Key message Chromosome regions affecting grain yield, grain yield components and plant water status were identified and validated in fall-sown spring wheats grown under full and limited irrigation. AbstractIncreases in wheat production are required to feed a growing human population. To understand the genetic basis of grain yield in fall-sown spring wheats, we performed a genome-wide association study (GWAS) including 262 photoperiod-insensitive spring wheat accessions grown under full and limited irrigation treatments. Analysis of molecular variance showed that 4.1% of the total variation in the panel was partitioned among accessions originally developed under fall-sowing or spring-sowing conditions, 11.7% among breeding programs within sowing times and 84.2% among accessions within breeding programs. We first identified QTL for grain yield, yield components and plant water status that were significant in at least three environments in the GWAS, and then selected those that were also significant in at least two environments in a panel of eight biparental mapping populations. We identified and validated 14 QTL for grain yield, 15 for number of spikelets per spike, one for kernel number per spike, 11 for kernel weight and 9 for water status, which were not associated with differences in plant height or heading date. We detected significant correlations among traits and colocated QTL that were consistent with those correlations. Among those, grain yield and plant water status were negatively correlated in all environments, and six QTL for these traits were colocated or tightly linked (< 1 cM). QTL identified and validated in this study provide useful information for the improvement of fall-sown spring wheats under full and limited irrigation.Electronic supplementary materialThe online version of this article (10.1007/s00122-018-3111-9) contains supplementary material, which is available to authorized users.

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Inbred cultivars and advanced breeding lines have been subjected to numerous recombination cycles, have strong allelic selection for desired traits, and share important attributes for adaptation and agronomic performance. Genetic variation in elite gene pools captured using molecular markers is immediately useful for cultivar development. The primary goal of this study was to implement a genome‐wide association study for 17 agronomic traits using elite inbred lines. A panel consisting of 237 elite hard red spring wheat (Triticum aestivum L.) lines from different wheat breeding institutions in North America were evaluated in 11 locations over 2 yr. A total of 19,192 polymorphic single‐nucleotide polymorphism (SNP) markers from the Illumina 90K SNP array and markers linked to major genes controlling plant height, photoperiod sensitivity, and vernalization were used to assay the population. Linkage disequilibrium was observed to decay within a map distance of ∼3 cM in the A and B genomes and 7 cM in the D genome. A total of 226 marker‐trait associations were identified. Potentially novel associations were detected for grain yield on chromosome 2B and kernels per spike on 1B and 7D, whereas others colocalized with well‐known adaptation loci for photoperiod response, vernalization, and plant height. The frequency of positive alleles for specific marker‐trait associations differed among the programs, suggesting targets for introgression by the respective breeding programs.

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An important objective of wheat improvement programmes is to breed varieties for high yield in optimum conditions and for minimum yield reduction under stress-prone conditions such as heat and drought. Analyses of yield and its components in multiple years allow a comprehensive and comparative understanding of genetic yield potential and stress-tolerance mechanisms in the study germplasm. The present study was carried out to evaluate performance of elite varieties and landraces of spring durum wheat under different water regimes, determine the repeatability of the examined traits, and identify superior genotypes for their potential use in breeding for drought tolerance. A total of 97 accessions of spring durum wheat (T. durum Desf.) were evaluated under rain-fed and well-watered conditions in the nursery of the Centre for Agricultural Research at Martonvásár, Hungary (2011. The experiments were laid out in an unbalanced, incomplete alpha lattice block design. The trait with the lowest broad-sense repeatability was seed length (0.075), while high h 2 values were observed for heading date (0.89), thousand-grain weight (0.85) and the protein content (0.85). Grain yield showed moderate level of repeatability (0.53) across the three years. The principal component analysis revealed that grain yield (t/ha) is positively associated with the fertile tiller number, chlorophyll content values at early waxy ripeness stages and plant height. Based on biplot analysis, 'DP-133′, 'DP-017′ and 'DP-061′ proved to be the best durum cultivars in terms of yield whereas genotypes 'DP-011′, 'DP-185′, 'DP-126′ and 'DP-136′ preceded them with their good yield stability.

