scholarly journals Investigation of genotype-environment interaction by cluster analysis in animal experiments

1994 ◽  
Vol 74 (4) ◽  
pp. 607-612 ◽  
Author(s):  
C. Y. Lin ◽  
C. S. Lin
Keyword(s):  
Cluster Analysis ◽  
Key Words ◽  
Animal Experiment ◽  
Animal Experiments ◽  
Environment Interaction ◽  
Mean Square ◽  
Ge Interaction ◽  
Interaction Structure ◽  
Genotype Environment Interaction ◽  
Animal Data

The conventional ANOVA (F ratio of GE interaction mean squares to error mean square) provides a means to test if GE interaction is significant, but it does not tell us which factor levels are significantly different or how they are interacting. To answer the latter question, plant researchers developed a technique to group genotypes for similarity of GE interactions and through the resulting groups to explore the GE interaction structure. The basic idea of the technique is to stratify genotypes (or environments) into subgroups such that GE interactions among genotypes (or environments) are homogeneous within groups but heterogeneous among groups. This technique is introduced in this paper using an animal experiment as an example for illustration. The possibilities and limitations of applying this technique to animal data are also discussed. Key words: Genotype-environment interaction, cluster analysis

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

Genotype × environment interactions for two-row barley grain yield and implications for selection of genotypes

1993 ◽  
Vol 73 (4) ◽  
pp. 939-946
Author(s):  
K. W. May ◽  
G. C. Kozub
Keyword(s):  
Grain Yield ◽  
Barley Grain ◽  
Data Sets ◽  
Environment Interaction ◽  
Ge Interaction ◽  
Hordeum Vulgare L ◽  
Canadian Prairie ◽  
Interaction Structure ◽  
Genotype Environment Interaction ◽  
Key Words Barley

The response of barley grain yield to Canadian prairie environments was studied to evaluate genotype × environment interactions with respect to barley genotype selection. Information from nine test sites and 11 entries over two 3-yr spans was used. Genotype × location × year interactions from analysis of variance were significant for grain yield in both data sets. The nature of these interactions was studied by considering the genotype mean performance, superiority and stability measures for each location, and joint regression and cluster analyses within each year. No single genotype was superior over all locations, and the groupings of genotypes for similarity of response at locations were not consistent for year. This indicated that genotypes selected on the basis of main effect means may not be those selected from a detailed consideration of the GE interaction structure. In the presence of sufficient genetic variability, examination of mean yield in conjunction with between-year variance at each location provides vital information on adaptation at specific locations, and is an appropriate selection tool for genotype registration and recommendation. Consideration of GE interaction, using joint regression and clustering, may indicate genotypes equivalent or marginally superior to the check. Key words: Barley, Hordeum vulgare L., genotype-environment interaction, grain yield

GENOTYPE-ENVIRONMENT INTERACTION OF YIELD IN CEREAL CROPS IN NORTHWESTERN CANADA

1981 ◽  
Vol 61 (2) ◽  
pp. 255-263 ◽  
Author(s):  
R. M. De PAUW ◽  
D. G. FARIS ◽  
C. J. WILLIAMS
Keyword(s):  
Triticum Aestivum L ◽  
Regression Coefficients ◽  
Cereal Crops ◽  
Environment Interaction ◽  
Ge Interaction ◽  
Hordeum Vulgare L ◽  
Genotype Environment Interaction ◽  
Early Maturing ◽  
Frost Free Period ◽  
Main Effects

Three cultivars of each crop, wheat (Triticum aestivum L.), oats (Avena sativa L.), and barley (Hordeum vulgare L.), were grown for 4 yr at five locations north of the 55th parallel in northwestern Canada. There were highly significant differences among all main effects and interactions. Galt barley produced the highest seed yield followed by Centennial barley, Random oats and Harmon oats. Victory oats, Olli barley, Neepawa wheat and Pitic 62 wheat yielded similarly to each other while Thatcher wheat was significantly lower yielding. Mean environment yields ranged from 2080 to 5610 kg/ha. The genotype-environment (GE) interaction of species and cultivars was sufficiently complicated that it could not be characterized by one or two statistics (e.g., stability variances or regression coefficients). However, variability in frost-free period among years and locations contributed to the GE interaction because, for example, some cultivars yielded well (e.g., Pitic 62) only in those year-location environments with a relatively long frost-free period while other early maturing cultivars (e.g., Olli) performed well even in a short frost-free period environment.

