Study of Genotype x Environment Interaction for Forage Yield in Oat (Avena sativa L.) with Joint Linear Regression Analysis and AMMI Analysis.

1997 ◽  
Vol 25 (1) ◽  
pp. 55-62
Author(s):  
H. A. Acciaresi ◽  
H. O. Chidichimo ◽  
C. B. Fusé
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Avena Sativa ◽  
Linear Regression Analysis ◽  
Forage Yield ◽  
Genotype X Environment Interaction ◽  
Environment Interaction ◽  
Genotype X Environment ◽  
Ammi Analysis

scholarly journals Genotype x environment interaction for forage yield and its components in oats (Avena sativa L.)

2017 ◽  
Vol 8 (1) ◽  
pp. 157
Author(s):  
Uzma Mehraj ◽  
Ishfaq Abidi ◽  
Mushtaq Ahmad ◽  
B.A. Wani ◽  
S.D. Mir ◽  
...  
Keyword(s):  
Avena Sativa ◽  
Forage Yield ◽  
Genotype X Environment Interaction ◽  
Environment Interaction ◽  
Genotype X Environment

scholarly journals DESEMPENHO DE CULTIVARES DE SOJA EM DIFERENTES AMBIENTES DE CULTIVO

Nativa ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 390-396
Author(s):  
Paulo Henrique Cerutti ◽  
Marcio Dos Santos ◽  
Anne Tietjen Muniz ◽  
Arthur Ribeiro Rodrigues ◽  
Luan Tiago dos Santos Carbonari ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Grain Yield ◽  
Linear Regression Analysis ◽  
Relevant Information ◽  
Environment Interaction ◽  
Breeding Programs ◽  
Soybean Cultivars ◽  
Genotype Environment Interaction ◽  
Analogous Behavior

Anualmente, inúmeros cultivares de soja são desenvolvidos por programas de melhoramento genético. Desse modo, é importante obter informações sobre o comportamento desses cultivares em distintos ambientes. Objetivou-se com a elaboração do trabalho avaliar o efeito da interação genótipo*ambiente no desempenho de cultivares de soja em diferentes ambientes de cultivo. O delineamento experimental utilizado foi de blocos ao acaso com três repetições. Durante a execução dos experimentos, foi avaliado o desempenho produtivo de seis cultivares de soja em seis ambientes. A variável considerada foi o rendimento de grãos (kg ha-1). As informações foram submetidas a análise de variância, análise de regressão linear simples e teste de comparação de médias. A média geral de produtividade de grãos foi de 2960 kg ha-1. Aanálise de regressão indicou dois cultivares com adaptabilidade ampla, três cultivares com adaptabilidade específica a ambientes desfavoráveis e um cultivar com adaptabilidade específica a ambientes favoráveis. Dentre os cultivares avaliados, quatro apresentaram comportamento esperado ao longo dos ambientes de cultivo. Os cultivares exibiram comportamento análogo quanto ao rendimento de grãos. Por meio da aplicação da metodologia da regressão linear, foi possível obter informações relevantes para cultivo de soja em ambientes subsequentes.Palavras-chave: Glicine max L.; interação genótipo*ambiente; adaptabilidade; estabilidade. PERFORMANCE OF SOYBEAN CULTIVARS IN DIFFERENT GROWING ENVIRONMENTS ABSTRACT:Annually, numerous soybean cultivars are developed by breeding programs. Thus, is important to obtain information about of these cultivars behavior in different environments. The objective of this work was to evaluate the effect of the genotype * environment interaction on the performance of soybean cultivars in different growing environments. The experimental design used was randomized blocks with three replications. During the execution of the experiments, was evaluated the productive performance of six soybean cultivars in six environments. The trait considered was grain yield (kg ha-1). The information was submitted to analysis of variance, simple linear regression analysis and means comparison test. The overall mean grain yield was 2960 kg ha-1. Regression analysis indicated two cultivars with broad adaptability, three cultivars with specific adaptability to unfavorable environments and one cultivar with specific adaptability to favorable environments. Among the evaluated cultivars, four showed prospective behavior throughout the cultivation environments. The cultivars exhibited analogous behavior regarding grain yield. The application of the linear regression methodology provided relevant information for soybean cultivation in subsequent environments.Keywords: Glicine max L.; genotype*environment interaction; adaptability; stability.

