Development of a mobile, high-throughput, and low-cost image-based plant growth phenotyping system

吞吐量 植物生长 生物 计算机科学 计算生物学 植物 电信 无线
作者
Liang Yu,Hayley Sussman,Olga Khmelnitsky,Maryam Rahmati Ishka,A. SRINIVASAN,Andrew D. L. Nelson,Magdalena Julkowska
出处
期刊:Plant Physiology [Oxford University Press]
卷期号:196 (2): 810-829 被引量:2
标识
DOI:10.1093/plphys/kiae237
摘要

Nondestructive plant phenotyping forms a key technique for unraveling molecular processes underlying plant development and response to the environment. While the emergence of high-throughput phenotyping facilities can further our understanding of plant development and stress responses, their high costs greatly hinder scientific progress. To democratize high-throughput plant phenotyping, we developed sets of low-cost image- and weight-based devices to monitor plant shoot growth and evapotranspiration. We paired these devices to a suite of computational pipelines for integrated and straightforward data analysis. The developed tools were validated for their suitability for large genetic screens by evaluating a cowpea (Vigna unguiculata) diversity panel for responses to drought stress. The observed natural variation was used as an input for a genome-wide association study, from which we identified nine genetic loci that might contribute to cowpea drought resilience during early vegetative development. The homologs of the candidate genes were identified in Arabidopsis (Arabidopsis thaliana) and subsequently evaluated for their involvement in drought stress by using available T-DNA insertion mutant lines. These results demonstrate the varied applicability of this low-cost phenotyping system. In the future, we foresee these setups facilitating the identification of genetic components of growth, plant architecture, and stress tolerance across a wide variety of plant species.

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