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Title:   Author  item
                                            ORRELLANA, MASSIEL - Monsanto Corporationitem
                                            Edwards, Jodeitem
                                            CARRIQUIRY, ALICIA - Iowa State University
  Submitted to: Crop Science
                                    Publication Type: Peer Reviewed Journal
                                    Publication Acceptance Date: 11/12/2013
                                    Publication  Date: 4/9/2014
                                    Citation: Orrellana, M., Edwards, J.W., Carriquiry, A. 2014. Heterogeneous variances in multi-environment yield trials for corn hybrids. Crop Science. 54(3):1048-1056.Interpretive Summary: Identifying cultivars with high yield and stable performance is a challenge for plant breeders and producers because differences between cultivars vary among environments.  Cultivars must therefore be compared in many environments to estimate average performance and identify cultivars with stable performance.  Several statistical procedures have been proposed for this problem but have not been used because of the complexity of the models and difficulty in interpreting results.  We have tested an alternative estimation approach to the classical model to provide additional robust information on stability of individual cultivars.  The model indicated that Maize hybrids submitted for testing to the Iowa Crop Performance Test for Corn differ substantially in their stability of performance and these differences were clearly identified by our statistical approach.  The results will benefit breeders and producers who are trying to identify stable and high performing cultivars.
                                Technical Abstract: Recent developments in statistics and computing have enabled much greater levels of complexity in statistical models of multi-environment yield trial data.  One particular feature of interest to breeders is simultaneously modeling heterogeneity of variances among environments and cultivars.  Our objective was to estimate the level of heterogeneity of genotype by environment interaction variance and error variance in the Iowa Crop Performance Test for Corn.  A Bayesian approach was used to estimate variance components in a hierarchical model that allows for heterogeneous error and GEI variances applied to corn yield data from the Iowa Crop Performance Test carried out between 1995 and 2005.  An average of 508 hybrids were tested per year with very little overlap between locations and years, which resulted in a very unbalanced data set. We divided the data into 16 subsets to study the effect of variability across locations and across years.  We found genotype by environment and error variances to be heterogeneous among both environments and genotypes.  Our results for corn contrasted previous work on Oat (Avena Sativa L.) in which very little heterogeneity was found for error variance among cultivars suggesting that in addition to cultivar-specific genotype by environment interaction variance as found in Oat, Maize hybrids also had cultivar-specific error variances.


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