Hyperspectral phenotyping of the reaction of grapevine genotypes to Plasmopara viticola.

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.

Metabolic characterization of Palatinate German white wines according to sensory attributes, varieties, and vintages using NMR spectroscopy and multivariate data analyses.

(1)H NMR (nuclear magnetic resonance spectroscopy) has been used for metabolomic analysis of 'Riesling' and 'Mueller-Thurgau' white wines from the German Palatinate region. Diverse two-dimensional NMR techniques have been applied for the identification of metabolites, including phenolics. It is shown that sensory analysis correlates with NMR-based metabolic profiles of wine. (1)H NMR data in combination with multivariate data analysis methods, like principal component analysis (PCA), partial least squares projections to latent structures (PLS), and bidirectional orthogonal projections to latent structures (O2PLS) analysis, were employed in an attempt to identify the metabolites responsible for the taste of wine, using a non-targeted approach. The high quality wines were characterized by elevated levels of compounds like proline, 2,3-butanediol, malate, quercetin, and catechin. Characterization of wine based on type and vintage was also done using orthogonal projections to latent structures (OPLS) analysis. 'Riesling' wines were characterized by higher levels of catechin, caftarate, valine, proline, malate, and citrate whereas compounds like quercetin, resveratrol, gallate, leucine, threonine, succinate, and lactate, were found discriminating for 'Mueller-Thurgau'. The wines from 2006 vintage were dominated by leucine, phenylalanine, citrate, malate, and phenolics, while valine, proline, alanine, and succinate were predominantly present in the 2007 vintage. Based on these results, it can be postulated the NMR-based metabolomics offers an easy and comprehensive analysis of wine and in combination with multivariate data analyses can be used to investigate the source of the wines and to predict certain sensory aspects of wine.