Using AMMI approach to delineate genotype by environment interaction and stability of barley (Hordeum vulgare L.) genotypes under northern Indian shivalik hill conditions

Author(s):  
Om Prakash Yadav ◽  
A. K. Razdan ◽  
Bupesh Kumar ◽  
Praveen Singh ◽  
Anjani K. Singh

Genotype by environment interaction (GEI) of 18 barley varieties was assessed during two successive rabi crop seasons so as to identify high yielding and stable barley varieties. AMMI analysis showed that genotypes (G), environment (E) and GEI accounted for 1672.35, 78.25 and 20.51 of total variance, respectively. Partitioning of sum of squares due to GEI revealed significance of interaction principal component axis IPCA1 only On the basis of AMMI biplot analysis DWRB 137 (41.03qha–1), RD 2715 (32.54qha–1), BH 902 (37.53qha–1) and RD 2907 (33.29qha–1) exhibited grain yield superiority of 64.45, 30.42, 50.42 and 33.42 per cent, respectively over farmers’ recycled variety (24.43qha–1).

2018 ◽  
Vol 17 (1) ◽  
pp. 81-86 ◽  
Author(s):  
Massaoudou Hamidou ◽  
Oumarou Souleymane ◽  
Malick N. Ba ◽  
Eric Yirenkyi Danquah ◽  
Issoufou Kapran ◽  
...  

AbstractSorghum is a staple food crop in Niger and its production is constrained by sorghum midge and the use of low yielding, local sorghum varieties. To improve sorghum productivity, it is crucial to provide farmers with high yielding sorghum cultivars that are resistant to midge. We evaluated 282 genotypes in four environments of Niger Republic. Alpha (0.1) lattice with two replications was the experimental design. Genotype and genotype by environment (GGE) biplot analysis was used to study grain yield (GY) stability and G × E interactions. The results revealed that two distinct mega environments were present. Genotype L232 was the best genotype for GY in the first planting date at Konni and the first and second planting dates (PDs) at Maradi. Genotype L17 was the best for GY in the second PD at Konni. The second PD at Konni was the most discriminating environment while the first PD at Konni is suitable for selecting widely adapted genotypes for GY.


Author(s):  
Saleem Abid ◽  
Saleem Zahid

Twenty six yellow maize hybrids on the basis of stability analysis were evaluated in National Uniform Maize Hybrid Yield Trials conducted across eight diversified environments of Pakistan. Combined analysis of variance based AMMI analysis shown highly significant differences for environments, genotypes and their interactions. The environments explained about 78 percent of the total yield variation followed by genotype by environment interaction. Environment was the main aspect that influences the performance of maize yield in study area. The first two interaction principal component axes (IPCA1 and IPCA2) explained about 63 percent of the grain yield variation due to genotype and genotype by environment interaction (GGE). The GGE biplot analysis shown that entry-2 (Mex-YLHY2) was the most stable hybrid and can be considered as adaptable to all the environments.


2021 ◽  
Vol 33 (3) ◽  
pp. 181-190
Author(s):  
Marco Acevedo Barona ◽  
Rubén Silva Díaz ◽  
Ramón Rea Suárez

The development of new high-performance and stable cultivars requires test multi-environmental validation to deal with the effect of genotype by environment interaction (GEI). With the objective to determine adaptability and stability for grain yield in hybrids and rice varieties through the models AMMI, SREG and REML/BLUP. Six experiments were evaluated during the 2015-2016 dry season in the main producing regions of Venezuela. The ANOVA detected differences for genotype (G), environment (E) and their interaction (GEI), representing 19, 65 and 16 % of the total variation, respectively, with prevalence of hybrid by localities interaction. The first major components of the AMMI and GGE biplot models explained 77 and 83 % of GEI, respectively. The three models coincided and identified the hybrid RHA-180 (H6) with improved average performance, adapted and stable. The hybrid HIAAL (H3) was the most prominent. Among the checks, 'Pionero FL' (V3) was the most stable with moderate yield; the opposite occurred with ‘Soberana FL’ (V4) and ‘SD-20A’ (V1), that the AMMI and GGE biplot models identified with high and unstable performances and specific adaptation to locality INIA Guárico (L1), not coinciding with the mixed model. Two mega-environments were identified with the winning genotypes H6 and V4. There was divergence between AMMI and GGE biplot to identify discriminatory and representative locations. The Plot 199 (L3) was the most representative, while the location L1 discriminated better the genotypes. The GGE biplot analysis was more informative and complete for the GEI analysis.


