Browsing by Author "Aunsa-Ard W."

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    Detection of COVID-19 infection based on electronic nose technique: preliminary study
    (2022-01-01) Phukkaphan N.; Eamsa-Ard T.; Aunsa-Ard W.; Khunarak C.; Nitivanichsakul T.; Roongpuvapaht B.; Kerdcharoen T.; Mahidol University
    The coronavirus COVID-19 pandemic have reached almost every country in the world and caused a global health crisis. It is necessary to detect COVID-19 with fast and accurate diagnosis method in order to prevent the rapid spread of Covid-19. This paper presents a preliminary study of using electronic nose (e-nose) technology for detection of COVD-19 infection. In this experiment, the human exhaled breaths of healthy volunteers, asymptomatic and symptomatic COVID-19 patients were collected with commercial face masks for 5 minutes followed by the measurement with an e-nose machine in a closed system. The COVID-19 positivity was confirmed by RT-PCR method. According to the experiment, the odor intensity of human exhaled breath can be described with the total sensing response value. The exhaled breath of COVID-19 infected patients show higher odor intensity than the healthy volunteers (control). The Principal Component Analysis (PCA) shows the classification of three data groups; healthy volunteers, COVID-19 infected patients and unclassified people. For the unclassified cases, the medical record has shown that these people have been subjected either to some respiratory diseases or just recovered from COVID-19 infection. From these preliminary results, e-nose technology and its measurement proto-cols can be considered as a viable tool for COVID-19 rapid detection.
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    Electronic Nose for Analysis of Coffee Beans Obtained from Different Altitudes and Origin
    (2022-01-01) Aunsa-Ard W.; Kerdcharoen T.; Mahidol University
    The coffee industry is facing increasing challenges due to climate change, pests, diseases, which leads to the reduced production and negative impact on coffee qualities. Thus, quality assurance of coffee from production to roasting and brewing becomes more important, especially coffee flavor and aroma. This research aims to study the applicability of electronic nose (e-nose) and algorithm to detect coffee aroma obtained from different origins. The coffee beans used in this experiment were obtained from different areas in northern Thailand. These coffee beans have different growing conditions, altitude, processing and roasting condition. In this study, the three aspects of e-nose were investigated; (i) e-nose sensitivity to coffee odors, (ii) e-nose capability of correctly recognizing the detected odors and (iii) factors that influence coffee odors such as altitude, processing and roasting conditions. The e-nose system comprises of eight metal oxide semiconductor (MOX) gas sensors and in-house developed analysis software. Principal Component Analysis (PCA) is a classification algorithm for pattern recognition of different coffee aroma. Based on experimental results, the e-nose technology shows a capability to detect and distinguish the coffee odors caused by different altitude, processing and roasting process. E-nose is a suitable method for aroma detection in coffee industry to enhance the quality.