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

Autor: Mehdi Khafif, François Tardieu, Ji Zhou, Aakash Chawade, Francesco Cellini, Koji Noshita, Daniel Reynolds, Mark Mueller-Linow, Joshua Ball, Aaron Bostrom, Argelia Lorence, Claude Welcker, Frédéric Baret
Přispěvatelé: Biotechnology and Biological Sciences Research Council, Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Agenzia Lucana di Sviluppo di Innovazione in Agricoltura, Partenaires INRAE, Arkansas State University, Department of Plant Breeding, Swedish University of Agricultural Sciences (SLU), Laboratoire des interactions plantes micro-organismes (LIPM), Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS), The University of Tokyo (UTokyo), Japan Science and Technology Agency (JST), Forschungszentrum Jülich GmbH | Centre de recherche de Juliers, Helmholtz-Gemeinschaft = Helmholtz Association, Nanjing Agricultural University, ANR-PIA project PHENOME FPPN (ANR-11-INBS-0012), Biotechnology and Biological Sciences Research Council (BBSRC), Core Strategic Programme Grant (BB/CSP17270/1), BBSRC’s Designing Future Wheat Strategic Programme (BB/P016855/1), (BBS/E/T/000PR9785), EPPN2020 (UE H2020 grant agreement No 731013), ANR-11-INBS-0012,PHENOME,Centre français de phénomique végétale(2011), European Project: 731013 ,EPPN2020(2017), Biotechnology and Biological Sciences Research Council (BBSRC), Nanjing Agricultural University (NAU)
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Plant Science
Plant Science, Elsevier, 2019, 282, pp.14-22. ⟨10.1016/j.plantsci.2018.06.015⟩
Plant Science (282), 14-22. (2019)
Plant Science, 2019, 282, pp.14-22. ⟨10.1016/j.plantsci.2018.06.015⟩
ISSN: 0168-9452
DOI: 10.1016/j.plantsci.2018.06.015⟩
Popis: International audience; 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 pot/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 objectives, “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.
Databáze: OpenAIRE
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