GENOTYPE–ENVIRONMENT INTERACTION VARIANCES IN CEREAL YIELDS IN WESTERN CANADA

1968 ◽  
Vol 48 (3) ◽  
pp. 293-298 ◽  
Author(s):  
R. J. Baker
Keyword(s):  
Variance Components ◽  
Western Canada ◽  
Environment Interaction ◽  
Genetic Theory ◽  
Yield Data ◽  
Components Of Variance ◽  
Genotype Environment Interaction ◽  
Quantitative Genetic ◽  
Cereal Yields ◽  
Location Interaction

Yield data for barley, oats, hard red spring and durum wheats from 10 years of testing m western Canada were analyzed. Variety, variety × location interaction, and error components of variance were estimated and the relative values of the latter two were found to differ from those already reported in the literature. The relative values of the variety × location interaction and error variances are important factors in determining the optimum allocation of test sites within years, and in designing experiments to test different aspects of quantitative genetic theory. The year-to-year variability of these relative values as demonstrated in this study will have to be considered in certain applications of estimates of variance components.

GENOTYPE-ENVIRONMENT INTERACTIONS IN YIELD OF WHEAT

1969 ◽  
Vol 49 (6) ◽  
pp. 743-751 ◽  
Author(s):  
R. J. Baker
Keyword(s):  
Detailed Analysis ◽  
Spring Wheat ◽  
Variance Components ◽  
Wheat Yield ◽  
Yield Stability ◽  
Western Canada ◽  
Environment Interaction ◽  
Hard Red Spring Wheat ◽  
Genotype Environment Interaction ◽  
Different Types

A detailed analysis of genotype-environment interactions was carried out among yields of six cultivars of hard red spring wheat grown at each of nine locations in five different years. Subdividing the sum of squares for genotype-environment interactions into components due to each cultivar indicated that the Finlay-Wilkinson method of measuring yield stability is of little value for wheat yield in western Canada. Conventional estimates of variance components due to the different types of genotype-environment interaction indicated that all except the genotype-year interaction were significant and important.

GENOTYPE × ENVIRONMENT INTERACTION AND STABILITY ANALYSIS OF SEED YIELD OF OILSEED RAPE GROWN IN MANITOBA

1988 ◽  
Vol 68 (2) ◽  
pp. 381-388 ◽  
Author(s):  
J. E. BRANDLE ◽  
P. B. E. McVETTY
Keyword(s):  
Brassica Napus ◽  
Oilseed Rape ◽  
Standard Error ◽  
Sums Of Squares ◽  
Environment Interaction ◽  
Brassica Napus L ◽  
Components Of Variance ◽  
Genotype Environment Interaction ◽  
Varying Environments ◽  
Location Interaction

Genotype × environment interactions, cultivar response to environments and cultivar stability for yield of oilseed rape (Brassica napus L.) were studied using five cultivars grown for 3 yr at nine locations in Manitoba. The objectives were: (1) to estimate the components of variance associated with the first- and second-order interactions and to determine their effects on the standard error of a cultivar mean so that optimum test combinations of replications, locations and years for cultivar testing in Manitoba could be determined; (2) to measure cultivar response to varying environments; and (3) to measure cultivar stability. The genotype × year and the genotype × year × location interactions were significant. The genotype × location interaction was not significant, indicating the cultivars tested performed similarly relative to each other across locations over years. Increasing years, locations and replications in that order had the greatest effects on the standard error of a cultivar mean. Calculation of the contribution of each variety to the G × E sums of squares indicated that Westar made the largest contribution and Altex the smallest.Key words: Rape (oilseed), Brassica napus L., stability, cultivar testing

EFFECTS OF GENOTYPE-ENVIRONMENT INTERACTION ON BREAD WHEAT QUALITY IN WESTERN CANADA

1977 ◽  
Vol 57 (1) ◽  
pp. 185-191 ◽  
Author(s):  
R. J. BAKER ◽  
F. G. KOSMOLAK
Keyword(s):  
Triticum Aestivum L ◽  
Western Canada ◽  
Loaf Volume ◽  
Environment Interaction ◽  
Hard Red Spring Wheat ◽  
Flour Protein ◽  
Genotype Environment Interaction ◽  
Protein Flour ◽  
Flour Yield ◽  
Composite Samples

Means, variances and correlations were used in the assessment of the importance of environment and of genotype–environment interaction in determining eight traits which relate to milling and baking quality in hard red spring wheat (Triticum aestivum L.). The study included two composite samples, representing different geographic areas within Western Canada, of 20–30 lines in each of four trials. Differences between environments were found in all traits. It was concluded that genotype–environment interaction was most important in determining mixograph development time, falling number and remix loaf volume, less important in determining farinograph absorption, and least important in determining flour protein, flour yield, grinding time and sedimentation value.

