The adoption of automated phenotyping by plant breeders

Phenomics or automated phenotyping (AP) is an emerging approach, identified as a priority for future crop breeding research. This approach promises to provide accurate, precise, fast, large-scale, and accumulated phenotyping data which when integrated with corresponding genomic and environmental data is expected to trigger a great leap forward in plant breeding. However, despite promising applications, AP adoption in plant breeding is still in its infancy. It is unclear to many plant breeders how or if much of the enormous volume, diversity, and velocity of imaging and remote-sensing data generated by AP is going to be usefully integrated into breeding programs. This paper develops an economical model of heterogeneous breeders' decision-making to examine adoption decisions regarding whether to adopt AP or continue using conventional phenotyping. The results of this model indicate that many interlocking factors, including genetic gain/expected return, variable and sunk costs, subsequent rate of technology improvement, and breeders' level of aversion to AP, are at work as breeders determine whether to adopt AP. This study also provides a numerical example to show the impact of breeders' aversion toward the adoption of a new technology (e.g., AP) on the expected return generated from breeding a new wheat variety.