NDLI: On the Design of Field Experiments with Correlated Treatment Effects

Content Provider	Springer Nature Link
Author	Butler, David G. Smith, Alison B. Cullis, Brian R.
Copyright Year	2014
Abstract	Large-scale field evaluation of genetic material forms an important part of the selection process in the early stages of plant breeding programs. These experiments are typically designed ignoring information on genetic relatedness, often available in the form of crossing history, or plant pedigree records. This paper considers the design of plant breeding experiments where the residuals may be correlated with an assumed autoregressive process, and there is a known genetic covariance structure among genotype effects. This structure is frequently more complex than simple nested family models, arising more generally from the pedigree, or possibly identity in state measures. It is widely accepted that the analysis of these data is improved using information on related individuals. The design of these experiments exploiting known genetic relatedness is considered using three case studies from industry that differ in selection goals, genetic complexity and scale.
Starting Page	539
Ending Page	555
Page Count	17
File Format	PDF
ISSN	10857117
Journal	Journal of Agricultural, Biological, and Environmental Statistics
Volume Number	19
Issue Number	4
e-ISSN	15372693
Language	English
Publisher	Springer US
Publisher Date	2014-12-04
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Optimal design Additive relationship matrix Plant breeding Mixed models Statistics for Life Sciences, Medicine, Health Sciences Agriculture Environmental Monitoring/Analysis Biostatistics
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Statistics and Probability Environmental Science Agricultural and Biological Sciences Statistics, Probability and Uncertainty

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