scholarly journals Analysis of yield stability of strawberry varieties and hybrids

2020 ◽  
Vol 25 ◽  
pp. 02014
Author(s):  
Vadim Lapshin ◽  
Valentina Yakovenko ◽  
Sergey Shcheglov
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster ◽  
Yield Stability ◽  
Environment Interaction ◽  
Multivariate Statistical ◽  
Genotype Environment Interaction ◽  
Yield Structure ◽  
Biological Yield ◽  
Factor Of Influence

The profitability of strawberry cultivation is largely determined by the capacity and quality of the yield, depended on the features of the variety genotype. The aim of this work was to estimate the yield stability of varieties and hybrids by the methods of multivariate statistical analysis and identify the best genotypes. To solve this problem, we have used the two-factor analysis of variance and hierarchical cluster analysis according to the Ward’s method as well as the integral estimate of the differences between the values of yield. The results of the studies have shown that the genotype of the variety (hybrid) are makes a decisive factor of influence for variability of the yield structure signs from 17,1% (number of inflorescences) to 32,2% (number of berries). The «genotype × environment» interaction is comparable with the genotype influence, the share of influence of the year conditions of the year is insignificant. Cluster analysis according to complex of economic valuable signs allows us to identify the eight forms that the most adapted to the conditions of the Krasnodar Territory as 13-1-15, Florence, Roxana, 18-1-15, Asia, Onda, Kemia, Nelli from which the Roxana, Florence, 18-1-15, 13-1-15 have a high and steadily rising biological yield.

scholarly journals Grouping genotypes and test environments by some cluster methods regarding genotype × environment interaction in multi-environment trials

Genetika ◽  
2012 ◽  
Vol 44 (3) ◽  
pp. 457-473 ◽  
Author(s):  
Naser Sabaghnia ◽  
Rahmatollah Karimizadeh ◽  
Mohtasham Mohammadi
Keyword(s):  
Lens Culinaris ◽  
Developed Countries ◽  
Environment Interaction ◽  
Stopping Criterion ◽  
Ge Interaction ◽  
Regression Methods ◽  
Genotype By Environment ◽  
Genotype Environment Interaction ◽  
Main Effect ◽  
Cluster Methods

Lentil (Lens culinaris Medik.) is an important source of protein and carbohydrate food for people of developing countries and is popular in some developed countries where they are perceived as a healthy component of the diet. Ten lentil genotypes were tested for grain yield in five different environmental conditions, over two consecutive years to classify thes genotypes for yield stability. Seed yield of lentil genotypes ranged from 989.3 to 1.367 kg ha-1 and the linear regression coefficient ranged from 0.75 to 1.18. The combined analysis of variance showed that the effect of environment (E) and genotype by environment (GE) interaction were highly significant while the main effect of genotype (G) was significant at 0.05 probability level. Four different cluster procedures were used for grouping genotypes and environments. According to dendograms of regression methods for lentil genotypes there were two different genotypic groups based on G plus GE or GE sources. Also, the dendograms of ANOVA methods indicated 5 groups based on G and GE sources and 4 groups based on GE sources. According to dendograms of regression methods for environments there were 5 different groups based on G plus GE sources while the dendograms of ANOVA methods indicated 9 groups based on G and GE sources and 3 groups based on GE sources. The mentioned groups were determined via F-test as an empirical stopping criterion for clustering. The most responsive genotypes with high mean yield genotypes are G2 (1145.3 kg ha-1), G8 (1200.2 kg ha-1) and G9 (1267.9 kg ha-1) and could be recommended as the most favorable genotypes for farmers.

