Evaluation of Genotype × Environment Interaction and Yield Stability Analysis in Peanut Under Phosphorus Stress Condition Using Stability Parameters of AMMI Model

2020 ◽  
Vol 9 (4) ◽  
pp. 477-486 ◽  
Author(s):  
B. C. Ajay ◽  
S. K. Bera ◽  
A. L. Singh ◽  
Narendra Kumar ◽  
K. Gangadhar ◽  
...  
Author(s):  
Sangeeta Yadav ◽  
Arun Kumar Barholia

Thirty five genotypes of coriander (Coriandrum sativum L.) were tested in four artificially created environments to judge their stability in performance of seed yield. The differences among genotypes and environments were significant for seed yield. Stability parameters varied considerably among the tested genotypes in all the methods used. The variation in result in different methods was due to non-fulfillment of assumption of different models. However, AMMI analysis provides the information on main effects as well as interaction effects and depiction of PCA score gives better understanding of the pattern of genotype – environment interaction. The sum of squares due to PCAs was also used for the computation of AMMI stability values for better understanding of the adaptability behavior of genotypes hence, additive main effects and multiplicative interaction (AMMI) model was most appropriate for the analysis of G x E interactions for seed yield in coriander. Genotypes RVC 15, RVC 19, RVC 22, RVC 25 and Panipat local showed wider adaptability while, Simpo S 33 exhibited specific adaptability to favourable conditions of high fertility. These genotypes could be utilized in breeding programmers to transfer the adaptability genes into high yielding genetic back ground of coriander.


Agronomy ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 2136
Author(s):  
Mohammad Rafiqul Islam ◽  
Bikas Chandra Sarker ◽  
Mohammad Ashraful Alam ◽  
Talha Javed ◽  
Mohammad Jahangir Alam ◽  
...  

Water deficit stress is a critical abiotic constraint to mung bean production that affects plant growth and development and finally reduces crop yield. Therefore, a field experiment was conducted at five diverse environments using four water stress-tolerant genotypes, namely BARI Mung-8, BMX-08010-2, BMX-010015, and BMX-08009-7, along with two popular cultivated varieties (check) of BARI Mung-6 and BARI Mung-7 to evaluate more stable tolerant genotypes across the country. Stability analysis was performed based on the grain yield. The combined analysis of variance showed significant variations among genotypes, environments, and their interactions. The AMMI analysis of variance indicated that genotype accounted for 91% of the total sum of squares for grain yield, followed by genotype × environment interaction (5%), and environment (4%). Partitioning of interaction indicated that the first three interaction principal components (IPCA1–IPCA3) were highly significant (p ≤ 0.01). Using these significant IPCAs, AMMI stability parameters and non-parameter indices BMX-010015 was found stable across the environment based on yield traits and grain yield. The BMX-08010-2 genotype also showed significant regression coefficient (bi) more than unity, and non-significant deviation from regression (S2di) values, indicating suitable for a favorable environment considering grain yield. So, based on the stability analysis (Eberhart and Russell), additive main effects, and multiplicative interactions (AMMI) analysis, the BMX-010015 and BMX-08010-2 could be suitable for having tolerance to water deficit stress.


2014 ◽  
Vol 8 ◽  
pp. 14-17 ◽  
Author(s):  
Hari K. Upreti ◽  
Sudarshan Bista ◽  
Surya N. Sah ◽  
Ramesh Dhakal

Genotype x Environment interaction limits the effectiveness of selection when selection is based only on mean yield. This G × E interaction was studied for grain yield in 7 genotypes  of mid-hill rice in five different environments across the Nepal. Significant difference was observed among genotype (G), environment (E) and interaction (G × E) but could not identify the stable high yielding genotypes for diverse environments. Therefore, stability parameters were calculated and analyzed. On the basis of stability parameters, two genotypes, NR 10414, NR 10492 and NR 10515 were found to be most stable over different environments. NR 10353 was identified as suitable genotypes with high grain yield for favorable environment.Nepal Agric. Res. J. Vol. 8, 2007, pp. 14-17DOI: http://dx.doi.org/10.3126/narj.v8i0.11565


Author(s):  
B. Arunkumar ◽  
E. Gangapp ◽  
S. Ramesh ◽  
D. L. Savithramma ◽  
N. Nagaraju ◽  
...  