Linear and non-linear regression analysis of genotype X environment interactions in pearl millet

1988 ◽  
Vol 75 (5) ◽  
pp. 736-740 ◽  
Author(s):  
D. S. Virk ◽  
P. S. Virk ◽  
B. K. Mangat ◽  
G. Harinarayana
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Pearl Millet ◽  
Linear Regression Analysis ◽  
Genotype X Environment ◽  
Genotype X Environment Interactions ◽  
Non Linear

Regression analysis of genotype x environment interaction in sweet potato

Euphytica ◽  
1993 ◽  
Vol 71-71 (3) ◽  
pp. 231-238 ◽  
Author(s):  
J. M. Ngeve
Keyword(s):  
Regression Analysis ◽  
Sweet Potato ◽  
Genotype X Environment Interaction ◽  
Environment Interaction ◽  
Genotype X Environment

Interference of Broadleaf Signalgrass (Brachiaria platyphylla) in Peanuts (Arachis hypogaea)

Weed Science ◽  
1982 ◽  
Vol 30 (1) ◽  
pp. 45-49 ◽  
Author(s):  
Rick W. Chamblee ◽  
Lafayette Thompson ◽  
Harold D. Coble
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Arachis Hypogaea ◽  
Linear Regression Analysis ◽  
Forage Yield ◽  
Brachiaria Platyphylla ◽  
Seed Yields ◽  
Interference Studies ◽  
Forage Yields

Interference studies utilizing natural infestations of broadleaf signalgrass [Brachiaria platyphylla(Griseb.) Nash] in peanuts [Arachis hypogaea(L.) ‘Florigiant′] were conducted at two sites in 1978 and repeated at the same sites in 1979. Full-season interference from broadleaf signalgrass populations of 8, 16, and 1050 plants/10 m of row reduced seed yields 14, 28, and 69%, respectively. Linear regression analysis showed that slightly less than 4 plants/10 m of row significantly reduced yields. Broadleaf signalgrass interference with peanuts for 6 weeks or less after planting did not reduce seed yields; however, interference for 8 weeks or longer after planting did. Peanuts kept weed-free for 6 weeks or more after planting had seed yields equal to peanuts kept weed-free all season. Full-season broadleaf signalgrass interference reduced mature peanut forage yields 64%, but peanut interference only reduced broadleaf signalgrass forage yield 10%.

scholarly journals Adaptability and Genotype x Environment Interaction of Spring Wheat Cultivars in Chile using Regression Analysis, AMMI, and SRAG

2012 ◽  
Vol 72 (2) ◽  
pp. 167-174 ◽  
Author(s):  
Dalma Castillo ◽  
Iván Matus ◽  
Alejandro del Pozo ◽  
Ricardo Madariaga ◽  
Mario Mellado
Keyword(s):  
Regression Analysis ◽  
Spring Wheat ◽  
Genotype X Environment Interaction ◽  
Environment Interaction ◽  
Wheat Cultivars ◽  
Genotype X Environment

scholarly journals AMMI Biplot Analysis in Cotton (Gossypium hirsutum L.) Genotypes for Genotype X Environment Interaction at Four Agro-ecologies in Telangana State

2020 ◽  
pp. 98-103
Author(s):  
N. Lingaiah ◽  
A. Sudharshanam ◽  
V. Thirumala Rao ◽  
Y. Prashant ◽  
M. Vijay Kumar ◽  
...  
Keyword(s):  
Analysis Of Variance ◽  
Block Design ◽  
Genotype X Environment Interaction ◽  
Superior Performance ◽  
Environment Interaction ◽  
Genotype X Environment ◽  
Kharif Season ◽  
Ammi Analysis ◽  
Cotton Genotypes ◽  
Telangana State

The objective of this study was to determine the genotype × environment interaction (GEI) and stability performance of eight promising cotton genotypes at four agro-ecologies in Telangana State. The experimental material consisting of eight genotypes were planted in randomized block design replicating thrice in four diverse environments of Telangana state during 2017, Kharif season. The present investigation was carried out in four diverse environments of Telangana state viz. RARS, Warangal, ARS, Adilabad, ARS, Modhole and RARS, Palem (Professor Jayashankar Telangana State Agricultural University) during 2017, Kharif season. The study was conducted at four diversified agro-ecologies of Telangana State. The experimental material comprised of eight genotypes viz., WGCV-109, ADB-638, WGCV-122, Narasimha, WGCV-119, WGCV-119, Srirama, WGCV-48 and ADB 645. First pooled analysis of variance was carried out to know the significance variation in genotype x environment interaction followed by AMMI analysis for genotype x environment interaction studies. Analysis of variance was significant for environments and (G x E) components indicating the use fullness of AMMI analysis in identifying the stable genotypes.  Among the eight cotton genotypes, WGCV-109, Narasimha and ADB-645 were found to be best yielders over environments whereas the genotypes G7 (WGCV-48) and G4 (Narasimha) found to be stable. Most of the genotypes showed environment specificity. As a result, almost all of the evaluated genotypes were affected by the genotype x environment interaction effects, hence no genotype had superior performance in all environments.  

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