Machine learning approach to study the effect of oxidation in edible almond oils using combined spectroscopy and principal component analysis

Gagan Raju, Soumyabrata Banik, Sindhoora Kaniyala Melanthota, Yana Baycerova, Yury Kistenev, Nirmal Mazumder

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Oxidative deterioration of edible oils makes it unfit for consumption and poses several serious health hazards on mankind. Present study employs PCA based machine learning along with spectroscopy to investigate the effect of oxidation on edible oils.

Original languageEnglish
Title of host publicationFrontiers in Optics, FiO 2022
PublisherOptica Publishing Group (formerly OSA)
ISBN (Electronic)9781557528209
Publication statusPublished - 2022
EventFrontiers in Optics, FiO 2022 - Rochester, United States
Duration: 17-10-202220-10-2022

Publication series

NameOptics InfoBase Conference Papers

Conference

ConferenceFrontiers in Optics, FiO 2022
Country/TerritoryUnited States
CityRochester
Period17-10-2220-10-22

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Mechanics of Materials

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