A High-Throughput Phenotyping Pipeline for Image Processing and Functional Growth Curve Analysis

Abstract

High-throughput phenotyping system has become more and more popular in plant science research. The data analysis for such a system typically involves two steps: plant feature extraction through image processing and statistical analysis for the extracted features. The current approach is to perform those two steps on different platforms. We develop the package "implant" in R for both robust feature extraction and functional data analysis. For image processing, the "implant" package provides methods including thresholding, hidden Markov random field model, and morphological operations. For statistical analysis, this package can produce nonparametric curve fitting with its confidence region for plant growth. A functional ANOVA model to test for the treatment and genotype effects on the plant growth dynamics is also provided.

Plant phenotyping relevance

植物画像からの特徴抽出と成長曲線解析を一体化したRパッケージを開発しており、表現型取得・解析手法が研究の中心である。

Code and data availability

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