SUMMARYClimate change is now unequivocal, particularly in terms of increasing temperature, increasing CO2 concentration, widespread melting of snow and ice and rising global average sea level, while the increase in the frequency of drought is very probable but not as certain.However, climate changes are not new and some of them have had dramatic impacts, such as the appearance of leaves about 400 million years ago as a response to a drastic decrease in CO2 concentration, the birth of agriculture due to the end of the last ice age about 11 000 years ago and the collapse of civilizations due to the late Holocene droughts between 5000 and 1000 years ago.The climate changes that are occurring at present will have – and are already having – an adverse effect on food production and food quality with the poorest farmers and the poorest countries most at risk. The adverse effect is a consequence of the expected or probable increased frequency of some abiotic stresses such as heat and drought, and of the increased frequency of biotic stresses (pests and diseases). In addition, climate change is also expected to cause losses of biodiversity, mainly in more marginal environments.Plant breeding has addressed both abiotic and biotic stresses. Strategies of adaptation to climate changes may include a more accurate matching of phenology to moisture availability using photoperiod-temperature response, increased access to a suite of varieties with different duration to escape or avoid predictable occurrences of stress at critical periods in crop life cycles, improved water use efficiency and a re-emphasis on population breeding in the form of evolutionary participatory plant breeding to provide a buffer against increasing unpredictability. ICARDA, in collaboration with scientists in Iran, Algeria, Jordan, Eritrea and Morocco, has recently started evolutionary participatory programmes for barley and durum wheat. These measures will go hand in hand with breeding for resistance to biotic stresses and with an efficient system of variety delivery to farmers.

The objective of this study was to compare nonparametric stability procedures and apply different nonparametric tests for genotype · environment (G · E) interactions on grain yields of 15 durum wheat genotypes selected from Iran/ ICARDA joint project grown in 12 environments during 2004-2006 in Iran. Results of nonparametric tests of G · E interaction and a combined ANOVA across environments indicated the presence of both crossover and noncrossover interactions, and genotypes varied significantly for grain yield. In this study, high values of TOP (proportion of environments in which a genotype ranked in the top third) and low values of sum of ranks of mean grain yield and Shukla's stability variance (ranksum) were associated with high mean yield. The other nonparametric stability methods were not positively correlated with mean yield but they characterized a static concept of stability. The results of correlation analysis indicated that only TOP and rank-sum methods would be useful for simultaneous selection for high yield and stability. These two methods identified lines Mrb3/Mna-1, Syrian-4 and Mna-1/Rfm-7 as genotypes with dynamic stability and wide adaptation. According to static stability parameters, the genotypes 12A-Mar8081 and 19A-Mar8081 with lowest grain yield were selected as genotypes with the highest stability.

Integrating yield and stability of genotypes tested in unpredictable environments is a common breeding objective. The main goals of this research were to identify superior durum wheat genotypes for the rainfed areas of Iran and to determine the existence of different mega-environments in the growing areas of Iran by testing 20 genotypes in 4 locations for 3 years via GGE (genotype + genotype-by-environment) biplot analysis. Stability of performance was assessed by the Kang’s yield-stability statistic (YSi) and 2 new methods of yield-regression statistic (Ybi) and yield-distance statistic (Ydi).The combined analysis of variance showed that environments were the most important source of yield variability, and accounted for 76% of total variation. The magnitude of the GE interaction was ~10 times the magnitude of the G effect. The GGE biplot suggested the existence of 2 durum wheat mega-environments in Iran. The first mega-environment consisted of environments corresponding to ‘cold’ locations (Maragheh and Shirvan) and a moderately cold location (Kermanshah), where ‘Sardari’ was the best adapted cultivar; the second mega-environment comprised ‘warm’ environments, including the Ilam and Kermanshah locations, where the recommended breeding lines G16 (Gcn//Stj/Mrb3), G17 (Ch1/Brach//Mra-i), and G18 (Lgt3/4/Bcr/3/Ch1//Gta/Stk) produced the highest yields. Ranking of genotypes based on GGE was found to be highly correlated with that based on the statistics YSi and Ybi. The discriminating power v. the representative view of the GGE biplot identified Kermanshah as the location with the least discriminating ability but greater representation, suggesting the possible of testing genotypes adapted to both warm and cold locations at the Kermanshah site. The results verified that the statistics YSi and Ybi were highly correlated (r = 0.94**) and could be a good alternative for GGE biplot analysis for selecting superior genotypes with high-yielding and stable performance.

Because of unpredictable conditions in Mediterranean environments, successful crop production requires improved adaptation and yield stability to mitigate major abiotic stresses such as drought and cold. In this study 380 durum wheat (Triticum turgidum L.) landraces with worldwide origins and four checks were evaluated in four rainfed research stations for 3 yr (2008–2011). The main objective was to investigate yield stability and adaptation patterns of the landraces to highland rainfed cold regions of Iran, where drought and cold are limiting factors. The experimental design was an unreplicated trial at each environment. Best linear unbiased predictions (BLUPs) data were used to analyze landrace × environment interactions using multivariate statistical methods. Considerable variability in yield, adaptation, and stability was observed for the landraces, which could be exploited for crop improvement. The landrace and environment groups allowed characterization of origins on the basis of similar performance of landrace within particular environments. Grouping of environments was not repeatable among the years. Many of the durum landraces exhibited a high combination of yield and stability for both drought and cold stresses, comparable to cold‐ and/or drought‐tolerant checks. Most landraces originating from Europe and the United States could be considered as a genetic resource for specific adaptation, while the landraces from Asia may enhance genetic potential of yield stability. In conclusion, current durum wheat selection may lead to yield stability and specific adaptation, which provides opportunities for this collection to be useful for genetic improvement of both drought and cold tolerance in durum wheat.

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SU MMARYPattern analysis, cluster and ordination techniques, was applied to grain yield data of 20 durum wheat genotypes grown in 19 diversified environments during 2005-07 to identify patterns of genotype (G), environment (E) and genotype-by-environment (GrE) interaction in durum multienvironment trials (METs). Main effects due to E, G and GrE interaction were highly significant, and 0 . 85 of the total sum of squares (SS) was accounted for by E. Of the remaining SS, the GrE interaction was almost 12 times the contribution of G alone. The knowledge of environmental and genotype classification helped to reveal several patterns of GrE interaction. This was verified by ordination analysis of the GrE interaction matrix. Grouping of environments, based on genotype performance, resulted in the separation of different types of environments. Pattern analysis confirmed the cold and warm mega-environments, and allowed the discrimination and characterization of adaptation of genotypes. However, several patterns of GrE interaction in Iran's regional durum yield trials were further discerned within these mega-environments. The warm environments tended to be closer to one another, suggesting that they discriminate among durum genotypes similarly, whereas cold environments tended to diverge more. The dwarf and early maturing breeding lines from ICARDA with low to medium yields and high contribution to GrE interaction were highly adapted to warm environments, whereas the tall and later maturing genotypes with low to high yields were highly adapted to the cold environments of Iran.

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