A gas sensor array, consisting of seven Metal Oxide Semiconductor (MOS) sensors that are sensitive to a wide range of organic volatile compounds was developed to detect rotten onions during storage. These MOS sensors were enclosed in a specially designed Teflon chamber equipped with a gas delivery system to pump volatiles from the onion samples into the chamber. The electronic circuit mainly comprised a microcontroller, non-volatile memory chip, and trickle-charge real time clock chip, serial communication chip, and parallel LCD panel.
User preferences are communicated with the on-board microcontroller through a graphical user interface developed using LabVIEW. The developed gas sensor array was characterized and the discrimination potential was tested by exposing it to three different concentrations of acetone (ketone), acetonitrile (nitrile), ethyl acetate (ester), and ethanol (alcohol). The gas sensor array could differentiate the four chemicals of same concentrations and different concentrations within the chemical with significant difference.
Experiment results also showed that the system was able to discriminate two concentrations (196 and 1964 ppm) of methlypropyl sulfide and two concentrations (145 and 1452 ppm) of 2-nonanone, two key volatile compounds emitted by rotten onions. As a proof of concept, the gas sensor array was able to achieve 89% correct classification of sour skin infected onions. The customized low-cost gas sensor array could be a useful tool to detect onion post harvest diseases in storage.
OVERVIEW OF THE SENSING SYSTEM
The gas sensor array system was designed to specifically detect volatile profiles of the odor released by onions. The system consisted of mechanical, electronic and software program components. The mechanical component had a gas delivery system to transport the volatiles from the headspace of the sample to the MOS sensors mounted inside a chamber. The electronic component included a circuit board with microcontroller (MCU), memory chip, time keeping chip, and other peripheral devices. Software programs were developed to control the MCU and to interface with the computer.
A square-shaped Teflon block was cut into three 132 × 132 × 19.8 mm sections placed on top of each other after customizing the middle and lower block. Holes (sockets) were bored into the lower block to mount the MOS sensors. Each socket varied in size and shape based on the size of the individual MOS sensor. In the middle block, a circular hole of diameter 112 mm was cut through the block to provide a head space for the sensors. The arrangement of the three blocks is shown in Figure 1. Any change in MOS sensor size or shape could be easily addressed by replacing the lower block with a suitable design.
A typical sampling process consists of three sequences: Baseline purging, sampling, and purging. “Baseline purging” involved injecting clean filtered air into the chamber preparing the device for the sampling phase. “Sampling phase” involved injecting sample odor into the chamber and the purging phase involved removing the sample odor from the chamber by purging with clean filtered air. This step always followed sampling phase.
The entire circuit required three different power supplies. The major portion of the circuit was designed to operate with a power supply of 5 V. The valve and the pump required a voltage supply of 12 V and an external coin battery (3 V) was provided to the DS1302 facilitating the chip to function constantly even when the device was switched off. This eliminated the need for updating the time of the micro-controller every time when the device was switched “on”. The pin connections for the above described components are shown in Figure 4. A top view of the prototype circuit board designed for the gas sensing device is shown in Figure 5.
The graphical user interface (GUI) in the PC was developed using LabVIEW. The purpose of designing this software was mainly to facilitate communication between the us er and the device, data processing, downloading and display. The device was configured by the user by making selections on the GUI and transferring them to the MCU in the form of instructions (Figure 7). The instructions were sent to the device through the RS 232 cable connected to the device.
The real time data (in the txt format) can be displayed and analyzed in the “Data processing and visualization tab” (Figure 9). Figure 9 shows the baseline, sampling and the purging phases in the left window. The generated graph was used by the user for quick observation of sensor responses. On the right side of Figure 9, principal component analysis (PCA) was conducted by specifying the path of the file in the “Select file to process” box and clicking “Process data” option. The PCA score plot was used for quick evaluation and diagnosis of the objects being investigated.
The jar was allowed to stand for 30 min to allow complete evaporation of the sample solution into the head space inside the jar. The sample inlet tubing was placed into the jar approximately 1 to 2 s be fore the device reached the sampling phase and the sample was drawn into the chamber for analysis. Th e pump speed affected the rate at which an odor sample was delivered to the MOS sensors resulting in varied response time. The maximum response and the time taken by the MOS sensors to reach maximum response for both pump speeds are presented in Figure 10, respectively.
The same procedure was followed as in previous tests, but the sample was drawn in two different directions represented as “Flow 1” and “Flow 2”. Flow 1 represented the sample flow where the entry point was close to TGS 813 and TGS 825 was the exit point. Flow 2 represented the sample flow where the entry point was TGS 825 and the exit point was close to TGS 813 (Figure 11).
The custom-built gas sensor array operated well at high pump speeds irrespective of the size of the sample head space. The location of the MOS sensors within the chamber did not have a significant effect on sensor response. The device was able to differentiate the four chemicals ethanol, acetone, acetonitrile and ethyl acetate when exposed with the same concentrations and was able to differentiate differences in the concentrations within and between the chemicals. The sensor was not only able to detect the presence of the two key volatile compounds emitted by diseased onions, but also to differentiate them at two concentration levels.
The gas sensor array was able to achieve 89% classification accuracy when healthy and sour skin infected onions are mixed. The main contribution of this paper was to develop a low cost customized gas sensor array with an automated gas delivery and data acquisition system to detect volatile compounds emitted by onions. The sensor characterization tests have proven the efficacy of the device for sour skin infected onion detection. The sensor was relatively inexpensive and therefore could be deployed in multiple units in a storage room. It could be modified for other specialty crops for post harvest quality evaluations.
Source: University of Georgia
Authors: Tharun Konduru | Glen C. Rains | Changying Li