Abstract
BackgroundThe efficient and robust statistical analysis of the shape of plant organs of different cultivars is an important investigation issue in plant breeding and enables a robust cultivar description within the breeding progress. Laserscanning is a highly accurate and high resolution technique to acquire the 3D shape of plant surfaces. The computation of a shape based principal component analysis (PCA) built on concepts from continuum mechanics has proven to be an effective tool for a qualitative and quantitative shape examination.ResultsThe shape based PCA was used for a statistical analysis of 140 sugar beet roots of different cultivars. The calculation of the mean sugar beet root shape and the description of the main variations was possible. Furthermore, unknown and individual tap roots could be attributed to their cultivar by means of a robust classification tool based on the PCA results.ConclusionThe method demonstrates that it is possible to identify principal modes of root shape variations automatically and to quantify associated variances out of laserscanned 3D sugar beet tap root models. The introduced approach is not limited to the 3D shape description by laser scanning. A transfer to 3D MRI or radar data is also conceivable.
Highlights
The efficient and robust statistical analysis of the shape of plant organs of different cultivars is an important investigation issue in plant breeding and enables a robust cultivar description within the breeding progress
We introduce a method for the statistical analysis of large ensembles of 3D tap roots as well as a classification tool based on information gained from the statistical analysis
The method is applied to sugar beets, where the mean root shape and the main variations within a group of sugar beets of the same growth period have been computed
Summary
The efficient and robust statistical analysis of the shape of plant organs of different cultivars is an important investigation issue in plant breeding and enables a robust cultivar description within the breeding progress. In breeding and precision agriculture there is a need for a precise description of the 3D architecture of a crop, a plant organ or a harvested product, in a fast and reproducible way [1]. Potential applications involve automated selection procedures in plant breeding of phenotypes with the desirable features and traits (like grain or root shape), assessment of crop development during the growth period, enabling an optimised crop management. One of the main targets of sugar beet breeding is the root development, including relevant quality parameters such as sugar content, non-sugar compounds or mark-content. It can be observed that the dynamic of storage root development in sugar beet has no specific growth stages. In sugar beet development of leaf biomass is not correlated to storage root biomass or yield formation. The shape of the sugar beet tap root plays a significant role for the entire processing chain
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