of heavy metals in polyethylene bags ranged from 1080 ppm to 1725 ppm, 76 ppm to 112 ppm, 35 ppm to 52 ppm, 18 ppm to 31 ppm for Pb, Cd, Cr and Co, respectively. Forty-eight posho (Ugali) samples were prepared and wrapped in these polyethylene bags and migration studies were carried out at 65°C and 80°C. The experimental data obtained were then compared to the modeled data using the models developed by Baner et al., and Limm and Hollifield to determine which model was a better estimator. Model fitting was done based on Non-linear least square analysis using Microsoft EXCEL 2003. Diffusion and partition coefficients both between food and the contact material were also obtained by fitting experimental data to the model equation. The modeling approaching could best describe the experimental data of the measured contaminants. The study revealed that all polyethylene bags showed highest contaminant concentration (above USFDA limit) of Pb, Cd, Cr and Co, respectively confirming the potential health risk to individuals if continuously eat food thermally prepared in polyethylene bags.
 
DOI10.3965/j.ijabe.20160903.1611
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