Location: Soil Management ResearchTitle: Multitrait mixed modeling and categorical data analyses of phenotypic variances
Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 11/5/2014
Publication Date: 11/5/2014
Citation: Jaradat, A.A., Starr, J.P., Rinke, J.L., Wente, C.D. 2014. Multitrait mixed modeling and categorical data analyses of phenotypic variances [abstract]. ASA-CSSA-SSSA Annual Meeting Abstracts. ASA-CSSA-SSSA Annual Meeting. Nov. 2-5, 2014, Long Beach, CA.
Technical Abstract: Quantitative and categorical data were digitally recorded, measured or scored on whole canopies; single plants, leaves, and siliques; and on random seed samples of 224 genotypes in a phenotyping nursery of Brassica napus. They were used to (1) develop a pyramiding phenotyping model based on multitrait field and laboratory characterization and evaluation data, and (2) account for fixed and random sources of variation and interpret components of phenotypic variance. A photothermal quotient, the soil series identified in the experimental area, and soil apparent electrical conductivity were measured for the whole nursery or for each plot and, in addition to a systematic check variety, were used as covariates in estimating and adjusting for soil spatial variation. We identified a minimum set of traits at different stages of plant ontogeny with maximum discriminating power between genotypes, partitioned total variance for each trait into its components, developed a reliable field phenotyping protocol; and identified and selected genotypes adapted to the short-growing season in the upper Midwest having 2-5% oil content larger than the check variety.