جستجوی مقالات مرتبط با کلیدواژه « ammi stability value » در نشریات گروه « زراعت »

IntroductionProduction of high-yielding and stable cultivars is the most important objective of crop breeding programs, including wheat. The final yield of each plant is determined by the potential of genotype (G), the effect of environment (E) and the interaction effect of genotype × environment (GE). Several methods have been presented to study the genotype × environment interaction and determine stable genotypes, which can totally be divided into two main categories, univariate and multivariate. Univariate methods do not provide a complete view of the complex and multidimensional nature of GE interaction, therefore, the use of multivariate methods is suggested to solve this problem. Among the multivariate methods, AMMI and GGE-Biplot methods are more important. The objective of the current experiment was to investigate the interaction between genotype and environment for grain yield of 20 wheat genotypes and to identify stable and high-yielding genotypes.Materials and methods The plant materials of this experiment were 20 wheat genotypes including 18 irrigated wheat lines along with two control cultivars, Rakhshan and Baharan. The experiment was carried out in a randomized complete block design with three replications in five temperate regions (Karaj, Kermanshah, Zarghan, Boroujerd and Mashhad stations) during two cropping years 2019-2020. Two multivariate methods, AMMI and GGE-Biplot, were used to investigate the interaction effect of genotype × environment and to evaluate the stability of genotypes. R software was used to analyze the experimental data using the AMMI method, and Genstat software was used to analyze the data using the GGE biplot graphic method.Research findingsThe results of combined analysis of variance showed that the interaction effect of genotype × year and genotype × year × location were significant at the 1% probability level. Based on the results of AMMI analysis, the effect of environment, genotype and genotype × environment interaction were significant. Based on AMMI1 and AMMI2 models, AMMI stability value (ASV) parameter and genotype stability index (GSI), genotype 12 with an avearage grain yield of 8.27 tons per hectare was determined as the best genotype. The study of GGE-biplot polygon led to the identification of three mega-environments, that Boroujerd had the highest power of representation and differentiation among different environments. Genotypes 12 and 9, in addition to having high yield, had higher yield stability. Genotypes 12 and 9 were placed in the center of the circle as the ideal genotype and genotypes 5, 7 and 18 were ranked next. Based on the results of both methods, genotype 12 was identified as the most stable genotype.ConclusionThe results of AMMI, AMMI stability index (ASV) and genotype stability index (GSI) compared to GGE biplot results showed that all these indices have a good potential to evaluate the performance stability of genotypes. Nevertheless, GGE biplot results are more effective and practical in examining the compatibility and stability of genotypes' performance in different environments due to the ease of interpreting graphical results.

Studying the interaction of genotype ×environment and identifying high-yielding and stable cultivars is very important for breeders. In this research, the yield stability and compatibility of ten grain sorghum genotypes were evaluated in seven regions of Iran, Karaj, Gorgan, Birjand, Isfahan, Shiraz, Hamadan and Zabol, during two years (2019-2020). The experiment was performed as randomized complete block design with three replications in all years and regions. The results of combined analysis of variance showed that the effect of location, year and genotype and all their interactions on grain yield significant at 1% probability level. The results of AMMI analysis also showed that the main effect of genotype, environment and interaction of genotype × environment as well as the first five main components of interaction on grain yield were significant (p≤0.01). In total, the cumulative share of the five main components was 93.61%. Genotypes 5 and 4 had the most positive and negative interactions, respectively. Although these genotypes had high grain yield, they were known as unstable genotypes. Genotypes 2 and 7 were selected as stable genotypes and are recommended to all regions based on the AMMI1 model. In this experiment, genotype number 7 with the lowest AMMI  stability value (ASV) was recognized as the most stable genotype and genotype number 1 with the highest ASV was recognized as the most unstable genotype. In terms of stability, genotype number 6 with the highest grain yield (7379 kg.ha-1) was ranked after genotypes 7 and 3. Genotype number 7 with the lowest value of interaction compared to the two axes (IPCA1 and IPCA2) was known as stable genotype and genotypes 2 and 9 had the highest values ​​of interaction. In terms of other stability indices such as MASV, SIPC, DZ, EV and ZA, genotypes 7 and 3 were determined as the most stable genotypes.

