Efficient in‐field plant phenomics for row‐crops with an autonomous ground vehicle

Abstract

The scientific areas of plant genomics and phenomics are capable of improving plant productivity, yet they are limited by the manual labor that is currently required to perform in-field measurement, and a lack of technology for measuring the physical performance of crops growing in the field. A variety of sensor technology has the potential to efficiently measure plant characteristics that are related to production. Recent advances have also shown that autonomous airborne and manually driven ground-based sensor platforms provide practical mechanisms for deploying the sensors in the field. This paper advances the state-of-the-art by developing and rigorously testing an efficient system for high throughput in-field agricultural row-crop phenotyping. The system comprises an autonomous unmanned ground-vehicle robot for data acquisition and an efficient data post-processing framework to provide phenotype information over large-scale real-world plant-science trials. Experiments were performed at three trial locations at two different times of year, resulting in a total traversal of 43.8 km to scan 7.24 hectares and 2423 plots (including repeated scans). The height and canopy closure data were found to be highly repeatable (r 2 = 1.00 N = 280, r 2 = 0.99 N = 280, respectively) and accurate with respect to manually gathered field data (r 2 = 0.95 N = 470, r 2 = 0.91 N = 361, respectively), yet more objective and less-reliant on human skill and experience. The system was found to be a more labor-efficient mechanism for gathering data, which compares favorably to current standard manual practices. K E Y W O R D Sagriculture, hyperspectral and lidar sensing, plant phenomics, row-crop phenotyping, terrestrial robotics INTRODUCTIONPredicted global population increases are expected to cause a doubling in food demand by 2050, while at the same time the ability to grow more food is threatened by problems of water scarcity, soil fertility, and climate change. 12 Significant increases in food production are required, which will necessitate greater productivity in terms of yield per hectare and efficient use of natural resources. Given that "genetic diversity provides the basis for all plant improvement," 12 the study of different genetic varieties of crop (genomics) and how well they grow in different environmental conditions (phenomics) is critical to meet this challenge. Each year, around the world, millions of agricultural crops (such as grains and legumes) with different genetic profiles are grown in the field, subjected to different environmental factors (e.g., exposed to disease, herbicides, water stress, etc.) and the physical response of the plants (e.g., how tolerant they are, how much yield they produce) is measured. The process is repeated annually, driving plant productivity and adaptability forward, however, advances in genomics have not been matched by similar advances in phenomics and the ability to obtain these physical measurements is considered to be the major bottleneck. 2,12,14 Crop characteristics (phenotype t...

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