Establishment of phenotyping routines for assessing tolerance levels to syndrome "Basses Richesses" of different Beta vulgaris varieties

Syndrome "Basses Richesses" (SBR) is a severe, fast spreading bacterial disease in sugar beet. The predominant causal agent of SBR is Candidatus Arsenophonus phytopathogenicus (ARSEPH), a y-3 proteobacterium. This agent is mainly transmitted to sugar beet plants via the plant hopper species Pentastiridius leporinus (reed glass-winged cicada). An outbreak of SBR reduces the sugar content and fresh mass of the taproot profoundly, causing sugar beet cultivation to be non-profitable for growers. The absence of effective control measures against SBR poses a significant threat to the entire sugar beet value chain in Europe. Sugar beet varieties which present a mitigation to the substantial yield loss have been discovered but robust screening methods for such varieties are needed. This thesis presents a set of phenotyping routines that facilitate the assessment of different sugar beet varieties' levels of tolerance to SBR. The creation of diseased plant material was achieved by subjecting sugar beets to inoculation with infective P. leporinus adults under controlled conditions. The ARSEPH-infected sugar beets were subjected to investigation through the application of non-invasive, invasive, time series and endpoint digital phenotyping methods. A comprehensive hyperspectral imaging (HSI) data quality assurance pipeline has been developed. This pipeline served as the basis for a HSI time series investigation of the SBR pathogenesis to identify the most important wavelengths and canopy parts for disease classification via machine learning (ML). The morphological alterations of the canopy and taproot were parametrized using two- and three-dimensional measurements. To provide a contextual framework of the SBR-induced canopy and taproot alterations for the host-pathogen interaction, an analysis of selected physiological parameters was conducted on ARSEPH-infected taproots. The analysis of alcohol insoluble residues and marc content indicates an increase of structural components in tolerant varieties induced by SBR, a finding corroborated by increased tissue strength. This thesis demonstrates the applicability of digital phenotyping methods to comprehensively parameterize and characterize the pathogenesis of systemic plant diseases, such as SBR. The findings of this thesis lay the basis for the establishment of a high-throughput screening method for the assessing of SBR-tolerance levels of different sugar beet varieties under controlled conditions.