About This Webinar
There is a need throughout multiple industries to monitor food ingredients such as protein and moisture in wheat, sort objects such as in plastic recycling, and determine the presence or absence of an ingredient. All of these can be accomplished by using a NIR hand-held spectrophotometer’s acquired data and chemometrics modelling such as partial least square (PLS), principal component analysis (PCA) and linear discriminant analysis (LDA).
Mani introduces digital light processing (DLP) technology, focuses on measurements of wheat kernels, and then shares on chemometrics modelling to determine protein and moisture percentages. The price of wheat depends on its protein content while its moisture content determines the storage conditions because moist samples get spoiled more quickly. PLS modelling results are used to predict these two factors in wheat.
Mani also discusses type identification for plastic recycling. Plastics are used as food containers and therefore are an essential part of the food industry. He then shares about PCA models and LDA models, which both identify different types of plastics.
*** This presentation premiered during the
2023 Photonics Spectra Spectroscopy Conference. For more information on Photonics Media conferences, visit
events.photonics.com.
About the presenter
Rez Mani, Ph.D., received a master’s degree in engineering physics from McMaster University in Hamilton, Ontario with a focus on the optical properties of semiconductors. He followed this with a doctorate degree in earth and space science from York University in Toronto, with a focus on satellite optical instrumentation. Mani has over 20 years of experience in photonics, which includes spectroscopic instrumentation, lasers, horticultural lighting, colorimetric standards, laser testing for single-event effects (SEE), and laser cleaning systems. He is a voting member of the Color Committee of the Illumination Engineering Society (IES), and he has worked for ASP Laser Inc. as an applications scientist since 2018.