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
Alfatni, M.S.M., Shariff, A.R.M., Abdullah, M.Z., Marhaban, M.H.B., & Ben Saaed, O.M. (2008). The application of internal grading system technologies for agricultural products – Review. Journal of Food Engineering, 116, 703–725.
Corollaro, M.L., Aprea, E., Endrizzi, I., Betta, E., Demattè, M.L., Charles, M., Bergamaschi, M., Costa, F., Biasioli, F., Grappadelli, L.C., & Gasperi, F. (2014). A combined sensory-instrumental tool for apple quality evaluation. Postharvest Biology and Technology, 96, 135–144.
DeBelie, N., Schotte, S., Coucke, P., & DeBaerdemaeker, J. (2000). Development of an automated monitoring device to quantify changes in firmness of apples during storage. Postharvest Biology and Technology, 18, 1–8.
Diezma-Iglesias, B., Valero, C., García-Ramos, F. J., & Ruiz-Altisent, M. (2006). Monitoring of firmness evolution of peaches during storage by combining acoustic and impact methods. Journal of Food Engineering, 77(4), 926-935.
FAO. (2011). Statistical Database/ faostat/collections. Production crop.
Florkowski, W.J., Shewfelt, R., Brueckner, B., & Prussia, S.E. (2009). Postharvest Handling: A Systems Approach. Academic Press. 615 pages. 
Garcia-Ramos, F.J., Ortiz-Canavate, J., Ruiz-Altisent, M., Diez, J., Flores, L., Homer, I., & Chavez, J. (2003). Development and implementation of an on-line impact sensor for firmness sensing of fruits. Journal of. Food Engineering, 58, 53–57.
Hajizade, H., Mostofi, Y., &  Talaie, A. (2008). Modified atmosphere packaging effects on quality maintenance and storage life extension of local Iranian Apple "Golab Kohanz". Acta Horticulture, 768. 111-116.
Han, J., Kamber, M., & Pei, J. (2012). Data mining: concepts and techniques. Third edition. Morgan Kaufmann.
Harker, F.R., Gunson, F.A., & Jaeger, S.R. (2003). The case of fruit quality: an interpretative review of consumer attitudes, and preferences for apples. Postharvest Biology and Technology, 28, 333–347.
Hastie, T., Tibshirani, R., Friedman, J., Hastie, T., Friedman, J., & Tibshirani, R. (2009). The elements of statistical learning. Vol. 2, No. 1. New York: springer.
Ishikawa, S., & Gulick, V. (2013). An automated mineral classifier using Raman spectra. Computers & Geosciences, 54, 259-268.
IEC 61672. (2002). Electroacoustics- Sound level meters.
IEC 60942. (2003). Electroacoustics- Sound calibrators.
James, G., Witten, D., Hastie, T., & Tibshirani, R. (2014). An Introduction to Statistical Learning: With Applications in R. New York: springer.
Kim, K.B., Lee, S., Kim, M.S., & Cho, B.K. (2009). Determination of apple firmness by nondestructive ultrasonic measurement. Postharvest Biology and Technology, 52, 44–48.
Khalifa, S., Komarizadeh, M.H., & Tousi, B. (2011). Usage of fruit response to both force and forced vibration applied to assess fruit firmness: a review. Australian Journal of Crop Science, 5(5), 516-522.
Lu, R., (2007). Nondestructive measurements of firmness and soluble solids content for apple fruit using hyperspectral scattering images. Sensing and Instrumentation for Food Quality and Safety, 1, 19–27.
Lv, G., Yang, H., Xu, N., & Mouazen, A.M. (2012). Identification of less-ripen, ripen, and over-ripen grapes during harvest time based on visible and near-infrared (Vis-NIR) spectroscopy. In Consumer Electronics, Communications and Networks (CECNet), Second International Conference on IEEE. (1067-1070).
Macrelli, E., Romani, A., Paganelli, R.P., Sangiorgi, E., & Tartagni, M. (2013).  Piezoelectric transducers for real-time evaluation of fruit firmness.Part I: Theory and development of acoustic techniques. Sensors and Actuators, 201, 487– 496.
Mendoza, F., Lu, R., & Cen, H. (2014). Grading of apples based on firmness and soluble solids content using Vis/SWNIR spectroscopy and spectral scattering techniques. Journal of Food Engineering, 125, 59–68.
Mucherino, A., Papajorgji, P., & Paradalos, P.M. (2009). Data mining in agriculture. Vol. 34. Springer Science & Business Media. 272 pages.
Nicolaï, B.M., Beullens, K., Bobelyn, E., Peirs, A., Saeys, W., Theron, K.I., & Lammertyn, J. (2007). Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review. Postharvest Biology and Technology, 46 (2), 99-118.
Peneau, S., Brockhoff, P.B., Hoehn, E., Escher, F., & Nuessli, J. (2007). Relating consumer evaluation of apple freshness to sensory and physico-chemical measurements. Journal of Sensory Studies, 22, 313–335.
Peng, Y., & Lu, R. (2008). Analysis of spatially resolved hyperspectral scattering images for assessing apple fruit firmness and soluble solids content. Postharvest Biology and Technology, 48 (1), 52–62.
Ruiz-Altisent, M., Ruiz-Garcia, L., Moreda, G. P., Lu, R., Hernandez-Sanchez, N., Correa, E. C., Diezma, B., Nicolaï, B., & García-Ramos, J. (2010). Sensors for product characterization and quality of specialty crops-A review. Computers and Electronics in Agriculture, 74(2), 176-194.
Shmulevich, I., Galili, N., & Howarth, M.S. (2003). Nondestructive dynamic testing of apples for firmness evaluation. Postharvest Biology and Technology, 29, 287-299.
Studman, C.J. (2001). Computers and electronics in postharvest technology: a review. Computers and Electronics in Agriculture, 30, 109–124.
Sun, D.W. (2009). Infrared spectroscopy for food quality analysis and control. Academic press. 448 pages.
Tiplica, T., Vandewalle, P., Verron, S., GremyGros, C., & Mehinagic, E. (2010). Identification of apple varieties using acoustic measurements. International metrology conference CAFMET. Cairo, Egypt.
Wang, J., Gomez, A. H., & Pereira, A.G. (2006). Acoustic impulse response for measuring the firmness of mandarin during storage. Journal of food quality, 29(4), 392-404.
Zhang, W., Cui, D., & Ying, Y. (2014). Nondestructive measurement of pear texture by acoustic vibration method. Postharvest Biology and Technology, 96, 99–105.
Zude, M., Herold, B., Roger, J. M., Bellon-Maurel, V., & Landahl, S. (2006). Non-destructive tests on the prediction of apple fruit flesh firmness and soluble solids content on tree and in shelf life. Journal of Food Engineering, 77(2), 254-260.