Climate change has generated unpredictability in the timing and amount of rain, as well as extreme heat and cold spells that have affected grain yields worldwide and threaten food security. Sources of specific adaptation related to drought and heat, as well as associated breeding of genetic traits, will contribute to maintaining grain yields in dry and warm years. Increased crop photosynthesis and biomass have been achieved particularly through disease resistance and healthy leaves. Similarly, sources of drought and heat adaptation through extended photosynthesis and increased biomass would also greatly benefit crop improvement. Wheat landraces have been cultivated for thousands of years under the most extreme environmental conditions. They have also been cultivated in lower input farming systems for which adaptation traits, particularly those that increase the duration of photosynthesis, have been conserved. Landraces are a valuable source of genetic diversity and specific adaptation to local environmental conditions according to their place of origin. Evidence supports the hypothesis that landraces can provide sources of increased biomass and thousand kernel weight, both important traits for adaptation to tolerate drought and heat. Evaluation of wheat landraces stored in gene banks with highly beneficial untapped diversity and sources of stress adaptation, once characterized, should also be used for wheat improvement. Unified development of databases and promotion of data sharing among physiologists, pathologists, wheat quality scientists, national programmes, and breeders will greatly benefit wheat improvement for adaptation to climate change worldwide.

The normalized difference vegetation index (NDVI) continues to provide easy and fast methodologies to characterize wheat genetic resources in response to abiotic stresses. This study identifies ways to maximize green leaf area duration during grain filling and develops NDVI models to predict physiological maturity and different stay-green parameters to increase grain yield of rainfed winter wheat under terminal drought. Three wheat populations were evaluated: one containing 240 landraces from Afghanistan, the second with 250 modern lines and varieties, tested for two years under low rainfall conditions in Turkey, and the third with 291 landraces from Central and Western Asia (grown for one year in the same location). The onset of senescence, maximum "greenness", rate of senescence and residual "greenness" at physiological maturity were estimated using sequential measurements of NDVI and have shown significant correlations with grain yield under low rainfall rainfed conditions. Trade-offs were identified among the different stay-green attributes, e.g. delayed onset of senescence and high maximum "greenness" resulted in accelerated rates of senescence and highest yields and were most evident in the landrace populations. It is concluded, that the use of rate of senescence to select for staygreen must be coupled with other stay-green components, e.g. onset of senescence or maximum "greenness" to avoid the effects of the trade-offs on final grain yield. The NDVI decay curves (using the last three NDVI measurements up to maturity) were used to estimate days to maturity using the NDVI decay during the senescence period and days to heading. A training and testing set (20 and 80% of each population, respectively) were used for calibrations allowing for correlations between predicted and observed maturity of up to r=+0.85 (P<0.0001). This procedure will facilitate large-scale wheat phenotyping in the future.

Wheat landraces in Turkey are an important genetic resource for wheat improvement. An exhaustive 5-year (2009–2014) effort made by the International Winter Wheat Improvement Programme (IWWIP), a cooperative program between the Ministry of Food, Agriculture and Livestock of Turkey, the International Center for Maize and Wheat Improvement (CIMMYT) and the International Center for Agricultural Research in the Dry Areas (ICARDA), led to the collection and documentation of around 2000 landrace populations from 55 provinces throughout Turkey. This study reports the genetic characterization of a subset of bread wheat landraces collected in 2010 from 11 diverse provinces using genotyping-by-sequencing (GBS) technology. The potential of this collection to identify loci determining grain yield and stripe rust resistance via genome-wide association (GWA) analysis was explored. A high genetic diversity (diversity index = 0.260) and a moderate population structure based on highly inherited spike traits was revealed in the panel. The linkage disequilibrium decayed at 10 cM across the whole genome and was slower as compared to other landrace collections. In addition to previously reported QTL, GWA analysis also identified new candidate genomic regions for stripe rust resistance, grain yield, and spike productivity components. New candidate genomic regions reflect the potential of this landrace collection to further increase genetic diversity in elite germplasm.

Erratic weather patterns associated with increased temperatures and decreasing rainfall pose unique challenges for wheat breeders playing a key part in the fight to ensure global food security. Within rain fed winter wheat areas of Turkey and Iran, unusual weather patterns may prevent attaining maximum potential increases in winter wheat genetic gains. This is primarily related to the fact that the yield ranking of tested genotypes may change from one year to the next. Changing weather patterns may interfere with the decisions breeders make about the ideotype(s) they should aim for during selection. To inform breeding decisions, this study aimed to optimize major traits by modeling different combinations of environments (locations and years) and by defining a probabilistic range of trait variations [phenology and plant height (PH)] that maximized grain yields (GYs; one wheat line with optimal heading and height is suggested for use as a testing line to aid selection calibration decisions). Research revealed that optimal phenology was highly related to the temperature and to rainfall at which winter wheat genotypes were exposed around heading time (20 days before and after heading). Specifically, later winter wheat genotypes were exposed to higher temperatures both before and after heading, increased rainfall at the vegetative stage, and reduced rainfall during grain filling compared to early genotypes. These variations in exposure to weather conditions resulted in shorter grain filling duration and lower GYs in long-duration genotypes. This research tested if diversity within species may increase resilience to erratic weather patterns. For the study, calculated production of a selection of five high yielding genotypes (if grown in five plots) was tested against monoculture (if only a single genotype grown in the same area) and revealed that a set of diverse genotypes with different phenologies and PHs was not beneficial. New strategies of progeny selection are discussed: narrow range of variation for phenology in families may facilitate the discovery and selection of new drought-resistant and avoidant wheat lines targeting specific locations.

One of the main goals of Triticale (xTriticosecale Wittmack) Breeding Program of Turkey is to improve high yielding and stable genotypes across environments. In this study, 16 parametric stability methods were used to evaluate the genotype x environment interaction (GEI) in 9 (4 officially registered varieties and 5 advanced lines) triticale (xTriticosecale Wittmack) genotypes. The genotypes were evaluated for grain yield at 4 different locations for 3 years in rain-fed areas of Turkey. The testing locations have different climatic and edaphic conditions providing the conditions necessary for the assessment of stability. A combined analysis of variance, parametric stability statistics and rank correlations among them were determined. Significant differences were detected between genotypes and their GEIs. Different parametric stability statistics were used to determine stability of the studied genotypes. The level of association among the statistics was assessed using Spearman?s rank correlation. Rank-correlation coefficients between yield and some parametric stability statistics were highly significant. Genotypes mean yield was significantly correlated to the parametric stability statistics Pi (r = 0.95**), PCA1 (r = 0.87**) and Di (r = 0.98**). A principal component analysis based on rank correlation matrix was performed for grouping the different parametric stability statistics studied. In conclusion, based on most parametric stability statistics, the genotype G8 was found to be the most stable and high yielding. This genotype is, therefore, recommended for release as a cultivar for rain-fed areas of Turkey.