Supporting grapevine breeding and research through sensor-based phenotyping applications

Abstract

Phenotyping refers to the description of phenotypes and can range from morphological characteristics to plant compounts. It plays a central role in both grapevine breeding and grapevine research, as it represents the only direct access to the expression of genetic traits under real environmental conditions. Only with precise and reproducible phenotype data genetic effects can be identified and genotypes can be reliably compared and selected. It thus forms the basis for marker development, breeding progress, and thus the transfer of genetic knowledge into practice. Against the backdrop of climate change, objective, high-resolution phenotyping is becoming increasingly important.

Traditional methods, especially for phenology and morphological characteristics, are often based on manual recording and classification using pre-defined scales (e.g., OIV, BBCH). These methods are cost-effective and easy to implement but predominantely time-intensive, subjective, and therefore restricted for a small amount of plant material. In addition, many phenotypic studies using manual methods or wet chemistry analysis, such as for the extraction of plant metabolites, are also destructive. Sensor-based automatic phenotyping enables fast, objective detection of traits and can increase sample throughput and thus efficiency.

Sensor-based phenotyping can be carried out on various scales, from individual plant organs or even individual cells to individual vines or even entire vineyards. In the area of breeding and breeding research, we usually range from the laboratory scale under controlled, standardized conditions to the field scale, including handheld sensors, ground-based, or airborne platforms.

This keynote presentation will highlight traits and topics that can be supported by sensor applications, the components and required setup steps of such pipelines, and successful solutions.

One example of such an application in grapevine breeding is the support of breeders by data provided by a field phenotyping platform with a multispectral camera system. This high-throughput-platform can support the pre-selection of breeding material at an early breeding stage. In the field of breeding research, digital tools can help evaluate plant material for the development of QTLs, for example, the classification of resistance levels on leaf discs using imaging techniques.

Sensor applications will broaden our options in grapevine breeding beyond individual characteristics to complex relationships between genetics, environment, and management. It is crucial that sensor technology is not seen as an end in itself, but as a tool that opens up new perspectives for grapevine breeding when used consciously, critically, and in dialogue with viticulturists.