High-resolution, time-lapse imaging for ecosystem-scale phenotyping in the field.
The high spatial and temporal resolution of data required for high-throughput phenotyping has typically been all but impossible to obtain in field populations of plants. When studies of individual and population genetic variation and microclimate sensor data are combined with phenology data, a landscape-level view of how populations respond to changing environments can be obtained. This chapter will discuss the development of a multi-billion pixel ("gigapixel") camera system that enables the collection of phenology data at up to hourly intervals from in situ plant populations. Such gigapixel time-lapse imaging systems represent a key technological advancement for enabling high-throughput phenotyping in field settings. Gigapixel resolution image datasets allow researchers to record life-history (phenology) data across an entire landscape over multiple seasons. Image data can be wirelessly transmitted to a remote server where it can be accessed online within hours of capture. The time-lapse panoramic images are browsable through an interactive web tool that can be used to compare plant phenology with environmental sensor data collected simultaneously from the field. The high spatial and temporal resolution data can be used to identify individual plant phenology, which can in turn be used to generate complete population level phenotype data. The Gigavision platform is especially powerful when coupled with next-generation population genomic analysis. The Gigavision system permits the rapid identification of the phenotypes and genotypes responding to natural selection in wild populations.
Time Science, Salt Lake City, UT, USA. tim@time-science.com
Tim
T
Brown
Christopher
C
Zimmermann
Whitney
W
Panneton
Nina
N
Noah
Justin
J
Borevitz
D017753:Ecosystem; D007091:Image Processing, Computer-Assisted; D007909:Lenses; D010641:Phenotype; D012984:Software; D013997:Time Factors; D059008:Time-Lapse Imaging / Q000191:economics / Q000295:instrumentation / Q000379:methods*