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Deep roots through time and crops: insight from five seasons at DeepRootLab.

The New phytologist · 13 Mar 2026 · 10.1111/nph.71065

Abstract

Deep-rooted crops accessing water and nutrients from deep soil layers enhance the resource base for crop production. However, studying these roots in field conditions is labour-intensive, limiting research scope. We established a field root research facility with 48 plots for replicated experiments. The facility includes 144 6-metre-long minirhizotron tubes and an AI-based pipeline for rapid root trait analysis. We also attempted to install access tubes and customized ingrowth core production for less-invasive root activity determination. Our study revealed significant differences in deep root density among species, particularly at depths of 2.5 to 4.5 m, over 5 years. The less-invasive studies using ingrowth cores reached depths of 4.2 m. Nutrient tracer 15 N analysis showed marked differences in deep root activity among crop species. Time domain reflectometry sensors indicated varying water depletion in deeper soil layers, influenced by crop species and root growth patterns. We established a field facility for studying deep root growth and function, demonstrating its effectiveness in analysing diverse deep-rooted plant species. This facility provides an ideal platform for conducting meaningful research in deep soil layers, yielding statistically and biologically significant results for agricultural applications.

Plant phenotyping relevance

深根研究施設とAIによる根形質解析パイプラインの構築・有効性評価が中心的に記述されており、根密度などの植物形質を取得するフェノタイピング基盤に該当する。

abstractThe facility includes 144 6-metre-long minirhizotron tubes and an AI-based pipeline for rapid root trait analysis.
abstractWe established a field facility for studying deep root growth and function, demonstrating its effectiveness in analysing diverse deep-rooted plant species.

Code and data availability

The supplied blocks describe the DeepRootLab facility, minirhizotron image datasets, RootPainter-based segmentation, and 15N/TDR measurements, but contain no data availability statement, deposit, or authors' public URL for any dataset, images, code, or trained model. RootPainter is cited prior work (Smith et al., 2022)

No evidence-backed public reproduction asset is currently recorded.

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