Genotype ∞ Environment Interaction Patterns for Grain Yield of Spring Barley in Different Regions of Kazakhstan

2013 ◽  
Vol 49 (2) ◽  
pp. 224-234
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

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 Some aspects of adaptation and adaptability of barley in European conditions.

1985 ◽  
Vol 33 (3) ◽  
pp. 195-213
Author(s):  
L. Jestin
Keyword(s):  
Statistical Models ◽  
Spring Barley ◽  
Winter Barley ◽  
General View ◽  
Environment Interaction ◽  
Interaction Patterns ◽  
Statistical Procedures ◽  
Genotype Environment Interaction ◽  
Nw Europe ◽  
Recent Extension

After a review of different approaches found in the literature to problems of adaptation and adaptability of barley, attention is paid to the ecophysiological reasons which may explain the recent extension of winter barley cultivation in NW Europe. A brief account is given of cooperative trials carried out in Europe to define spring barley varietal adaptability ("ESBAN" and "JESBT" trials). A general view of current statistical procedures to analyse adaptability and genotype environment interaction patterns is presented. Some indications are given of the use that the breeder can make of ecophysiological methodology and statistical models in breeding barley for wider adaptation. (Abstract retrieved from CAB Abstracts by CABI’s permission)

scholarly journals Delineation of Genotype × Environment Interaction for Identification of Stable Genotypes to Grain Yield in Mungbean

2020 ◽  
Vol 2 ◽  
Author(s):  
Santhi Madhavan Samyuktha ◽  
Devarajan Malarvizhi ◽  
Adhimoolam Karthikeyan ◽  
Manickam Dhasarathan ◽  
Arumugam Thanga Hemavathy ◽  
...  
Keyword(s):  
Grain Yield ◽  
Tamil Nadu ◽  
Stability Index ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Genotype Environment Interaction ◽  
South Indian ◽  
Indian State ◽  
Wide Adaptation ◽  
High Yields

In the present study, fifty-two mungbean (Vigna radiata) genotypes were evaluated for seven morphological traits at three different environments in South Indian state Tamil Nadu, namely Virinjipuram (E1), Eachangkottai (E2), and Bhavanisagar (E3) during Kharif 2017, 2018, and 2019, respectively. The data collected were subjected to variability and correlation analyses, followed by stability analysis using additive main effects and multiplicative interaction (AMMI) model, genotype and genotype × environment interaction effects (GGE) biplot. Variablility was observed among the genotypes for the following traits viz., plant height, days to fifty per cent flowering, number of pods per plant, pod length, number of seeds per pod, hundred seed weight and grain yield. Correlation analysis showed that the trait number of pods per plant was significantly associated with grain yield. The G × E was smaller than the genetic variation of grain yield as it portrayed the maximum contribution of genotypic effects (61.07%). GGE biplot showed E3 as a highly discriminating and representative environment. It also identified environment-specific genotypes viz., EC 396111 for E1, EC 396125 for E2 and EC 396101 for E3 environments. The genotypes with minimum genotype stability index (GSI) viz., V2802BG (7), HG 22 (13), and EC 396098 (13) were observed with wide adaptation and high yields across all the three environments. In summary, we identified stable genotypes adapted across environments for grain yield. These genotypes can be used as parent/pre-breeding materials in future mungbean breeding programs.

scholarly journals Performance evaluation of commercial maize hybrids across diverse Terai environments during the winter season in Nepal

2016 ◽  
Vol 2 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Mahendra Prasad Tripathi ◽  
Jiban Shrestha ◽  
Dil Bahadur Gurung
Keyword(s):  
Grain Yield ◽  
Winter Season ◽  
First Year ◽  
Environment Interaction ◽  
Maize Hybrids ◽  
Site Analysis ◽  
Maize Cultivars ◽  
Genotype Environment Interaction ◽  
Winter Time ◽  
Hybrid Maize

