Raspberry Pi Powered Imaging for Plant Phenotyping

Abstract

ABSTRACT• Premise of the study: Image-based phenomics is a powerful approach to capture and quantify plant diversity. However, commercial platforms that make consistent image acquisition easy are often cost-prohibitive. To make high-throughput phenotyping methods more accessible, low-cost microcomputers and cameras can be used to acquire plant image data.• en masse using open-source image processing software such as PlantCV.• Conclusion: This protocol describes three low-cost platforms for image acquisition that are useful for quantifying plant diversity. When coupled with open-source image processing tools, these imaging platforms provide viable low-cost solutions for incorporating high-throughput phenomics into a wide range of research programs.

High-throughput root phenotyping of crop cultivars tolerant to low N in waterlogged soils

“…IS such as red, green, and blue (RGB) sensors that take images within the wavelength range of 400-700 nm are termed visible IS, while IS that go beyond the visible wavelength are known as spectral IS (SIS) (Beisel et al, 2018;Bruning et al, 2020). In controlled conditions such as glasshouses or growth chambers, IS range from low-cost cameras to costly custom-made imaging setups (Tovar et al, 2018). Recently, Xia et al (2019) used hyperspectral and RGB to phenotype WL in rape plants and found promising results.…”