جستجوی مقالات مرتبط با کلیدواژه « تجزیه AMMI » در نشریات گروه « زراعت »

Introduction:

The genotype × environment interaction is one of the most important factors in limiting breeding programs. The compatibility of a given genotype determines its ability and genetic capacity to produce high production and yield stability in different environments. Therefore, it is necessary to study the genotype × environment interaction in order to introduce stable genotypes in different environments. The current research was carried out to determine the compatibility and stability of yield for 10 tobacco genotypes and estimate the most stable genotype for tobacco growing areas in Iran (i.e. Guilan, Mazandaran and Golestan provinces). 

Materials and Methods:

In this study, 10 male sterile flue cured tobacco genotypes, which they completely tested in terms of quality and taste, including 7 internal modified hybrids named RVH5, RVH6, RVH8, RVH27, RVH30, RVH48, RVH70 along with 3 imported genotype DVH2101, PVH19 and NC100 in 6 tobacco growing regions of Guilan, Mazandaran and Golestan in two years of experiment (2018-2019). In total, 12 environments were studied in a randomized complete block design with 3 replications. Combined analysis was performed by considering the environments as a random factor and genotypes as a fixed factor. Then the stability analysis of genotypes was done by 10 stability statistics and the first 3 components of AMMI (Additive Main effects and Multiplication Interaction) analysis including IPCA1, IPCA2 and IPCA3. Analysis of variance was done using SAS.9 software, AMMI analysis and related graphs were performed using IRRISTAT software. 

Results and Discussion:

The results of combined analysis of variance showed that the effect of location and year × location interaction, the effect of genotype and genotype × year × location interaction were significant at the 1% probability level for yield. Genotype × environment interaction analysis using the first three main components of the AMMI analysis justified 69.47% of the total variance. The lowest coefficient of variation was related to DVH2101 and RVH27 genotypes. RVH30, RVH27 and RVH8 genotypes were selected as the most stable genotypes. According to Rick equivalence and Shoklaʹs stability variance parameters. The least squares deviation from the regression line were related to RVH27, RVH30 and RVH8 genotypes. In terms of regression coefficient, RVH27, RVH30 and DVH2101 genotypes had a line slope close to 1. Based on the coefficient of determination and Jenkins and Perkins statistics, RVH27, RVH30 and RVH8 genotypes were in the same rank in terms of stability. RVH27 and RVH30 were the most stable genotypes with superiority index. RVH27, RVH30 and DVH2101 genotypes were selected as the most stable hybrids based on the AMMI first model due to their proximity to the plot center, low interaction and high yield. Based on the second model of AMMI analysis, RVH27 and DVH2101 genotypes were selected as stable genotypes. In the third AMMI model, the RVH27 genotype was selected as the stable genotype due to its closeness to the biplot center and high yield. 

Conclusion:

Considering most of the stability statistics and AMMI analysis, the most stable genotype was RVH27 hybrid. RVH30 and DVH2101 hybrids were placed in the next categories of stability. In addition, genotypes RVH6 and NC100 showed high private compatibility to Tirtash tobacco growing area and genotype RVH27 to Rasht region.

Combinining features of the best linear unbiased predictions (BLUP) and additive main effects and multiplicative interaction (AMMI) through “Weighted average of absolutescores of best linear unbiased predictions” (WAASB) index in multi-environment experiments may lead to more percise evaluation of genotypes and assessment of genotype × environment interaction. In the present study, the seed yield stability of 14 advanced lentil lines was evaluated in a multi-environment trials in four locations including; Gachsaran, Khorramabad, Moghan and Ilam, Iran in 2018-2019 and 2019-2020 cropping seasons. The experimental design was s randomized complete block design with three replications. Statistical analyzes were performed using multi-environment trials analysis. Considering the significant G×E interaction based on the results of the relative likelihood test (LRT), it was possible to perform BLUP analysis on the data. The highest predicted seed yield by BLUP method belonged to genotype no. 9 followed by genotypes no. 11, 10, 5, which had higher than average predicted seed yield. To enable simultaneous selection based on both seed yield and yield stability, by combining seed yield (Y) and WAASB, a new index “WAASBY” was created. Considering 50% contribution of each of the two components of seed yield and yield stability, eight genotypes showed above average WAASBY. Genoype no. 9 had considerably higher WAASBY when compared with other genotypes and was identified as the best genotype followed by genotypes no. 10, 1, 2, 12, 14, 7 and 13 were ranked respectively. Both control cultivars (genotypes 15 and 16) had lower than average WAASBY. In conclusion, considering WAASBY index, genotypes 9, 10, 1 were identified as genotypes with highe seed yield and yield stability, and can be considered for being released as new lentil cultivars.

