Knowledge of the reflectance spectrum of grape leaves is important to the identification of grape varieties in images of viticultural regions where several cultivars co-exist. As a non-destructive technique, spectroradiometry delivers reflectance spectra with high signal-to-noise ratios.
This work reports results from field measurements of the reflectance spectra of five grape varieties in the spectral range 450nm to 2500nm, performed in south Brazil. Four viticultural regions were visited, with different soils originated from basalt, granite, and sandstone. In vivo measurements of Cabernet Sauvignon, Merlot, Pinot Noir, Chardonnay and Italian Riesling were performed. All spectra were normalized to have unit area and were compared. The very high signal/noise ratio allowed the systematic detection of subtle spectral features of each variety, with intensities of the order of 10-4 to 10-5 with respect to the normalized reflectance range from 0 to 1. These spectral features were attributed to differentiation factors as the presence of pigments in leaves, which has an impact in leaf texture and so in infrared reflectance. Spectral differentiation due to terroir effects was also investigated.
The spectral database was subjected to statistical discriminant analysis to search for separation either of grape varieties and terroirs/regions. Grape varieties and terroirs were separated to accuracies of up to 100%. This methodology can be applied to zoning studies which look for typicity parameters; besides, a detailed knowledge of the spectral signatures of grape varieties can be relevant to the development of identification algorithms used to classify remote sensing images of viticultural regions where several cultivars are present, and to in-field inspections using radiometers.
Authors: Jorge Ricardo DUCATI (1), Magno G. BOMBASSARO (1), Diniz C. ARRUDA (1), Virindiana C. BORTOLOTTO (2), Rosemary HOFF (3)
(1) Remote Sensing Center, Universidade Federal do Rio Grande do Sul, Av. Bento Goncalves 9500, CEP 91501-970 Porto Alegre, Brazil
(2) Instituto de Ciências Agrárias e Ambientais, Universidade Federal de Mato Grosso, Av. Alexandre Ferronato 1200, CEP 78557-267 Sinop, Brazil
(3) Centro Nacional de Pesquisas em Uva e Vinho, Empresa Brasileira de Pesquisa Agropecuária, Rua Livramento 515, CEP 95700-000 Bento Goncalves, Brazil
Email: ducati@if.ufrgs.br
Keywords: Remote Sensing, Spectroradiometry, Soils, Reflectance, Classification