A genotype is considered to be most adaptive / stable, when it registers high mean yield but show a minimum interaction with the environment. Knowledge of genotype × environment interaction and yield stability are important parameters in breeding new cultivars with improved adaptation to environmental constraints prevailing in the target environments. Therefore, an effort was made to know the genotype - environment interaction and to identify stable single cross hybrids across the environments. Eight newly synthesized single cross maize hybrids and 7 checks were evaluated in a Randomized Block Design with three replications during Rabi-2016 across three locations spread over different agro-climatic zones of Karnataka state, India. Different stability parameters as suggested by Eberhart and Russell [1] were estimated. Joint analysis of variance revealed significant differences among environments, hybrids and environments × hybrids interactions advocating the adequacy of stability analysis. Hybrids, viz., MAI 349×MAI 283, KDMI 16×BGUDI 118 were stable for days to anthesis and silking, respectively. Whereas, hybrids viz., KDMI 16×BGUDI 118, BGUDI 120×VL 109252 and MAI 283× KDMI 16 registered mean values lower than the overall mean with bi value nearer to unity and non significant S2di for anthesis silking interval. Hybrid, MAI 349×MAI 283 for plant height and cob length, KDMI 16×MAI 283 for cob length, number of kernel rows-1 and 100 grain weight, BGUDI 88×MAI 349 for cob diameter, MAI 394×BGUDI 88  for shelling % and KDMI 16×BGUDI 118 for grain yield plant-1 registered stable performance across the environments. Based on the positive and negative environmental indices, production environment at location 1 (K Block UAS, GKVK, Bengaluru), was most favorable for expression of majority of characters studied. Hybrid KDMI 16×MAI 283 was found stable across the environments for most of the characters studied.


2012 ◽  
Vol 10 (1) ◽  
pp. 1-7
Author(s):  
P L Biswas ◽  
U K Nath ◽  
S Ghosal ◽  
A K Patwary

Genotype-environment interactions through different stability parameters and performance traits of four fine rice genotypes were studied. The traits were; days to 50% flowering, days to maturity, plant height (cm), number of effective tillers per hill, panicle length (cm), number of fertile grains per panicle, number of sterile grains per panicle and yield (t/ha) in four fine rice genotypes across nine environments along with experimental farm of Genetics and Plant Breeding department, Bangladesh Agricultural University (BAU) Mymensingh. Significant differences were observed for genotypes, environments and genotypes–environment interaction. Stability analysis after Eberhat and Russell’s model suggested that the genotypes used in study were more or less responsive to environmental changes. Most of the genotypes performed better in Comilla. BAU125 was found stable for effective tillers per hill and comparatively less sensitive to other genotypes in panicle length and number of sterile grains per panicle. BR5 was stable for days to maturity and plant height whereas Kalizira performed better than other genotypes for fertile grains per panicle. In general, only the genotype BAU125 was found stable for effective tillers per hill, panicle length and lowest number of sterile grains per panicle.   DOI: http://dx.doi.org/10.3329/jbau.v10i1.12011   J. Bangladesh Agril. Univ. 10(1): 1–7, 2012  


2001 ◽  
Vol 137 (3) ◽  
pp. 329-336 ◽  
Author(s):  
M. A. IBAÑEZ ◽  
M. A. DI RENZO ◽  
S. S. SAMAME ◽  
N. C. BONAMICO ◽  
M. M. POVERENE

Genotype–environment interaction and yield stability were evaluated for 19 genotypes of lovegrass (Eragrostis curvula). The study was conducted in the central semi-arid region of Argentina. Three locations and two growing seasons in combination generated six environments. Genotypic responses and stability of yield under variable environments were investigated. The genotype–environment interaction was analysed by three methods: regression analysis, AMMI and principal coordinates analysis (PCO). Analysis of variance showed that effects of genotype, environment and genotype–environment interaction were highly significant (P < 0·01). The genotypes accounted for 20% of the treatment sum of squares, with environment responsible for 65% and interaction for 14·5%. The biplot indicated that there was partial agreement between the AMMI and regression model. However the scatter point diagrams obtained from PCO analysis revealed only limited agreement with the results obtained by the regression analysis and the AMMI model. The results show that the AMMI model as a whole explained twice as much of the interaction sum of squares as did regression analysis and was more adequate than PCO analysis in quantifying environment and genotype effects for forage yield. AMMI analysis of the genotype–environment interaction effects showed that there were responses characteristic of a particular location. This type of association implies some predictability of genotype–environment interaction effects on forage yield production when differential responses across genotypes are associated with locations. Environmental factors may contribute to the interpretations of genotype–environment interaction. However in the semi-arid region, where fluctuations in growing conditions are unpredictable, additional research is required to obtain an integration of interaction analysis with external environmental (or genotypic) variables.


1969 ◽  
Vol 49 (6) ◽  
pp. 743-751 ◽  
Author(s):  
R. J. Baker

A detailed analysis of genotype-environment interactions was carried out among yields of six cultivars of hard red spring wheat grown at each of nine locations in five different years. Subdividing the sum of squares for genotype-environment interactions into components due to each cultivar indicated that the Finlay-Wilkinson method of measuring yield stability is of little value for wheat yield in western Canada. Conventional estimates of variance components due to the different types of genotype-environment interaction indicated that all except the genotype-year interaction were significant and important.


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