scholarly journals Genotype environment interaction analysis for fruit yield in okra (Abelmoschus esculentus L.) under alkaline environments

2021 ◽  
Vol 81 (01) ◽  
pp. 101-110
Author(s):  
Satish Kumar Sanwal ◽  
Anita Mann ◽  
Hari Kesh ◽  
Gurpreet Kaur ◽  
Raj Kumar ◽  
...  
Keyword(s):  
Interaction Analysis ◽  
Stability Index ◽  
Genotype By Environment Interaction ◽  
Fruit Yield ◽  
Environment Interaction ◽  
Genotype Environment Interaction ◽  
Alkaline Environments ◽  
Prone Area ◽  
Marketable Fruit ◽  
Ph Range

Twenty four Okra genotypes were evaluated for marketable fruit yield and its related traits for genotype environment interaction during 2015-16 and 2016-17. The genotypes were exposed to alkaline environment with a pH range of 8.0±0.2, 8.5±0.2, 9.0±0.2 and 9.5±0.2. A significant level of deviation in expression of different traits was observed in all the genotypes with increasing pH. Based on Additive Main Effects and Multiplicative Interaction (AMMI), Genotype and Genotype Environment Interaction (GGE) biplot, Wrick’s ecovalence (Wi2 ), AMMI Stability Value (ASV) and Yield Stability Index (YSi) stable genotypes with high fruit yield were identified over the eight environments. The combined AMMI analysis of variance indicated that genotype main effect, environment and genotype-by-environment interaction effects showed variation of 19.83%, 63.07% and 17.10%, respectively for fruit yield. On the basis of different stability measures, VRO-112, VRO-110, Kashi Kranti, VROB178, AE-70 and VRO-108 were differentiated as high yielding and stable genotypes over the tested environments. This study will be helpful for selecting alkali tolerant okra parents for further breeding programme and recommending the suitable genotypes for alkalinity prone area

Genotype by environment interaction for yearling weight in Nellore cattle applying reaction norms models

2018 ◽  
Vol 58 (11) ◽  
pp. 1996
Author(s):  
S. Ribeiro ◽  
J. P. Eler ◽  
V. B. Pedrosa ◽  
G. J. M. Rosa ◽  
J. B. S. Ferraz ◽  
...  
Keyword(s):  
Genetic Correlation ◽  
Environmental Gradient ◽  
Genotype By Environment Interaction ◽  
Reaction Norms ◽  
Breeding Value ◽  
Environment Interaction ◽  
Genotype By Environment ◽  
Genotype Environment Interaction ◽  
Nellore Cattle ◽  
Gradient Variation

In the present study, a possible existence of genotype × environment interaction was verified for yearling weight in Nellore cattle, utilising a reaction norms model. Therefore, possible changes in the breeding value were evaluated for 46 032 animals, from three distinct herds, according to the environmental gradient variation of the different contemporary groups. Under a Bayesian approach, analyses were carried out utilising INTERGEN software resulting in solutions of contemporary groups dispersed in the environmental gradient from –90 to +100 kg. The estimates of heritability coefficients ranged from 0.19 to 0.63 through the environmental gradient and the genetic correlation between intercept and slope of the reaction norms was 0.76. The genetic correlation considering all animals of the herds in the environmental gradient ranged from 0.83 to 1.0, and the correlation between breeding values of bulls in different environments ranged from 0.79 to 1.0. The results showed no effect of genotype × environment interaction on yearling weight in the herds of this study. However, it is important to verify a possible influence of the genotype × environment in the genetic evaluation of beef cattle, as different environments might cause interference in gene expression and consequently difference in phenotypic response.

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.

Evaluation of sugarcane genotypes with respect to sucrose yield across three crop cycles using GGE biplot analysis

2021 ◽  
pp. 1-13
Author(s):  
Aliya Momotaz ◽  
Per H. McCord ◽  
R. Wayne Davidson ◽  
Duli Zhao ◽  
Miguel Baltazar ◽  
...  
Keyword(s):  
Block Design ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Genotype By Environment ◽  
Biplot Analysis ◽  
Genotype Environment Interaction ◽  
Area 5 ◽  
Randomized Complete Block Design ◽  
Main Effects

Summary The experiment was carried out in three crop cycles as plant cane, first ratoon, and second ratoon at five locations on Florida muck soils (histosols) to evaluate the genotypes, test locations, and identify the superior and stable sugarcane genotypes. There were 13 sugarcane genotypes along with three commercial cultivars as checks included in this study. Five locations were considered as environments to analyze genotype-by-environment interaction (GEI) in 13 genotypes in three crop cycles. The sugarcane genotypes were planted in a randomized complete block design with six replications at each location. Performance was measured by the traits of sucrose yield tons per hectare (SY) and commercial recoverable sugar (CRS) in kilograms of sugar per ton of cane. The data were subjected to genotype main effects and genotype × environment interaction (GGE) analyses. The results showed significant effects for genotype (G), locations (E), and G × E (genotype × environment interaction) with respect to both traits. The GGE biplot analysis showed that the sugarcane genotype CP 12-1417 was high yielding and stable in terms of sucrose yield. The most discriminating and non-representative locations were Knight Farm (KN) for both SY and CRS. For sucrose yield only, the most discriminating and non-representative locations were Knight Farm (KN), Duda and Sons, Inc. USSC, Area 5 (A5), and Okeelanta (OK).

scholarly journals Genomic Prediction with Genotype by Environment Interaction Analysis for Kernel Zinc Concentration in Tropical Maize Germplasm

