137,014 research outputs found

    Genotype x Environment Interaction and Its Stability Measures; Major emphasis in Arabica Coffee: A Review

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    Understanding the implication of genotype x environment interaction (GEI) structure is an important consideration in plant breeding programs. The phenotype of an individual is determined by both the genotype and the environment, these two effects are not always additive which indicates that genotype x environment interactions (GEI) are present. The presence of genotype x environment interaction contributes to the unreliability 'of crop yield over a wide range of environments. The occurrence of large genotype x environment interaction makes the selection of superior genotypes difficult and inhibits progress from selection. It prevents the full understanding of genetic control of variability. In the absence of GEI, the superior genotype in one environment may be regarded as the superior genotype in all, whereas the presence of the GEI confirms particular genotypes being superior in particular environments. Therefore, it is important to understand the nature of genotype x environment interaction to make testing and selection of genotypes more efficient. A variety of statistical procedures are available to analyze the results of multi-environment trials. Additive Main Effects and Multiplicative Interaction (AMMI) model which combines the conventional analyses of variance for additive main effects with the principal components analysis (PCA) for the non-additive residuals and Genotypic Main effect plus genotype by environment interaction (GGE) biplot are two popular graphical analysis systems for multi-environment trials. Other method like the regression of genotype means on the environment means is also worthwhile. Keywords: Additive Main Effects and Multiplicative Interaction, genotype x environment interactions, Stability DOI: 10.7176/ALST/89-01 Publication date:August 31st 202

    Two-stage clustering in genotype-by-environment analyses with missing data

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    Cluster analysis has been commonly used in genotype-by-environment (G x E) analyses, but current methods are inadequate when the data matrix is incomplete. This paper proposes a new method, referred to as two-stage clustering, which relies on a partitioning of squared Euclidean distance into two independent components, the G x E interaction and the genotype main effect. These components are used in the first and second stages of clustering respectively. Two-stage clustering forms the basis for imputing missing values in the G x E matrix so that a more complete data array is available for other GxE analyses. Imputation for a given genotype uses information from genotypes with similar interaction profiles. This imputation method is shown to improve on an existing nearest cluster method that confounds the G x E interaction and the genotype main effect

    Genotype x Environment Interaction and Yield Stability in Improved Rice varieties (Oryza sativa L.) Tested Over Different Locations in Western Oromia, Ethiopia

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    Eleven rice genotypes were evaluated at 6 environments in Western Ethiopia during 2015 and 2016 main cropping season. The objective of the study was to determine the magnitude of genotype x environment interaction and performance stability in the rice genotypes. The study was conducted using a randomized complete design with 3 replications. Genotype x environment interaction and yield stability were estimated using the additive main effects and multiplicative interaction and site regression genotype plus genotype x environment interaction bi plot pooled analysis of variance for grain yield showed significant (P<0.01) to significant (P<0.05)  differences among  genotypes, environment, genotype x environment interaction effects. This indicates that genotypes differentially respond to the change in test environments or the test environments differentially discriminated the genotypes or both. Environment accounted for 69.39%, of the total yield variation, genotype for 8.50% and genotype x environment for 3.90%, indicating the need for spatial and temporal replication of the trials.  Regression and AMMI analysis were employed in order to determine the stability of genotypes. The two models regression analysis and AMMI revealed similar result in that Adet and Hidassie  were stable and widely adapted genotypes. Adet and Hidassie varieties were the most stable and high yielding genotype and was therefore recommended for commercial production in the western Ethiopia upland rice  growing areas. Keywords: Rice, genotype x environment interaction, stability parameters, yiel

    GGE Bi Plot Analysis of Genotype X Environment Interaction and Grain Yield Stability of Bread Wheat (Triticum aestivum L.) Genotypes in Ethiopia

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    There is limitation of information on G x EI of bread wheat genotypes in Ethiopia. The study cried out with objectives to estimate Genotype x Environment interaction and stability of bread wheat genotypes in Ethiopia. Thirty Bread wheat genotypes were evaluated by Alpha lattice design using three replications at eight locations in Ethiopia. The mean grain yield of genotypes across environments was 4.53 ton ha-1. Bread wheat grain yield was significantly affected by the E, G and G x E interaction. Environment, G x E interaction and genotype explained 45.59%, 25.37% and 2.59% of the total (G + E + GEI) variation respectively. Genotype ETBW71942 (3), ETBW7038 (9), ETBW8511 (1) and ETBW8512 (14) were considered specifically adapted. Considering simultaneously yield and stability, Genotype ETBW7871 (15), ETBW7058 (11), ETBW8513 (16) and ETBW7101 (25) showed the best performances. Keywords: genotype; environment; genotype x environment interaction; Stability

