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1887

access icon free Use of hyperspectral imaging for cake moisture and hardness prediction

© The Institution of Engineering and Technology
Received 28/02/2018, Accepted 11/03/2019, Revised 26/12/2018, Published 22/03/2019

Industrial baking of sponge cakes requires various quality indicators to be measured during production such as moisture content and sponge hardness. Existing techniques for measuring these properties require randomly selected sponges to be removed from the production line before samples are manually cut out of each sponge in a destructive way for testing. These samples are subsequently processed manually using dedicated analysers to measure moisture and texture properties in a lengthy process, which can take a skilled operator around 20 min to complete per sponge. In this study, the authors present a new, single sensor hyperspectral imaging approach, which has the potential to measure both sponge moisture content and hardness simultaneously. In the last decade, hyperspectral imaging systems have reduced in cost and size and, as a result, they are becoming widely used in a number of industries and research areas. Recently, there has been an increased use of this technology in the food industry and in food science applications and research. The application of this technology in the cake production environment, empowered by sophisticated signal and image processing techniques and prediction algorithms as presented in this study has the potential to provide on-line, real-time, stand-off cake quality monitoring.

Inspec keywords: quality control; image sensors; food products; product quality; moisture; food processing industry; image processing

Other keywords: sophisticated signal; cake production environment; texture properties; industrial baking; image processing techniques; sponge cakes; single sensor hyperspectral imaging; time 20.0 min; cake moisture; cake quality monitoring; quality indicators; production line; hardness prediction; hyperspectral imaging systems; lengthy process; sponge moisture content

Subjects: Inspection and quality control; Products and commodities; Testing; Engineering materials; Industrial processes; Computer vision and image processing techniques; Image sensors; Statistics; Optical, image and video signal processing; Food industry

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