Knowledge about genotype × environment interaction helps breeders to select the best adaptable and stable genotypes for different regions. The main objective of this research was to select higher yielding bread wheat genotypes, compared to control cultivar, that are adaptable to the climatic conditions of the tropical and subtropical rainfed regions of Iran. Thus, 15 bread wheat genotypes selected from advanced yield comparison experiments, along with the check cultivar of Aftab, were studied in a randomized complete block design with three replications for three cropping seasons (2017-2020) in four regions (Gachsaran, Gonbad, Khorramabad and Moghan). In order to analyze the genotype × environment interaction the multivariate method of Additive Main Effects and Multiplicative Interaction (AMMI) was used. The Results of combined analysis of variance indicated that 91.49, 1.54 and 5.03 percentage of the total variations are related to environment, genotype and genotype × environment interaction, respectively. Moreover, results showed that the first seven principal components of the AMMI model were significant and explained 97.94% of genotype × environment interactions. The biplot of mean grain yield and the first principle component of genotypes and environments revealed that genotypes G1, G12 and G11 with a higher grain yield than the overall mean and lowest genotype × environment interaction were stable with high grain yield. Among them, genotype 11 with suitable general adaptability can be selected as promising genotype and a candidate for introducing a new cultivar for arid and semiarid rainfed regions. In this research, Khorramabad, with high proportion of genotype × environment interaction was recognized as the ideal environment for differentiation and separation of bread wheat genotypes. The cluster analysis classified the studied environments into three groups. The inclusion of all three years experiments related to Moghan location in one group indicates the high predictability and repeatability of this region.

One of the most complicated issues in plant breeding programs is genotype by environment interaction. To evaluate seed yield stability of 18 chickpea promising lines, a field experiment was conducted using randomized complete block design with four replications in two cropping seasons (2018-19 and 2019-2020) in four research stations (Maragheh, Kurdistan West Azerbaijan and Hamedan), Iran. Combined analysis of variance (ANOVA) as well as additive main effects and multiplicative interaction (AMMI) were performed to evaluate the genotype × environment interactions. Combined ANOVA showed that of the total variation, 35.62% were explained by "location" and 36.1% by the interaction effect of "year × location". Whereas, "year" explained only 13.06% of the total sum of squares. Based on AMMI analysis, chickpea seed yield was affected by genotype (7.10%), environment (84.8%) and genotype × environment interaction efect (8.04%). The significance of GEI showed that both the performance and ranking of genotypes fluctuated under the influence of GEI. On the other hand, the sum of squares of GEI showed the existence of cross-interaction between genotype and environment. AMMI analysis divided the GEI sum of squares into two main components. These two main components (IPC1 and IPC2) were significant and collectively accounted for 82.9% of the total variation and are, therefore, sufficient to explain the complex patterns of GE interaction. Genotypes were ranked based on AMMI stability value (ASV), and G3 line was designated as the genotype with highest seed yield stabilty. The AMMI1 model also identified the G5 line with high seed yield stability and performance. On the other hand, the AMMI2 bioplot identified the G11 line as a genotype with high general adaptability and seed yield stability. Among the experimental environments, the highest and lowest seed yields were obtained in E5 and E4 environments (Kurdistan in second year and West Azerbaijan in first year), respectively. According to the results of this study, G5 and G3 lines with seed yield of 941.4 and 911.1 kg.ha-1, respectively, were identified as high yielding with yield stability in all environments.

To identify bread wheat genotypes with higher grain yield and stability in saline regions of Iran, 17 elite genotypes along with three salinity tolerant control (Ofogh, Narin and Sistan) were evaluated in five regions including Birjand, Yazd, Zabol, Isfahan and Kerman, during two consecutive cropping seasons (2016-2018) under saline conditions. In all regions, the experiments were performed based on the randomized complete block with four replications. The result of combined analysis of variance indicated that the interactions of year×location×genotype were significant. To dissection of genotype-by-environment interaction (GE) and yield stability of genotypes, AMMI analysis and several parametric and non-parametric statistics were estimated. Based on AMMI2's biplot and stability statistics, G1, G2, G3, G6, G9, G10 and G20 genotypes were identified as the most stable genotypes. The results of correlation analysis showed that among all stability statistics, only ASV had a positive and significant association with grain yield. Taken together, our results revealed that G9 genotype had the highest grain yield (4.60 t. ha–1); hence, this genotype can be recommended as a high-yielding and stable genotype for cultivation in saline-prone regions of Iran.