    The Role of Genotype by Environmental Interaction in Plant Breeding

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    A genotype x environment interaction is a change in the relative performance of a character of two or more genotypes measured into two or more environments. Living organisms are made up of genes whose expressions are subject to modification by environment; therefore, genotypic expression of a phenotype is environmentally dependent. This is because genotypes exhibit different level of phenotypic expression under different environmental conditions resulting in cross over performances. In genotype x environment interaction, the magnitude of the observed genetic variation changes from one environment to another and tends to be larger in better environments than poor environments. Genotype x environment interaction is a fundamental component in understanding complex trait variation and the most challenging factor in identification of genetic variation. Interaction involves a change in rank order for genotypes between environments and the relative magnitude of genetic, environmental and phenotypic variance between environments. Genotype x environmental interaction can lead to differences in performance of genotypes over environments. The relationship between selection environments and target production environment had been a major problem because many of the selected activities performed by the conventional approach. Genotype x environment interaction analysis can be used to analyze the stability of genotypes and the value of test locations. Genotypes by environment interactions are almost unanimously considered to be among the major factors limiting response to selection and, in general, the efficiency of breeding programs. Exploitation of genetic variability is the most important tool in plant breeding and this has to be inferred by phenotypic expression. The consequences of the phenotypic variation depend largely on the environment. This variation is further complicated by the fact that not all genotypes react in similar ways to change in environment and no two environments are exactly the same. If relative performance of genotypes grown in different environments is different, then genotype x environment interaction becomes a major challenging factor to crop breeding programs. Genotype x environment interaction is one of the main challenge in the selection of broad adaptation and stable genotypes in most breeding programs. The varietal stability could be challenged not only due to the change in the test environment but also due to change in growing season per environment. Some environmental variations are predictable (soil type, soil fertility, plant density) whereas others also may be unpredictable (rainfall, temperature, humidity).Generally, genotype x environment interaction is the most critical in plant breeding to make selection of genotypes based on their adaptability and stability for desirable traits. Keywords: Genotype x Environmental Interaction; Environment; Phenotype; Genotype; Interaction; Variation DOI: 10.7176/JNSR/11-20-02 Publication date:October 31st 202

    Effects of Genotype, Environment and their Interaction on Quality Characteristics of Winter Bread Wheat

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    Grain quality is a complex character that depends on a number of traits, and the individual contribution of each trait varies depending on specific reaction to environmental conditions. The objective of this study was to assess the effects of genotype, environmental, and genotype x environmental interaction on quality characteristic of 16 wheat genotypes as well as to analyse the relationships between quality traits. The results of two-way analysis of variance showed that the effect of genotype, environment and genotype x environment interaction were significant (p≤0.001) for the investigated physical characteristics of grain. The strongest individual influence for thousand kernel weight, test weight and vitreousness had genotype. The interaction genotype x environment had stronger influence on the variance for the crude protein (44.98%) and the lysine (34.93%) than genotype and environment effects. Sources of variation genotype and genotype x environment interaction (year) had almost the equal influence on the variance of wet gluten content and bread making strength index. Genotype demonstrated the strongest influence on the sedimentation value and dry gluten content. The genotype x environment interaction influenced in the largest rate on the variance of gluten weakness. Protein content showed significant positive correlation with wet gluten content (0.676), gluten weakness (0.646) and dry gluten content. Vitreousness correlated positively with sedimentation value (0.541) while the test weight significantly correlated with dry gluten content. The results of this study can be used as selection criteria to increase grain quality in bread wheat in the region

