Vol. 10, Issue 10 (2021)

Author(s):
Akashamrut M Patel, HG Bhatt and RF Sutar

Abstract:
Adulteration in food commodities is common and thus easy, fast and reliable detection methods are essential to discourage it. Present study is focused on achieving this by using Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR) spectra collection along with Artificial Neural Network (ANN) classification of spectra for detection of boric acid added in wheat flour as adulterant. ATR-FTIR is non-destructive and fast method and gives signature spectra for many chemicals for easy identification and ANNs are very good at detection in pattern in data. It was found that combination of ATR-FTIR and ANN approach can detect more than 2% adulteration of boric acid in wheat flour successfully. The detection was on higher side and it was concluded that further studies using fast but effective sample preparation methods can improve detection levels by improving quality of signal.