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A comparison between joint regression analysis and the AMMI model: A case study with barley

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A comparison between joint regression analysis and the AMMI model : A case study with barley. / Pereira, Dulce G.; Rodrigues, Paulo C.; Mejza, Stanislaw; Mexia, João T.

In: JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, Vol. 82, No. 2, 02.2012, p. 193-207.

Research output: Contribution to journalArticleScientificpeer-review

Harvard

Pereira, DG, Rodrigues, PC, Mejza, S & Mexia, JT 2012, 'A comparison between joint regression analysis and the AMMI model: A case study with barley', JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, vol. 82, no. 2, pp. 193-207. https://doi.org/10.1080/00949655.2011.615839

APA

Pereira, D. G., Rodrigues, P. C., Mejza, S., & Mexia, J. T. (2012). A comparison between joint regression analysis and the AMMI model: A case study with barley. JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 82(2), 193-207. https://doi.org/10.1080/00949655.2011.615839

Vancouver

Pereira DG, Rodrigues PC, Mejza S, Mexia JT. A comparison between joint regression analysis and the AMMI model: A case study with barley. JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION. 2012 Feb;82(2):193-207. https://doi.org/10.1080/00949655.2011.615839

Author

Pereira, Dulce G. ; Rodrigues, Paulo C. ; Mejza, Stanislaw ; Mexia, João T. / A comparison between joint regression analysis and the AMMI model : A case study with barley. In: JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION. 2012 ; Vol. 82, No. 2. pp. 193-207.

Bibtex - Download

@article{4b025f3243ef4275be5636a5cddb2558,
title = "A comparison between joint regression analysis and the AMMI model: A case study with barley",
abstract = "Joint regression analysis (JRA) and additive main effects and multiplicative interaction (AMMI) models are compared in order to (i) access the ability of describing a genotype by environment interaction effects and (ii) evaluate the agreement between the winners of mega-environments obtained from the AMMI analysis and the genotypes in the upper contour of the JRA. An iterative algorithm is used to obtain the environmental indexes for JRA, and standard multiple comparison procedures are adapted for genotype comparison and selection. This study includes three data sets from a spring barley (Hordeum vulgare L.) breeding programme carried out between 2004 and 2006 in Czech Republic. The results from both techniques are integrated in order to advise plant breeders, farmers and agronomists for better genotype selection and prediction for new years and/or new environments.",
keywords = "AMMI models, joint regression analysis, mega-environments, multiple comparisons, spring barley, zigzag algorithm",
author = "Pereira, {Dulce G.} and Rodrigues, {Paulo C.} and Stanislaw Mejza and Mexia, {Jo{\~a}o T.}",
year = "2012",
month = "2",
doi = "10.1080/00949655.2011.615839",
language = "English",
volume = "82",
pages = "193--207",
journal = "JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION",
issn = "0094-9655",
publisher = "Taylor & Francis",
number = "2",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - A comparison between joint regression analysis and the AMMI model

T2 - A case study with barley

AU - Pereira, Dulce G.

AU - Rodrigues, Paulo C.

AU - Mejza, Stanislaw

AU - Mexia, João T.

PY - 2012/2

Y1 - 2012/2

N2 - Joint regression analysis (JRA) and additive main effects and multiplicative interaction (AMMI) models are compared in order to (i) access the ability of describing a genotype by environment interaction effects and (ii) evaluate the agreement between the winners of mega-environments obtained from the AMMI analysis and the genotypes in the upper contour of the JRA. An iterative algorithm is used to obtain the environmental indexes for JRA, and standard multiple comparison procedures are adapted for genotype comparison and selection. This study includes three data sets from a spring barley (Hordeum vulgare L.) breeding programme carried out between 2004 and 2006 in Czech Republic. The results from both techniques are integrated in order to advise plant breeders, farmers and agronomists for better genotype selection and prediction for new years and/or new environments.

AB - Joint regression analysis (JRA) and additive main effects and multiplicative interaction (AMMI) models are compared in order to (i) access the ability of describing a genotype by environment interaction effects and (ii) evaluate the agreement between the winners of mega-environments obtained from the AMMI analysis and the genotypes in the upper contour of the JRA. An iterative algorithm is used to obtain the environmental indexes for JRA, and standard multiple comparison procedures are adapted for genotype comparison and selection. This study includes three data sets from a spring barley (Hordeum vulgare L.) breeding programme carried out between 2004 and 2006 in Czech Republic. The results from both techniques are integrated in order to advise plant breeders, farmers and agronomists for better genotype selection and prediction for new years and/or new environments.

KW - AMMI models

KW - joint regression analysis

KW - mega-environments

KW - multiple comparisons

KW - spring barley

KW - zigzag algorithm

UR - http://www.scopus.com/inward/record.url?scp=84856990001&partnerID=8YFLogxK

U2 - 10.1080/00949655.2011.615839

DO - 10.1080/00949655.2011.615839

M3 - Article

VL - 82

SP - 193

EP - 207

JO - JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION

JF - JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION

SN - 0094-9655

IS - 2

ER -