Discrimination of Golab apple storage time using acoustic impulse response and LDA and QDA discriminant analysis techniques

Document Type: Full Article


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


ABSTRACT- Firmness is one of the most important quality indicators for apple fruits, which is highly correlated with the storage time. The acoustic impulse response technique is one of the most commonly used nondestructive detection methods for evaluating apple firmness. This paper presents a non-destructive method for classification of Iranian apple (Malus domestica Borkh. cv. Golab) according to the duration of storage. Several data preprocessing methods were tested: normalization, detrending, Savitzky-Golay smoothing, first and second derivatives, multiplicative scatter correction, standard normal variate and moving average. It was observed that the maximum average Fβ value of classification on the test dataset (0.84) belongs to non-preprocessing. In this study, principal component analysis (PCA) technique was performed to determine the key variables that explain most differences in the spectra. Seven principal components were used to calibrate linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) classifiers. The classification accuracy for LDA and QDA models were about 80.56% and 83.33%, respectively. The results indicated that the acoustic impulse response method is potentially applicable for the detection of apple firmnes


Article Title [Persian]

طبقه‏ بندی سیب گلاب براساس زمان نگهداری با استفاده از پاسخ فرکانسی و روش‏‏های تجزیه و تحلیل تشخیصی LDA و QDA

Authors [Persian]

  • مجید لشگری
  • رضا محمدی‏ گل
بخش مکانیک بیوسیستم، دانشکده کشاورزی، دانشگاه اراک، اراک، ج. ا. ایران
Abstract [Persian]

چکیده- سفتی بافت یکی از مهمترین شاخص‏های کیفیت برای میوه سیب به شمار می‏آید که همبستگی بالایی با زمان نگهداری دارد. یکی از رایج‏ترین روش‏های تشخیص غیرمخرب برای ارزیابی سفتی سیب، پاسخ فرکانسی است. این مقاله روشی غیرمخرب برای طبقه‏بندی سیب رقم گلاب براساس زمان نگهداری ارائه می‏نماید. روش‏های متعدد پیش‏پردازش داده از جمله هنجارسازی، شیب‏گیری، هموارسازی ساویتزکی-گولای، مشتق‏گیری اول و دوم، تصحیح پراکنش افزاینده، توزیع نرمال استاندارد و میانگین‏‏گیری متحرک مورد بررسی قرار گرفت. مشاهده شد که بیشینه مقدار معیار Fβ مربوط به وضعیت بدون پیش‏پردازش بوده و مقدار آن برابر 84/0 به‏دست آمد. در این تحقیق روش PCA برای تعیین متغیرهای اصلی که بیانگر بیشترین تفاوت در طیف فرکانسی است مورد استفاده قرار گرفت. تعداد هفت مولفه اصلی برای کالیبره‏کردن مدل‏های LDA و QDA مورد استفاده قرار گرفت. دقت طبقه‏بندی برای مدل‏های تحلیل تفکیک خطی و درجه دوم به ترتیب 56/80 و 33/83 درصد به‏دست آمد. نتایج نشان دادند که روش پاسخ فرکانسی از توانمندی بالایی برای تشخیص بافت میوه سیب برخوردار است.

Keywords [Persian]

  • واژه های کلیدی:
  • سفتی
  • روش غیر مخرب
  • پیش‏پردازش
  • تحلیل مولفه‏های اصلی
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