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Proceedings Paper

Detecting red blotch disease in grape leaves using hyperspectral imaging
Author(s): Mehrube Mehrubeoglu; Keith Orlebeck; Michael J. Zemlan; Wesley Autran
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Paper Abstract

Red blotch disease is a viral disease that affects grapevines. Symptoms appear as irregular blotches on grape leaves with pink and red veins on the underside of the leaves. Red blotch disease causes a reduction in the accumulation of sugar in grapevines affecting the quality of grapes and resulting in delayed harvest. Detecting and monitoring this disease early is important for grapevine management. This work focuses on the use of hyperspectral imaging for detection and mapping red blotch disease in grape leaves. Grape leaves with known red blotch disease have been imaged with a portable hyperspectral imaging system both on and off the vine to investigate the spectral signature of red blotch disease as well as to identify the diseased areas on the leaves. Modified reflectance calculated at spectral bands corresponding to 566 nm (green) and 628 nm (red), and modified reflectance ratios computed at two sets of bands (566 nm / 628 nm, 680 nm / 738 nm) were selected as effective features to differentiate red blotch from healthy-looking and dry leaf. These two modified reflectance and two ratios of modified reflectance values were then used to train the support vector machine classifier in a supervised learning scheme. Once the SVM classifier was defined, two-class classification was achieved for grape leaf hyperspectral images. Identification of the red blotch disease on grape leaves as well as mapping different stages of the disease using hyperspectral imaging are presented in this paper.

Paper Details

Date Published: 23 May 2016
PDF: 8 pages
Proc. SPIE 9840, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXII, 98400D (23 May 2016); doi: 10.1117/12.2223814
Show Author Affiliations
Mehrube Mehrubeoglu, Texas A&M Univ. Corpus Christi (United States)
Keith Orlebeck, Surface Optics Corp. (United States)
Michael J. Zemlan, Surface Optics Corp. (United States)
Wesley Autran, Surface Optics Corp. (United States)

Published in SPIE Proceedings Vol. 9840:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXII
Miguel Velez-Reyes; David W. Messinger, Editor(s)

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