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Fig. 7 | Plant Methods

Fig. 7

From: DeepCob: precise and high-throughput analysis of maize cob geometry using deep learning with an application in genebank phenomics

Fig. 7

Clustering of individual images by their heterogeneity of maize cob traits within images. Clustering approaches with the extracted cob traits. A First two principal components showing the average color of individual cobs (\(n=\mathrm{19,867}\) cobs) (left) and average cob color per analyzed image (\(n=\mathrm{3,302}\) images) (right). The colors of each dot reflect the average RGB values (i.e., the color) of each cob, or image, respectively. B PCA plots showing clusters identified with the multivariate clustering methods CLARA (left) and \(k\)-means clustering (right). C Distribution of cob traits within each method and cluster

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