RESUMO
Massive outbreaks of virus yellows (VY) and syndrome "basses richesses" (SBR) are thought to be responsible for the major loss of sugar beet yields in 2020 in western cantons of Switzerland. Typical yellowing symptoms were visible during field inspections, and control measures were reportedly ineffective or even absent. Both diseases induce yellowing but have distinct etiologies; while VY is caused by aphid-transmitted RNA viruses, SBR is caused by the cixiid-transmitted γ-proteobacterium Candidatus Arsenophonus phytopathogenicus. To clarify the situation, samples from diseased plants across the country were screened for the causal agents of VY and SBR at the end of the season. Beet yellows virus (BYV) and Beet chlorosis virus (BChV) showed high incidence nationwide, and were frequently found together in SBR-infected fields in the West. Beet mild yellowing virus (BMYV) was detected in two sites in the West, while there was no detection of Beet western yellows virus or Beet mosaic virus. The nucleotide diversity of the detected viruses was then investigated using classic and high-throughput sequencing. For both diseases, outbreaks were analyzed in light of monitoring of the respective vectors, and symptoms were reproduced in greenhouse conditions by means of insect-mediated inoculations. Novel quantification tools were designed for BYV, BChV and Ca. A. phytopathogenicus, leading to the identification of specific tissues tropism for these pathogens.
RESUMO
The quantitative resistance of sugar beet (Beta vulgaris L.) against Cercospora leaf spot (CLS) caused by Cercospora beticola (Sacc.) was characterised by hyperspectral imaging. Two closely related inbred lines, differing in two quantitative trait loci (QTL), which made a difference in disease severity of 1.1-1.7 on the standard scoring scale (1-9), were investigated under controlled conditions. The temporal and spatial development of CLS lesions on the two genotypes were monitored using a hyperspectral microscope. The lesion development on the QTL-carrying, resistant genotype was characterised by a fast and abrupt change in spectral reflectance, whereas it was slower and ultimately more severe on the genotype lacking the QTL. An efficient approach for clustering of hyperspectral signatures was adapted in order to reveal resistance characteristics automatically. The presented method allowed a fast and reliable differentiation of CLS dynamics and lesion composition providing a promising tool to improve resistance breeding by objective and precise plant phenotyping.
