Hazelnut Quality Sorting Using High Dynamic Range Short-Wave Infrared Hyperspectral Imaging
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A rapid, robust, unbiased, and inexpensive discriminant method capable of classifying hazelnut (Corylus avellana, L.) in compliance with the statements set out by the Commission Regulation (EC) No. 1284/2002 is economically important to the fresh and processed industries. Thus, in this study, the feasibility of high dynamic range (HDR) hyperspectral imaging for hazelnut kernel sorting (cv. Tonda Gentile Romana) of four quality classes (Class Extra, Class I, Class II, and Waste) has been investigated. Two different exposure times (5 and 8 ms) were selected for experiments, and the respective spectra were combined to obtain a HDR over the full spectral range. The illumination setup was optimized to improve the intensity and uniformity of the light along the field of view of the camera. PLS-DA was used to classify the kernels based on their spectra and the spectral pretreatment was optimized through an iterative routine. The performance of each PLS-DA model was defined based on its accuracy, sensitivity, and selectivity rates. All of the selected models provided a very good (>90 %) or good (>80 %) sensitivity and selectivity for the predefined classes. Misclassified kernels were primarily assigned to the low-quality classes (i.e., Class II and Waste). Moreover, the spatial domain was used to evaluate the feasibility of distinguishing hazelnut classes on the basis of their size and shape. It was found that hazelnut dimensions can be used to improve the accuracy of the classification of the kernels. Thanks to this combination of both spectral and spatial information spectral imaging could be used for quality sorting of hazelnuts.
KeywordsCorylus avellana L Tonda gentile romana Computer vision SWIR PLS-DA
This research has been financially supported by Mipaaf through the project “Miglioramento della filiera corilicola laziale - Mi.F.CO.L.” represented by the “AOP Nocciola Italia Soc. Cons. s.r.l” and “CeFAS - Azienda speciale CCIAA Viterbo”. The authors gratefully acknowledge I.W.T.-Flanders for the financial support through the Chameleon project (IWT 100021).
- Alasalvar, C., & Shahidi, F. (2008). In C. Alasalvar & F. Shahidi (Eds.), Tree nuts: Composition, phytochemicals, and health effects (1st ed.). Boca Raton: CRC Press.Google Scholar
- Boysworth, M. K., & Booksh, K. S. (2008). Aspects of multivariate calibration applied to near-infrared spectroscopy. In D. A. Burns & E. W. Ciurczak (Eds.), Handbook of near-infrared analysis (3rd ed., pp. 207–229). New York, USA: CRC Press.Google Scholar
- Capinera, J. L. (2001). Order Hemiptera—bugs. In Handbook of vegetable pests (pp. 243–278). New York: Academic.Google Scholar
- European Commission. (2002). Commission Regulation (EC) No. 1284/2002 of 15 July 2002 laying down the marketing standard for hazelnuts in shell. Official Journal of the European Union (L), 187, 14–20.Google Scholar
- Massantini, R., Moscetti, R., Monarca, D., Cecchini, M., Contini, M., & Mordacchini, L. (2009). The influence of cover crops and double harvest on storage of fresh hazelnuts (Corylus avellana L.). Advances in Horticultural Science, 23(4), 231–237.Google Scholar
- Miles, P. W. (1972). The saliva of hemiptera. Advances in Insect Physiology, 9, 183–255.Google Scholar
- Montgomery, D. C. (2001). Design and analysis of experiments (5th ed., p. 699). New York: Wiley.Google Scholar
- Naes, T., Isaksson, T., Fearn, T., & Davies, T. (2004). A user-friendly guide to multivariate calibration and classification (p. 344). Chichester, UK: NIR publications.Google Scholar
- USDA. (2014). National nutrient database for standard reference—release 26. URL http://ndb.nal.usda.gov/ndb/search/list. Accessed 03.12.14.
- Vaccinio, P., Guidone, L., Corbellini, M., & Tavella, L. (2008). Detection of damage due to bug feeding on hazelnut and wheat by biochemical techniques. Bulletin of Insectrology, 61(1), 189–190.Google Scholar
- Wise, B. M. (2009). Eigen vector research wiki - using cross-validation. URL http://wiki.eigenvector.com. Accessed 02.21.2014.
- Workman, J., & Weyer, L. (2008). Practical guide to interpretive near-infrared spectroscopy (p. 344). London: CRC Press.Google Scholar