Hyperspectral phenotyping of the reaction of grapevine genotypes to Plasmopara viticola

Abstract

A major aim in grapevine breeding is the provision of cultivars resistant to downy mildew. As Plasmopara viticola produces sporangia on the abaxial surface of susceptible cultivars, disease symptoms on both leaf sides may be detected and quantified by technical sensors. The response of cultivars 'Mueller-Thurgau', 'Regent', and 'Solaris', which differ in resistance to P. viticola, was characterized under controlled conditions by using hyperspectral sensors. Spectral reflectance was suitable to differentiate between non-infected cultivars and leaf sides of the bicolored grapevine. Brown discoloration of tissue became visible on both leaf sides of resistant cultivars 2 days before downy mildew symptoms appeared on the susceptible 'Mueller-Thurgau' cultivar. Infection of this cultivar resulted in significant (P<0.05) reflectance changes 1-2 days prior to abaxial sporulation induced by high relative humidity, or the formation of adaxial oil spots. Hyperspectral imaging was more sensitive in disease detection than non-imaging and provided spatial information on the leaf level. Spectral indices provided information on the variability of chlorophyll content, photosynthetic activity, and relative water content of leaf tissue in time and space. On 'Mueller-Thurgau' downy mildew translated reflectance to higher values as detectable by the index DMI_3=(R₄₇₀+R₆₈₂+R₈₀₀)/(R₈₀₀/R₆₈₂) and affected reflectance at 1450nm. Tissue discoloration on 'Regent' and 'Solaris' cultivars was associated with lower reflectance between 750 and 900nm; blue and red reflectance demonstrated differences from leaf necroses. With high inoculum densities, P. viticola sporulated on even resistant cultivars. Hyperspectral characterization at the tissue level proved suitable for phenotyping plant resistance to pathogens and provided information on resistance mechanisms.

Keywords: Plasmopara viticola; Disease resistance; downy mildew; grapevine; hyperspectral analysis; imaging; phenotyping; spectral signature..