Agritech imaging of underground plant root growth using a distributed fiber optic sensor

Tei, Mika; Barbieri, Ettore; Soma, Fumiyuki; Uga, Yusaku; Kawahito, Yousuke

doi:10.1117/12.2606308

Cited by 2 publications

(2 citation statements)

References 5 publications

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“…Their low attenuation also allows long distance sensor arrays to be deployed without severe signal decay [12]. Recently, distributed fiber optic sensors (DFOS) [13] and fiber Bragg grating (FBG) based sensors [14] have shown promising results in providing non-destructive measurements of root structures. While providing accurate measurements, current DFOS root sensing systems based on Rayleigh backscatter are restricted to growing vessels containing Greens Grade and complex fiber configurations [13].…”

Section: Introductionmentioning

confidence: 99%

“…Recently, distributed fiber optic sensors (DFOS) [13] and fiber Bragg grating (FBG) based sensors [14] have shown promising results in providing non-destructive measurements of root structures. While providing accurate measurements, current DFOS root sensing systems based on Rayleigh backscatter are restricted to growing vessels containing Greens Grade and complex fiber configurations [13]. Widespread deployment is further limited by the requirement of complex components and characteristically low signalto-noise ratio (SNR) due to weak Rayleigh backscatter [15].…”

Section: Introductionmentioning

confidence: 99%

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Non-destructive underground fiber Bragg grating sensing system with ResNet prediction for root phenotyping

Binder,

Hossain,

Bucksch

et al. 2024

Machine Learning in Photonics

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The quantitative evaluation of plant organs in a non-destructive and continuous fashion is the technological bottleneck to meet the food, fuel, and fiber needs for the 10 billion people on earth by 2050 [1]. Quantifying crop root architecture paves promising ways to improve resource uptake in the face of the resource limitations in the degraded soils of future climates [2]. Current root measurement methods either have low resolution or involve uprooting the plant. In all cases, the measurement methods do not provide any prediction on how well the plant is growing. We propose the usage of three fiber Bragg gratings (FBG) embedded within soil to measure underground strain change due to pseudo-root growth and a Residual Neural Network (ResNet) to predict its characteristics in a non-destructive fashion. To generate large amounts of sensor data similar to that of a growing root, we developed an automated robot that inserts pseudo-roots of 1mm and 5mm in diameter to 15cm below the soil's surface over the span of 11 minutes. We used 2,582 and 240 samples in training of the diameter and depth models, while testing was performed using 646 and 60 samples. The models were able to achieve accuracy of 92% and 93% for diameter and depth prediction, respectively. Through transfer learning, our base models will be expanded so that real time prediction on actual plant roots diameter and depth can be achieved.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Non-destructive underground fiber Bragg grating sensing system with ResNet prediction for root phenotyping

Binder,

Hossain,

Bucksch

et al. 2024

Machine Learning in Photonics

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

Binder,

Hossain,

Bucksch

et al. 2024

Preprint

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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. The sensing system continuously logs three-dimensional strain generated by a growing pseudo-root. Two ResNet models confirm the utility of in-soil fiber Bragg grating sensors and predict root width and depth from sensor output data and achieve accuracies of 92% and 93% respectively. Our presented prototype has potential prospects to go beyond measuring root parameters and sense its surrounding soil environment.

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Agritech imaging of underground plant root growth using a distributed fiber optic sensor

Cited by 2 publications

References 5 publications

Non-destructive underground fiber Bragg grating sensing system with ResNet prediction for root phenotyping

Non-destructive underground fiber Bragg grating sensing system with ResNet prediction for root phenotyping

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

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