A Study of Erythrocyte Deformation Level Related to Biomass Burning Emission Exposures Using Artificial Neural Networks

Abstract

Emissions from burning biomass have become a problem in Indonesia. As found on the Indonesian island of Lombok, agricultural waste is burned for traditional industrial activities. On the other hand, biomass burning emissions contain many PMs (particulates) in different size distributions recognized to have a significant correlation to health impact. This study is conducted to predict the impact of the PM exposure on blood using a ANN (artificial neural network) model as well as a histological examination. The relationship between both methods is determined to estimate the impact of biomass burning emissions on the blood. This study used male mice as the experimental animals exposed to PM emissions (PM0.1, PM2.5, and PM10) produced from the burning of various biomass (rice straw, rice husks, corn cobs, corn stalks, and tobacco) taken from Lombok Island. The sample exposure was conducted in a chamber for 100 s for ten sequence days. The blood samples were observed using a microscope with the 400 x magnification. The cell deformation was examined histologically by calculating the normal and abnormal cells. The percentage of the erythrocyte deformation was assessed using a fixed back and forth propagation ANN. The result shows that the biomass burning PM emissions have a significant impact on the erythrocyte deformation depending on the type of biomass and the particulate matter emissions. The ANN model confirms the erythrocyte deformation data obtained by the histological examination method.