نوع مقاله : مقاله پژوهشی
نویسندگان
1 گروه فنی کشاورزی،پردیس ابوریحان،دانشگاه تهران،
2 دانشیار گروه فنی کشاورزی، پردیس ابوریحان، دانشگاه تهران، تهران
3 گروه مهندسی بیوسیستم- دانشگاه شهر کرد
چکیده
کلیدواژه‌ها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Health and security of foods are recognized as one of the most important human priorities, so effective and new policies have been implemented to improve and develop the position of effective laws in the food industry. Extra Virgin Olive Oil (EVOO) has many amazing benefits for the human body's health. Due to the nutritional value and high price of EVOO, there is a lot of adulteration in it. The ultrasonic approach has many advantages in the food studies, it is fast and non-destructive. In this study, to fraud detection of EVOO four ultrasonic properties of oil in five levels of adulteration (5%, 10%, 20%, 35% and 50%) were extracted. The 2 MHz ultrasonic probes were used in the DOI 1000 STARMANS diagnostic ultrasonic device in a "probe holding mechanism". The four extracted ultrasonic features include: "percentage of amplitude reduction, time of flight (TOF), the difference between the first and second maximum amplitudes of the domain (in the time-amplitude diagram) and the ratio of the first and second maximum of amplitude". Seven classification algorithms include "Naïve Bayes, support vector machine, gradient boosting classifier, K-nearest neighbors, artificial neural network, logistic regression and Ada-Boost" were used to classifying the pre-processed data. Results showed that the Naïve Bayes algorithm with 90.2% provided the highest accuracy among the others, and the SVM and GBC with 88.2% were in the next ranks after Naïve Bayes.
کلیدواژه‌ها [English]
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