Boric Acid Adulteration Detection in Wheat Flour using Solvent Extraction Followed by ATR-FTIR Spectra Collection and Applying Feed Forward Neural Network

Author: Akashamrut M. Patel, Nilesh R. Sardar, Ramesh B. Modi, Arvind N. Nakiya, Bhavesh H. Joshi and Samit Dutta

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Abstract

Food adulteration is very common and thus its detection requires easy, fast and reliable methods. It is self-evident that availability of easy detection methods discourages adulteration. Current study is striving to develop fast and easy method for detection of boric acid adulteration in wheat flour by using by using Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR) spectra collection along with Artificial Neural Network (ANN) classification of spectra. Thus objective of study was to help in solving challenge of adulteration detection using easy to use methods. Extraction of adulterated samples was done both with water and alternatively with methanol. In case of methanol used as solvent for extraction, later on methanol was evaporated and samples was re-suspended in water. Finally spectra is collected by applying extract to FTIR crystal. It was assumed that instead of applying samples directly, extraction will increase detection rate. It was discovered that combination solvent extraction with ATR-FTIR spectra and ANN approach can detect equal or more than 2% adulteration of boric acid in wheat flour successfully. Objective of the current study to easily detect adulteration was solved to an extent. It was concluded that improved sample preparation along with more sensitive ATR-FTIR technology can improve detection levels further.

Keywords

Adulteration, Wheat Flour, Boric Acid, ATR FTIR, Neural Network

Conclusion

Feed forward artificial neural networks can be successfully used to detect boric acid adulteration in wheat flour at more than or equal to2% levels using FTIR spectra. It can be concluded that detection level is on higher side and improvement scope remains on side of sample preparation and spectra collection techniques rather than on tweaking ANN.

References

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How to cite this article

Akashamrut M. Patel, Nilesh R. Sardar, Ramesh B. Modi, Arvind N. Nakiya, Bhavesh H. Joshi and Samit Dutta (2022). Boric Acid Adulteration Detection in Wheat Flour using Solvent Extraction Followed by ATR-FTIR Spectra Collection and Applying Feed Forward Neural Network. Biological Forum – An International Journal, 14(4): 767-771.