Litcius/Paper detail

Discrimination of Volatiles of Shiitakes (Lentinula edodes) Produced during Drying Process by Electronic Nose

Hui Zhang, Jing Peng, Yu-ren Zhang, Qiang Liu, Leiqing Pan, Kang Tu

2020International Journal of Food Engineering19 citationsDOIOpen Access PDF

Abstract

Abstract This study aimed to investigate the potential of electronic nose (E-nose) to differentiate volatiles of shiitakes produced at different drying stages. Shiitakes at different drying time slots were categorized into four groups (fresh, early, middle and late stage) by sensory evaluation. E-nose was used to analyze the volatiles and compared with headspace solid phase micro-extraction combined with gas chromatography-mass spectrometry (HS/GC-MS). The principal component analysis results showed that shiitakes at each stage could be successfully discriminated by E-nose and HS/GC-MS. The differences in volatile organic compounds produced at each stage were mainly caused by sulfurs and alcohols, leading to apparent changes of sensors sensitive to sulfurs, alcohols and aromatic compounds. The discriminant models were established by partial least squares discriminant analysis and support vector machine classification, with accuracy rates of 91.25 % and 95.83 %, respectively. The results demonstrated the potential use of E-nose in classifying and monitoring shiitakes during drying process.

Topics & Concepts

Electronic noseChemistryPrincipal component analysisChromatographyGas chromatography–mass spectrometryGas chromatographyExtraction (chemistry)OdorLinear discriminant analysisPartial least squares regressionMass spectrometryArtificial intelligenceOrganic chemistryComputer scienceMachine learningAdvanced Chemical Sensor TechnologiesFungal Biology and ApplicationsFermentation and Sensory Analysis