For sustainable rice production in Iran the optimum use of production resources and the reduction of production costs are the two important issues. In this situation, water availability is a major limiting factor in sustainable rice production. Hence, changing of rice production system from lowland irrigated to aerobic production system, which is based on dry-seed sowing in non-puddled and non-satuared soil, is main goal in the national research plan. Six selected aerobic rice genotypes from preliminary yield trials together with two local checks of rice including; Neda, as tolerant and Tarom, as susceptible cultivars to aerobic conditions were evaluated using randomized comlete block design with three replications in Mazandaran and Golestan, Iran, provinces for three years from 2013-2015. Simple analysis of variance for each location showed significant differences among rice genotypes for all traits. Combined analysis of variance for grain yield was performed. There were highly significant differences for main effect of genotype, year × location and year × location ×genotype interactions effect. Grain yield stability analysis through AMMI and GGE bioplot methods indicated that aerobic rice cv. Vandana with an average grain yield of 2760 kg.ha-1 over all environments had high and grain yield with yield stability. This cultivar was also close to ideal rice genotype with lower plant height (98.8 cm) and phenology (97.0 days to 50% flowering), followed by the other two  aerobic rice genotypes; G2 (IR78908-193-B-3-B) and G6 (IR80508-B-194-3-B) with high grain yield over all environments. Therefore, these aerobic rice genotpes were selected and could be used in the national rice breeding programs or recommended for being grown in aerobic rice production system in Mazandaran and Golestan province under water-shortage conditions.

To study the adaptability and seed yield stability, in this experiment, ten quinoa genotypes including; Red Carina, Titicaca, Giza1, Q12, Q18, Q21, Q22, Q26, Q29, Q29 and Q31 were evaluated using randomized complete block design with three replications in 2017 and 2018 in four locations; Karaj, Shahr-e-Kord, Kashmar and Urmia for their adaptability and grain yield stability. The results showed that quinoa genotypes had significant differences for most of the studied traits. However, genotype × location × year interaction effects on plant height, inflorescence length and days to flowering was not significant. Q26 genotype had the highest grain yield (2007 kg.ha-1) in Shahr-e-Kord. The lowest yield (338.33 kg.ha-1) was related to Q21 genotype in Karaj. The results of AMMI stability analysis showed that Q29 genotype had the highedt grain yiled stability with the shortest distance from the center of the graph. Cv. Giza1, cv. Red Carina, Q31 and Q26 genotypes also ranked next in terms of grain yield stability. Also, Q12, Red Carina and Q22 genotypes had specific adaptation in Karaj and Kashmar, and Giza1 and Q18 genotypes showed high specific adaptation in Urmia. In general, the results of this experiment showed that all quinoa genotypes were compatible with spring cultivation in experimental sites.

Identification of adapted genotypes with high grain yield is the most important goal in durum wheat breeding programs. To study adaptation and grain yield stability of durum wheat genotypes, 18 durum wheat promising lines with two commercial durum and bread wheat cultivars were used. The durum wheat genotypes were evaluated in four locations; Isfahan, Karaj, Kermanshah and Neishabour in temperate agro-climate zone of Iran in 2013-14 and 2014-15 cropping cycles. The experiments were conducted using ranodomized complete block design with three replications. Combined analyses of variance were performed for grain yield. The genotype and genotype × year × location effects were significant. Therefore, for more precise evaluation of genotype by environment interactions and grain yield stability, parametric and non-parametric analysis methods such as AMMI, rank and standadard deveiation (SD) of rank, coefficient of environmental variation was employed. Results of all three stability analysis methods showed that genotypes no. 3 and no. 4 with high grain yield (8650 and 8699 kg.ha-1, respectively) and low G × E interaction were adapted with grain yield stability durum wheat genotypes. These superior durum wheat genotypes were identified for being released as new commercial durum wheat cultivars for temperate agro-climatic zone of Iran.

Significancet genotype environment (G E) interactions effects in a major constraint in evaluation and release of new cultivars. To achieve this goal and in order to evaluate and advance towards new high-yielding and stable/adaptable cultivars suitable for the temperate agro-ecological zone in Iran, a set of yield trials was conducted with 20 elite barley lines using a Randomized Complete Block Design (RCBD) with three replicates at nine different experimental field stations during two successive years (1380-1382). Grain yield was studied and the results obtained from the combined analysis of variance revealed significance of all effects i.e. genotype, environment and genotype environment interactions. Genotypes mean showed that the entries No. 9 (LB.Iran/Una8271//Gloria"S"/Come"s"-11M/3/Kavir) and No. 16 (L.131/Cerbel//Alger-Ceres/3/Gloria"s"-Copal"s") had the highest grain yield. To have a better interpretation of G × E interaction multivariate AMMI method was used, which resulted in five main principle components that explained 74.68% of the interaction mean square. Additionally, the genotypes No. 16 (L.131/Cerbel//Alger-Ceres/3/Gloria"s"-Copal"s") and No. 17 (L.131/Cerbel//Alger-Ceres/3/Kavir) had the lowest IPC1 and IPC2 and the highest levels of stability. Using the results of biplot and AMMI analysis, parameters integrated with those of grain yield, the entries 9 and 16 were selected as candidates lines with both best performance and grain yield stability.