Spectral reflectance technology has recently opened up new possibilities to characterize traits that are resource intensive or difficult to measure directly in large germplasm collections. We have previously reported various spectral reflectance indices that have selectable genetic variations, strong associations with yield, and moderate to high efficiency of indirect selection in winter wheat (Triticum aestivum L.) adapted to the US Pacific Northwest. The objective of this study was to identify genomic regions of agronomic importance by using these indices as surrogates in genome‐wide association studies. Yield plots were evaluated for agronomic traits, canopy spectral reflectance, and canopy temperature under rainfed and irrigated conditions for 3 yr (2012–2014). Eight spectral reflectance indices were used for the association mapping study: green normalized difference vegetation index, normalized chlorophyll‐pigment ratio index, normalized difference vegetation index, normalized water index, plant nitrogen content index, photochemical reflectance index, simple ratio index, and xanthophyll epoxidation state. Marker‐based population structure explained 8 to 20% of phenotypic variation in these indices. Association mapping was conducted using 3653 single‐nucleotide polymorphism markers, two population subgroups, and reduced kinship matrices. We identified 80 quantitative trait loci for these indices across 16 chromosomes, most of which showed significant pleiotropic effect and positional proximity to grain yield, grain number per spike, thousand‐kernel weight, volume weight, plant height, and heading date. The study demonstrated the impending possibility of using canopy spectral reflectance in identifying novel and previously known loci that contribute to yield and yield stability under variable environments.

The goals of this study were to evaluate the use of spectral reflectance indices (SRIs) in indirect selection of genotypes with superior agronomic performance and to identify chromosome regions that contribute to drought tolerance and yield potential in North American spring wheat (Triticum aestivum L.). A diversity panel with 250 elite lines was evaluated for various SRIs, grain yield, heading date, plant height, and grain volume weight under irrigated and drought‐stressed field conditions for 2 yr (2012 and 2013) in Othello, WA. Analysis of variance across environments revealed that normalized chlorophyll‐pigment ratio index (NCPI), normalized difference vegetation index (NDVI), and normalized water index‐1 (NWI1) showed high genetic correlation (0.37–0.64) with grain yield, heritability, and efficiency of indirect selection. Population structure had lower effects on SRIs (≤14%) compared with the agronomic traits (8–57% on whole grain protein). Association mapping using 19,967 single nucleotide polymorphism markers revealed 42 loci on 15 chromosomes that were associated with the SRIs in two or more field trials, 10 of which colocalized with phenology measurements and plant height. Grain yield shared quantitative trait locus regions with NDVI, NCPI, and NWI1. Lines with a greater number of SRI‐favorable alleles showed higher grain yield (9–16%). Overall, this study highlights the utility of spectral reflectance technology to identify chromosome regions that contribute to yield and drought tolerance in North American spring wheat.

Grain yield and agronomic traits, key breeding goals for most crops, are under complex genetic control and subject to environmental interactions. Plant breeders require that the genetic architecture of agronomic traits be identified in locally relevant germplasm. Our goal was to conduct a genome‐wide association study to identify quantitative trait loci for eight agronomic traits in a diversity panel containing 402 Pacific Northwest winter wheat (Triticum aestivum L.) lines. Phenotypic evaluations of yield, yield components, phenology, and plant height were conducted under drought, rainfed, and irrigated conditions in 2012, 2013, and 2014. Linkage disequilibrium analysis, using 6492 single nucleotide polymorphism (SNP) markers from the 9K SNP array, determined that 70% of markers were in significant LD with other markers and formed 539 LD blocks with an average distance of 3.5 cM. Population structure analysis was conducted using 719 SNP tags that represent marker distribution. Three genetic subgroups were identified in the population, explaining 3 to 38% of the total phenotypic variation. A mixed linear model with 3653 SNP markers of known genetic position, the first two membership coefficients (Q = 2) of population structure and a compressed kinship (Kc = 192) was used in the association analysis. In this study, a total of 94 marker‐trait associations that were significant (false discovery rate < 0.05) were identified. Multiple trait associations for yield and component traits were identified on chromosomes 2B, 4B, 5A, 5B, 6A, and 7B. These findings highlight the possibility of using historical recombination in northern latitude winter wheat to identify genomic regions associated with desired agronomic traits.