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Research article - Peer-reviewed, 2021

Phenocave: An Automated, Standalone, and Affordable Phenotyping System for Controlled Growth Conditions

Leiva, Fernanda; Vallenback, Pernilla; Ekblad, Tobias; Johansson, Eva; Chawade, Aakash

Abstract

Controlled plant growth facilities provide the possibility to alter climate conditions affecting plant growth, such as humidity, temperature, and light, allowing a better understanding of plant responses to abiotic and biotic stresses. A bottleneck, however, is measuring various aspects of plant growth regularly and non-destructively. Although several high-throughput phenotyping facilities have been built worldwide, further development is required for smaller custom-made affordable systems for specific needs. Hence, the main objective of this study was to develop an affordable, standalone and automated phenotyping system called "Phenocave" for controlled growth facilities. The system can be equipped with consumer-grade digital cameras and multispectral cameras for imaging from the top view. The cameras are mounted on a gantry with two linear actuators enabling XY motion, thereby enabling imaging of the entire area of Phenocave. A blueprint for constructing such a system is presented and is evaluated with two case studies using wheat and sugar beet as model plants. The wheat plants were treated with different irrigation regimes or high nitrogen application at different developmental stages affecting their biomass accumulation and growth rate. A significant correlation was observed between conventional measurements and digital biomass at different time points. Post-harvest analysis of grain protein content and composition corresponded well with those of previous studies. The results from the sugar beet study revealed that seed treatment(s) before germination influences germination rates. Phenocave enables automated phenotyping of plants under controlled conditions, and the protocols and results from this study will allow others to build similar systems with dimensions suitable for their custom needs.

Keywords

affordable; phenotyping; drought; image analysis; automated

Published in

Plants
2021, volume: 10, number: 9, article number: 1817
Publisher: MDPI

Authors' information

Swedish University of Agricultural Sciences, Department of Plant Breeding
Vallenback, Pernilla
Lantmannen Lantbruk
Ekblad, Tobias
Lantmännen Lantbruk
Swedish University of Agricultural Sciences, Department of Plant Breeding
Swedish University of Agricultural Sciences, Department of Plant Breeding

UKÄ Subject classification

Agricultural Science

Publication Identifiers

DOI: https://doi.org/10.3390/plants10091817

URI (permanent link to this page)

https://res.slu.se/id/publ/113888