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Precipitation and temperature are two main climatic factors that influence crop productivity in arid and semi-arid areas. Study of the variability in these variables is thus important especially under dryland farming. In the present study, we evaluated the relationship between minimum, maximum, and mean temperatures; precipitation; and dryland wheat yield in northwest of Iran. The association between long-term weather data and dryland wheat yield for the time period bracketing 1990 and 2004 was investigated in seven stations (Ahar, Tabriz, Maragheh, Myaneh, Urmia, Khoy, and Makou) homogenously distributed over the study region. Aridity index (AI) was also calculated and its relationship with wheat yield was studied. Results showed that AI significantly decreased in the whole region (except for Urmia) with the highest variation in Maragheh and Myaneh. Increase in temperature was the major contributing factor to the increasing AI. Association between weather variables and dryland wheat yield at annual, seasonal, and monthly scales showed different results. At seasonal scale, spring was the main season affecting wheat yield. Also, at monthly scale, January, April, and May had more important role in wheat yield variation compared to the other months. The association between dryland wheat yield and weather variables was stronger in Maragheh and Myaneh. At the end, it was concluded that wheat yield was more affected by the variability in the climate in East Azerbaijan compared to that in West Azerbaijan. [ABSTRACT FROM AUTHOR]

Sustainable land resource management depends on the good assessment and planning of current landscapes. This may be possible with application of multidisciplinary researches, as this study presented a multidisciplinary approach in a spatial database frame work using Geographic Information System. 'Agroecological zones' concept is used to integrating and characterizing homogenous spatial units. This approach combine theme layers include of available water resources, climate, terrain and soil conditions, associated with land use and settlement patterns. Climatic indices layers, including of growing degree days, aridity index, length of growing period and freezing period were created using the correlation between climatic parameter and digital elevation model. Using this approach the Borujen watershed was divided in 28 'agroecological zones' which defined 3 landscapes or agricultural regions. The most important constraints for developing agriculture in landscape I has topographic, climatic and soil constrains, landscape II has topographic and soil constrains and landscape III has the some limitations of soil. Landscape I and II are much less attractive from an agricultural perspective. Landscape III is suitable for agriculture but, the potential for rainfed cropping system is limited by a lack of growing period during which neither temperature nor moisture is limiting to plant production. In general, the case study of the Borujen watershed indicated that this approach can be used for different scales and adaptive to the particular planning. [ABSTRACT FROM AUTHOR]

Genotype x environment interactions complicate selection of superior genotypes for narrow and wide adaptation. Multienvironment yield trials of twenty durum wheat genotypes were conducted at five locations of Iran (Gachsaran, Gonbad, Moghan, Ilam and Khorram abad) over four years (2009-2013). Combined ANOVA of yield data of the twenty environments (year/location combined) revealed highly significant differences among genotypes and environments as well as significant genotype-environment interaction indicated differential performance of genotypes over test environments. The GE interaction was examined using multivariate analysis technique as principal coordinate analysis (PCOA). According to grand means and total mean yield, test environments were grouped into two main groups as high mean yield (H) and low mean yield (L). There were eleven H test environments and nine L test environments which analyzed in the sequential cycles. For each cycle, both scatter point diagram and minimum spanning tree plot were drawn. The identified most stable genotypes with dynamic stability concept and based on the minimum spanning tree plots and centroid distances were G12 (3342 kg ha-1), G10 (3470.3 kg ha-1), G5 (3203.0 kg ha-1), and G1 (3263.5 kg ha-1), and therefore could be recommended for unfavorable or poor conditions. Genotypes G10 (3470.3 kg ha-1) and G9 (3404.2 kg ha-1) were located several times in the vertex positions of high cycles according to the principal coordinates analysis (PCOA) and therefore could be recommended for favorable or rich conditions. Finally, the results of principal coordinates analysis in general confirmed the breeding value of the genotypes, obtained on the basis of the yield stability evaluation. [ABSTRACT FROM AUTHOR]