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Unlocking plant secrets: A systematic review of 3D imaging in plant phenotyping techniques

Akhtar, Muhammad Salman, Zafar, Zuhair, NAWAZ, Raheel and Fraz, Muhammad Moazam (2024) Unlocking plant secrets: A systematic review of 3D imaging in plant phenotyping techniques. Computers and Electronics in Agriculture, 222. p. 109033. ISSN 01681699

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Official URL: http://dx.doi.org/10.1016/j.compag.2024.109033

Abstract or description

Phenotyping is a systematic process of quantifying and assessing a wide range of structural and physiological traits to understand the intricate interplay between an organism's genetic makeup, its surrounding environment, and management practices, often referred to as genome-to-environment (GxE) interaction. In the context of plants, these traits can include aspects such as plant height, stem diameter, leaf size, angle, and shape, chlorophyll content, biomass, leaf area, etc. 3D plant phenotyping plays a crucial role in advancing our understanding of plant biology, improving crop breeding, and agricultural practices. 3D imaging has become a powerful phenotyping tool, offering in-depth insights into plant structures and traits. In contrast to 2D imaging, 3D imaging enables precise measurement of plant traits that cannot be sufficiently evaluated in two dimensions by overcoming challenges such as partial occlusion through the utilization of depth perception and multiple viewpoints. However, even with significant recent progress, various challenges persist, including the need for well-designed experimental setups for standardized data collection, the automation of processing pipelines, and the robust analysis techniques of 3D representations, which still impede the widespread adoption of 3D plant phenotyping. To propel the progress of 3D imaging-based phenotyping, an all-encompassing assessment of existing strategies is imperative, yet there is currently a lack of specialized reviews that scrutinize and emphasize distinct facets for future enhancement. To bridge this gap, we perform a systematic survey of 81 research studies that employ 3D imaging for various trait assessments of plants. Our review thoroughly investigates the stages of data acquisition, encompassing sensing technologies, representations, preprocessing approaches, analysis methodologies, and techniques for estimating phenotypic traits. We believe that this comprehensive review will serve as a valuable guide for researchers and professionals engaged in high throughput plant phenotyping, equipping them to formulate effective experimental setups and utilize appropriate processing and analysis methods, thereby fostering its continued advancement. © 2024 Elsevier B.V.

Item Type: Article
Faculty: Executive
Depositing User: Raheel NAWAZ
Date Deposited: 13 Sep 2024 11:33
Last Modified: 13 Sep 2024 11:35
URI: https://eprints.staffs.ac.uk/id/eprint/8437

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