GENOTYPE-ENVIRONMENT INTERACTION VARIANCES IN YIELD TRIALS OF FALL RYE

1970 ◽  
Vol 50 (1) ◽  
pp. 77-80 ◽  
Author(s):  
P. J. KALTSIKES
Keyword(s):  
Genotype By Environment Interaction ◽  
Western Canada ◽  
Environment Interaction ◽  
First Order ◽  
Genotype By Environment ◽  
Genotype Environment Interaction ◽  
Yield Difference ◽  
The Mean ◽  
Yield Trials ◽  
Interaction Variance

Estimates of genotype by environment interaction variances were obtained from the western Canada Co-operative fall rye tests grown in 1963–1967. All first-order interactions and the second-order interactions were significantly greater than zero at the 0.05 level of probability. Although the estimate of cultivar by year interaction variance was relatively small, it accounted for 40% of the variance of a cultivar mean when only three years of testing were considered. However, testing in 20 locations for three years with four replicates could detect yield differences of approximately 10% of the mean of the highest yielding cultivar. If further reduction of the yield difference detectable is desired, more locations should be included in the test.

Selection of environments using simultaneous clustering based on genotype × environment interaction

1994 ◽  
Vol 74 (2) ◽  
pp. 311-317 ◽  
Author(s):  
C. P. Baril ◽  
J-B. Denis ◽  
P. Brabant
Keyword(s):  
Cluster Analysis ◽  
Wheat Yield ◽  
Environment Interaction ◽  
Ge Interaction ◽  
Yield Data ◽  
Cluster Procedure ◽  
Genotype Environment Interaction ◽  
Series Of Experiments ◽  
The Common ◽  
Selection Of

Cluster analysis is used to classify genotypes and environments to decompose and interpret genotype × environment (GE) interaction. A simultaneous clustering method is applied to wheat-yield data collected over 8 yr in seven locations, with two agronomic treatments per location. This approach evidenced redundancies among the used environments constituting the Institut National de la Recherche Agronomique series of experiments in northern France. The aim is to reduce the number of environments without losing GE interaction. A graphical method based on the decreasing mean square of GE interaction is proposed to provide a cutting criterion of the cluster procedure. The comparison of groupings made independently for successive years suggested the removal of some environments, hence providing rational savings in the breeding program. Lastly, the simultaneous two-way clustering procedure is compared with the common one-way clustering procedure. Key words: Cluster analysis, genotype × environment interaction, pattern analysis, series of experiments, wheat

MEASURES OF REPEATABILITY OF GENOTYPE BY LOCATION INTERACTIONS USING DATA FROM BARLEY TRIALS IN NORTHERN SYRIA

2006 ◽  
Vol 42 (2) ◽  
pp. 189-198 ◽  
Author(s):  
M. SINGH ◽  
S. GRANDO ◽  
S. CECCARELLI
Keyword(s):  
Variance Components ◽  
Field Experiments ◽  
Specific Aspect ◽  
Environment Interaction ◽  
Location Factor ◽  
Genotype Environment Interaction ◽  
Using Data ◽  
One Year ◽  
Estimate Variance ◽  
Plant Breeding Programme

Genotype × environment interaction plays an important role in the identification of genotypes with high and stable yields. The environmental components of such interaction can be attributed to location (spatial) and year (temporal) factors. This study considers a specific aspect of the location factor, i.e. that locations not geographically close to each other are likely to vary in terms of the conditions that determine the effect of the year factor, even during the same calendar year. In these situations, the year effects are considered to be random variables within each location. This study addresses the question of whether genotype × location interactions are consistent (or repeatable) over time: a question which is crucial when defining the target environments in a plant breeding programme and when deciding the optimum environment for selection. Using three sets of data from field experiments, various computation methods were developed to estimate variance components; the methods and estimates are presented here. Using the bootstrapping procedure to sample one year from each location within a given calendar year, we obtained bootstrap replicated values of genotype × location interaction and their summary statistics, including the coefficient of variation (CV). We suggest that the CV can be used to measure the repeatability of genotype × location interactions. A Genstat program that can be used to perform the required computations is available from the authors upon request.

scholarly journals Climate change has increased genotype-environment interactions in wheat breeding

