HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Figures Only Full Text Free Full Text (PDF) Free Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in ISI Web of Science Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via ISI Web of Science (15) Citing Articles via Google Scholar Google Scholar Articles by Holland, J. B. Search for Related Content PubMed Articles by Holland, J. B. Agricola Articles by Holland, J. B. Related Collections Software Crop Genetics Statistics

CROP BREEDING, GENETICS & CYTOLOGY

Estimating Genotypic Correlations and Their Standard Errors Using Multivariate Restricted Maximum Likelihood Estimation with SAS Proc MIXED

USDA-ARS Plant Science Research Unit, Dep. of Crop Science, Box 7620, North Carolina State University, Raleigh, NC 27695-7620

^* Corresponding author (James_Holland{at}ncsu.edu)

Plant breeders traditionally have estimated genotypic and phenotypic correlations between traits using the method of moments on the basis of a multivariate analysis of variance (MANOVA). Drawbacks of using the method of moments to estimate variance and covariance components include the possibility of obtaining estimates outside of parameter bounds, reduced estimation efficiency, and ignorance of the estimators' distributional properties when data are missing. An alternative approach that does not suffer these problems, but depends on the assumption of normally distributed random effects and large sample sizes, is restricted maximum likelihood (REML). This paper illustrates the use of Proc MIXED of the SAS system to implement REML estimation of genotypic and phenotypic correlations. Additionally, a method to obtain approximate parametric estimates of the sampling variances of the correlation estimates is presented. MANOVA and REML methods were compared with a real data set and with simulated data. The simulation study examined the effects of different correlation parameter values, genotypic and environmental sample sizes, and proportion of missing data on Type I and Type II error rates and on accuracy of confidence intervals. The two methods provided similar results when data were balanced or only 5% of data were missing. However, when 15 or 25% data were missing, the REML method generally performed better, resulting in higher power of detection of correlations and more accurate 95% confidence intervals. Samples of at least 75 genotypes and two environments are recommended to obtain accurate confidence intervals using the proposed method.

Abbreviations: CI, confidence interval • GDD, growing degree days • GEI, genotype x environment interaction • MANOVA, multivariate analysis of variance • MCAR, missing completely at random • MPAR, missing plots at random • PH, plant height • REML, restricted maximum likelihood

This article has been cited by other articles:

				M. Prudent, M. Causse, M. Genard, P. Tripodi, S. Grandillo, and N. Bertin Genetic and physiological analysis of tomato fruit weight and composition: influence of carbon availability on QTL detection J. Exp. Bot., March 1, 2009; 60(3): 923 - 937. [Abstract] [Full Text] [PDF]

				R. E. Lorenzana and R. Bernardo Genetic Correlation between Corn Performance in Organic and Conventional Production Systems Crop Sci., May 1, 2008; 48(3): 903 - 910. [Abstract] [Full Text] [PDF]

				A. J. Cardinal, R. E. Dewey, and J. W. Burton Estimating the Individual Effects of the Reduced Palmitic Acid fapnc and fap1 Alleles on Agronomic Traits in Two Soybean Populations Crop Sci., March 19, 2008; 48(2): 633 - 639. [Abstract] [Full Text] [PDF]

				M. L. Wayne, M. Telonis-Scott, L. M. Bono, L. Harshman, A. Kopp, S. V. Nuzhdin, and L. M. McIntyre Simpler mode of inheritance of transcriptional variation in male Drosophila melanogaster PNAS, November 20, 2007; 104(47): 18577 - 18582. [Abstract] [Full Text] [PDF]

				A. J. Cardinal and J. W. Burton Correlations between Palmitate Content and Agronomic Traits in Soybean Populations Segregating for the fap1, fapnc, and fan Alleles Crop Sci., September 1, 2007; 47(5): 1804 - 1812. [Abstract] [Full Text] [PDF]

				S. B. Milligan, M. Balzarini, K. A. Gravois, and K. P. Bischoff Early Stage Sugarcane Selection Using Different Plot Sizes Crop Sci., September 1, 2007; 47(5): 1859 - 1864. [Abstract] [Full Text] [PDF]

				J. G. Robins, D. Luth, T. A. Campbell, G. R. Bauchan, C. He, D. R. Viands, J. L. Hansen, and E. C. Brummer Genetic Mapping of Biomass Production in Tetraploid Alfalfa Crop Sci., January 22, 2007; 47(1): 1 - 10. [Abstract] [Full Text] [PDF]

				J. G. Robins, G. R. Bauchan, and E. C. Brummer Genetic Mapping Forage Yield, Plant Height, and Regrowth at Multiple Harvests in Tetraploid Alfalfa (Medicago sativa L.) Crop Sci., January 22, 2007; 47(1): 11 - 18. [Abstract] [Full Text] [PDF]

				K. B. Jensen, J. G. Robins, B. L. Waldron, and M. D. Peel Genetic Variation in Dry Matter Production and Nutritional Characteristics of Meadow Bromegrass under Repeated Defoliation Crop Sci., July 25, 2006; 46(5): 1948 - 1954. [Abstract] [Full Text] [PDF]