title: Canopy Temperature and Vegetation Indices from High-Throughput Phenotyping Improve Accuracy of Pedigree and Genomic Selection for Grain Yield in Wheat.
abstract: Genomic selection can be applied prior to phenotyping, enabling shorter breeding cycles and greater rates of genetic gain relative to phenotypic selection. Traits measured using high-throughput phenotyping based on proximal or remote sensing could be useful for improving pedigree and genomic prediction model accuracies for traits not yet possible to phenotype directly. We tested if using aerial measurements of canopy temperature, and green and red normalized difference vegetation index as secondary traits in pedigree and genomic best linear unbiased prediction models could increase accuracy for grain yield in wheat, Triticum aestivum L., using 557 lines in five environments. Secondary traits on training and test sets, and grain yield on the training set were modeled as multivariate, and compared to univariate models with grain yield on the training set only. Cross validation accuracies were estimated within and across-environment, with and without replication, and with and without correcting for days to heading. We observed that, within environment, with unreplicated secondary trait data, and without correcting for days to heading, secondary traits increased accuracies for grain yield by 56% in pedigree, and 70% in genomic prediction models, on average. Secondary traits increased accuracy slightly more when replicated, and considerably less when models corrected for days to heading. In across-environment prediction, trends were similar but less consistent. These results show that secondary traits measured in high-throughput could be used in pedigree and genomic prediction to improve accuracy. This approach could improve selection in wheat during early stages if validated in early-generation breeding plots.
authors.affiliation: International Programs, College of Agriculture and Life Sciences, Cornell University, Ithaca, New York 14853 Plant Breeding and Genetics Section, School of Integrated Plant Sciences, Cornell University, Ithaca, New York 14853 Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), Ciudad de Mexico, 06600, Mexico jer263@cornell.edu.
authors.forename: Jessica
authors.initials: J
authors.lastname: Rutkoski
authors.affiliation: Department of Plant Pathology, Kansas State University, Manhattan, Kansas 66506.
authors.forename: Jesse
authors.initials: J
authors.lastname: Poland
authors.affiliation: Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), Ciudad de Mexico, 06600, Mexico.
authors.forename: Suchismita
authors.initials: S
authors.lastname: Mondal
authors.affiliation: Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), Ciudad de Mexico, 06600, Mexico.
authors.forename: Enrique
authors.initials: E
authors.lastname: Autrique
authors.affiliation: Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), Ciudad de Mexico, 06600, Mexico.
authors.forename: Lorena González
authors.initials: LG
authors.lastname: Pérez
authors.affiliation: Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), Ciudad de Mexico, 06600, Mexico.
authors.forename: José
authors.initials: J
authors.lastname: Crossa
authors.affiliation: Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), Ciudad de Mexico, 06600, Mexico.
authors.forename: Matthew
authors.initials: M
authors.lastname: Reynolds
authors.affiliation: Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), Ciudad de Mexico, 06600, Mexico.
authors.forename: Ravi
authors.initials: R
authors.lastname: Singh
mesh_terms: D001947:Breeding; D002523:Edible Grain / Q000235:genetics / Q000254:growth & development; D004734:Energy Metabolism / Q000235:genetics*; D018745:Genome, Plant; D023281:Genomics; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci / Q000235:genetics*; D012641:Selection, Genetic; D013696:Temperature; D014908:Triticum / Q000235:genetics* / Q000254:growth & development
keywords: GenPred; Secondary traits in genomic selection; multivariate analysis; selection index; shared data resource