scholarly journals Genotype × Environment (G × E) Interaction in Southernpea [Vigna unguiculata (L.) Walp] Genotypes in the Southeastern USA

HortScience ◽  
1998 ◽  
Vol 33 (4) ◽  
pp. 596c-596
Author(s):  
John C. Alleyne ◽  
Teddy E. Morelock ◽  
Clay H. Sneller
Keyword(s):  
Vigna Unguiculata ◽  
Principal Component ◽  
Visual Assessment ◽  
Yield Potential ◽  
Environment Interaction ◽  
Interaction Patterns ◽  
Genotype Environment Interaction ◽  
Principal Component Axis ◽  
Biological Interpretation ◽  
Testing Environments

Genotype by environment (G × E) effects in Regional Cooperative Southernpea trials for the southeastern United States were investigated to characterize the extent, pattern, and potential impact of G × E on seed yield of southernpea [Vigna unguiculata (L.) Walp] genotypes. The structure of G × E effects was investigated using the Additive Main Effect and Multiplicative Interaction (AMMI) method. AMMI analyses revealed a highly significant genotype × environment interaction, most of which was partitioned into a genotype × location component of variance. AMMI first principal component axis scores stratified environments into two groups that minimized variation within groups. Biological interpretation of groupings and visual assessment of the AMMI biplot, revealed high-yielding genotypes interacting positively with one group of environments and conversely, low-yielding genotypes interacting positively with the other group. There were some significant rank changes of genotypes as yield potential varied across environments. Some environments showed similar main effects and interaction patterns indicating that most of the G × E effects could be captured with fewer testing sites, and consequently redundancy of some testing environments over years.

Interpreting genotype×environment interaction in sesame (Sesamum indicum L.)

2006 ◽  
Vol 145 (3) ◽  
pp. 263-271 ◽  
Author(s):  
H. LAURENTIN ◽  
D. MONTILLA ◽  
V. GARCIA
Keyword(s):  
Yield Components ◽  
Principal Component ◽  
Environment Interaction ◽  
Genotype By Environment ◽  
Silt Content ◽  
Genotype Environment Interaction ◽  
Principal Component Axis ◽  
Superior Genotypes ◽  
Edaphic Properties ◽  
Selection Of

An understanding of genotype by environment (G×E) interaction would be useful for establishing breeding objectives, identifying the best test conditions, and finding areas of optimal cultivar adaptation. Data from field assays including eight environments and eight elite lines were analysed to identify environmental and genotypic variables related with G×E interaction for yield in sesame multi-environment trials in Venezuela. Both predictable and unpredictable environmental variables were recorded. Yield components were recorded as genotypic variables. Yield and yield components were used to perform additive main effect and multiplicative interaction (AMMI) analysis. Significant differences (P<0·01) for G×E interaction were observed for all variables examined, except for the number of branches per plant. For yield, 0·28 of the total sum of squares corresponded to G×E interaction. Using environmental and genotypic data, correlation analysis was carried out between genotypic and environmental scores of the first interaction principal component axis (IPCA 1) for all variables examined. Significant correlations (P<0·05) were observed between IPCA 1 for yield and content of sand and silt in soil. No significant correlation was found between IPCA 1 score for yield and genotypic variables. These results indicate that edaphic properties at the trial locations play an important role in yield G×E interaction in Venezuelan sesame. These results should help select test sites for sesame in Venezuela to minimize G×E interaction and make selection of superior genotypes easier. Two strategies can be recommended: multi-environment trials at sites with average, not extreme, sand and silt content, or stratification of sites according to sand and silt content.

