طبقهبندی ارقام مختلف برنج ایرانی و برنج تقلبی بر اساس ترکیبات فرار شناسایی شده با روش بینی الکترونیکی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانش آموخته کارشناسی ارشد دانشکده مهندسی و فناوری کشاورزی، دانشگاه تهران، کرج، ایران

2 استاد دانشکده مهندسی و فناوری کشاورزی، دانشگاه تهران، کرج، ایران

چکیده

عطر و رایحه برنج یکی از ویژگی های مهم در بررسی کیفیت و موثر در میزان بازارپسندی آن است. در این پژوهش از یک سامانه بینی الکترونیکی متشکل از شش حسگر نیمه‌هادی اکسید فلزی به‌عنوان یک روش غیرمخرب در بررسی امکان تفکیک ارقام مختلف برنج ایرانی و یک نوع برنج تقلبی که از تقلب های رایج در عرضه برنج است، استفاده‌شده است. روش تحلیل مؤلفه‌های اصلی با دو مؤلفه اصلی قادر بود 89% از واریانس (تغییرات) داده‌ها را برای پنج نمونه از ارقام اصلی برنج را پوشش دهد. همچنین این تحلیل توسط دو مؤلفه اصلی اول و دوم، 96% از واریانس داده‌ها را برای چهار نمونه برنج که شامل دو رقم برنج اصلی و دو نمونه برنج تقلبی است، را توصیف کند. با استفاده از روش‌ تحلیل تفکیک خطی، دقت %100  برای هر دو گروه از نمونه‌ها به دست آمد. دقت شبکه عصبی مصنوعی در طبقه‌بندی نمونه ها، 6/98% برای تفکیک دو گروه ارقام ایرانی و نمونه‌های اختلاطی به دست آمد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Classification of Different Iranian Rice Varieties and Frauded Rice Based on Volatile Compounds Detected by Electronic Nose Method

نویسندگان [English]

  • Bahlool Ramesh 1
  • Seyed Saeid Mohtasebi 2
  • shahin rafiee 2
1 M.Sc. Graduated, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran
2 Professor, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran
چکیده [English]

Rice aroma is one of the important features of rice quality which affects its marketability. In this study, an electronic system consisting of six semiconductor metal oxide sensors was used as a non-destructive method for the separation of Iranian rice varieties and a frauded rice sample, which is a kind of common fraud in rice supply. Analysis of PCA with two main components covered 89% of the variance (variation) of the data for five original rice samples. Also, described 96% of the variance of data for four rice samples, which included two varieties of rice and two fraud samples using LDA method with the accuracy of 100%. The precision of the ANN method was obtained as 98.6% for separation of the two groups of Iranian varieties and the frauded samples.

کلیدواژه‌ها [English]

  • Iranian rice
  • frauded rice
  • electronic nose
  • pattern recognition

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