Selecting stable and high-yielding sorghum cultivars for the semi-arid tropics

1994 ◽  
Vol 74 (4) ◽  
pp. 759-762
Author(s):  
O. P. Dangi ◽  
R. I. Hamilton ◽  
C. S. Lin ◽  
D. Andre ◽  
J. J. Johnson
Keyword(s):  
High Yield ◽  
Annual Rainfall ◽  
Environment Interaction ◽  
Mean Square ◽  
Stability Parameters ◽  
The North ◽  
Genotype Environment Interaction ◽  
Northern Cameroon ◽  
The Stability ◽  
Extreme North

A sorghum breeding program was reactivated in 1981 and selected cultivars, along with local checks, were evaluated in two experiments in the sorghum growing region of northern Cameroon. Experiment 1 was conducted in the Extreme North Province where annual rainfall ranges from 450 to 850 mm. Experiment 2 was conducted in the North Province where annual rainfall exceeds 850 mm. The objective of the study was to select a high yield and high stability sorghum cultivar for each region. The cultivar's responses were investigated using two analyses: the adaptability analysis and the stability analysis. The former used the method of superiority measure, defined by distance mean square between the test cultivar and the maximum (the highest yield in the location), and the latter used type 4 stability parameter, defined by the years within location mean square averaged over all locations. The conceptual separation of adaptability and stability facilitated the cultivars assessment. The results showed that in exp. 1, three cultivars S–35, CS–54 and CS–61 had similar adaptability and stability, while in the exp. 2, S–34 was best in terms of yield but was unstable due to susceptibility to grain mold. In contrast, the second best cultivar CS–63 was poorer in the high-yielding environments but was more stable than S–34. Key words: Sorghum, genotype-environment interaction, adaptability, stability parameters

Genotype × environment interactions for two-row barley grain yield and implications for selection of test locations

1995 ◽  
Vol 75 (3) ◽  
pp. 571-575 ◽  
Author(s):  
K. W. May ◽  
G. C. Kozub
Keyword(s):  
Cluster Analysis ◽  
Grain Yield ◽  
Barley Grain ◽  
Significant Loss ◽  
Data Sets ◽  
Environment Interaction ◽  
Hordeum Vulgare L ◽  
Canadian Prairie ◽  
Genotype Environment Interaction ◽  
Yield Responses

The response of barley grain yield to Canadian prairie environments was studied to evaluate genotype × environment interactions, and to group locations according to genotype response, which identifies locations whose removal would not significantly affect the validity of conclusions. The data were also used to illustrate a method for handling a large genotype × location × year data base with few common entries. Information from 20 test locations with 11–19 annual entries over 7 yr was used. Analyses of variance of data sets with three to seven common entries in adjacent years indicated significant genotype × location × year interactions for grain yield. The structure of the genotype × location interaction was studied using cluster analysis within each year and summarized over years. Cluster analysis using individual years allowed more test entries and should increase the reliability of the conclusions compared to that using average over years with few entries. Clustering identified six locations with dissimilar genotype yield responses. In the 7 yr, 19 pairs of locations usually clustered together. The 19 pairs involved eight of the 20 locations and most were in the same geographical region. Some of the eight locations could be eliminated without significant loss of reliability. Rankings of test entries for grain yield at locations within a cluster were generally similar when genotype effects were larger. Key words:Barley, Hordeum vulgare L, genotype-environment interaction, grain yield

scholarly journals Assessment of Genotype × Environment Interaction of Safflower (Carthamus tinctorius L.) Genotypes by Parametric and Non-Parametric Methods

2021 ◽  
Vol 3 (1) ◽  
pp. 112-118
Author(s):  
İlhan Subaşı ◽  
Dilek Başalma
Keyword(s):  
Seed Yield ◽  
Positive Association ◽  
Stability Index ◽  
Oil Yield ◽  
Coefficient Of Determination ◽  
Mean Deviation ◽  
Environment Interaction ◽  
Ge Interaction ◽  
Stability Parameters ◽  
Genotype Environment Interaction

