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. Competing Interest Statement The authors have declared no competing interest. Footnotes (email: steven.binder{at}uga.edu; mfok{at}uga.edu). (email: hossaink{at}arizona.edu; bucksch{at}arizona.edu). This work was supported by the National Science Foundation Award No. 1653525. Additional experimental data added demonstrating the use of the ResNet models predicting the depth and width of an actual corn plant's root.