Classification of puffed snacks freshness based on crispiness-related mechanical and acoustical properties

Sanahuja, Solange; Fédou, Manuel; Briesen, Heiko (2018). Classification of puffed snacks freshness based on crispiness-related mechanical and acoustical properties Journal of Food Engineering, 226, pp. 53-64. Elsevier 10.1016/j.jfoodeng.2017.12.013

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The use of instrumental methods to support sensory panels in the routine quality control of crispiness remains challenging. Texture analysis is often insufficient to accurately classify this complex sensory attribute. Herein, 70 different food properties were combined via machine learning algorithms to mimic multisensory integration. Force and sound were measured during crushing of puffed snacks equilibrated at different humidity levels. Sensory panels then ranked crispiness-related freshness and preference based on the recorded sounds. Selected feature combinations were used to train machine learning models to recognize the freshness levels at different humidity levels. The classification accuracy was improved compared with traditional texture analysis techniques; an accuracy of up to 92% could be achieved with quadratic support vector machine or artificial neural network algorithms. Moreover, third-octave frequency bands, characterizing breakage frequencies and sound pitches, were determined to be main descriptors to be taken into account during the research and development of puffed snacks.

Item Type:

Journal Article (Original Article)

Division/Institute:

School of Agricultural, Forest and Food Sciences HAFL > HAFL Continuing education

Name:

Sanahuja, Solange;
Fédou, Manuel and
Briesen, Heiko

Subjects:

Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QC Physics
T Technology > TJ Mechanical engineering and machinery

ISSN:

0260-8774

Publisher:

Elsevier

Language:

English

Submitter:

Solange Sanahuja

Date Deposited:

04 Nov 2019 14:51

Last Modified:

04 Nov 2019 14:51

Publisher DOI:

10.1016/j.jfoodeng.2017.12.013

Uncontrolled Keywords:

Food textureMechanical propertiesCrushing soundsSensory crispiness/crispnessMultisensory integrationMachine learning

ARBOR DOI:

10.24451/arbor.8701

URI:

https://arbor.bfh.ch/id/eprint/8701

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