Deployment of Lidar from a Ground Platform: Customizing a Low-Cost, Information-Rich and User-Friendly Application for Field Phenomics Research
Abstract
Using sensors and electronic systems for characterization of plant traits provides valuable digital inputs to support complex analytical modeling in genetics research. In field applications, frequent sensor deployment enables the study of the dynamics of these traits and their interaction with the environment. This study focused on implementing lidar (light detection and ranging) technology to generate 2D displacement data at high spatial resolution and extract plant architectural parameters, namely canopy height and cover, in a diverse population of 252 maize (Zea mays L.) genotypes. A prime objective was to develop the mechanical and electrical subcomponents for field deployment from a ground vehicle. Data reduction approaches were implemented for efficient same-day post-processing to generate by-plot statistics. The lidar system was successfully deployed six times in a span of 42 days. Lidar data accuracy was validated through independent measurements in a subset of 75 experimental units. Manual and lidar-derived canopy height measurements were compared resulting in root mean square error (RMSE) = 0.068 m and r2 = 0.81. Subsequent genome-wide association study (GWAS) analyses for quantitative trait locus (QTL) identification and comparisons of genetic correlations and heritabilities for manual and lidar-based traits showed statistically significant associations. Low-cost, field-ready lidar of computational simplicitymore »
- Authors:
- Publication Date:
- Research Org.:
- Colorado State Univ., Fort Collins, CO (United States); Univ. of Arizona, Tucson, AZ (United States)
- Sponsoring Org.:
- USDOE Advanced Research Projects Agency - Energy (ARPA-E)
- OSTI Identifier:
- 1577209
- Alternate Identifier(s):
- OSTI ID: 1614878
- Grant/Contract Number:
- AR0000826
- Resource Type:
- Published Article
- Journal Name:
- Sensors
- Additional Journal Information:
- Journal Name: Sensors Journal Volume: 19 Journal Issue: 24; Journal ID: ISSN 1424-8220
- Publisher:
- MDPI AG
- Country of Publication:
- Switzerland
- Language:
- English
- Subject:
- 60 APPLIED LIFE SCIENCES; 47 OTHER INSTRUMENTATION; lidar; phenotyping; maize; GWAS
Citation Formats
Heun, John T., Attalah, Said, French, Andrew N., Lehner, Kevin R., McKay, John K., Mullen, Jack L., Ottman, Michael J., and Andrade-Sanchez, Pedro. Deployment of Lidar from a Ground Platform: Customizing a Low-Cost, Information-Rich and User-Friendly Application for Field Phenomics Research. Switzerland: N. p., 2019.
Web. doi:10.3390/s19245358.
Heun, John T., Attalah, Said, French, Andrew N., Lehner, Kevin R., McKay, John K., Mullen, Jack L., Ottman, Michael J., & Andrade-Sanchez, Pedro. Deployment of Lidar from a Ground Platform: Customizing a Low-Cost, Information-Rich and User-Friendly Application for Field Phenomics Research. Switzerland. https://doi.org/10.3390/s19245358
Heun, John T., Attalah, Said, French, Andrew N., Lehner, Kevin R., McKay, John K., Mullen, Jack L., Ottman, Michael J., and Andrade-Sanchez, Pedro. Thu .
"Deployment of Lidar from a Ground Platform: Customizing a Low-Cost, Information-Rich and User-Friendly Application for Field Phenomics Research". Switzerland. https://doi.org/10.3390/s19245358.
@article{osti_1577209,
title = {Deployment of Lidar from a Ground Platform: Customizing a Low-Cost, Information-Rich and User-Friendly Application for Field Phenomics Research},
author = {Heun, John T. and Attalah, Said and French, Andrew N. and Lehner, Kevin R. and McKay, John K. and Mullen, Jack L. and Ottman, Michael J. and Andrade-Sanchez, Pedro},
abstractNote = {Using sensors and electronic systems for characterization of plant traits provides valuable digital inputs to support complex analytical modeling in genetics research. In field applications, frequent sensor deployment enables the study of the dynamics of these traits and their interaction with the environment. This study focused on implementing lidar (light detection and ranging) technology to generate 2D displacement data at high spatial resolution and extract plant architectural parameters, namely canopy height and cover, in a diverse population of 252 maize (Zea mays L.) genotypes. A prime objective was to develop the mechanical and electrical subcomponents for field deployment from a ground vehicle. Data reduction approaches were implemented for efficient same-day post-processing to generate by-plot statistics. The lidar system was successfully deployed six times in a span of 42 days. Lidar data accuracy was validated through independent measurements in a subset of 75 experimental units. Manual and lidar-derived canopy height measurements were compared resulting in root mean square error (RMSE) = 0.068 m and r2 = 0.81. Subsequent genome-wide association study (GWAS) analyses for quantitative trait locus (QTL) identification and comparisons of genetic correlations and heritabilities for manual and lidar-based traits showed statistically significant associations. Low-cost, field-ready lidar of computational simplicity make possible timely phenotyping of diverse populations in multiple environments.},
doi = {10.3390/s19245358},
journal = {Sensors},
number = 24,
volume = 19,
place = {Switzerland},
year = {2019},
month = {12}
}
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