The potential of spectral reflectance technique for the detection of Grapevine leafroll-associated virus-3 in two red-berried wine grape cultivars

By R. Naidu, E. Perry, F. Pierce, T. Mekuria. 2009

250 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/ea9b9eb0c4323542ace6977ce913bc33fdcd1a7b

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In Ecology

In Plant Science

Citations in the corpus

Spectral discrimination of healthy and Ganoderma-infected oil palms from hyperspectral data (2011, background): “The results in this study do agree with other published data (Schmidt and Skidmore 2002, Naidu et al. 2009) that indicate that the visible, red and infrared regions do feature important wavelengths for disease detection in vegetation.”
Advanced methods of plant disease detection. A review (2014, unknown): “…RS: Fiji leaf gall sugarcane disease (Purcell et al. 2009), wheat powdery mildew and take-all disease (Graeff et al. 2006), curl mite (Stilwell et al. 2013), sugarcane yellow leaf virus (Grisham et al. 2010), grapevine viruses (Naidu et al. 2009), and winter wheat yellow rust (Zhang et al. 2014).”
Comparison of two aerial imaging platforms for identification of Huanglongbing-infected citrus trees (2013, background): “For instance, Naidu et al. (2009) identified viral infection (leafroll) in grapevines (Vitis vinifera L.) under field conditions using leaf spectral response from field portable spectrometer equipped with a leaf-probe.”
Visible-near infrared spectroscopy for detection of Huanglongbing in citrus orchards (2011, methodology): “For example, Naidu et al. (2009) applied visibleinfrared spectroscopy (350–2500 nm) for detecting grapevine leafroll disease.”
Spectral signatures of sugar beet leaves for the detection and differentiation of diseases (2010, methodology): “Optical methods such as hyper-spectral imaging and non-imaging sensors have been proved to be a useful tool to detect changes in plant vitality (Hatfield et al. 2008; Nilsson 1995; West et al. 2003).”
Early detection of basal stem rot disease (Ganoderma) in oil palms based on hyperspectral reflectance data using pattern recognition algorithms (2014, background): “…vegetation indices (VIs), showed the ability to distinguish between healthy and diseased plants due to the changes in plant biophysiological parameters caused by the diseases (Steddom et al. 2003; Delalieux et al. 2009; Naidu et al. 2009; Sankaran and Ehsani 2011; Zhang, Pu, Huang, et al. 2012).”
Spectral analysis of winter wheat leaves for detection and differentiation of diseases and insects (2014, methodology): “Photochemical reflectance index (PRI) and Aphid Index (AI) have been used for disease/insect detection (Naidu et al., 2009; Mirik et al., 2006).”