2020 ◽  
Vol 10 (8) ◽  
pp. 2629-2639
Author(s):  
Edna K. Mageto ◽  
Jose Crossa ◽  
Paulino Pérez-Rodríguez ◽  
Thanda Dhliwayo ◽  
Natalia Palacios-Rojas ◽  
...  
Keyword(s):  
Genomic Prediction ◽  
Prediction Models ◽  
Interaction Analysis ◽  
Genotype By Environment Interaction ◽  
Zn Deficiency ◽  
Environment Interaction ◽  
Prediction Ability ◽  
Association Panel ◽  
Maize Germplasm ◽  
Zn Concentration

Zinc (Zn) deficiency is a major risk factor for human health, affecting about 30% of the world’s population. To study the potential of genomic selection (GS) for maize with increased Zn concentration, an association panel and two doubled haploid (DH) populations were evaluated in three environments. Three genomic prediction models, M (M1: Environment + Line, M2: Environment + Line + Genomic, and M3: Environment + Line + Genomic + Genomic x Environment) incorporating main effects (lines and genomic) and the interaction between genomic and environment (G x E) were assessed to estimate the prediction ability (rMP) for each model. Two distinct cross-validation (CV) schemes simulating two genomic prediction breeding scenarios were used. CV1 predicts the performance of newly developed lines, whereas CV2 predicts the performance of lines tested in sparse multi-location trials. Predictions for Zn in CV1 ranged from -0.01 to 0.56 for DH1, 0.04 to 0.50 for DH2 and -0.001 to 0.47 for the association panel. For CV2, rMP values ranged from 0.67 to 0.71 for DH1, 0.40 to 0.56 for DH2 and 0.64 to 0.72 for the association panel. The genomic prediction model which included G x E had the highest average rMP for both CV1 (0.39 and 0.44) and CV2 (0.71 and 0.51) for the association panel and DH2 population, respectively. These results suggest that GS has potential to accelerate breeding for enhanced kernel Zn concentration by facilitating selection of superior genotypes.

scholarly journals Yield Components Stability Assessment of Peas in Conventional and Low-Input Cultivation Systems

Agriculture ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 805
Author(s):  
Vasileios Greveniotis ◽  
Elisavet Bouloumpasi ◽  
Stylianos Zotis ◽  
Athanasios Korkovelos ◽  
Constantinos G. Ipsilandis
Keyword(s):  
Seed Yield ◽  
Stability Index ◽  
Farming Systems ◽  
Farming System ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Low Input ◽  
Cultivation Systems ◽  
Biplot Analysis ◽  
Stable Performance

The primary purpose of this study was to explore yield stability of pea (Pisum sativum L.) cultivars based on stability index, with specific aim at studying cultivar behavior regarding yield of peas under both conventional and low-input cultivation systems. Five cultivars of peas were used in a strip-plot design. Correlations showed a significant positive relation between seed yield and some other traits. Indirect seed yield improvement may be implemented by improving pod length, which generally showed high stability indices in Greek mega-environment. Comparisons between conventional and low-input farming systems generally did not affect stability estimations, but revealed cultivars that exhibited stable performance, even in low-input farming systems. The additive main effects and multiplicative interaction (AMMI) biplot analysis, genotype by environment interaction (GGE) biplot analysis and analysis of variance (ANOVA) showed statistically significant differences between genotypes and environments, and also the farming system. This way, we have certain cultivars of peas to recommend for specific areas and farming system, in order to achieve the most stable performance. Vermio proved to be a stable cultivar for seed yield performance, in Giannitsa, Trikala and Kalambaka area, in low-inputs farming systems, while Olympos was the best in Florina area and low-input farming.

scholarly journals Genetic and Environmental Variation of Glucosinolate Content in Chinese Cabbage

HortScience ◽  
2006 ◽  
Vol 41 (6) ◽  
pp. 1382-1385 ◽  
Author(s):  
Ji Yeon Kang ◽  
Khalid E. Ibrahim ◽  
John A. Juvik ◽  
Doo Hwan Kim ◽  
Wha Jeung Kang
Keyword(s):  
Health Promotion ◽  
Chinese Cabbage ◽  
Phenotypic Variation ◽  
Genetic Manipulation ◽  
Genotype By Environment Interaction ◽  
Glucosinolate Content ◽  
Environment Interaction ◽  
Genotype Environment Interaction ◽  
Total Head ◽  
Risk Of Cancer

Strong evidence exists to suggest that increased consumption of glucosinolates from Brassica vegetables is associated with reduced risk of cancer induction and development. Development of elite germplasm of these vegetables with enhanced levels of glucosinolates will putatively enhance health promotion among the consuming public. To evaluate levels of glucosinolate phenotypic variation in Chinese cabbage tissue and partition the total phenotypic variation into component sources (genotype, environment, and genotype-by-environment interaction), a set of 23 Brassica rapa L. var. pekinensis genotypes were grown in two different environments (field plots and greenhouse ground beds). Gluconasturtiin and glucobrassicin were found to account for ≈80% of total head glucosinolate content. Significant differences were found in glucosinolate concentrations between the lowest and highest genotypes for glucobrassicin (6-fold) and for gluconasturtiin (2.5-fold). Analysis of variance showed that for the three major glucosinolates (gluconasturtiin, glucobrassicin, and progoitrin), the genotypic effects described most of the phenotypic variation (62% averaged over the three compounds). The next most important factor was genotype × environment interaction (29%), whereas variation affiliated with the environment was found to be relatively minor (8%). These results suggest that genetic manipulation and selection can be conducted to increase glucosinolate content and the putative health promotion associated with consumption of Chinese cabbage.

Genotype-by-environment interaction analysis across three crop cycles in sugarcane

2020 ◽  
pp. 1-15
Author(s):  
Aliya Momotaz ◽  
R. Wayne Davidson ◽  
Duli Zhao ◽  
P.H. McCord ◽  
Hardev S. Sandhu ◽  
...  
Keyword(s):  
Interaction Analysis ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Genotype By Environment
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