The interaction of genotype × environment creates complications in yield prediction and is a challenge for agronomy and plant breeding programs. To evaluate grain yield stability and genotype × environment interaction for 18 local and exotic grain sorghum cultivars, lines, and hybrids, a field experiment was conducted using randomized complete block design with three replications in four regions of Karaj, Gorgan, Birjand, and Isfahan, Iran in two cropping seasons (2016 and 2017). Combined analysis of variance showed that locations, genotypes and their interaction effect were signifinat on grain yield. Mean comparisons showed that genotype No. 15 (High yield700) had the highest grain yield (7986 kg.ha-1) followed bygenotypes No. 17, 6, 16, and 8 with grain yield of 6894, 6172, 5960, and 5906 kg.ha-1, respectively. Genotypes No. 15 and 17 had the lowest year within location variance, and in addition to high grain yield stability had optimal grain yield. Analysis of variance by AMMI model and fitting of principal components to the interactions of genotype × environment showed that five main components were significant (P ≤0.01). These five components explained 94.1% of the observed variance of genotype × environment interaction. Cluster analysis identified four genotypic groups based on the first main component of genotype × environment interaction. In this study, high yielding genotypes also had good grain yield stability. AMMI model and AMMI stability value (ASV) parameter showed that genotypes No. 17 (Drought tolerant), 4 (Fast green400), 6 (FGCSI04), 15 (High yield700) and 16 (Human900) had high grain yield and yield stability. Genotypes No. 15 and 17 identiifed as superior genotypes well adapted to different test environments, in this study.

This study was carried to assess seed yield stability and genotype × environment interaction of 15 faba bean promising lines together with four control cultivars using randomized complete block design with three replications in four experimental field stations; Gorgan (rainfed), Dezful (irrigated), Borujerd (rainfed), Iranshahr (irrigated), in two cropping seasons (2015 -17). Combined analysis of variance showed that genotypes differed significantly for days to 50% flowering, plant height, number of pods per plant, number of seeds per pod, 100-seed weight and seed yield. FLIP03-069FB, ILB1266 × ILB1814 and WRB2-7 × Giza Blanca promising lines had the highest seed yield, respectively. Environment main effect accounted for 76.43% of total observed variation in seed yield, whereas genotype and genotype × environment interaction effect accounted for 6.31% and 17%, respectively. The multivariate analysis using additive main effects and multiplicative interaction (AMMI) showed that the six first principal components had significant effect in explaining genotype × environment interaction effect, and explained 99.69% of the total of observed variation. The AMMI stability value (ASV) discriminated WRB2-7 × Giza Blanca, ILB 3626, Barkat × BPL 465 promising lines and cv. Barkat with high seed yield stability, respectively. Barkat × New Mammoth promising line and cv. Zereshki had low seed yield stability, respectively. Also, Gorgan and Borujerd environments, due to their high interaction, were identified as the ideal environments for discriminating faba bean genotypes. In conclusion, WRB2-7 × Giza Blanca promising line with average seed yield of 3285 kg ha-1, high yield stability and wide adaptation was identified as the superior genotype for being released as new commercial faba bean cultivar for target regions.

Barley (Hordeum vulgare L.) After wheat, maize and rice is the fourth grain, which is cultivated for grain use and has a perennial diploid and polyploid, and has been dispersed throughout the world. The adaptation of cultivars in different environmental conditions in plant breeding programs is of particular importance. Reactions between genotypes and environmental effects are referred to as genotype and environment interaction.The interaction between the genotype and the environment creates complexity in yield prediction and is a challenge for plant production and breeding programs. Methods for reducing the interaction between genotype and environment and increasing performance can be used to select and introduce high-performance and sustainable lines in different regions. Therefore, the aim of this study was to investigate the genotype × environment interaction and adaptability and performance stability of 21 barley genotypes using the analysis of the main and multiplicative effects (AMMI) model. Data related to location and years in the form of integrated environment and data analysis were carried out based on six environments. Then AMMI analysis and calculation of the main components of the interaction effect for all genotypes and drawing of the plot and calculation of ASV stability index was performed using IRRISTAT software.

The present experiment was carried out in randomized complete block designs with two replications during 2014-2015, 2015-2016, 2016-2017 under rain-fed and irrigation conditions (a total of six environments) at the research farm of Faculty of Agriculture, Razi University, Kermanshah, Iran.

The combined analysis of variance for grain yield showed significant differences for year, genotype, genotype × year, year × location and year × location × genotype effects. The results of the analysis of AMMI model showed a significant difference between genotype and environment and four components of the interaction for grain yield were significant. The first and second components in AMMI model accounted for 52.78% and 26.00% of the interaction sum of squares, respectively. Genotypes with high values of the first major components (positive or negative) have a high interaction with the environment, while the genotypes with the first major component near zero have lower interaction. Genotypes 2, 5, 8, 10, 13 and 20 with fewer values of the first component of interaction were more stable than the other genotypes. The value of ASV was obtained from the ratio of sum of squares of IPCA1 (the first component of interaction) to IPCA2 (the second component of the interaction) for each genotype. According to the stability Index, the genotypes 9, 12, 15 were selected with the lowest values of AMMI stability as most stable genotypes. In order to determine sustainable genotypes with general and specific adaptation, AMMI Biplot was used for different locations. The results showed that genotype 2, 5, 8, 10, 13, which are at the center of biplot, have general stability and the genotypes that are closer to any environment the environment have specific adaptability to the environment. Among stable genotypes, genotypes 10 (Roho / 4 / Zanbaka / 3 / ER / Apm / Lignee131 / 5 / Otis), 8 (Baladieldawaia / 5 / AwBlack / Aths // Arar / 3 / 9Cr279-07 / Roho / 4 / DD-14 / Rhn-03) and 2 (Zarjau/80-5151//Skorohod/3/Robur/WA2196-68//DZ40-66) had higher mean grain yield. Therefore, these genotypes can be proposed for using in future breeding programs to introduce new cultivars.

