Prediction of watermelon quality based on vibration spectrum |
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| Institution: | 1. Agricultural Institute, Iranian Research Organization for Science and Technology, Faculty of Agricultural Engineering and Technology, Tehran University, Karaj, Iran;2. Faculty of Agricultural Engineering and Technology, Tehran University, Karaj, Iran;3. Faculty of Mechanical Engineering, Tehran University, Tehran, Iran;4. Faculty of Agricultural Sciences and Engineering, Tehran University, Karaj, Iran;1. School of Agriculture, Meiji University, Kawasaki, Kanagawa 214-8571, Japan;2. School of Science and Technology, Department of Physics, Meiji University, Kawasaki, Kanagawa 214-8571, Japan;3. Hagihara Farm Co., LTD., Tawaramoto, Shiki, Nara 636-0222, Japan;1. Agricultural Institute, Iranian Research Organization for Science and Technology, Iran;2. Faculty of Agricultural Engineering and Technology, Tehran University, Karaj, Iran;3. Faculty of Mechanical Engineering, Tehran University, Tehran, Iran;4. Faculty of Agricultural Sciences and Engineering, Tehran University, Karaj, Iran;1. Department of Biosystems and Agricultural Engineering, University of Kentucky, Lexington, KY 40503, USA;2. Department of Electrical and Computer Engineering, University of Kentucky, Lexington, KY 40508, USA;3. Department of Entomology, University of Kentucky, Princeton, KY 42445-0469, USA;1. Institute of Agricultural Engineering, Tropics and Subtropics Group, Universität Hohenheim, Garbenstrasse 9,70599 Stuttgart, Germany;2. Department of Food Technology, Faculty of Engineering and Industrial Technology, Silpakorn University, 73000 Nakhon Pathom, Thailand;1. Rural and Agri-food Engineering Department, Universitat Politècnica de València, Valencia, 46022, Spain;2. Instituto Universitario de Automática e Informática Industrial, Universitat Politècnica de València, Valencia, 46022, Spain |
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| Abstract: | Judging watermelon quality based on its apparent properties such as size or skin color is difficult. A non-destructive method is employed here, based on vibrational response spectrum, to determine the quality indices of watermelon (Charleston gray). The responses of samples to vibration excitation were recorded by laser Doppler vibrometry (LDV). The phase shift between input and output signals were extracted over a wide frequency range. The total soluble solids (TSS), titratable acidity (TA) and TSS/TA ratio also measured as watermelon quality characters. Stepwise multiple linear regression (SMLR) as well as partial least square regression (PLS) was applied to extracted vibration spectrums to construct prediction models of watermelon quality. The results showed that performance of SMLR models were better than PLS. The determination coefficients (R2) of SMLR validation models were 0.9976, 0.9985 and 0.9542 for TSS, TA and TSS/TA respectively. It is likely that reduction of cell wall materials to soluble solids during ripening process changes viscoelastic properties of watermelon reflected by vibrational response. This study demonstrated the feasibility of mentioned method for predicting the quality of watermelons in an industrial grading system. |
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| Keywords: | Watermelon quality Laser Doppler vibrometry Phase shift Vibration spectrum Stepwise multiple linear regression Partial least square |
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