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A low-cost and open-source platform for automated imaging.

Max R Lien | Richard J Barker | Zhiwei Ye | Matthew H Westphall | Ruohan Gao | Aditya Singh | Simon Gilroy | Philip A Townsend
Plant methods | 2019

Remote monitoring of plants using hyperspectral imaging has become an important tool for the study of plant growth, development, and physiology. Many applications are oriented towards use in field environments to enable non-destructive analysis of crop responses due to factors such as drought, nutrient deficiency, and disease, e.g., using tram, drone, or airplane mounted instruments. The field setting introduces a wide range of uncontrolled environmental variables that make validation and interpretation of spectral responses challenging, and as such lab- and greenhouse-deployed systems for plant studies and phenotyping are of increasing interest. In this study, we have designed and developed an open-source, hyperspectral reflectance-based imaging system for lab-based plant experiments: the HyperScanner. The reliability and accuracy of HyperScanner were validated using drought and salt stress experiments with Arabidopsis thaliana.

Pubmed ID: 30705688

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RRID:SCR_004129

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