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Hyperspectral fluorescence imaging for disease monitoring and yield estimation of mandarin orange (Conference Presentation)
Author(s): Jayoung Lee; Irina T. Rodriguez; Hyungjin Bae; Jihoon Bae; Hee-Young Lee; Ana G. Varo; Dolores P. Marin; Byoungkwan Cho
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Paper Abstract

Mandarin orange is a popularly consumed fruit in Asian countries. Over 99% of cultivation area in Korea for mandarin oranges is concentrated in Jeju Island. Despite of this high concentration, detecting infection and estimating fruit yields has been done manually, resulting in loss of money and time. In this study, hyperspectral fluorescence imaging technique was explored to distinguish green mandarin oranges from leaves to estimate fruit density. In addition, early stage detection for disease infection of leaves and fruits were investigated. The fluorescence spectral images showed reliable performance for distinguishing green mandarin oranges from leaves, and detecting disease infection on both leaves and fruits. The result demonstrated that hyperspectral fluorescence imaging might be used for rapid and non-destructive detection of disease infection and yield estimation of mandarin orange in the field.

Paper Details

Date Published: 15 May 2018
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Proc. SPIE 10665, Sensing for Agriculture and Food Quality and Safety X, 1066508 (15 May 2018); doi: 10.1117/12.2307705
Show Author Affiliations
Jayoung Lee, Chungnam National Univ. (Korea, Republic of)
Irina T. Rodriguez, Univ. de Córdoba (Spain)
Hyungjin Bae, Chungnam National Univ. (Korea, Republic of)
Jihoon Bae, Chungnam National Univ. (Korea, Republic of)
Hee-Young Lee, Life & Technology (Korea, Republic of)
Ana G. Varo, Univ. de Córdoba (Spain)
Dolores P. Marin, Univ. de Córdoba (Spain)
Byoungkwan Cho, Chungnam National Univ. (Korea, Republic of)


Published in SPIE Proceedings Vol. 10665:
Sensing for Agriculture and Food Quality and Safety X
Moon S. Kim; Kuanglin Chao; Bryan A. Chin; Byoung-Kwan Cho, Editor(s)

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