What is cost-efficient phenotyping? Optimizing costs for different scenarios

Reynolds, Daniel, Baret, Frederic, Welcker, Claude, Bostrom, Aaron ORCID: https://orcid.org/0000-0002-7300-6038, Ball, Joshua, Cellini, Francesco, Lorence, Argelia, Chawade, Aakash, Khafif, Mehdi, Noshita, Koji, Mueller-Linow, Mark, Zhou, Ji and Tardieu, François (2019) What is cost-efficient phenotyping? Optimizing costs for different scenarios. Plant Science, 282. pp. 14-22. ISSN 0168-9452

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Abstract

Progress in remote sensing and robotic technologies decreases the hardware costs of phenotyping. Here, we first review cost-effective imaging devices and environmental sensors, and present a trade-off between investment and manpower costs. We then discuss the structure of costs in various real-world scenarios. Hand-held low-cost sensors are suitable for quick and infrequent plant diagnostic measurements. In experiments for genetic or agronomic analyses, (i) major costs arise from plant handling and manpower; (ii) the total costs per plant/microplot are similar in robotized platform or field experiments with drones, hand-held or robotized ground vehicles; (iii) the cost of vehicles carrying sensors represents only 5–26% of the total costs. These conclusions depend on the context, in particular for labor cost, the quantitative demand of phenotyping and the number of days available for phenotypic measurements due to climatic constraints. Data analysis represents 10–20% of total cost if pipelines have already been developed. A trade-off exists between the initial high cost of pipeline development and labor cost of manual operations. Overall, depending on the context and objsectives, “cost-effective” phenotyping may involve either low investment (“affordable phenotyping”), or initial high investments in sensors, vehicles and pipelines that result in higher quality and lower operational costs.

Item Type: Article
Uncontrolled Keywords: phenotyping,phenomics,cost,imaging,information system,affordable
Faculty \ School: Faculty of Science > School of Computing Sciences
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 16 Aug 2018 13:31
Last Modified: 09 Mar 2024 01:06
URI: https://ueaeprints.uea.ac.uk/id/eprint/68074
DOI: 10.1016/j.plantsci.2018.06.015

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