Phenotyping: Using Machine Learning for Improved Pairwise Genotype Classification Based on Root Traits.

ABSTRACT: Phenotyping local crop cultivars is becoming more and more important, as they are an important genetic source for breeding - especially in regard to inherent root system architectures. Machine learning algorithms are promising tools to assist in the analysis of complex data sets; novel approaches are need to apply them on root phenotyping data of mature plants. A greenhouse experiment was conducted in large, sand-filled columns to differentiate 16 European Pisum sativum cultivars based on 36 manually derived root traits. Through combining random forest and support vector machine models, machine learning algorithms were successfully used for unbiased identification of most distinguishing root traits and subsequent pairwise cultivar differentiation. Up to 86% of pea cultivar pairs cou

SUBMITTER: Zhao J 

PROVIDER: S-EPMC5138212 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature