r. karimizadeh

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.

In this study, 14 advanced chickpea genotypes selected from regional experiments with Adel and Azad, as control cultivars, were cultivated in a randomized complete block design with three replications in eight environments (Gonbad, Gachsaran, Ilam and Khorramabad in three, two, two and one years, respectively) in Iran during 2017-2020 growing seasons. Combined analysis of variance showed that environment, genotype and genotype by environment interaction (GEI) explained 43.5, 19.8 and 36.7% of the total variation of grain yield, respectively. The first and second principal components accounted for 50.89% and 19.39% of variation, respectively. The polygonal view of biplot showed that genotypes G11, G14 and G9 were the most adaptable genotypes for environments E2, E3, E6, E7, E8, E4 and E5 and G8, G5 and G13 for E1. Based on average tester coordinate (ATC) view, genotypes G11, G5, G13 and G14 were the most stable and high-yielding genotypes. The GGE-biplot based on genotype-focused scaling showed that genotypes G11, G14, G8, G9 and G13, in the circles around the ideal genotype, were the most preferred genotypes. The priority index (PI) showed that in all environments and favourable environments (environments with higher than average grain yields), genotypes G11, G9, G16, G13 and G14 and in unfavourable environments (environments with lower than average grain yields), genotypes G11, G13, G14, G12 and G5 were superior genotypes. Based on different biplot views as well as priority index, genotypes G11, G14 and G5 had grain yields higher than average yield and yield of Adel and Azad cultivars. Further, given their grain yield stability in all environments they can be suitable candidates for introduction of new cultivars.

Sixteen chickpea genotypes and two commercial cultivars; Adel and Azad as check were evaluated under rainfed conditions using randomized complete block design with three replications at four filed stations; Gachsaran, Gonbad, Khorramabad and Ilam for three cropping seasons (2016-2019). Genotypes 5, 12, 11, 17 and 4 had the highest seed yield. Genotypes 18, 16, 6, and 3 had high seed yield stability based on Shukla variance (2i ), Wrick's equvalence (Wi), root mean square error (RMSE), Si1 and Si2 statistics. Genotypes 16 and 18 with regression coefficient close to one, seed yield higher than average yield and the lowest deviation from regression line were the superior genotypes. Analysis of variance using Eberhart and Russell method showed a significant genotype × environment interaction effect (linear) which indicated different response of genotypes to environmental conditions. Genotypes 4, 5, 9, 11, 12, 15, 16 and 18 were the best genotypes based on yield-stability index (YSi). Based on TOP nonparametric statistics, genotypes 5, 12, 15, 9 and 4 were superior genotypes. Based on Lin and Binns priority index, genotypes 12, 5, 11, 17 and 18 were desirable genotypes in all environments. In conclusion, genotypes 4, 5 and 12 can be considered as high yielding with yield stability and suitable for further verification in research and development projects.

Lentil cultivar Sepehr was first introduced as FLIP 2005-53L line through LIDTN-L-08 ICARDA international nursery and was evaluated in Gachsaran and Maragheh stations in 2007-2008 cropping season. FLIP 2005-53L line in the cropping seasons 2008-2009 and 2009-2010 was evaluated in the preliminary and advanced yield trials in Gachsaran and Khorramabad research stations. After evaluating the results of advanced experiments, this line was selected to participate in the national uniform regional yield trial (2010-2013) in Gachsaran, Khorramabad, Gonbad and Moghan research stations. Stability analysis of genotypes grain yield in this experiment showed that this line had the lowest contribution in the interaction of genotype × environment using different statistical methods and also it had the lowest mean rank values ​​for non-parametric stability parameters as well as 19% increases in the grain yield (with grain yield of 1166 kgha-1) ‌ compared to the control cultivar Gachsaran (with grain yield of 978 kgha-1) and therefore can be considered as "one of the most stable genotypes" with high grain yield. FLIP 2005-53L line with average grain yield of 1902 kgha-1 in farmers field in the research-extension trials, had a 15% advantage of grain yield over control cultivar Gachsaran with grain yield of 1651 kgha-1. In addition to high grain yield, good yield stability, high resistance to fusarium disease, desirable 100-seed weight (4.2 g) and suitable plant type and plant height for machine harvesting were other reasons for releasing Sepehr cultivar. Sepehr cultivar is suitable for cultivation in subtropical regions of the country including Khuzestan, Fars, Kohgiluyeh and Boyer-Ahmad, Lorestan, Kermanshah, Ardabil (Moghan) and Ilam provinces.

In this study, 18 lentil genotypes were grown under rainfed conditions for three growing seasons (2013-2016) in Gachsaran, Ilam and Khorramabad field stations in Iran. Analysis of additive main effects and multiplicative interaction (AMMI) revealed that the effect of environment, genotype and genotype by environment interaction and the first three principal components were significant for seed yield. According to the simultaneous selection indices: ssiASV; G12, G16, G8, G9 genotypes and G2, ssiSIPC: G11, G12, G9, G2 and G7 genotypes, ssiEV; G9, G11, G2, G7 and G15 genotypes, ssiZA; G12, G9, G2, G16 and G7 genotypes, and ssiWAAS; G12, G9, G16, G2 and G8 genotypes were identified as genotypes with yield stability. Polygon view of biplot demonstrated that G2 and G12 genotypes with yield stability. The average tester coordinate (ATC) view of biplot illustrated that G1, G10, G18 and G12 genotypes, in addition to high grain yield, had seed yield stability. G1, G16, G8, G18, G10, G15 and G12 genotypes were desirable based on the ideal genotype view of biplot. The vector view of GGE biplot indicated that the first environment (Gachsaran in 2013-2014) was highly discriminating and representative, and could discriminate the genotypes with yield stability. In conclusion, based on different views of biplot and simultaneous selection indices using AMMI analysis, G12 genotype was identified as superior genotype and can be considered as a candidate for being released as new lentil cultivar for dryland conditions.

About 250,000 hectares of warm dryland regions have moderate to low rainfall, high temperatures and poor soil fertility with low production potential. Wheat cultivars which are currently used by farmers in these harsh environments, have low production in many years or they cannot be harvested due to their short plant's height or shriveled grains. Aseman cultivar with pedigree of KABY/3/TEVEE2/URES//FUN/KAUZ was generated by using the compatible parents at Gachsaran Agricultural Research Station in 2005-2006 cropping season. After a six-year period evaluation of the genetic material in the segregating populations, Aseman along with other selected pure lines were selected for further investigation through preliminary, advanced, and elite regional yield trails for four consecutive cropping seasons. In these experiments, average grain yield of new cultivar in Gachsaran and Behbahan stations, as well as in low-yield farms located in Golestan (Agh Ghala), Bushehr (Deilam) and Khuzestan (Haftakel) provinces was 2894 kgha-1, showing 3% superiority to Karim as the check cultivar. The average grain yield of Aseman in uniform regional trials was 2737 kgha-1 and it had a significant difference (p < /em> < 0.01) with Chamran (21% superiority) in the Gachsaran and Agh Ghala )for two years), as well as Behbahan, Haftkhel and Deilam (for one year) stations. Under severe drought and heat stresses in Deilam, Behbahan and Haftakel stations, the mean grain yield of the new cultivar increased by 37% and 10% compared to the Chamran and Karim cultivars, respectively. Early maturity, taller height and appropriate seed weight, especially under severe heat and drought stresses conditions and also superior baking quality are prominent characteristics of Aseman cultivar. These characteristics justify the importance of introducing this new cultivar for cultivation in the low-yield warm dryland regions of Iran.

One of the applications of Non-Parametric methods is determination of genotypes rank in different environments, which is also used as a measuring stability. A stable genotype shows similar ranks across different environments and has minimum rank variance in different environments. Non-Parametric Stability Statistics require no statistical assumptions about the distribution of the phenotypic values and are easy to use. This study was carried out to determine the ranks of 10 Lentil genotypes (Lens culinaris Medikus) across ten environments in 2002-2004, using a randomized complete block design with four replications. Analysis of Thennarasu non-parametric statistics showed that genotypes 8 and 9 had high stability by NP(1) statistic and genotypes 9, 8 and 1 had stable yield in NP(2) method. Result of the NP(3) statistic was similar to NP(1) statistic. NP(4) statistic selected genotypes 9 and 1 as the most stable genotypes and ultimately NP(5) statistic introduced 9 and 1 genotypes as stable genotypes in this experiment. Also analysis of Nassar and Huhn non-parametric statistics revealed that genotypes 1 and 2 were most stable and well adapted across ten environments. In addition, it was concluded that plots obtained by both mean yield (kg ha-1) vs.Si(1) and mean yield (kg ha-1) vs. Si(2) values could enhance visual efficiency of selection based on genotype × environment interaction. According to these configurations, genotypes in section 1 can be considered as stable and well adapted to all environments, having general adaptable ability. For recognition a daptability,Si(1) and  Si(2) take preferred over other non-parametric statistics.

Estimation of genotype environment (GE) interaction is very important for plant breeders. The additive main effects and multiplicative interaction (AMMI) model is the combination of the analysis of variance (ANOVA) and principal components analysis (PCA) which calculates both additive and multiplicative effects. To estimate GE interaction by AMMI model, ten corn hybrids including nine hybrids that were the best hybrids in yield trials, and KSC301 were evaluated for two years in seven locations of Iran in a randomized complete block design with four replications. Results showed that the first four IPCAs and the fifth IPCA were significant at 1% and 5% probability levels, respectively. The first IPCA displayed 25.2% of GE interaction sum of squares and the other IPCAs 65.1% of GE interaction sum of squares. Four parameters including SIPC4, AMGE4, ASV and EV4 were calculated for stability determination of corn hybrids. ASV parameter showed positive and highly significant correlation with Wricke ecovalence (r = 0.76) and Huehn's S2 nonparametric statistics (r = 0.67). EV4, SIPC4 and ASV parameters had no correlation with each others. The highest grain yield belonged to hybrids No. 8 and No. 2 with 9705 and 9272 kgha-1 respectively. According to ASV parameter, hybrid No. 8 was determined as a stable hybrid with minimum interaction (260.274) and maximum grain yield (9705 kgha-1) and hybrid No. 3 with minimum interation (1899.58) was determined as unstable hybrid. According to obtained results for stability determination, hybrid No. 8 was selected as the most stable hybrid and ASV parameter was selected as the best stability parameter regarding its accurate results in comparison to the other AMMI parameters

To facilitate the interpretation of data from a genotype by environment experiment (GE), a cluster method is proposed to group genotypics according to their response to the environments especially when the GE interaction is large. The interaction structure of two-way classification data often can be identified if the data stratified into homogeneous subsets. In this paper four GE interaction cluster methods are proposed for this purpose. The stability of the 10 maize hybrids including 9 hybrids that were the best hybrids in yield trials and KSC 301 (check hybrid) were evaluated for 2 years in 4 locations of Iran. The randomized complete block design with 4 replications was conducted for each environment with different layouts. Simple analysis of variance revealed significant genetic differences between hybrids for grain yield. The results of combined analysis of variance indicated that genotype × year, genotype × location, and genotype × year × location interaction effects were significant (P < 0.01). Results also showed that models 1 and 3 and models 2 and 4 had the same responses. Hybrids 8 (K1263/1 × KE8212/12) with high yield stability in both models 1 and 3 were in one group and other hybrids were in another group. In models 2 and 4 results led to 3 groups: Group1 included hybrids 3, 7 and 9 that were very stable and had high yield group 2 included hybrid 1 alone that had medium stability and yield and group 3 included other hybrids that had low stability and yield.