    1975 Wild oat genotype x environment interaction

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    To investigate the interrelationships between wild oat (Avena sativa; fatua form) genotypes, herbicide treatment and time of application. Method: Split plot glasshouse (Forrestfield) experiment Reps (3) - plus three internal reps. Genotypes (5) - selected from north to south of southwest Western Australia Herbicides (4) - Avenge, S29761, Neoban, Water (Control) Times (6) - Average of 1 to 6 leaf stage Main plots were times and herbicides. Results: The following parameters were measured. .Growth stage at each time of application (number of leaves) .Height at each time of application .Date of full head emergence .Dry weight at full head emergence .Number of tillers .Number of spikelets on main tiller To date, only plant weight has been perused (Table ). Subject to analysis, the results show that there is a difference between the performance of each herbicide. More importantly Avenge and Neoban have optimum application times whereas this is much less critical for S29761. Also, the effect of each herbicide is not uniform on each genotype, possibly explaining variable field results sometimes obtained. The plant weight data will be correlated with other parameters to determine the relationship between herbicide effectiveness and an observable field plant character. The experiment was terminated successfully and the results will be published

    Pengaruh Interaksi Genotipe Dan Lingkungan Terhadap Hasil Kacang Hijau

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    Genotype x Environment Interaction (GEI) is a common phenomena, causing differences in grain yield ranking of genotypes among environments. Identification of genotypes that are stable and adaptive to specific environment is important in cultivar development. Nineteen mungbean genotypes were tested at 8 locations, namely Ngawi, Demak, and Probolinggo in dry season of 2011, and Ngawi, Demak, Probolinggo, Gresik and Lamongan in dry season of 2012. The trial was arranged in a randomized block design with three replications. Each genotype was planted on plot size of 4 m x 4 m (10 rows, 4 m long), with a spacing of 40 cm x 10 cm, two plants/hill. The data were analyzed using the MSTAC program. Analyses on genotype x environment interaction, stability, and adaptability were done referring to Eberhart and Russell (1966), while biplot analyses were done using the AMMI program. The effect of genotype x environment interaction, and the genotype x environment (linear) interaction which was significant to yield were important in determining the yield stability of mungbean genotypes. Locations contributed the highest to the total variance (71.7%), followed by genotype x environment interaction (25.1%). The average yields of the mungbean genotypes at eight locations ranged from 1.25 to 2.15 t/ha, and the average yield across locations of each mungbean genotype ranged from 1.59 to 1.80 t/ha. Two lines were considered as stable genotypes and with high yields, namely G12 and G17. Genotypes G5 and G6 were stable and adapted to optimal environment, while G4 was adapted to sub-optimal environment. All genotypes were considered stable based on both AMMI also stable on regression techniques

    Genotype x environment interaction for fruit yield of some cucumber (Cucumissativus) genotypes

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    The present study was performed to analyze the genotype x environment (G×E) interaction for fruit yield of 5 genotypes in four environments; Ikom, Calabar, Obubra and Obudu located at different agro-ecological zones of Cross River State. The cucumber genotypes were grown in randomized complete block design in three replicates in 2015 cropping season. The yield data was analyzed using additive main effect and multiplicative interaction (AMMI) and genotype plus genotype by environment (GGE). Additive main effect and multiplicative interaction (AMMI) analysis of variance showed statistically significant effect of genotypes, environments and the genotype x environment interaction (P < 0.01%). The environment explained 59.59%which showed high differences in variety response to different locations tested. Genotype (G) and genotype x environment interaction (G x E) accounted 15.83% and 11.89% respectively. The first interaction principal component axis (IPCA1) was significant (P < 0.01) except the (IPCA 2) and explained 11.50% and 0.36% of the G X E sum of squares respectively. The Additive main effect and multiplicative interaction stability value (ASV) showed that significant difference existed in the G x E component. Based on the stability parameters, it revealed that none of the genotypes were stable for fruit yield, however according to ASV, and GGE Bi-plot graphical representation, Ashley genotype in relative terms was stable. The genotypes Poinsett (48.43 t ha-1) , Ashley(47.49 t ha-1) and Marketer (41.66 t ha-1) were considered to have adaptability to favorable environments, while Market More (MM 13.97t ha-1) and Super Marketer (SM 16.66 t ha-1) adapted to unfavorable conditions for fruit yield. Based on AMMI and GGE bi-plot, ASL had the widest adaptation and was considered as the ideal genotype, whereas P.ST showed specific adaptation. The ideal environments were IKOM (66.85 t ha-1) and OBURA (56.93 t ha-1). Through the GGE bi-plot and AMMI analysis, the superior genotypes identified could serve as references for genotype evaluation and inclusion in further testing in other seasons and environments.Keywords: Environment, Genotype, Interaction, Stability and Yiel