Phenotyping roots in darkness: disturbance-free root imaging with near infrared illumination.

Abstract

Root systems architecture (RSA) and size properties are essential determinants of plant performance and need to be assessed in high-throughput plant phenotyping platforms. Thus, we tested a concept that involves near-infrared (NIR) imaging of roots growing along surfaces of transparent culture vessels using special long pass filters to block their exposure to visible light. Two setups were used to monitor growth of Arabidopsis, rapeseed, barley and maize roots upon exposure to white light, filter-transmitted radiation or darkness: root growth direction was analysed (1) through short-term cultivation on agar plates, and (2) using soil-filled transparent pots to monitor long-term responses. White light-triggered phototropic responses were detected for Arabidopsis in setup 1, and for rapeseed, barley and maize roots in setups 1 and 2, whereas light effects could be avoided by use of the NIR filter thus confirming its suitability to mimic darkness. NIR image-derived 'root volume' values correlated well with root dry weight. The root system fractions visible at the different pot sides and in different zones revealed species- and genotype-dependent variation of spatial root distribution and other RSA traits. Following this validated concept, root imaging setups may be integrated into shoot phenotyping facilities in order to enable root system analysis in the context of whole-plant performance investigations.

Plant phenotyping relevance

NIR画像を用いた根系形態（RSA）取得法を開発・検証し、根容積と乾物重の相関や既存施設への統合可能性を評価しており、表現型取得法が研究の中心である。

Code and data availability

The supplied blocks describe NIR root imaging experiments and reference Supplementary Material (Fig. S1–S6), but contain no public dataset, image, code, or model deposit with an authors' URL. Software used (SmartRoot, WinRhizo, SigmaPlot, GENSTAT) are third-party tools, not paper-specific assets.

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