Applications of Drones and Image Analytics in Field Phenotyping: A Potential Breakthrough in Uganda’s Agricultural Research
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Date
2022
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Abstract
We are in the race against time to find new solutions amidst the threat of climate change, to
increase food production by 70% to feed the ever-growing world population which is expected
to double by 2050. Agricultural research plays astonishing roles in crop and livestock
improvement through breeding programs and good agronomic practices to enable sustainable
agriculture and food systems. The advanced molecular breeding or modern breeding
technologies in genotyping have been well-embraced by most research institutions worldwide.
However, phenotyping which plays great role in agricultural research and breeding programs
has achieved little development or still a traditional method in most institutions across African
countries. Noteworthy, the advancement of phenotyping has been gaining momentum and
attracted a number of researchers in the recent past, this led to the coining of high-throughput
phenotyping concept. Nevertheless, the comprehensive understanding of this concept remains
limited in most research institutions in developing countries, especially Uganda. Therefore, the
present review aimed to provide a summary of drone-based high throughput phenotyping used
across different crops. The electronic literature search was conducted from non-academic and
academic databases. The literature sources in the form of peer-reviewed journal articles, books,
book sections, conference papers, thesis and dissertations, policy papers, organisation or
company manuals, working papers, and reports were considered. In this review, the concepts
of field phenotyping are discussed, drone classification and specifications are elaborated, the
use cases of the drone-based high-throughput phenotyping are presented, drone imaging
systems for phenotyping are discussed, and high-throughput image analytics method is
explained. In this paper, it was found that cereals have been the most studied crop for drone
based phenotyping application in academic literature. However, root crops were the list studied,
hence, extensive research is needed for drone-based phenotyping adoption in root crops.
Moreover, limited studies have been focused on the effect of drones’ operation parameters.
Therefore, research focusing on the optimization of the drones’ performance is required.
Description
Keywords
Crop phenotyping, Plant phenotyping, UAV, Agricultural drone, Remote sensing, High-throughput phenotyping, Precision phenotyping, Precision Agriculture, Image processing, Field phenotyping, High-throughput phenotyping platform, Image processing, Image analysis, Machine learning, Deep learning
Citation
Bongomin, O., Lamo, J., Guina, J., Okello, C., Ocen, G., Obura, M., ... & Ojok, S. (2022). Applications of drones and image analytics in field phenotyping: A potential breakthrough in Uganda's agricultural research. Available at SSRN 4158755.