Winter jujube (Zizyphus jujuba Mill.) quality forecasting method based on electronic nose

Food Chem. 2015 Mar 1:170:484-91. doi: 10.1016/j.foodchem.2014.08.009. Epub 2014 Aug 19.

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.

Keywords: Double-layered cascaded series stochastic resonance; Electronic nose; Signal-to-noise ratio spectrum; Winter jujube quality.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Ascorbic Acid / analysis
  • Electronic Nose*
  • Food Quality*
  • Food Technology / instrumentation
  • Food Technology / methods*
  • Fruit / chemistry
  • Fruit / standards*
  • Gases / analysis
  • Principal Component Analysis
  • Reproducibility of Results
  • Signal-To-Noise Ratio
  • Temperature
  • Ziziphus / chemistry*
  • Ziziphus / metabolism

Substances

  • Gases
  • Ascorbic Acid