scholarly journals Assessment of genotype x environment interaction and pod yield evaluation of groundnut (Arachis hypogaea L.) genotypes in Zimbabwe

2017 ◽  
Vol 11 (3) ◽  
pp. 54-60 ◽  
Author(s):  
N. Savemore Ngirazi ◽  
P. Manjeru ◽  
B. Ncube
Keyword(s):  
Arachis Hypogaea ◽  
Genotype X Environment Interaction ◽  
Environment Interaction ◽  
Genotype X Environment ◽  
Pod Yield ◽  
Arachis Hypogaea L

Genotype X Environment Interaction Among Peanut Lines in Oklahoma1

1982 ◽  
Vol 9 (1) ◽  
pp. 24-27 ◽  
Author(s):  
K. E. Dashiell ◽  
J. S. Kirby ◽  
R. W. McNew
Keyword(s):  
Variance Components ◽  
Unit Area ◽  
Genotype X Environment Interaction ◽  
Environment Interaction ◽  
Performance Tests ◽  
Genotype X Environment ◽  
Pod Yield ◽  
Arachis Hypogaea L ◽  
The Difference ◽  
Interaction Variance

Abstract Data from Oklahoma peanut (Arachis hypogaea L.) performance tests from 1969 through 1978 were used to estimate genotype X environment interaction variance components for pod yield, %TSMK, % SS, % OK, and gross return per unit area. The objectives of this study were to determine if it would be advantageous to select cultivars for specific regions, and to determine the most efficient combination of years, locations, and replications to use when evaluating peanut lines. Evidence was obtained that genotypes perform consistently between irrigated and nonirrigated locations for the traits studied. The variance of the difference between two cultivars or lines was calculated for % TSMK, pod yield, and gross return using various combinations of years, locations, and replications. Results indicate that, when testing for gross return, the time presently allotted for testing could be reduced without sacrificing accuracy.

scholarly journals Genotype X Environment Interaction of Food Barley

2015 ◽  
Vol 21 ◽  
pp. 41-48
Author(s):  
Gebremedhin Welu
Keyword(s):  
Grain Yield ◽  
Block Design ◽  
Genotype X Environment Interaction ◽  
Environment Interaction ◽  
Genotype X Environment ◽  
Genotype Effect ◽  
Environment Effects ◽  
Randomized Complete Block Design ◽  
Barley Genotypes

The objective of this experiment was to estimate the magnitude of genotype X environment interaction on grain yield and yield related traits. Twelve varieties of food barley were included in the study planted in randomized complete block design with three replications. The ANOVA of combined and individual location revealed significant differences among the food barley genotypes for grain yield and other traits. The results of ANOVA for grain yield showed highly significant (p≤0.01) differences among genotypes evaluated for grain yield at Maychew and significant (p≤0.05) differences in Korem, Alage and Mugulat. The ANOVA over locations showed a highly significant (p≤0.01) variation for the genotype effect, environment effects, genotype X environment interaction (GEI) effect and significant (p≤0.05) variation for GEI effect of yield and for most of the yield related traits of food barley genotypes. Haftysene, Yidogit, Estayish and Basso were the genotypes with relatively high mean grain yield across all locations and they are highly performing genotypes to the area. Among locations, the highest mean grain yield was recorded at Korem and it was a suited environment to all the genotypes whereas Mugulat is unfavoured one. ECOPRINT 21: 41-48, 2014DOI: http://dx.doi.org/10.3126/eco.v21i0.11903

scholarly journals Eclipta (Eclipta prostrata L.) Control in Peanuts (Arachis hypogaea L.)1

1995 ◽  
Vol 22 (2) ◽  
pp. 114-120 ◽  
Author(s):  
J. V. Altom ◽  
R. B. Westerman ◽  
D. S. Murray
Keyword(s):  
Arachis Hypogaea ◽  
Field Experiments ◽  
Butanoic Acid ◽  
Late Season ◽  
Nitrobenzoic Acid ◽  
Pod Yield ◽  
Eclipta Prostrata ◽  
Arachis Hypogaea L ◽  
Herbicide Treatments ◽  
Sequential Treatments

Abstract Field experiments were conducted from 1991 to 1993 to evaluate eclipta, Eclipta prostrata L., control and peanut, Arachis hypogaea L., response to herbicide treatments. Fomesafen {5-[2-chloro-4-(trifluoro-methyl)phenoxy]-N-(methylsulfonyl)-2-nitrobenzamide} applied at cracking was the only preemergence-applied herbicide which provided season-long control (>84%). Herbicides applied postemergence were more effective when the eclipta was less than 5 cm in height. The most consistent early postemergence treatments were bromoxynil (3,5-dibromo-4-hydroxybenzonitrile), bentazon [3-(1-methylethyl)-(1H)-2,1,3-benzothiadiazm-4(3H)-one 2,2-dioxide], and bentazon + acifluorfen {5-[2-chloro-4-(trifluoromethyl)phenoxy]-2-nitrobenzoic acid} + 2,4-DB [4-(2,4-dichloro-phenoxy)butanoic acid]. Various other early postemergence followed by late postemergence sequential treatments also were equally effective. Minor peanut injury was observed at the early season rating from several herbicides; however, all injury had disappeared by the late season rating. Eclipta control did not consistently improve peanut pod yield.

scholarly journals Genotype x Environment Interaction and Yield-Stability Analyses of Rice Grown in Tropical Inland Swamp

2011 ◽  
Vol 39 (1) ◽  
pp. 220 ◽  
Author(s):  
Adesola L. NASSIR ◽  
Omolayo J. ARIYO
Keyword(s):  
Total Variation ◽  
Yield Stability ◽  
Genotype X Environment Interaction ◽  
Environment Interaction ◽  
Rice Varieties ◽  
Environmental Indices ◽  
Genotype X Environment ◽  
Additional Information ◽  
Gxe Interaction ◽  
The Stability

Twelve rice varieties were cultivated in inland hydromorphic lowland over a four year-season period in tropical rainforest ecology to study the genotype x environment (GxE) interaction and yield stability and to determine the agronomic and environmental factors responsible for the interaction. Data on yield and agronomic characters and environmental variables were analyzed using the Additive Main Effect and Multiplicative Interaction (AMMI), Genotype and Genotype x Environment Interaction, GGE and the yield stability using the modified rank-sum statistic (YSi). AMMI analysis revealed environmental differences as accounting for 47.6% of the total variation. The genotype and GxE interaction accounted for 28.5% and 24% respectively. The first and second interaction axes captured 57% and 30% of the total variation due to GXE interaction. The analysis identified ‘TOX 3107’ as having a combination of stable and average yield. The GGE captured 85.8%of the total GxE. ‘TOX 3226-53-2-2-2’ and ‘ITA 230’ were high yielding but adjudged unstable by AMMI. These two varieties along with ‘WITA 1’ and ‘TOX 3180-32-2-1-3-5’ were identified with good inland swamp environment, which is essentially moisture based. The two varieties (‘TOX 3226-53-2-2-2’ and ‘ITA 230’), which were equally considered unstable in yield by the stability variance, ?2i, were selected by YSi in addition to ‘TOX 3107’, ‘WITA 1’, ‘IR 8’ and ‘M 55’. The statistic may positively complement AMMI and GGE in selecting varieties suited to specific locations with peculiar fluctuations in environmental indices. Correlation of PC scores with environmental and agronomic variables identified total rainfall up to the reproductive stage, variation in tillering ability and plant height as the most important factors underlying the GxE interaction. Additional information from the models can be positively utilized in varietal development for different ecologies.

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