| MS Seminar

Name of the Speaker: Ms. MATHU MATHI M (EE21S072)
Guide: Prof. Shanti Bhattacharya
Venue: ESB-244 (Seminar Hall)
Date/Time: 20th September 2024 (Friday), 11:00 AM
Title: Diffuse Reflectance Spectroscopy for analyzing Chicory Content in Ground Coffee.

Abstract :

Diffuse reflectance (DR) near-infrared spectroscopy is of interest for a variety of reasons. One of the most important ones being that sample preparation is relatively simple, compared to other forms of spectroscopy. It is possible to develop affordable and compact systems, which when used with in-built data processing, can yield results quickly. Diffuse spectroscopy can be used when samples are available in granular or powder form, which makes this an ideal technique for analyzing coffee. This beverage is widely consumed in India, and requires regular scrutiny for adulteration. While there are many different adulterants used with coffee, a common one is chicory. In India, chicory is often also used as an acceptable addition both for its flavor and lower cost. In that case, the percentage of chicory needs to be verified. This poses a significant challenge for quality assurance. This study presents the design and development of an in-house diffuse reflection collection optical system for NIR spectroscopy, aimed at simplifying the analysis of powdered samples with minimal sample preparation. The system was designed using Ansys Zemax software, incorporating off-axis parabolic mirrors and other off-the-shelf optical components to collect the maximum diffuse reflection. The performance of the assembled system was compared to that of the modeled system, and shown to behave as designed. Coffee samples with varying amounts of chicory were studied in both the built system, as well as using a commercial DR instrument. DR spectra contain the fingerprint information, moisture content, and variation in particle size. The collected complex spectra were analyzed using the multivariate calibration methods like principal component analysis and partial least squares regression. The developed optical system is found to be efficient and the current model can predict the amount of chicory with an accuracy of 5% for chicory addition up to 20%. Interestingly, the accuracy and repeatability is also good for values above 35% chicory, but not in the intermediate range.