Novel indicators of oat quality

Ulla Holopainen-Mantila (Corresponding author), Iina Jokinen, Jussi Gillberg, Anna Liisa Välimaa, Emilia Nordlund

Research output: Chapter in Book/Report/Conference proceedingConference abstract in proceedingsScientific

Abstract

Oats is a versatile food ingredient, and its importance is increasing due to the need of shift to plant based diets. In order to facilitate oat-based trade and selection of oat raw materials for various food applications, we have developed machine learning -based quality indicators for oats enabling identification of suitable raw materials already from grains, groats or flours by utilising hyperspectral imaging. Prediction of oat material process behaviour boosts and generates savings in industrial oat supply chain.
Original languageEnglish
Title of host publicationOAT2022 International Oat Conference
Subtitle of host publicationProgram book
Pages29-30
Publication statusPublished - Oct 2022
MoE publication typeNot Eligible
EventInternational Oat Conference, OAT 2022 - Perth, Australia
Duration: 10 Oct 202213 Oct 2022

Conference

ConferenceInternational Oat Conference, OAT 2022
Country/TerritoryAustralia
CityPerth
Period10/10/2213/10/22

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