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Assessment of Watermelon Quality Using Vibration Spectra

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Book cover Innovative Computing Technology (INCT 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 241))

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Abstract

Judging watermelon quality based on its apparent properties such as size or skin color is difficult. Traditional methods have various problems and limitations. In this paper a nondestructive method for quality watermelon test using laser Doppler vibrometery technology (LDV) have been presented which hasn’t some limitations. At first the sample was excited by a vibration generator in a frequency range. Applied vibration was measured using accelerometer attached in resting place of fruit. Synchronically vibrational response of fruit upside was detected by LDV. By means of a fast Fourier transform algorithm and considering response signal to excitation signal ratio, vibration spectra of fruit are analyzed and the first and second resonances were extracted. After nondestructive tests, watermelons were sensory evaluated. So the samples were graded in a range of ripeness by panel members in terms of overall acceptability (total desired traits consumers). Using two mentioned resonances as well as watermelon weight, a multivariate linear regression model to determine watermelon quality scores obtained. Correlation coefficient for calibration model was 0.82. For validation of model leave one out cross validation method was applied and r= 0.78 was achieved. Stepwise discriminant analysis was also used to classify ripe and unripe watermelons. The results showed 87.5% classification accuracy for original and cross validation cases. This study appeared utilization of this technique for watermelons sorting based on their costumer acceptability.

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Abbaszadeh, R., Rajabipour, A., Ahmadi, H., Delshad, M., Mahjoob, M. (2011). Assessment of Watermelon Quality Using Vibration Spectra. In: Pichappan, P., Ahmadi, H., Ariwa, E. (eds) Innovative Computing Technology. INCT 2011. Communications in Computer and Information Science, vol 241. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27337-7_3

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  • DOI: https://doi.org/10.1007/978-3-642-27337-7_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27336-0

  • Online ISBN: 978-3-642-27337-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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