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Quantitative and qualitative phenotyping of disease resistance of crops by hyperspectral sensors: seamless interlocking of phytopathology, sensors, and machine learning is needed!

  • Autor/in: Mahlein, A.-K., M.T. Kuska, S. Thomas, M. Wahabzada, J. Behmann, U. Rascher, K. Kersting
  • Jahr: 2019
  • Zeitschrift: Current Opinion in Plant Biology (50)
  • Seite/n: 156-162

Abstract

Determination and characterization of resistance reactions of crops against fungal pathogens are essential to select resistant genotypes. In plant breeding, phenotyping of genotypes is realized by time consuming and expensive visual plan tratings. During resistance reactions and during pathogenesis plants initiate different structural and biochemical defence mechanisms, which partly affect theoptical properties of plant organs. Recently, intensive research has been conducted to develop innovative optical methods for an assessmen tof compatible and incompatible plant pathogen interaction. These approaches, combining classical phytopathology ormicrobiology with technology driven methods—such as sensors, robotics, machine learning, and artificia lintelligence -are summarized by the term digital phenotyping. In contrast to common visual rating, detection and assessment methods, optical sensors in combination with advanced data analysis methods are able to retrieve pathogen induced changes in the physiology of susceptible orresistant plants non-invasively and objectively. Phenotyping disease resistance aims different tasks. In an early breeding step, aqualitative assessment and characterization of specific resistance actionis aimed to link it ,for example, to agenetic marker .Later, during greenhouse and field screening, the assessment of the level of susceptibility of different genotypes is relevant. Within this review, recent advances of digital phenotyping technologies for the detection of subtle resistance reactions and resistance breeding are highlighted and methodological requirements are critically discussed.
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