UAV are classified into the following: single-rotor, multirotor, fixed-wing, and hybrid VTOL (vertical takeoff and landing) fixed-wing. While UAV can be classified based on a diverse set of features, in the context of a plant sciences/breeding practitioner, it is useful to simply classify them according to their physical features or configuration. We first provide a taxonomy of UAV devices through the lens of plant phenotyping. For complementary reading on UAS phenotyping topics not directly covered in our work, readers can refer to additional review articles. The intent of this review paper is to provide an overview of the state of the art in aerial-based analytics to plant sciences and breeding practitioners who are interested in deploying this phenotyping modality matching their specific phenotyping needs. The key decisions a practitioner needs to make include: Which UAV and sensor package should one choose? What are the critical steps to successful deployment, and steps to successful processing of the data? What has been done in this scientific discipline? What are current state-of-the-art applications of UAS in plant phenotyping? Where are we headed next? What are the open questions, trends, and challenges ? This paper reviews the state-of-the-art in UAS deployment, data collection, curation, storage, and analyses, discusses pressing technical challenges, and identifies future trends in this arena. There are several technical decisions that the practitioner has to make to ensure that the UAS operation and subsequent postprocessing analysis produce actionable information from the plant science perspective. In order to avoid ambiguity, we choose to call these systems as UAS, with the definition used by the United States Federal Aviation Administration (FAA): вЂњan unmanned aircraft (an aircraft that is operated without the possibility of direct human intervention from within or on the aircraft) and associated elements (including communication links and the components that control the unmanned aircraft) that are required for the pilot in command to operate safely and efficiently in the national airspace system.вЂќ (Public Law 112-95, Section 331 (8-9) United States). There are, however, a diversity of names and nomenclature for these devices depending on country of use, with drones, unmanned air vehicle (UAV), and unmanned aircraft system (UAS) being commonly used terms. Most air vehicles used for plant phenotyping are based on the concept of a remotely piloted aircraft system (RPAS) as defined by the International Civil Aviation Organization (ICAO). This review provides a broad account of the state of the art in UAS-based phenotyping to reduce the barrier to entry to plant science practitioners interested in deploying this imaging modality for phenotyping in plant breeding and research areas. We discuss pressing technical challenges, identify future trends in UAS-based phenotyping that the plant research community should be aware of, and pinpoint key plant science and agronomic questions that can be resolved with the next generation of UAS-based imaging modalities and associated data analysis pipelines. This paper reviews the state of the art in the deployment, collection, curation, storage, and analysis of data from UAS-based phenotyping platforms. These advantages have expanded the use of UAS-based plant phenotyping approach in research and breeding applications. It does not store any personal data.Unmanned aircraft system (UAS) is a particularly powerful tool for plant phenotyping, due to reasonable cost of procurement and deployment, ease and flexibility for control and operation, ability to reconfigure sensor payloads to diversify sensing, and the ability to seamlessly fit into a larger connected phenotyping network. The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. The cookie is used to store the user consent for the cookies in the category 'Performance'. This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category 'Other.

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Neofinder review