Abstract
Phenotyping is a crucial building block in crop breeding research, integrating our understanding of crop development, growth and yield under different environments, with the genetic inheritance of key traits. Acquiring crop trait data traditionally involves time-consuming, laborious and destructive sampling techniques, limiting the unification of phenomics data with high-throughput genomics data. Advanced phenotyping platforms developed in the past two decades, deployed both in controlled environments and field, have revolutionized data capture, analysis and output. The combination of high-throughput, accurate sensor technology, with advanced image analysis pipelines, computer learning techniques and data storage systems, have contributed to remote, precise and non-destructive phenotyping. Visible, multispectral, hyperspectral, fluorescence and laser sensors and cameras can non-invasively monitor biochemical, water content, biomass, morphological, phenological, yield- and root-related traits. Here, we describe developments of sensor-based phenotyping for cereals, especially wheat. By examining traits amenable to efficient phenotyping, and the usage of various high-throughput platforms in crop research and breeding, the key benefits of sensor-based phenotyping are demonstrated.
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Thoday-Kennedy, E., Good, N., Kant, S. (2022). Basics of Sensor-Based Phenotyping in Wheat. In: Bilichak, A., Laurie, J.D. (eds) Accelerated Breeding of Cereal Crops. Springer Protocols Handbooks. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1526-3_16
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