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Proceedings Paper

Application of laser to nondestructive detection of fruit quality
Author(s): Jing Li; Long Xue; Muhua Liu; Zhanlong Li; Yong Yang
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Paper Abstract

In this study, a hyperspectral imaging system using a laser source was developed and two experiments were carried out. The first experiment was detection of pesticide residue on navel orange surface. We calculated the mean intensity of regions of interest to plot the curves between 629nm to 638nm. The analysis of the mean intensity curves showed that the mean intensity can be described by a characteristic Gaussian curve equation. The coefficients a in characteristic equations of 0%, 0.1% and 0.5% fenvalerate residue images were more than 2400, 1570-2400 and less than 1570, respectively. So we suggest using equation coefficient a to detect pesticide residue on navel orange surface. The second experiment was predicting firmness, sugar content and vitamin C content of kiwi fruit. The optimal wavelength range of the kiwi fruit firmness, sugar content, vitamin C content line regressing prediction model were 680-711nm, 674-708nm, 669-701nm. The correlation coefficients (R) of prediction models for firmness, sugar content and vitamin C content were 0.898, 0.932 and 0.918. The mean errors of validation results were 0.35×105Pa, 0.32%Brix and 7mg/100g. The experimental results indicate that a hyperspectral imaging system based on a laser source can detect fruit quality effectively.

Paper Details

Date Published: 18 February 2009
PDF: 6 pages
Proc. SPIE 7276, Photonics and Optoelectronics Meetings (POEM) 2008: Laser Technology and Applications, 72760R (18 February 2009); doi: 10.1117/12.823295
Show Author Affiliations
Jing Li, Jiangxi Agricultural Univ. (China)
Long Xue, East China JiaoTong Univ. (China)
Muhua Liu, Jiangxi Agricultural Univ. (China)
Zhanlong Li, Jiangxi Agricultural Univ. (China)
Yong Yang, Jiangxi Agricultural Univ. (China)


Published in SPIE Proceedings Vol. 7276:
Photonics and Optoelectronics Meetings (POEM) 2008: Laser Technology and Applications
Peixiang Lu; Katsumi Midorikawa; Bernd Wilhelmi, Editor(s)

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