2020 ◽  
Vol 12 (6) ◽  
pp. 98
Author(s):  
Charles Andiku ◽  
Geofrey Lubadde ◽  
Charles J. Aru ◽  
Michael A. Ugen ◽  
Johnie Ebiyau

Genotype-by-environment interaction analysis is vital for cultivar release, and to identify suitable crop production sites. The current study aimed to determine sorghum grain yield stability and adaptability and to identify the most informative and representative environments for sorghum grain yield performance in Uganda. Sorghum grain yield data of eight (08) genotypes; ICSR 160, IS8193, IESV92043DL, IESV92172DL, GE17/1/2013A, GE35/1/2013A, SESO1, and SESO3 tested across eight (08) major sorghum production area in Uganda for two consecutive seasons of 2017 using randomised complete block design with 2 replications were analysed via Additive Main effects and Multiplicative Interaction (AMMI) and Genotype Main Effect and Genotype by Environment interaction effects (GGE) using PB tools. Genotype IESV92043DL was the ideal genotype in the entire test environments with mean grain yield of 2783 kg ha-1 however genotype ICSR 160 had the highest grain yield of 2823 kg ha-1 across all the test environment. On the other hand, GE17/1/2013A was the most stable and adapted genotype across all the test environment. Of the eight (08) environments tested, biplot analysis precisely grouped the test environments into two presumed mega-environments with the best genotype being IS8193 and ICSR 160. Out of eight (08) trial sites, two (02) environments; Abi and Mayuge were the most representative and informative environment for sorghum grain yield performance in Uganda.


2021 ◽  
Vol 73 (4) ◽  
Author(s):  
Marzougui Salem

Genotype by environment interaction and stability analyses are among the most important evaluations conducted in plant breeding. In this study, we evaluated the yield-related traits of 32 Tunisian barley (<em>Hordeum vulgare </em>L.) accessions over three consecutive cropping seasons in a semi-arid environment. Phenotypic analysis identified heading date and spike length as the two major traits contributing most to the total phenotypic variation under a semiarid climate. Hierarchical clustering grouped the 32 accessions into four groups. Although the effect of the interaction between genotype and environment was important for yield (48%), it had comparatively little influence on heading date (9.9%) and plant height (8.14%). Stability analysis identified the djebali accession, with the smallest coefficient of variability, as a stable genotype across the three assessed environments. Overall, based on the higher yield and small coefficient of variance, we selected 11 promising genotypes. In addition, varieties developed by the Tunisian breeding program were found to show high mean yield, stability across all environments, and greater adaptability. Accessions with superior adaptation and stability will be introduced into the national breeding program for further evaluation and characterization.


2021 ◽  
Vol 50 (2) ◽  
pp. 343-350
Author(s):  
Meijin Ye ◽  
Zhaoyang Chen ◽  
Bingbing Liu ◽  
Haiwang Yue

Stability and adaptability of promising maize hybrids in terms of three agronomic traits (grain yield, ear weight and 100-kernel weight) in multi-environments trials were evaluated. The analysis of AMMI model indicated that the all three agronomic traits showed highly significant differences (p < 0.01) on genotype, environment and genotype by environment interaction. Results showed that genotypes Hengyu321 (G9), Yufeng303 (G10) and Huanong138 (G3) were of higher stability on grain yield, ear weight and 100-kernel weight, respectively. Genotypes Hengyu1587 (G8) and Hengyu321 (G9) showed good performance in terms of grain yield, whereas Longping208 (G2) and Weike966 (G12) showed broad adaptability for ear weight. It was also found that the genotypes with better adaptability in terms of 100-kernel weight were Zhengdan958 (G5) and Weike966 (G12). The genotype and environment interaction model based on AMMI analysis indicated that Hengyu1587 and Hengyu321 were the ideal genotypes, due to extensive adaptability and high grain yield under both testing sites. Bangladesh J. Bot. 50(2): 343-350, 2021 (June)


2021 ◽  
pp. 1-13
Author(s):  
Aliya Momotaz ◽  
Per H. McCord ◽  
R. Wayne Davidson ◽  
Duli Zhao ◽  
Miguel Baltazar ◽  
...  

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).


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