Using AMMI approach to delineate genotype by environment interaction and stability of barley (Hordeum vulgare L.) genotypes under northern Indian shivalik hill conditions

2020 ◽  
Vol 80 (03) ◽  
Author(s):  
Om Prakash Yadav ◽  
A. K. Razdan ◽  
Bupesh Kumar ◽  
Praveen Singh ◽  
Anjani K. Singh
Keyword(s):  
Hordeum Vulgare ◽  
Grain Yield ◽  
Principal Component ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Hordeum Vulgare L ◽  
Genotype By Environment ◽  
Biplot Analysis ◽  
Principal Component Axis ◽  
Ammi Analysis

Genotype by environment interaction (GEI) of 18 barley varieties was assessed during two successive rabi crop seasons so as to identify high yielding and stable barley varieties. AMMI analysis showed that genotypes (G), environment (E) and GEI accounted for 1672.35, 78.25 and 20.51 of total variance, respectively. Partitioning of sum of squares due to GEI revealed significance of interaction principal component axis IPCA1 only On the basis of AMMI biplot analysis DWRB 137 (41.03qha–1), RD 2715 (32.54qha–1), BH 902 (37.53qha–1) and RD 2907 (33.29qha–1) exhibited grain yield superiority of 64.45, 30.42, 50.42 and 33.42 per cent, respectively over farmers’ recycled variety (24.43qha–1).

GROUPING LOCATIONS FOR EFFICIENT CASSAVA EVALUATION IN MALAWI

2003 ◽  
Vol 39 (2) ◽  
pp. 167-179 ◽  
Author(s):  
J. MKUMBIRA ◽  
N. M. MAHUNGU ◽  
U. GULLBERG
Keyword(s):  
Environmental Heterogeneity ◽  
Principal Component ◽  
Environment Interaction ◽  
Scatter Plot ◽  
Genotype Environment Interaction ◽  
Breeding Zone ◽  
Adverse Environmental Conditions ◽  
The Tropics ◽  
Pair Wise Comparison ◽  
Better Than

Cassava, a crop widely adapted in the tropics, has the important attribute of withstanding adverse environmental conditions better than do many other staple crops. The performance of an individual genotype, however, is influenced by the environment in which it grows. In Malawi, the heterogeneity of agro-ecologies requires the cumbersome and costly assessment of new cassava genotypes at many sites. This study was conducted, therefore, to test the feasibility of selecting only a few locations for cassava evaluation that would be representative of all the agro-ecologies in which cassava is grown in Malawi. Enormous environmental effects, largely contributed by the interaction between season and location, were manifested. Genotype×environment interaction, due largely to a third level interaction (genotype×season×location), was highly significant for all the traits studied. A principal component analysis scatter plot showed no particular grouping of environments, but a pair-wise comparison showed that some of the locations had limited genotype×environment interaction, indicating that it would be sufficient to use one of these sites for evaluating these traits. The value of the residual was often large, probably as an effect of environmental heterogeneity in the test sites. The authors conclude that cassava genetic improvement will continue to be slow if Malawi is used as a single breeding zone. They recommend a much finer grouping of the locations and the use of smaller plot sizes to allow more clones to be tested at more sites for the same cost. Locations may be selected for intensive cassava breeding work from those that give the best discrimination between genotypes while having insignificant genotype×environment interactions in a relatively large number of environments.

Genotype × environment interaction patterns for grain yield of spring barley in different regions of Kazakhstan

2013 ◽  
Vol 49 (2) ◽  
pp. 196-205 ◽  
Author(s):  
Y. Turuspekov ◽  
B. Sariev ◽  
V. Chudinov ◽  
G. Sereda ◽  
L. Tokhetova ◽  
...  
Keyword(s):  
Grain Yield ◽  
Spring Barley ◽  
Environment Interaction ◽  
Interaction Patterns ◽  
Genotype Environment Interaction

scholarly journals Genotype × Environment Interaction for Resistance to Spider Mites in Fragaria

1999 ◽  
Vol 124 (4) ◽  
pp. 353-357 ◽  
Author(s):  
José López Medina ◽  
Patrick P. Moore ◽  
Carl H. Shanks ◽  
Fernando Flores Gil ◽  
Craig K. Chandler
Keyword(s):  
Spider Mite ◽  
The United States ◽  
Spider Mites ◽  
Environment Interaction ◽  
Interaction Patterns ◽  
First Order ◽  
Genotype Environment Interaction ◽  
Main Effect ◽  
Ammi Analysis ◽  
Main Effects

