Acoustic detection of apple mealiness based on support vector machine

Document Type: Full Article


Department of Biosystems Engineering, College of Agriculture, Arak University, Arak, I. R. Iran



Mealiness degrades the quality of apples and plays an important role in fruit market. Therefore, the use of reliable and rapid sensing techniques for nondestructive measurement and sorting of fruits is necessary. In this study, the potential of acoustic signals of rolling apples on an inclined plate as a new technique for nondestructive detection of Red Delicious apple mealiness was investigated. According to destructive confined compression tests, the mealiness of apples was evaluated by the hardness and juiciness measurements. In addition, support vector machine (SVM) models were developed to classify apples. The radial basis function (RBF) as the kernel was used in SVM models. According to exhaustive search method, the model with nine features combination was found to be the best model. Results indicated overall accuracy of 85.5 % to classify apples in mealy and healthy groups. The results indicated that this method is potentially useful for apple mealiness detection.


Article Title [Persian]

تشخیص صوتی آردی شدن سیب براساس ماشین‌بردار پشتیبان

Authors [Persian]

  • مجید لشگری
  • عبداله ایمان مهر
بخش مکانیک بیوسیستم، دانشکده کشاورزی و منابع طبیعی، دانشگاه اراک، اراک، ج. ا. ایران
Abstract [Persian]

آردی‏شدن، کیفیت میوه سیب را تنزل می‏دهد و این پدیده نقش مهمی در بازار میوه ایفا می‏کند. بنابراین استفاده از تکنیکی سریع و قابل اعتماد برای اندازه‏گیری و درجه‏بندی میوه‏ها ضروری است. در این تحقیق، قابلیت سیگنال‏های صوتی سیب‏های غلتان بر روی صفحه شیب‏دار به عنوان روشی نوین در تشخیص غیرمخرب آردی شدن سیب رقم رد دلیشز مورد بررسی قرار گرفت. با استفاده از آزمون مخرب فشردگی محصور، میزان آردی شدن نمونه‏ها ارزیابی شد. مدل‏های ماشین بردار پشتیبان برای طبقه‏بندی سیب‏ها در نظر گرفته شد. از کرنل تابع پایه شعاعی در مدل‏های ماشین بردار پشتیبان استفاده شد. مطابق روش جستجوی جامع، مدلی با ترکیب 9 ویژگی به عنوان بهترین مدل انتخاب شد. نتایج نشان داد که میزان دقت کلی این روش برای تشخیص سیب‏های سالم و آردی برابر 5/85 درصد به دست آمد. نتایج حاکی از آن بود که روش مذکور از توانمندی خوبی برای تشخیص سیب‏های آردی برخوردار است

Keywords [Persian]

  • طبقه‏بندی
  • صفحه شیب‏دار
  • رقم رد دلیشز
  • کرنل تابع پایه شعاعی
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