An Electronic Nose for Royal Delicious Apple Quality Assessment - A Tri-layer Approach.

Foodborne pathogens cause serious health issues and have a strong impact on the economy of the country. In this context, quality testing of royal delicious apple by detecting pathogen contamination using an electronic nose, which contains an array of six ready-made sensors, has been proposed. To estimate the types of pathogens, fresh, half and completely contaminated apple samples were considered for bacterial studies. This study revealed the presence of Staphylococcus, Salmonella and Shigella bacteria, which were in the order of zero, 102, 103-104 CFU/mL. Further, the recorded headspace GC-MS spectra of contaminated samples confirmed the presence of bacterial spoilage markers namely acetone, ethyl acetate, ethyl alcohol and acetaldehyde. Voltage swing of 0.2 and 0.5 V was observed for half and completely contaminated apple samples respectively with reference to the fresh sample. Voltage responses of the sensors fed to Principal component analysis and Ward's method of hierarchical cluster algorithms helped to assess the quality of apple samples. By correlating the results of tri-layers namely bacterial count, GCMS data and classification results, reference table was developed and embedded in the ATmega processor of the electronic nose for real-time quality estimation of apple samples.

• Publication year

  2018

• Venue

  Food Research International

• Publication date

  2018-04-11

• Fields of study

  Agricultural and Food Sciences, Medicine, Chemistry, Environmental Science

• Identifiers
  DOI 10.1016/j.foodres.2018.04.009PMID 29803469
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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