Combined analysis of variance showed significant effect of year, genotype and genotype × year interaction for grain yield. The significant effect of genotype indicates the diversity of studied genotypes in terms of grain yield. Among the stable genotypes, genotypes 2, 8 and 10 had also higher grain yield, therefore, it can be suggested that the genotypes can be introduced as new cultivars or for use in future breeding programs. However, it is not appropriate to use a stablity method to identify high-performance and stable genotypes, so, it is recommended to use different methods to assess the stability.

To evaluate the interaction pattern of genotype × environment and grain and dry forage yield stability of 10 promising dual purpose sorghum lines, a field experiment was carried out using randomized complete block design with four replications in six field stations of Karaj, Mashhad, Birjand, Zabol, Moghan and Isfahan in 2014 and 2015 growing seasons. Combined analysis of variance showed that the main effects of year, location, and genotypes as well as their interaction effects were significant (p <0.01) on grain yield, dry forage yield and biological yield. Mean comparison showed that line No. 3 (KDFGS9) with grain yield of 7.8 tha-1 had the highest grain yield, and line No. 1 (KDFGS4) and line number 9 (KDFGS26) with 26.2 and 26.1 tha-1 had the highest dry forage yield, respectively. Line No. 1 (KDFGS4), No. 2 (KDFGS6) and No. 9 (KDFGS26) were superior to the others by producing of 34.3, 33 and 32.5 tha-1 of biological yield, respectively. Analysis of variance by AMMI model and fitting of main components to the genotype by environment interaction effect showed that two main components for grain yield, dry forage yield and biological yield were significant. The first two components explained 67.8 percent of the sum of the squares of the interaction. According to the AMMI model and ASV stability parameter, lines No. 2 (KDFGS6) and No. 3) KDFGS9( with high grain and dry forage yield stability were the most suitable lines for dual purpose with the priority of grain production. On the other hand, lines No. 9 (KDFGS26) and No. 1 (KDFGS4) can be released as dual-purpose cultivars with the priority of forage production.

In order to determine yield stability of 20 durum wheat genotypes, a trial was carried as randomized complete block design with four replications in four years during 2009- 2014 in Sarab-Changae station of Khorramabad, Iran. Analysis of combine variance showed that environment, genotype and genotype × environment interaction were significant at 1% probability level. Variance analysis of additive main effects and multiplicative (AMMI) showed that two IPCAs were significant at 1% probability level. Also, AMMI stability value (ASV) was used for simultaneously using information obtained from two significant components of AMMI. According to ASV index, genotypes G2, G12, G14 and G19 had the lowest ASV value and were known as the most stable genotypes. Genotype G9 had the highest ASV value and distance from the center of Bi-plot. Therefore, it was known as stable genotype. Also, Genotype G9 had the highest grain yield. Using cluster analysis of genotypes based on ASV, genotypes divided to three groups that genotypes of each group were similar as stable.

Genotype by environment interaction creates intricacy in yield prediction and is a challenge in agronomy and plant breeding. In order to assess yield stability of eight bread wheat genotypes in eight environments (four years under normal and drought stress conditions)¡ eight randomized complete block design with three replications were conducted out in Kerman. Results analyzed as a combined design. Environment¡ genotypes and genotype by environment interaction were highly significant. Significant interaction pointed out different yield stability of evaluated cultivars. Stability was evaluated using environmental variance¡ coefficient of variation¡ Wricke''s ecovalence¡ Shukla''s stability variance¡ regression slope¡ deviation from regression slope¡ Additive Main effects and Multiplicative Interaction (AMMI) and AMMI Stability Value (ASV). Azar 2 and Kavir cultivars with high ranks in univariate stability parameters and the lowest ASV considered as the most stable genotypes. Shiraz was the most unstable cultivar in all univariate and multivariate methods. Considering mean over four years¡ Mahdavi and Shiraz had the highest yield performance in drought stress and normal conditions¡ respectively.