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Updated: Apr 22, 2026

Fruit Volatile Analysis Using an Electronic Nose
Published on: March 30, 2012
Winter jujube (Zizyphus jujuba Mill.) quality forecasting method based on electronic nose
Guohua Hui1, Jiaojiao Jin2, Shanggui Deng3
1School of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou 310018, China; College of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou 310018, China.
Abstract:
Winter jujube (Zizyphus jujuba Mill.) quality forecasting method utilising electronic nose (EN) and double-layered cascaded series stochastic resonance (DCSSR) was investigated. EN responses to jujubes stored at room temperature were continuously measured for 8 days. Jujubes' physical/chemical indexes, such as firmness, colour, total soluble solids (TSS), and ascorbic acid (AA), were synchronously examined. Examination results indicated that jujubes were getting ripe during storage. EN measurement data was processed by stochastic resonance (SR) and DCSSR. SR and DCSSR output signal-to-noise ratio (SNR) maximums (SNR-MAX) discriminated jujubes under different storage time successfully. Multiple variable regression (MVR) results between physical/chemical indexes and SR/DCSSR eigen values demonstrated that DCSSR eigen values were more suitable for jujube quality determination. Quality forecasting model was developed using non-linear fitting regression of DCSSR eigen values. Validating experiments demonstrated that forecasting accuracy of this model is 97.35%. This method also presented other advantages including fast response, non-destructive, etc.
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