Development of a multispectral imaging system for online quality assessment of pomegranate fruit

Khodabakhshian, R. and Emadi, B. and Khojastehpour, M. and Golzarian, M. R. and Sazgarnia, A. (2017) Development of a multispectral imaging system for online quality assessment of pomegranate fruit. International Journal of Food Properties, 20 (1). pp. 107-118.

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Abstract

The objective of this study was to develop a prototype multispectral imaging system for online quality assessment on pomegranate fruit. At first, a visible/near infrared spectroscopy (400–1100 nm) was tested for non-destructive determination of total soluble solids, titratable acidity, and pH. The spectral data were analyzed using the partial least square analysis. Then to establish consistent multispectral imaging system, the highest absolute values of β-coeffcients correspond to wavelengths from the best partial least square calibration model were selected and used for identifying the optimal wavelengths. Consequently, a multispectral imaging system was developed based on the effective wavelengths 700, 800, 900, and 1000 nm. The performance of the developed multispectral imaging system was evaluated by multiple linear regression models. The multiple linear regression model predict total soluble solids with r = 0.97, root mean square error of calibration = 0.21°Brix, and ratio performance deviation = 6.7 °Brix. Also, the results showed that the models had good predictive ability for pH and titratable acidity. Results showed that the developed multispectral imaging system based on the optimal wavelengths could be used for online quality assessment of pomegranate fruit. © 2017 Taylor & Francis Group, LLC.

Item Type: Article
Additional Information: Cited By :9 Export Date: 16 February 2020 CODEN: IJFPF Correspondence Address: Emadi, B.; Department of Mechanics of Biosystem Engineering, Ferdowsi University of Mashhad, Azadi square, Iran; email: bagheremadi@yahoo.com
Uncontrolled Keywords: Multispectral imaging Optimal wavelengths PLS, MLR Pomegranate Quality Fruits Image quality Infrared spectroscopy Linear regression Mean square error Regression analysis Soil conditioners Multi-spectral imaging systems Multiple linear regression models Optimal wavelength Root mean square error of calibrations Visible/near infrared spectroscopy Imaging systems
Subjects: W General medicine- Health professions
Divisions: Mashhad University of Medical Sciences
Depositing User: mr lib3 lib3
Date Deposited: 03 Mar 2020 10:39
Last Modified: 03 Mar 2020 10:39
URI: http://eprints.mums.ac.ir/id/eprint/16891

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