Grain yield is a major goal for the improvement of durum wheat, particularly in drought-prone areas. In this study, the genetic basis of grain yield (GY), heading date (HD), and plant height (PH) was investigated in a durum wheat population of 249 recombinant inbred lines evaluated in 16 environments (10 rainfed and 6 irrigated) characterized by a broad range of water availability and GY (from 5.6 to 58.8 q ha À1 ). Among the 16 quantitative trait loci (QTL) that affected GY, two major QTL on chromosomes 2BL and 3BS showed significant effects in 8 and 7 environments, with R 2 values of 21.5 and 13.8% (mean data of all 16 environments), respectively. In both cases, extensive overlap was observed between the LOD profiles of GY and PH, but not with those for HD. QTL specific for PH were identified on chromosomes 1BS, 3AL, and 7AS. Additionally, three major QTL for HD on chromosomes 2AS, 2BL, and 7BS showed limited or no effects on GY. For both PH and GY, notable epistasis between the chromosome 2BL and 3BS QTL was detected across several environments.

Association mapping was used to dissect the genetic basis of drought-adaptive traits and grain yield (GY) in a collection of 189 elite durum wheat accessions evaluated in 15 environments highly different for water availability during the crop cycle (from 146 to 711 mm) and GY (from 9.9 to 67.3 q ha(-1)). For highly heritable traits (e.g. heading date, kernel weight, etc.) several significant experiment-wise marker-trait associations were detected across five or more (up to 13 for kernel weight) environments, with R(2) values ranging from ca. 5 to 10%. As to GY, significant associations (R(2) from 2.5 to 4.2%) were mostly detected in one environment only (56 markers), while decreasing rapidly from two to five environments (from 20 to three markers, respectively) and with only one marker (Xbarc197 on chr. 5A) found significant in six environments (ranging from low- to high-yielding). These results are probably due to the complex genetic basis of GY and its interaction with environmental conditions. The number of markers significantly affecting GY decreased considerably under drought conditions, suggesting a limited effectiveness of association mapping to identify loci for GY under low-moisture conditions, most likely because different genotypes can attain similar phenotypes via different morpho-physiological traits and corresponding gene networks. Our study confirmed the role of major loci for phenology previously described in biparental mapping populations, highlighted a novel set of loci for drought-adaptive traits, and provided information on the agronomic value of the alleles at such loci across a broad range of soil moisture conditions.

The ability to assess green biomass is of particular interest in a number of wheat breeding environments. However, the measurement of this and similar traits is either tedious and time-consuming or requires the use of expensive, sophisticated equipment, such as field-based spectroradiometers to measure vegetation indices (VIs). Here, conventional digital cameras are proposed as affordable and easy-touse tools for gathering field data in wheat breeding programmes. Using appropriate software, a large set of images can be automatically processed to calculate a number of VIs, based on the performance of simple colour operations on each picture. The purpose of this study was to identify a set of picture-derived vegetation indices (picVIs) and to evaluate their performance in durum wheat trials growing under rainfed and supplementary irrigation conditions. Here, zenithal pictures of each plot were obtained roughly 2 weeks after anthesis, and the picVIs that were calculated were compared with the normalised difference vegetation index (NDVI), an index derived from spectroradiometrical measurements, and with the grain yield (GY) from the same plots. The picVIs that performed best were the Hue, CIE-Lab a* and CIE-Luv u* components of the average colour of each picture, the relative green area (GA) and the 'greener area', similar to GA but excluding the more yellowish-green pixels. Our results showed a high correlation between all these picVIs and the NDVI. Moreover, in rainfed conditions, each picVI provided an estimation of GY similar to or slightly better than that provided by the NDVI. However, in irrigated conditions during anthesis, neither these picVIs nor the NDVI provided a good estimation of GY, apparently because of the saturation of the VI response in conditions of complete soil cover and high plant density.

Increasing crop yields to ensure food security is a major challenge. Mutagenesis is an important tool in crop improvement and is free of the regulatory restrictions imposed on genetically modified organisms. The forward genetic approach enables the identification of improved or novel phenotypes that can be exploited in conventional breeding programmes. Powerful reverse genetic strategies that allow the detection of induced point mutations in individuals of the mutagenized populations can address the major challenge of linking sequence information to the biological function of genes and can also identify novel variation for plant breeding. This review briefly discusses recent advances in the detection of mutants and the potential of mutagenesis for crop improvement.

Population structure and genome-wide linkage disequilibrium (LD) were investigated in 192 Hordeum vulgare accessions providing a comprehensive coverage of past and present barley breeding in the Mediterranean basin, using 50 nuclear microsatellite and 1,130 DArT((R)) markers. Both clustering and principal coordinate analyses clearly sub-divided the sample into five distinct groups centred on key ancestors and regions of origin of the germplasm. For given genetic distances, large variation in LD values was observed, ranging from closely linked markers completely at equilibrium to marker pairs at 50 cM separation still showing significant LD. Mean LD values across the whole population sample decayed below r (2) of 0.15 after 3.2 cM. By assaying 1,130 genome-wide DArT((R)) markers, we demonstrated that, after accounting for population substructure, current genome coverage of 1 marker per 1.5 cM except for chromosome 4H with 1 marker per 3.62 cM is sufficient for whole genome association scans. We show, by identifying associations with powdery mildew that map in genomic regions known to have resistance loci, that associations can be detected in strongly stratified samples provided population structure is effectively controlled in the analysis. The population we describe is, therefore, shown to be a valuable resource, which can be used in basic and applied research in barley.