LAUSR

Abstract Premise With modern advances in genetic sequencing technology, plant phenotyping has become a substantial bottleneck in crop improvement programs. Traditionally, researchers have manually measured phenotypic traits to help determine genotype–phenotype relationships, but manual measurements can be time consuming and expensive. Recently, automated phenotyping systems have increased the spatial and temporal density of measurements, but most of these systems are extremely expensive and require specialized expertise. In the present paper, we develop and validate a low‐cost, scalable, high‐throughput phenotyping (HTP) system for automating the measurement of foliar area and greenness. Methods During a greenhouse experiment on the effects of abiotic stress on Brassica rapa, we collected images of hundreds of plants every hour for over a month with a system that cost approximately US$1000. Results In comparison with manually acquired images, this HTP system was able to produce similar estimates of foliar area and greenness, developmental trends, and treatment effects. Foliar area was correlated between the two image sets, but greenness was not. Discussion These findings highlight the potential of HTP systems built from low‐cost hardware and freely available software. Future work can use this system to investigate genotype–environment interactions and the genetic loci underlying morphological changes resulting from abiotic stress.