Clustering environments to minimize change in rank of cultivars

W. K. Russell, K. M. Eskridge, D. A. Travnicek, F. R. Guillen-Portal

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

Crossover interactions occur in evaluation trials when ranks of cultivars change across environments. Determining groups of environments within which crossover interactions are minimized may facilitate making cultivar recommendations. The goal of this research was to test a new approach for determining these environmental groups in which crossover interaction between a pair of cultivars was defined across all environments. The number of groups was based both on reduction in crossover interaction and repeatability of cultivar means within groups. The validity of this procedure was tested on three simulated data sets with known crossover interactions. For each data set, the approach divided the environments into the two groups that minimized crossover interactions. The approach also was applied to yield data from a maize (Zea mays L.) trial in which 59 environments previously had been clustered by a different measure of crossover interaction. Three groups of 12 environments and one group of 23 environments were defined. The previous clustering had identified six clusters. The amount of crossover interaction within the four environmental groups was reduced by 53% from the total crossover inter action in all 59 environments. The results of the clustering depended on whether all pairwise comparisons among cultivars or only the significant crossover interactions among the higher yielding cultivars were used. The latter method was deemed more appropriate when the goal is to recommend specific cultivars for specific groups of environments. Regardless of the approach used, clustering based on crossover interactions only has practical significance if these interactions are repeatable.

Original languageEnglish (US)
Pages (from-to)858-864
Number of pages7
JournalCrop Science
Volume43
Issue number3
StatePublished - May 1 2003

Fingerprint

cultivars
high-yielding varieties
repeatability
Zea mays
corn
testing
methodology

ASJC Scopus subject areas

  • Agronomy and Crop Science

Cite this

Russell, W. K., Eskridge, K. M., Travnicek, D. A., & Guillen-Portal, F. R. (2003). Clustering environments to minimize change in rank of cultivars. Crop Science, 43(3), 858-864.

Clustering environments to minimize change in rank of cultivars. / Russell, W. K.; Eskridge, K. M.; Travnicek, D. A.; Guillen-Portal, F. R.

In: Crop Science, Vol. 43, No. 3, 01.05.2003, p. 858-864.

Research output: Contribution to journalArticle

Russell, WK, Eskridge, KM, Travnicek, DA & Guillen-Portal, FR 2003, 'Clustering environments to minimize change in rank of cultivars', Crop Science, vol. 43, no. 3, pp. 858-864.
Russell WK, Eskridge KM, Travnicek DA, Guillen-Portal FR. Clustering environments to minimize change in rank of cultivars. Crop Science. 2003 May 1;43(3):858-864.
Russell, W. K. ; Eskridge, K. M. ; Travnicek, D. A. ; Guillen-Portal, F. R. / Clustering environments to minimize change in rank of cultivars. In: Crop Science. 2003 ; Vol. 43, No. 3. pp. 858-864.
@article{7603120400274f499ecbb498aad008ee,
title = "Clustering environments to minimize change in rank of cultivars",
abstract = "Crossover interactions occur in evaluation trials when ranks of cultivars change across environments. Determining groups of environments within which crossover interactions are minimized may facilitate making cultivar recommendations. The goal of this research was to test a new approach for determining these environmental groups in which crossover interaction between a pair of cultivars was defined across all environments. The number of groups was based both on reduction in crossover interaction and repeatability of cultivar means within groups. The validity of this procedure was tested on three simulated data sets with known crossover interactions. For each data set, the approach divided the environments into the two groups that minimized crossover interactions. The approach also was applied to yield data from a maize (Zea mays L.) trial in which 59 environments previously had been clustered by a different measure of crossover interaction. Three groups of 12 environments and one group of 23 environments were defined. The previous clustering had identified six clusters. The amount of crossover interaction within the four environmental groups was reduced by 53{\%} from the total crossover inter action in all 59 environments. The results of the clustering depended on whether all pairwise comparisons among cultivars or only the significant crossover interactions among the higher yielding cultivars were used. The latter method was deemed more appropriate when the goal is to recommend specific cultivars for specific groups of environments. Regardless of the approach used, clustering based on crossover interactions only has practical significance if these interactions are repeatable.",
author = "Russell, {W. K.} and Eskridge, {K. M.} and Travnicek, {D. A.} and Guillen-Portal, {F. R.}",
year = "2003",
month = "5",
day = "1",
language = "English (US)",
volume = "43",
pages = "858--864",
journal = "Crop Science",
issn = "0011-183X",
publisher = "Crop Science Society of America",
number = "3",

}

TY - JOUR

T1 - Clustering environments to minimize change in rank of cultivars

AU - Russell, W. K.

AU - Eskridge, K. M.

AU - Travnicek, D. A.

AU - Guillen-Portal, F. R.

PY - 2003/5/1

Y1 - 2003/5/1

N2 - Crossover interactions occur in evaluation trials when ranks of cultivars change across environments. Determining groups of environments within which crossover interactions are minimized may facilitate making cultivar recommendations. The goal of this research was to test a new approach for determining these environmental groups in which crossover interaction between a pair of cultivars was defined across all environments. The number of groups was based both on reduction in crossover interaction and repeatability of cultivar means within groups. The validity of this procedure was tested on three simulated data sets with known crossover interactions. For each data set, the approach divided the environments into the two groups that minimized crossover interactions. The approach also was applied to yield data from a maize (Zea mays L.) trial in which 59 environments previously had been clustered by a different measure of crossover interaction. Three groups of 12 environments and one group of 23 environments were defined. The previous clustering had identified six clusters. The amount of crossover interaction within the four environmental groups was reduced by 53% from the total crossover inter action in all 59 environments. The results of the clustering depended on whether all pairwise comparisons among cultivars or only the significant crossover interactions among the higher yielding cultivars were used. The latter method was deemed more appropriate when the goal is to recommend specific cultivars for specific groups of environments. Regardless of the approach used, clustering based on crossover interactions only has practical significance if these interactions are repeatable.

AB - Crossover interactions occur in evaluation trials when ranks of cultivars change across environments. Determining groups of environments within which crossover interactions are minimized may facilitate making cultivar recommendations. The goal of this research was to test a new approach for determining these environmental groups in which crossover interaction between a pair of cultivars was defined across all environments. The number of groups was based both on reduction in crossover interaction and repeatability of cultivar means within groups. The validity of this procedure was tested on three simulated data sets with known crossover interactions. For each data set, the approach divided the environments into the two groups that minimized crossover interactions. The approach also was applied to yield data from a maize (Zea mays L.) trial in which 59 environments previously had been clustered by a different measure of crossover interaction. Three groups of 12 environments and one group of 23 environments were defined. The previous clustering had identified six clusters. The amount of crossover interaction within the four environmental groups was reduced by 53% from the total crossover inter action in all 59 environments. The results of the clustering depended on whether all pairwise comparisons among cultivars or only the significant crossover interactions among the higher yielding cultivars were used. The latter method was deemed more appropriate when the goal is to recommend specific cultivars for specific groups of environments. Regardless of the approach used, clustering based on crossover interactions only has practical significance if these interactions are repeatable.

UR - http://www.scopus.com/inward/record.url?scp=0037695244&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0037695244&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:0037695244

VL - 43

SP - 858

EP - 864

JO - Crop Science

JF - Crop Science

SN - 0011-183X

IS - 3

ER -