Abstract
Abstract A new heavy metal pollution index (HMI) has been proposed for ranking noncarcinogenic heavy metal pollution in vegetable, rice, and milk. HMI comprises a pair of one positive index (Pqi) and one negative index (Nqi). Pqi represents metals present above the maximum allowable concentration, while Nqi corresponds to those below. Higher the Pqi, greater is the pollution. In the case two similar food items have same or close Pqi, Nqi decides the relative degree of contamination; lower the Nqi, lesser is the pollution. Three different databases of 12 heavy metals in 57 vegetable samples (15 different species), 12 in 14 rice samples, and 10 in 24 milk samples were separately used for developing and calibrating the newly proposed HMI. All the samples were collected from mineral-rich country sides of Jharkhand state in India. USEPA Hazard Index (HI) was used as the referral standard for calibrating HMI using a Multi-Variate Linear Regression (MVLR) model. It is also possible to apply the same model to other types of food items. If properly calibrated, HMI may not only be independently used for ranking heavy metal pollution in food but may also be used for theoretically predicting maximum allowable metal concentrations in food items for which reliable experimental data are not available.
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