Introduction
Wheat (Triticum aestivum L.) is one of the most important staple crops worldwide and plays a crucial role in food security in Iran. A large proportion of wheat production in the country occurs under rainfed conditions, where yields are highly sensitive to drought, climatic variability, and limited genetic diversity among cultivated varieties. In semi-arid regions, the increasing frequency of dry years associated with climate change has further intensified yield instability and production risks in rainfed wheat systems. Under such conditions, reliance on genetically uniform improved cultivars—typically developed under relatively stable environments—may limit the adaptive capacity of cropping systems. Increasing intraspecific genetic diversity through heterogeneous populations has therefore been proposed as an alternative strategy to enhance resilience in variable environments. Evolutionary populations and dynamic mixtures represent practical approaches within the framework of evolutionary plant breeding, in which genetically diverse populations are cultivated in farmers’ fields and allowed to evolve over time under natural selection and local environmental conditions. The high level of genetic diversity maintained in these populations can enhance buffering capacity against environmental stresses and contribute to improved yield stability across environments. However, evaluating their performance requires analytical approaches that consider not only mean yield but also yield variability and production risk. Among the available stability measures, the reliability index combines mean performance with environmental variance and provides an estimate of the minimum yield expected under unfavorable conditions. The objective of this study was to evaluate the agronomic performance, yield stability, and reliability of wheat evolutionary populations and dynamic mixtures compared with landraces and improved varities under rainfed conditions in Iran.

Materials and Methods
This study was conducted over three consecutive cropping seasons (2019–2021) at four rainfed locations in Iran: Ravansar–Moradabad in Kermanshah province, Firoozabad and Naqsh-e Rostam in Fars province, and Faruj in North Khorasan province, Iran. These sites represent a range of environmental conditions typical of rainfed wheat production systems in Iran. Sixteen wheat genotypes were evaluated, including twelve evolutionary populations and dynamic mixtures, two landraces (Sardari and Kal Heydari), and two improved cultivars (Azar 2 and Chamran 2). The experiment was arranged in a randomized complete block design with three replications at each location. In each season, part of the harvested seed from each genotype was replanted in the following year to maintain the evolutionary process within the heterogeneous populations. Several agronomic and morphological traits were measured during the growing season, including grain yield, biomass yield, straw yield, harvest index, thousand kernel weight, plant height, and spike length. In addition, selected traits were assessed at the individual plant level to evaluate within-population variability. The data were analysed using a mixed model, the significance of tested effects was assessed using F-tests, and mean comparisons among entries were performed using the Bonferroni test. To assess genotype stability across environments, five stability indices were calculated: cultivar superiority, environmental variance, Wricke’s ecovalence, mean ranks, and variance of ranks. In addition, the reliability index was calculated for grain yield, biomass yield, straw yield, and plant height. This index combines mean performance with environmental variance and estimates the minimum yield expected under most environmental conditions, thus providing an indicator of yield risk.

Results and Discussion
The mixed-model analysis showed significant year × location effects for all measured traits, indicating strong environmental heterogeneity across the rainfed testing environments. The main effect of entry was not significant for most plot-level yield traits, including grain yield and biomass yield, while harvest index and some plant-level traits, particularly spike length and kernel number per spike, showed significant entry effects. Mean grain yield and biomass yield of the evolutionary populations and dynamic mixtures were not significantly different from those of the landraces and improved cultivars, indicating that increased within-crop genetic diversity did not reduce average performance. However, several evolutionary populations and dynamic mixtures ranked higher in stability and reliability indices than the reference landraces and improved cultivars. In particular, EP-Sharareh and MIX-4096 showed higher grain-yield reliability than Sardari, while MIX-6097, MIX-Sararood and MIX-6093 outperformed Azar 2 in reliability. These findings suggest that evolutionary populations and dynamic mixtures should be evaluated not only by mean yield, but also by genotype × environment responses, stability and reliability under variable rainfed conditions.

Conclusion
Overall, the results of this study demonstrate that increasing intraspecific genetic diversity through evolutionary populations and dynamic mixtures can enhance yield stability and reduce production risk in rainfed wheat systems. Although the mean yield of these populations was not significantly different from that of landraces and improved cultivars, some populations showed clear advantages in terms of stability and reliability indices. These findings suggest that heterogeneous wheat populations may provide a promising strategy for improving the resilience of rainfed cropping systems under increasing climatic variability.