Data from: Combining high-throughput phenotyping and genomic information to increase prediction and selection accuracy in wheat breeding

Genomics and phenomics have promised to revolutionize the field of plant
breeding. The integration of these two fields has just begun and is being
driven through big data by advances in next-generation sequencing and
developments of field-based high-throughput phenotyping (HTP) platforms.
Each year the International Maize and Wheat Improvement Center (CIMMYT)
evaluates tens-of-thousands of advanced lines for grain yield across
multiple environments. To evaluate how CIMMYT may utilize dynamic HTP data
for genomic selection (GS), we evaluated 1170 of these advanced lines in
two environments, drought (2014, 2015) and heat (2015). A portable
phenotyping system called ‘Phenocart’ was used to measure normalized
difference vegetation index and canopy temperature simultaneously while
tagging each data point with precise GPS coordinates. For genomic
profiling, genotyping-by-sequencing (GBS) was used for marker discovery
and genotyping. Several GS models were evaluated utilizing the 2254 GBS
markers along with over 1.1 million phenotypic observations. The
physiological measurements collected by HTP, whether used as a response in
multivariate models or as a covariate in univariate models, resulted in a
range of 33% below to 7% above the standard univariate model. Continued
advances in yield prediction models as well as increasing data generating
capabilities for both genomic and phenomic data will make these selection
strategies tractable for plant breeders to implement increasing the rate
of genetic gain.