Relationship between meteorological data, physical-mechanical characteristics of grapes and Botrytis bunch rot

Abstract

Botrytis bunch rot (BBR) is the economically third most important disease in cool climate viticulture. In order to avoid or delay spreading of BBR infections until the grapes reach physiological ripeness, different management strategies like early defoliation or specific fungicide applications were developed. The scope of most grapevine breeding programs is the selection of mildew fungus-resistant, climatic adapted grapevines with balanced, healthy yield and outstanding wine quality. Within the long-term breeding process, the application of marker-assisted selection (MAS) is the most efficient way for early selection of desired grapevine seedlings. Since no resistances have yet been described for BBR, grapevines shall be selected for developing fruits with physical-mechanical barriers reducing the risk for BBR infection like loose grape bunch architecture and thick, impermeable berry cuticle. In the present study first results regarding the investigation of the relationship between physical-mechanical fruit traits (bunch architecture, berry impedance and berry texture), meteorological data and the degree of BBR infection are shown. Varieties and elite breeding lines were phenotyped using high-throughput, objective sensors in 2021 and 2022, two years with contrasting growing conditions (Siebeldingen, Germany). In comparison to 2021, 2022 was characterized by a higher temperature sum D (+196°days between veraison and harvest) and huge differences in the precipitation sum (PS; -62 mm up to + 105 mm). In order to categorize BBR resistance/ susceptibility, berries from different genotypes showing high variability in their berry characteristics were sampled at maturity and were tested under controlled lab conditions for BBR susceptibility. For some varieties, it could be shown that meteorological conditions affect both, berry traits as well as infection with BBR. In addition to the environment and the training system, physical-mechanical berry traits and the mean berry diameter could be confirmed as promising phenotypic traits for the prediction of BBR resistance. In summary, the consideration of sensor-based physical-mechanical berry traits enables an improved risk prediction for BBR, which is of outstanding importance for the evaluation of breeding material and new varieties growing under different environmental conditions, as well as for phenotyping of mapping populations for QTL analyses and the development of molecular markers. As meteorological conditions were contrasting in 2021 and 2022 and varieties with high phenotypic variability were considered, additional years of investigations are recommended in order to verify the reliability of the detected relationships.