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• MRI was used to detect clubroot of oilseed rape. • Average sample grayscale histograms of MRI images were extracted and analyzed. • Root architecture parameters were extracted from reconstructed 3D root by MRI images. • Good classification performances of clubroot detection were obtained using MRI. Plant root diseases threat plant growth and eventually cause plant death without proper treatment. It is difficult to diagnose root diseases without digging the roots from the soil, and it is late when the above-ground parts show symptoms under the stress of root diseases. This study used magnetic resonance imaging (MRI) for non-invasive root phenotyping to detect oilseed rape clubroot. MRI images of healthy oilseed rape roots and roots infected by clubroot were obtained. After image preprocessing, average sample grayscale histograms (Avg-SGH) were extracted to build classification models for disease identification using logistic regression (LR), support vector machine (SVM) and random forest (RF). Reconstruction of three-dimensional (3D) root architectures was also conducted. Root architecture parameters were extracted from the reconstructed roots. Analysis of variance (ANOVA) showed that the root architecture parameters differed significantly between healthy and infected roots. RF model using root architecture parameters showed good performances, and the feature importance for clubroot identification was also explored. The overall results showed that MRI could effectively detect clubroot diseases in a non-invasive manner, indicating significant potential for plant root phenotyping. [ABSTRACT FROM AUTHOR]