Planning incomplete block experiments when treatments are genetically related

J. S D S Bueno Filho; Steven G. Gilmour

doi:10.1111/1541-0420.00044

Planning incomplete block experiments when treatments are genetically related

J. S D S Bueno Filho^*, Steven G. Gilmour

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

32 Citations (Scopus)

Abstract

Selection trials in plant and animal breeding, in incomplete blocks, are described by linear models with random effect parameters associated with treatments with known genetic covariance structure. It is now well known that the information on relatives can improve the analysis and many extensions of this model have been proposed, but no studies have been done on the consequences of this genetical relatedness among treatments for the optimality of block designs. Using a suitable optimality criterion, we show that the knowledge on relatedness may imply that the optimal design is not in the class of designs which are optimal for unrelated treatments. Implications for practical applications are discussed.

Original language	English
Pages (from-to)	375-381
Number of pages	7
Journal	Biometrics
Volume	59
Issue number	2
DOIs	https://doi.org/10.1111/1541-0420.00044
Publication status	Published - Jun 2003

Keywords

Breeding
Design of experiments
Family structure
Mixed models
Optimal design

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1111/1541-0420.00044

Cite this

@article{95bac3d655c7459ab5b04b2cd652c960,

title = "Planning incomplete block experiments when treatments are genetically related",

abstract = "Selection trials in plant and animal breeding, in incomplete blocks, are described by linear models with random effect parameters associated with treatments with known genetic covariance structure. It is now well known that the information on relatives can improve the analysis and many extensions of this model have been proposed, but no studies have been done on the consequences of this genetical relatedness among treatments for the optimality of block designs. Using a suitable optimality criterion, we show that the knowledge on relatedness may imply that the optimal design is not in the class of designs which are optimal for unrelated treatments. Implications for practical applications are discussed.",

keywords = "Breeding, Design of experiments, Family structure, Mixed models, Optimal design",

author = "{Bueno Filho}, {J. S D S} and Gilmour, {Steven G.}",

year = "2003",

month = jun,

doi = "10.1111/1541-0420.00044",

language = "English",

volume = "59",

pages = "375--381",

journal = "Biometrics",

issn = "0006-341X",

publisher = "John Wiley & Sons, Ltd (10.1111)",

number = "2",

}

TY - JOUR

T1 - Planning incomplete block experiments when treatments are genetically related

AU - Bueno Filho, J. S D S

AU - Gilmour, Steven G.

PY - 2003/6

Y1 - 2003/6

N2 - Selection trials in plant and animal breeding, in incomplete blocks, are described by linear models with random effect parameters associated with treatments with known genetic covariance structure. It is now well known that the information on relatives can improve the analysis and many extensions of this model have been proposed, but no studies have been done on the consequences of this genetical relatedness among treatments for the optimality of block designs. Using a suitable optimality criterion, we show that the knowledge on relatedness may imply that the optimal design is not in the class of designs which are optimal for unrelated treatments. Implications for practical applications are discussed.

AB - Selection trials in plant and animal breeding, in incomplete blocks, are described by linear models with random effect parameters associated with treatments with known genetic covariance structure. It is now well known that the information on relatives can improve the analysis and many extensions of this model have been proposed, but no studies have been done on the consequences of this genetical relatedness among treatments for the optimality of block designs. Using a suitable optimality criterion, we show that the knowledge on relatedness may imply that the optimal design is not in the class of designs which are optimal for unrelated treatments. Implications for practical applications are discussed.

KW - Breeding

KW - Design of experiments

KW - Family structure

KW - Mixed models

KW - Optimal design

UR - http://www.scopus.com/inward/record.url?scp=0038545795&partnerID=8YFLogxK

U2 - 10.1111/1541-0420.00044

DO - 10.1111/1541-0420.00044

M3 - Article

C2 - 12926722

AN - SCOPUS:0038545795

SN - 0006-341X

VL - 59

SP - 375

EP - 381

JO - Biometrics

JF - Biometrics

IS - 2

ER -

Planning incomplete block experiments when treatments are genetically related

Abstract

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this