PARVEEN SIWACH AND PRASANTH R. KUMAR*
Department of Physics, School of Chemical Engineering and Physical Sciences, Lovely Professional University,
Phagwara-144 411 (Punjab), India
*(e-mail: amukam@gmail.com; Mobile: 88470 56454)
(Received: June 25, 2022; Accepted: July 25, 2022)
ABSTRACT
Pearl millet (Pennisetum glucum) is cherished among consumers for its high nutritional content and
health benefits. The present study was focused on classification as well as correlation analysis of pearl
millet samples based on their near infrared, Fourier transform infrared spectra and proximate compositions
using principal component analysis (PCA). All 41 samples were collected from different geographical
locations of India. The infrared (IR) spectra of pearl millet samples were collected by using near infrared
(NIR) and Fourier transform infrared (FTIR) vibrational spectroscopy and proximate composition by
employing Association of Official Analytical Chemists methods. Furthermore, principal component analysis
(PCA) was applied on the spectral and chemical data to classify the pearl millet samples based on the
geographical origin. Overall, this study revealed the efficiency of principal component analysis method
in geographical classification of pearl millet samples on the basis of infrared spectral and chemically
processed data.
Key words : Fourier transform infrared spectroscopy, near infrared spectroscopy, principal component analysis, proximate analysis, pearl millet