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 simplicity make possible timely phenotyping of diverse populations in multiple environments.
Highlights
The advent of sub-meter precision GNSS (Global Navigation Satellite Systems) hardware and ruggedized field-ready electronics has created an opportunity to develop a number of applications for field-based experimentation serving a variety of academic disciplines with interest in characterizing stresses in complex biological systems such as agriculture
Field-ready electronics are suitable for deployment from moving ground platforms, which are useful in high-throughput phenotyping (HTP) applications of small-size plot research [3,4,5,6]
This paper is focused on the implementation of displacement sensing technology aimed at characterizing the growth dynamics of maize plants with multiple frequent observations over time
Summary
The advent of sub-meter precision GNSS (Global Navigation Satellite Systems) hardware and ruggedized field-ready electronics has created an opportunity to develop a number of applications for field-based experimentation serving a variety of academic disciplines with interest in characterizing stresses in complex biological systems such as agriculture. Sensors 2019, 19, 5358 spatial resolution [1,2,3] These digital tools offer substantial improvements in repeatability and accuracy while maintaining their operational characteristics for prolonged periods of time. They provide adaptability to various field and weather conditions. Engineered platforms provide off-road mobility as well as mechanical and electrical interface for electronics that capture and record data on-the-go These instrumented platforms are capable of capturing a range of plant traits such as the thermal response of the crop to abiotic conditions, the spectral reaction to incoming light and reflectance, the architectural characteristics of growing plants, and other applications. This paper is focused on the implementation of displacement sensing technology aimed at characterizing the growth dynamics of maize plants with multiple frequent observations over time
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