Genotype-environment interaction is a significant factor for finding and selecting stable and productive varieties in safflower breeding programs. This study was conducted at three locations over two years (2016-2017) to determine the extent of genotype by environment (GE) interaction in seed and oil yield. 20 safflower lines and cultivars were evaluated in terms of stability in 3 environments. Considering the stability and performance, the most suitable genotypes were determined as Remzibey-05 and Genotype-125 in seed yield, Genotype-8 and Genotype-155 in oil yield. In terms of stability and performances of genotypes, the environment of Ikizce 2017 (E4) was prominent. Correlation analysis among parametric and nonparametric features was given only for seed yield. The following stability parameters were calculated: the coefficient of variation (CV), regression constant (ai), regression coefficient (bi), mean deviation squares from regression (S2di), coefficient of determination (Ri2), stability variance (σi2), ecovalance value (Wi), stability index (Pi) and as nonparametric stability measures Si(1) and Si(2) values. This analysis indicated that seed yield was significantly positively correlated only with Pi (P<0.01). CV showed a positively significant correlation with ai. S2di and ri2 had a positive association with Ri2, σi2, Wi, Pi, Si(1), Si(2), and between each other.

scholarly journals AMMI and GGE Biplot for genotype × environment interaction: a medoid–based hierarchical cluster analysis approach for high–dimensional data

2018 ◽  
Vol 55 (2) ◽  
pp. 97-121 ◽  
Author(s):  
Anderson Cristiano Neisse ◽  
Jhessica Letícia Kirch ◽  
Kuang Hongyu
Keyword(s):  
Cluster Analysis ◽  
Wheat Yield ◽  
Hierarchical Cluster ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Spring Bread Wheat ◽  
Genotype Environment Interaction ◽  
Complex Process ◽  
Yield Trial ◽  
Selection Of

SummaryThe presence of genotype-environment interaction (GEI) influences production making the selection of cultivars in a complex process. The two most used methods to analyze GEI and evaluate genotypes are AMMI and GGE Biplot, being used for the analysis of multi environment trials data (MET). Despite their different approaches, both models complement each other in order to strengthen decision making. However, both models are based on biplots, consequently, biplot-based interpretation doesn’t scale well beyond two-dimensional plots, which happens whenever the first two components don’t capture enough variation. This paper proposes an approach to such cases based on cluster analysis combined with the concept of medoids. It also applies AMMI and GGE Biplot to the adjusted data in order to compare both models. The data is provided by the International Maize and Wheat Improvement Center (CIMMYT) and comes from the 14th Semi-Arid Wheat Yield Trial (SAWYT), an experiment concerning 50 genotypes of spring bread wheat (Triticum aestivum) germplasm adapted to low rainfall. It was performed in 36 environments across 14 countries. The analysis provided 25 genotypes clusters and 6 environments clusters. Both models were equivalent for the data’s evaluation, permitting increased reliability in the selection of superior cultivars and test environments.

scholarly journals Genetic Variability and G×E Interactions in a Diverse Set of Groundnut Accessions

2022 ◽  
Author(s):  
K. Gangadhara ◽  
H.K. Gor
Keyword(s):  
Cluster Analysis ◽  
Euclidean Distance ◽  
Agronomic Traits ◽  
Environment Interaction ◽  
Pod Yield ◽  
Genotype Environment Interaction ◽  
Ammi Analysis ◽  
Days To Maturity ◽  
Component Traits

Background: Knowledge of the genetic diversity for various agronomic traits and their interaction with the environment and subsequent classification of genotypes will be beneficial for identification of divergent and stable sources of agronomic traits. Methods: A set of 96 groundnut germplasm accessions belonging to four botanical groups were evaluated for three years (2017 to 2019) for pod yield and component traits using AMMI analysis and subsequently accessions were classified based Euclidean cluster analysis. Result: Among different botanical groups, Virginia genotypes matured late and possessed high SPAD chlorophyll meter readings (SCMR) and pod yield compared to Spanish types. The component traits of pod maturity like days to flowering (first and 50%) showed low heritability and high genotype × environment interaction (GEI) and significant negatively affected sound mature kernel (SMK) and shelling per centage (SP). The cumulative contribution of environment and GEI component to the total variance was the highest in the expression of SP (67%) followed by days to maturity (54%) and days to 50% flowering (52%). Euclidean distance-based cluster analysis grouped the 96 accessions into five major clusters. Cluster I had accessions with higher pod yield, whereas cluster V contained accessions with low SLA, high SCMR and moderate pod yield. High yielding as well as stable accessions identified based on AMMI stability value (ASV) are NRCG 17332, 10076, 17268, 17197, 17108, 10106, 10089 and 17165. Trait specific as well as stable accessions identified in the present study can be useful donors for groundnut breeding programme.

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