Genotype × environment interaction for resistance to the twospotted spider mite (Tetranychus urticae Koch) of eleven clones of Fragaria L. sp. (strawberries) grown in six environments throughout the United States was examined using two multivariate analysis techniques, principal coordinate analysis (PCA) and additive main effect and multiplicative interaction (AMMI). Both techniques provided useful and interesting ways of investigating genotype × environment interaction. PCA analysis indicated that clones X-11 and E-15 were stable across both low and high environments for the number of spider mites per leaflet. The initial AMMI analysis showed that the main effects of genotype, environment, and their first-order interaction were highly significant, with genotype × environment interaction due mainly to cultivar `Totem' and environment FL94. A second AMMI analysis, which excluded `Totem' and FL94, showed that the main effects of the remaining genotypes, environments, and genotype × environment interaction were also highly significant. AMMI biplot analysis revealed that FL93 and GH93 were unstable environments, but with opposite interaction patterns; and GCL-8 and WSU2198 were unstable genotypes with similar interactions that were opposite those of WSU 2202.

Genotype × environment interaction and genetic association of grain iron and zinc content with other agronomic traits in RIL population of pearl millet

2018 ◽  
Vol 69 (11) ◽  
pp. 1092
Author(s):  
Tripti Singhal ◽  
C. Tara Satyavathi ◽  
Aruna Kumar ◽  
S. Mukesh Sankar ◽  
S. P. Singh ◽  
...  
Keyword(s):  
Pearl Millet ◽  
Agronomic Traits ◽  
Pennisetum Glaucum ◽  
Recombinant Inbred Lines ◽  
Selection Index ◽  
Principal Component ◽  
Zinc Content ◽  
Environment Interaction ◽  
Genotype Environment Interaction ◽  
Zn Content

Biofortification of lines of pearl millet (Pennisetum glaucum (L.) R.Br.) with increased iron (Fe) and zinc (Zn) will have great impact because pearl millet is an indispensable component of food and nutritional security of inhabitants of arid and semi-arid regions. The aim of the present study was to assess the stability of Fe and Zn content in recombinant inbred lines (RILs) developed for grain Fe and Zn content, and to use these lines in developing micronutrient-rich pearl millet hybrids. A mapping population consisting of 210 RILs along, with parents and checks, was assessed in three consecutive years (2014–16) under rainfed conditions at the same experimental location in an alpha design with two repetitions. Significant differences were observed in genotype, environment and genotype × environment interaction mean squares for all variables, particularly grain micronutrients. The first two principal components of an interaction principal component analysis cumulatively explained 100% of the total variation; respective contributions of the first and second components were 64.0% and 36.0% for Fe, and 58.1% and 41.9% for Zn. A positive and moderately high correlation (0.696**) between Fe and Zn contents suggests good prospects of simultaneous improvement for both micronutrients. Among the 210 RILs, RIL 69, RIL 186, RIL 191, RIL 149 and RIL 45 were found to be more stable with higher mean micronutrient content, additive main effects and multiplicative interaction stability value (ASV) and genotype selection index (GSI) under rainfed condition. These RILs are promising and can be tested further for their combining ability for yield as well as grain micronutrient content for developing superior biofortified, heterotic pearl millet hybrids.

Effect of genotype-environment interaction on grain yield of exotic rice (Oryza sativa L.) hybrids

2018 ◽  
Vol 44 (4) ◽  
pp. 507-514
Author(s):  
MU Kulsum ◽  
MJ Hasan ◽  
MN Haque ◽  
M Shalim Uddin ◽  
KM Iftekharduddaula
Keyword(s):  
Oryza Sativa L ◽  
Major Complication ◽  
Genotype By Environment Interaction ◽  
Yield Potential ◽  
High Yield ◽  
Environment Interaction ◽  
Genotype Environment Interaction ◽  
Wide Range ◽  
Main Effects ◽  
Moderate Yield

Genotype by environment interaction (GEI) is a major complication in plant breeding. Authors used additive main effects and multiplicative interaction (AMMI) to evaluate the effects of GEI in hybrid rice genotype and their adaptation in three years at four locations. Among rice hybrid genotypes ACI93024 was stable in all environments with high yield potential. Using AMMI analysis AMMI 1 biplot showed the genotypes HS-273, Heera-2, ACI-2 and HRM-02 were highly stable with moderate yield potential but the genotype ACI93024 was more adapted to a wide range of environment than the rest of the genotypes, while BRRI dhan28 indices the lowest stability. ACI-2, LP-70 and Mayna were specifically adapted to the environment of Rangpur, Jessore and Gazipur, respectively. Comilla was identified as stable environment for all the genotypes.

