Abstract
Imaging sensors can extend phenotyping capability, but they require a system to handle high-volume data. The overall goal of this study was to develop and evaluate a field-based high throughput phenotyping system accommodating high-resolution imagers. The system consisted of a high-clearance tractor and sensing and electrical systems. The sensing system was based on a distributed structure, integrating environmental sensors, real-time kinematic GPS, and multiple imaging sensors including RGB-D, thermal, and hyperspectral cameras. Custom software was developed with a multilayered architecture for system control and data collection. The system was evaluated by scanning a cotton field with 23 genotypes for quantification of canopy growth and development. A data processing pipeline was developed to extract phenotypes at the canopy level, including height, width, projected leaf area, and volume from RGB-D data and temperature from thermal images. Growth rates of morphological traits were accordingly calculated. The traits had strong correlations (r = 0.54–0.74) with fiber yield and good broad sense heritability (H2 = 0.27–0.72), suggesting the potential for conducting quantitative genetic analysis and contributing to yield prediction models. The developed system is a useful tool for a wide range of breeding/genetic, agronomic/physiological, and economic studies.
Highlights
In the past decade, greenhouse- and chamber-based high throughput phenotyping systems have been developed by several transnational companies, public institutions, and universities[6]
The system demonstrated the capability of simultaneously acquiring and storing high-volume images generated by multiple imaging sensors of high resolution
The system could be a useful tool for field data collection, and the system design is reusable for field-based high throughput phenotyping (FB-HTP) projects aiming to utilize high-resolution imaging sensors
Summary
Greenhouse- and chamber-based high throughput phenotyping systems have been developed by several transnational companies, public institutions, and universities[6]. Plant growth and development can be significantly affected by environmental factors such as soil, and these factors are extremely difficult (or sometimes impossible) to simulate in controlled environments To address these issues, it is imperative to develop systems for field-based high throughput phenotyping (FB-HTP). Specific objectives were to: (1) develop a modular and customizable ground mobile system integrated with multiple high resolution imagery modules including RGB-D, thermal, and hyperspectral cameras, (2) calibrate and validate the sensing system, and (3) evaluate the usefulness of the FB-HTP system for breeding programs and genomics studies. Additional operators were on the tractor to test the image acquisition software during field data collection
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