بررسی عملکرد سامانه بینی الکترونیکی بر پایه حسگرهای نیمه‌هادی اکسید فلزی(MOS) به منظور تشخیص خلوص اسانس نعناع فلفلی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی بیوسیستم، دانشکده کشاورزی، دانشگاه تبریز

2 گروه مهندسی بیوسیستم، دانشکده کشاورزی، دانشگاه فردوسی مشهد

3 گروه مهندسی بیوسیستم، دانشکده کشاورزی، دانشگاه ارومیه

چکیده

چکیده 
اسانس گیاهان دارویی براساس میزان ماده موثره موجود در آن­ها در صنایع داروسازی و غذایی ارزش­ گذاری و استفاده می­ شود. یکی از روش­های کارآمد برای شناسایی و ارزیابی اسانس­ ها بینی الکترونیک می­ باشد که نسبت به روش­ های متداول نقاط ضعف کمتری دارد. در این مطالعه یک سامانه بینی الکترونیک متشکل از 8 حسگر نیمه ­هادی اکسید فلزی(MOS) برای تعیین درجه خلوص اسانس نعناع فلفلی طراحی و ساخته شد. روش PCA برای کاهش ابعاد داده­ها و شناسایی حسگرهای موثر به­کار گرفته شد و روش شبکه عصبی مصنوعی برای طبقه ­بندی داده­ ها استفاده گردید. بر اساس نتایج، روش تحلیل مولفه ­های اصلی با دو مولفه اصلی PC1 و PC2 توانست 82 درصد از واریانس داده­ ها را پوشش دهد. همچنین حسگرهایی که تاثیر بیشتری در تفکیک کلاس­های خلوص اسانس داشتند شناسایی شدند. در ادامه دقت طبقه ­بندی داده­ها در مرحله آموزش و آزمون در روش شبکه عصبی مصنوعی به ترتیب 81 درصد و 70 درصد بدست آمد. بنابراین سامانه بینی الکترونیکی پیشنهادی بر پایه الگوریتم مذکور نشان داد که می­تواند تا حدودی ابزار قابل اعتماد و کم­ هزینه ه­ای جهت درجه­ بندی کیفی نمونه­ های مختلف خلوص اسانس نعناع فلفلی از یکدیگر باشد.

کلیدواژه‌ها

عنوان مقاله [English]

Evaluation of Electronic Nose System Based on Metal Oxide Semiconductor (MOS) Sensors to Detect the Purity of Peppermint Ssential Oil

نویسندگان [English]

  • Mosarreza Samadi 1
  • Seyed Sadegh Seyedloo 1
  • Abbas Rouhani 2
  • Ali Mohammad Nikbakhat 3
1 Department of Biosystems Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, Iran.
2 Department of Biosystems Engineering, Faculty of Agriculture, University of Fedosi Mashhad, Mashhad, Iran.
3 Department of Biosystems Engineering, Faculty of Agriculture, University of Urmia, Urmia, Iran.
چکیده [English]

Abstract
The essential oils of medicinal plants are evaluated and used in the pharmaceutical and food industry based on the amount of active ingredients in them. One of the effective methods for identifying and evaluating essential oils is the electronic nose, which has fewer weaknesses than conventional methods. In this study, an electronic nose system consisting of 8 metal oxide semiconductor sensors was designed to determine the purity of peppermint essential oil. The PCA method was used to reduce the size of the data and identify effective sensors, and the artificial neural network method was used to calculate the accuracy of data classification. Based on the results, the principal component analysis method with two main components PC1 and PC2 was able to explain 82% of the variance of the data. Sensors that had a greater impact on the separation of essential oil purity classes were also identified. The accuracy of data classification in the training and testing stages in the artificial neural network method was 81% and 70%, respectively. Therefore, the proposed electronic nose system based on the mentioned algorithm is a reliable and low-cost tool for qualitative grading of different samples of purity of peppermint essential oil from each other.
 

 

کلیدواژه‌ها [English]

  • Keywords: Essential oil
  • Electronic nose
  • Principal component analysis
  • Artificial neural network
  • Quality control

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مکانیزاسیون کشاورزی
دوره 6، شماره 2
تیر 1400
صفحه 31-37

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سابقه مقاله

  • تاریخ دریافت: 02 شهریور 1400
  • تاریخ پذیرش: 02 شهریور 1400

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