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A customized metal oxide semiconductor-based gas sensor array for onion quality evaluation: system development and

Tharun Konduru¹, Glen C Rains², Changying Li³

¹College of Engineering, University of Georgia, 200 D.W. Brooks Dr., Athens, GA 30602, USA. kondurutharun@gmail.com.

Sensors (Basel, Switzerland)

|January 15, 2015

Summary

This summary is machine-generated.

A novel gas sensor array using Metal Oxide Semiconductor (MOS) technology can detect rotten onions by identifying specific volatile organic compounds. This low-cost system achieved 89% accuracy in classifying diseased onions, offering a promising tool for postharvest disease detection.

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Area of Science:

Agricultural Engineering
Sensor Technology
Food Science

Background:

Postharvest diseases in onions lead to significant economic losses.
Early detection of spoilage is crucial for maintaining onion quality and safety.
Current detection methods can be time-consuming or lack specificity.

Purpose of the Study:

To develop and evaluate a low-cost gas sensor array for detecting rotten onions.
To identify key volatile organic compounds associated with onion spoilage.
To assess the system's ability to discriminate between healthy and diseased onions.

Main Methods:

A seven-sensor Metal Oxide Semiconductor (MOS) array was designed and integrated with a gas delivery system.
The array was exposed to various concentrations of volatile organic compounds, including those emitted by rotten onions.
A graphical user interface developed in LabVIEW was used for data acquisition and analysis.
The system's classification accuracy was tested using sour skin infected onions.

Main Results:

The gas sensor array successfully differentiated between various organic volatile compounds at different concentrations.
The system could discriminate between two concentrations of methlypropyl sulfide and 2-nonanone, key compounds in rotten onions.
The array achieved an 89% correct classification rate for sour skin infected onions.

Conclusions:

The developed MOS gas sensor array is effective in detecting rotten onions based on their volatile emissions.
This technology offers a potential low-cost solution for real-time monitoring of onion postharvest quality.
The system shows promise as a tool for identifying onion postharvest diseases during storage.