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Hyperspectral Sensors and Imaging Technologies in Phytopathology: State of the Art.
Mahlein, A-K; Kuska, M T; Behmann, J; Polder, G; Walter, A.
Afiliação
  • Mahlein AK; Institute of Sugar Beet Research (IfZ), 37079 Göttingen, Germany; email: mahlein@ifz-goettingen.de.
  • Kuska MT; Institute of Crop Science and Resource Conservation (INRES)-Plant Diseases and Plant Protection, University of Bonn, 53115 Bonn, Germany.
  • Behmann J; Institute of Crop Science and Resource Conservation (INRES)-Plant Diseases and Plant Protection, University of Bonn, 53115 Bonn, Germany.
  • Polder G; Greenhouse Horticulture, Wageningen University and Research, 6708PB Wageningen, Netherlands.
  • Walter A; Institute of Agricultural Sciences, ETH Zürich, 8092 Zürich, Switzerland.
Annu Rev Phytopathol ; 56: 535-558, 2018 08 25.
Article em En | MEDLINE | ID: mdl-30149790
ABSTRACT
Plant disease detection represents a tremendous challenge for research and practical applications. Visual assessment by human raters is time-consuming, expensive, and error prone. Disease rating and plant protection need new and innovative techniques to address forthcoming challenges and trends in agricultural production that require more precision than ever before. Within this context, hyperspectral sensors and imaging techniques-intrinsically tied to efficient data analysis approaches-have shown an enormous potential to provide new insights into plant-pathogen interactions and for the detection of plant diseases. This article provides an overview of hyperspectral sensors and imaging technologies for assessing compatible and incompatible plant-pathogen interactions. Within the progress of digital technologies, the vision, which is increasingly discussed in the society and industry, includes smart and intuitive solutions for assessing plant features in plant phenotyping or for making decisions on plant protection measures in the context of precision agriculture.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doenças das Plantas / Tecnologia de Sensoriamento Remoto / Patologia Vegetal Idioma: En Revista: Annu Rev Phytopathol Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doenças das Plantas / Tecnologia de Sensoriamento Remoto / Patologia Vegetal Idioma: En Revista: Annu Rev Phytopathol Ano de publicação: 2018 Tipo de documento: Article