2020 ◽  
Author(s):  
Wei Xiong ◽  
Matthew Reynolds ◽  
Jose Crossa ◽  
Thomas Payne ◽  
Urs Schulthess ◽  
...  
Keyword(s):  
Climate Change ◽  
Genetic Model ◽  
Climatic Factors ◽  
Wheat Breeding ◽  
Environment Interaction ◽  
Genotype Environment Interaction ◽  
Quantitative Genetic ◽  
Quantitative Genetic Model ◽  
Yield Responses ◽  
Wheat Lines

Abstract The International Maize and Wheat Improvement Center (CIMMYT) develops and distributes annually elite wheat lines as international trials worldwide to assess their performance in different environments and utilization by partners for use in breeding or release as varieties. However, as elsewhere, the collaborator test sites where trials are evaluated have experienced climate change, with implications for how adapted wheat genotypes are bred. Using a standard quantitative genetic model and archived datasets for four global spring wheat trials, we show that the genotype-environment-interaction (GEI) has increased by up to 500% over recent decades. Notably crossover has increased over time, a critical indicator of changes in the ranking of cultivar performance in different environments. Climatic factors explain over 70% of the year-to-year variability in GEI and crossover interactions for yield. Examining yield responses of all genotypes in all trial environments from 1985 to 2017 reveals that climate change has increased GEI by ~ 49% and ranking change by ~38%. Genetic improvement of wheat targeted to high-yielding environments has exacerbated this increase, but the performance of new wheat germplasm developed to withstand heat and drought stress is more adapted and stable, offsetting the increase in ranking changes due to the warmer climate.

CULTIVAR BY ENVIRONMENT INTERACTIONS, YIELD STABILITY AND GROUPING OF TEST LOCATIONS FOR FIELD BEAN CULTIVAR TRIALS IN ONTARIO

1987 ◽  
Vol 67 (3) ◽  
pp. 653-659 ◽  
Author(s):  
S. J. PARK
Keyword(s):  
Phaseolus Vulgaris ◽  
Variance Components ◽  
Yield Stability ◽  
Regression Coefficients ◽  
Yield Potential ◽  
Field Bean ◽  
Environment Interaction ◽  
Phaseolus Vulgaris L ◽  
Yield Data ◽  
Bean Cultivar

Yield data of six recommended cultivars grown at seven locations (L) over 6 yr (Y) in the Ontario field bean (Phaseolus vulgaris L.) cultivar trials were analyzed to examine cultivar by environment interaction components, to determine yield stability of cultivars, and to group test locations. Cultivar (C), C × L, and C × L × Y effects were highly significant with large variance components indicating the importance of cultivar and test locations. The C × Y interaction was not significant. When yield stability was evaluated using cultivar means, regression coefficients (b), and deviations from linear regression (S2d), Ex Rico 23 was identified as being stable and potentially high yielding. Test locations were grouped into four homogeneous subareas by a biological classification method. Since breeding or recommending cultivars for four small subareas is not practical, efforts should be devoted to improving average stability and yield potential by testing at locations representative of homogeneous subareas.Key words: Bean (field), Phaseolus vulgaris, yield testing, genotype × environment interactions

Resource allocation in Maritime cereal cultivar trials

1994 ◽  
Vol 74 (3) ◽  
pp. 501-505
Author(s):  
G. N. Atlin ◽  
K. B. McRae
Keyword(s):  
Variance Components ◽  
Selection Response ◽  
Testing System ◽  
Environment Interaction ◽  
Acceptance Probability ◽  
Genotype Environment Interaction ◽  
The Mean ◽  
Single Standard ◽  
Variance Component Estimates ◽  
The Impact

Research funding for cooperators in the cereal cultivar testing system in Canada is declining, and cooperators are under pressure to reduce their testing effort. The impact of reducing the number of years, test sites, and replications on the standard error of cultivar means (SE), predicted response to selection (R), and the probability of accepting inferior cultivars in Maritime spring cereal registration trials was examined using variance component estimates. Reducing the number of replications increased SE less than reducing the number of sites or years of testing. Reducing replicates per site from four to two increased SE by no more than 0.02 t ha−1 when the number of sites was three or more. Reducing the number of trial sites from five to three, however, increased SE by up to 0.06 t ha−1 and reduced R by as much as 16%. The probability that a cultivar with a true yield 5% less than that of a standard would equal or exceed the standard in a 3-yr series of trials conducted at five sites ranged from 6% in 2-row barley to 21% in winter wheat. Cost reductions in the Maritime cereal registration trials should be achieved, where possible, by reducing within-site replication rather than reducing the number of trial sites. Some reduction in the risk of registering inferior cultivars can be achieved by comparing test cultivars with the mean of several standards, rather than with a single standard. Key words: Replication, genotype × environment interaction, selection response, acceptance probability, variance components, residual maximum likelihood

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