scholarly journals Stability of Expression and Concentration of Ascorbic Acid in North American Potato Germplasm

HortScience ◽  
2004 ◽  
Vol 39 (1) ◽  
pp. 156-160 ◽  
Author(s):  
Stephen L. Love ◽  
Thomas Salaiz ◽  
Bahman Shafii ◽  
William J. Price ◽  
Alvin R. Mosley ◽  
...  
Keyword(s):  
Ascorbic Acid ◽  
North American ◽  
Principal Component ◽  
Environment Interaction ◽  
Interaction Patterns ◽  
Potato Germplasm ◽  
Plot Analysis ◽  
Essential Nutrient ◽  
Ammi Model ◽  
Stability Statistics

Ascorbic acid (vitamin C) is an essential nutrient in the human diet and potatoes are a valuable source. As a first step in breeding for potatoes (Solanum tuberosum L.) with higher levels of ascorbic acid, 75 clones from 12 North American potato-breeding programs were evaluated for concentration, and 10 of those for stability of expression. Trials were grown in Idaho, Oregon, and Washington in 1999 and 2000, tubers sampled, and ascorbic acid quantified. There were significant differences among clones and clone by environment interaction was also significant. Concentration of ascorbic acid of the clones was continuously distributed over a range of 11.5 to 29.8 mg/100 g. A subgroup of 10 clones was analyzed using an additive main effects and multiplicative interaction (AMMI) model, to diagnose interaction patterns and measure clone stability. The first two principal component axes accounted for over 80% of the variability. Bi-plot analysis showed `Ranger Russet' to be highly unstable across the environments tested. A plot of Tai's stability statistics found six of the 10 clones to be stable for ascorbic acid expression. Appropriate evaluation methods for ascorbic acid concentration must involve multi-year testing.

Yield Stability of Different Elite Wheat Lines under Drought and Irrigated Environments using AMMI and GGE Biplots

2021 ◽  
Vol 9 (2) ◽  
pp. 98-106
Author(s):  
Dipendra Regmi ◽  
Mukti Ram Poudel ◽  
Bishwas K.C. ◽  
Padam Bahadur Poudel
Keyword(s):  
Principal Component ◽  
Environment Interaction ◽  
Lattice Design ◽  
Genotype Environment Interaction ◽  
Stability Model ◽  
Winter Crop ◽  
Ideal Line ◽  
Genotype Evaluation ◽  
The Mean ◽  
Wheat Lines

Wheat is the principal winter crop in Nepal. Drought affects 44% of the lands of the total wheat area in the country with a yield loss of 15–20%. This research focuses to minimize this loss through the identification of high-yielding lines stable across the drought stress and irrigated environments. The experiment was conducted in Alpha Lattice Design with 20 genotypes replicated twice with five blocks per replication from November 2019 to April 2020. The findings showed that genotypes, environments, and genotype-environment interaction have a highly significant effect on grain yield and explained 28.95%, 52.57%, and 18.47% of variation on yield, respectively. The which-won-where model revealed elite line NL 1420 is the most responsive line in the drought environment, followed by BL 4407, while elite line NL 1179 is the most stable line in irrigated environment. The mean vs stability model with principal component 1 and 2 explaining 65.76% and 34.24% respectively, showed that elite line NL 1420, BL 4407, BL 4919, Bhrikuti are both high yielding and stable lines while line NL 1179, Gautam, and NL 1384 are less stable in both test environments. Similarly, the ranking genotypes model indicated lines close to the ideal line are NL 1420, BL 4407, BL 4919, Bhrikuti as the most representative line for genotype evaluation. Thus, elite wheat line NL 1420 and NL 1179 are recommended as specifically adapted to drought and irrigated environments, respectively, and elite line NL 1420, BL 4407, BL 4919, Bhrikuti are recommended for further evaluation for stability. Int. J. Appl. Sci. Biotechnol. Vol 9(2): 98-106

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