The hybrid maize cultivars of multinational seed companies are gradually being popular among the farmers in Nepal. This paper reports on research finding of 117 maize hybrids of 20 seed companies assessed for grain yield and other traits at three sites in winter season of 2011 and 2012. The objective of the study was to identify superior maize hybrids suitable for winter time planting in eastern, central and inner Terai of Nepal. Across site analysis of variance revealed that highly significant effect of genotype and genotype × environment interaction (GEI) on grain yield of commercial hybrids. Overall, 47 genotypes of 16 seed companies identified as high yielding and stable based on superiority measures. The statistical analysis ranked topmost three genotypes among tested hybrids as P3856 (10515 kg ha-1), Bisco prince (8763 kg ha-1) as well as Shaktiman (8654 kg ha-1) in the first year; and 3022 (8378 kg ha-1), Kirtiman manik (8323 kg ha-1) as well as Top class (7996 kg ha-1) in the second year. It can be concluded that stable and good performing hybrids identified as potential commercial hybrids for general cultivation on similar environments in Nepal.

Adaptation of field pea varieties to organic farming across different environments of Italy

2019 ◽  
Vol 70 (4) ◽  
pp. 327 ◽  
Author(s):  
Luciano Pecetti ◽  
Angelo R. Marcotrigiano ◽  
Luigi Russi ◽  
Massimo Romani ◽  
Paolo Annicchiarico
Keyword(s):  
Grain Yield ◽  
Southern Italy ◽  
Ascochyta Blight ◽  
Genetic Correlations ◽  
Field Pea ◽  
Environment Interaction ◽  
Adaptive Responses ◽  
Climatic Regions ◽  
Organic Systems ◽  
Genotype Environment Interaction

This study aimed to support field pea (Pisum sativum L.) breeding strategies for organic systems of southern European environments, by assessing the size of genotype × environment interaction (GEI) due to spatial and temporal factors across climatically contrasting regions and identifying plant characters associated with genotype adaptive responses. Twelve recent varieties were evaluated for grain yield and other traits in six organically managed environments (three sites × two cropping years) of northern, central and southern Italy. GEI for grain yield was large, with the variety × site × year interaction greatly exceeding the variety × site interaction. This finding, and the similar magnitude of the mean genetic correlations for variety yields across pairs of sites (rg = 0.56) and pairs of years (rg = 0.51), indicated the difficulty of exploiting variety × site interaction effects by breeding for specific climatic regions. Pattern analysis highlighted the large inconsistency across years for GEI pattern of the sites from central and southern Italy. GEI also complicated the targeting of varieties, owing to inconsistent top-performing material across years according to additive main effects and multiplicative interaction (AMMI)-modelled yields. Higher genotype mean yield was strictly associated (P < 0.01) with lower weed proportion (hence, greater competitiveness against weeds: r = –0.96), taller plants (r = 0.89) and larger seeds (r = 0.78), with looser associations with lower susceptibility to lodging and ascochyta blight. These traits, which also contributed to preferential adaptation to the moisture-favourable environments of northern Italy, could be selected in breeding widely adapted varieties.

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.

scholarly journals Genotype environment interaction and stability for yield and its components in advanced breeding lines of red rice (Oryza sativa L.)

2020 ◽  
Vol 49 (3) ◽  
pp. 425-435
Author(s):  
BM Dushyantha Kumar ◽  
AP Purushottam ◽  
P Raghavendra ◽  
T Vittal ◽  
KN Shubha ◽  
...  
Keyword(s):  
Grain Yield ◽  
Oryza Sativa L ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Red Rice ◽  
Yield Performance ◽  
Breeding Lines ◽  
Genotype Environment Interaction ◽  
Ammi Analysis ◽  
Total Variability

Effects of genotype, environment and their interaction for grain yield and yield attributing characters in 20 advanced breeding lines of rice across six environments was investigated. Yield stability and adaptability of yield performance were analyzed by Eberhart and Russel model and (GGE) bi-plot. The AMMI analysis of variance indicated that mean squares due to genotypes, location and genotype location contributed per cent 59.08, 5.79 and 21.63, respectively for total variability in grain yield per hectare. Estimates of GGE bi-plot revealed that the lines G1, G3, G11, G13, G15, G12, G16, G7 and G10 were positioned near GGL bi-plot origin indicating wider adaptation for the trait grain yield per hectare. Eberhart and Russel Model and GGE biplot model showed the advanced breeding lines viz., JB 1-11-7 (G1) and JA 6-2 (G15) exhibited wider adaptability across the tested environments for number of productive tillers per plant and yield per hectare.

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