Abstract
Field-based high throughput plant phenotyping has recently gained increased interest in the efforts to bridge the genotyping and phenotyping gap and accelerate plant breeding for crop improvement. In this paper, we introduce a large-scale, integrated robotic cable-driven sensing system developed at University of Nebraska for field phenotyping research. It is constructed to collect data from a 0.4 ha field. The system has a sensor payload of 30 kg and offers the flexibility to integrate user defined sensing modules. Currently it integrates a four-band multispectral camera, a thermal infrared camera, a 3D scanning LiDAR, and a portable visible near-infrared spectrometer for plant measurements. Software is designed and developed for instrument control, task planning, and motion control, which enables precise and flexible phenotypic data collection at the plot level. The system also includes a variable-rate subsurface drip irrigation to control water application rates, and an automated weather station to log environmental variables. The system has been in operation for the 2017 and 2018 growing seasons. We demonstrate that the system is reliable and robust, and that fully automated data collection is feasible. Sensor and image data are of high quality in comparison to the ground truth measurements, and capture various aspects of plant traits such as height, ground cover and spectral reflectance. We present two novel datasets enabled by the system, including a plot-level thermal infrared image time-series during a day, and the signal of solar induced chlorophyll fluorescence from canopy reflectance. It is anticipated that the availability of this automated phenotyping system will benefit research in field phenotyping, remote sensing, agronomy, and related disciplines.
Highlights
High throughput field-based plant phenotyping has recently attracted substantial interest because of its importance in: (1) closing the gap between plant genotyping and phenotyping, (2) accelerating the cycle of breeding for crop improvement, and (3) meeting the global demands of food, fiber and fuel that can be produced from agricultural sectors (Furbank and Tester, 2011; White et al, 2012)
We reported a large-scale, cable-driven, integrated sensing and robotic platform for high-precision, field-based plant phenotyping research developed at University of Nebraska, U.S (NUSpidercam)
It is envisioned that these three research facilities will complement and amplify each other for plant genomics-phenomics discovery pipelines
Summary
High throughput field-based plant phenotyping has recently attracted substantial interest because of its importance in: (1) closing the gap between plant genotyping and phenotyping, (2) accelerating the cycle of breeding for crop improvement, and (3) meeting the global demands of food, fiber and fuel that can be produced from agricultural sectors (Furbank and Tester, 2011; White et al, 2012). It is anticipated that appropriately deployed field phenotyping technologies will enable us the collection of high volume, multifaceted plant phenotypic data. These field measured data, together with the co-measured environmental variables, will enable an accelerated pace of scientific discovery, from understanding complex interactions between genotype and environment to identifying the best performers among thousands of candidate genotypes as part of crop improvement efforts (Araus and Cairns, 2013). Field-based plant phenotyping platforms include manually operated carts (White and Conley, 2013; Bai et al, 2016), tractor-based vehicles (Andrade-Sanchez et al, 2014; Jiang et al, 2018) and field robotics (Underwood et al, 2017), and unmanned aerial vehicles (UAV) (Sankaran et al, 2015; Shi et al, 2016). UAVs, on the other hand, are suitable for tall crops, but have limited sensor payload capacity and measurement duration
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