Fiber Bragg grating based sensing system for non-destructive root phenotyping using ResNet prediction

Abstract

Real-time measurements of crop root architecture can overcome limitations faced by plant breeders when developing climate-resilient plants. Due to current measurement methods failing to continuously monitor root growth in a non-destructive and scalable fashion, we propose a first in-soil sensing system based on fiber Bragg gratings (FBG). The sensing system logs three-dimensional strain generated by a growing pseudo-root. Two ResNet models confirm the utility of in-soil FBG sensors by predicting pseudo-root width and depth with accuracies of 92% and 93%, respectively. To analyze model robustness, a preliminary experiment was performed where FBGs logged strain generated from a corn plant’s roots for 30 days. The models were then retrained on new data where they achieved accuracies of 98% and 96%, respectively. Our presented prototype has potential prospects to go beyond measuring root parameters and sense its surrounding soil environment.

Plant phenotyping relevance

FBGセンサーとResNetモデルを用いて、非破壊・連続的に根の幅と深さを推定するセンシングシステムを開発・検証しており、植物表現型取得手法が研究の中心である。

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