Research on Root traits of European Vicia faba cultivars published in top journal!

EUROLEGUME partner BOKU has recently published their study "Root traits of European Vicia faba cultivars – Using machine learning to explore adaptations to agro-climatic conditions" in one of the field's leading journals: Plant, Cell & Environment.

The study, authored by Jiangsan Zhao, Peter Sykacek, Gernot Bodner, and Boris Rewald, looked into the root architecture and morphology of 16 European faba bean cultivars at maturity. Different machine learning (ML) approaches were tested in their usefulness to analyse trait variations between cultivars. A supervised, i.e. hypothesis-driven, ML approach revealed that cultivars from Portugal feature greater and coarser but less frequent lateral roots at the top of the taproot, potentially enhancing water uptake from deeper soil horizons. Unsupervised clustering revealed that trait differences between Northern and Southern cultivars are not predominant but that two cultivar groups, independently from major and minor types, differ largely in overall root system size. Beside the useful information gathered about the phenotypical differentiation of faba bean across Europe in specific, the innovative use of powerful machine learning methods in analysing the EUROLEGUME datasets is enhancing the phenotypical exploration of plants in general. The EUROLEGUME project thus made an important contribution to the development of statistical methods in the field of plant phenotyping.

The 2D image illustrates the supervised k-NN classification of 16 Vicia faba cultivars based on Northern (blue, majority group) / Southern (red) European origin-labelled data and three important root traits (frequency, morphology and biomass of laterals roots from 0-10 cm along the tap root).

Read more about the research published and the main findings at here.