Leaf and stripe rust are major threats to wheat production worldwide. The effective, multiple rust resistances present in the Brazilian cultivar Toropi makes it an excellent choice for a genetic study of rust resistance. Testing of DNA from different seed lots of Toropi with 2,194 polymorphic 90K iSelect single nucleotide polymorphism markers identified significant genetic divergence, with as much as 35% dissimilarity between seed lots. As a result, further work was conducted with a single plant line derived from Toropi variant Toropi-6.4. A double haploid population with 168 lines derived from the cross Toropi-6.4 × Thatcher was phenotyped over multiple years and locations in Canada, New Zealand, and Kenya, with a total of seven field trials undertaken for leaf rust and nine for stripe rust. Genotyping with the 90K iSelect array, simple sequence repeat and Kompetitive allele-specific polymerase chain reaction markers resulted in a genetic map of 3,043 cM, containing 1,208 nonredundant markers. Significant quantitative trait loci (QTL) derived from Toropi-6.4 were identified in multiple environments on chromosomes 1B (QLr.crc-1BL/QYr.crc-1BL), 3B (QLr.crc-3BS), 4B (QYr.crc-4BL), 5A (QLr.crc-5AL and QYr.crc-5AL), and 5D (QLr.crc-5DS). The QTL QLr.crc-1BL/QYr.crc-1BL colocated with the multi-rust resistance locus Lr46/Yr29, while the QTL QLr.crc-5DS located to the Lr78 locus previously found in a wheat backcross population derived from Toropi. Comparisons of QTL combinations showed QLr.crc-1BL to contribute a significantly enhanced leaf rust resistance when combined with QLr.crc-5AL or QLr.crc-5DS, more so than when QLr.crc-5AL and QLr.crc-5DS were combined. A strong additive effect was also seen when the stripe rust resistance QTL QYr.crc-1BL and QYr.crc-5AL were combined.

Some studies have investigated the potential of genomic selection (GS) on stripe rust, leaf rust, Fusarium head blight (FHB), and leaf spot in wheat, but none of them have assessed the effect of the reaction norm model that incorporated GE interactions. In addition, the prediction accuracy on common bunt has not previously been studied. Here, we investigated within-population prediction accuracies using the baseline M1 model and two reaction norm models (M2 and M3) with three random cross-validation (CV1, CV2, and CV0) schemes. Three Canadian spring wheat populations were evaluated in up to eight field environments and genotyped with 3158, 5732, and 23,795 polymorphic markers. The M3 model that incorporated GE interactions reduced residual variance by an average of 10.2% as compared with the main effect M2 model and increased prediction accuracies on average by 2–6%. In some traits, the M3 model increased prediction accuracies up to 54% as compared with the M2 model. The average prediction accuracies of the M3 model with CV1, CV2, and CV0 schemes varied from 0.02 to 0.48, from 0.25 to 0.84, and from 0.14 to 0.87, respectively. In both CV2 and CV0 schemes, stripe rust in all three populations, common bunt and leaf rust in two populations, as well as FHB severity, FHB index, and leaf spot in one population had high to very high (0.54–0.87) prediction accuracies. This is the first comprehensive genomic selection study on five major diseases in spring wheat.

Fusarium head blight (FHB) resistance is quantitatively inherited, controlled by multiple minor effect genes, and highly affected by the interaction of genotype and environment. This makes genomic selection (GS) that uses genome-wide molecular marker data to predict the genetic breeding value as a promising approach to select superior lines with better resistance. However, various factors can affect accuracies of GS and better understanding how these factors affect GS accuracies could ensure the success of applying GS to improve FHB resistance in wheat. In this study, we performed a comprehensive evaluation of factors that affect GS accuracies with a multi-parental population designed for FHB resistance. We found larger sample sizes could get better accuracies. Training population designed by CDmean based optimization algorithms significantly increased accuracies than random sampling approach, while mean of predictor error variance (PEVmean) had the poorest performance. Different genomic selection models performed similarly for accuracies. Including prior known large effect quantitative trait loci (QTL) as fixed effect into the GS model considerably improved the predictability. Multi-traits models had almost no effects, while the multi-environment model outperformed the single environment model for prediction across different environments. By comparing within and across family prediction, better accuracies were obtained with the training population more closely related to the testing population. However, achieving good accuracies for GS prediction across populations is still a challenging issue for GS application.

Field trials were conducted under natural infection and artificial inoculation from 2012 to 2014 at seven sites across the Canadian prairies to determine genetic and management effects on Fusarium head blight (FHB) in wheat production systems. A system of management, which consisted of (1) a control of no fungicide was compared with (2) the seed treatment (ST) thiamethoxam + difenoconazole + metalaxyl-M + S-isomer, (3) an in-crop foliar fungicide (tebuconazole + prothioconazole), or (4) ST + foliar fungicide, was integrated with four wheat cultivars of contrasting growth habits and levels of FHB resistance. Results indicated the cultivars expressing improved FHB resistance, Carberry (spring wheat) and Emerson (winter wheat), were superior over susceptible cultivars, Harvest (spring wheat) and CDC Falcon (winter wheat), in reducing Fusarium-damaged kernel (FDK) and deoxynivalenol (DON) levels, and displayed higher yield under high Fusarium pressure. Winter wheat displayed higher overall yield, with Emerson producing the highest and most stable yields across environments. Application of foliar fungicide, with or without the ST, increased grain yield, seed mass, and test weight; and lowered FDK and DON. Seed treatment alone increased test weight, spring plant density of both winter wheat varieties, and kernel weight in Emerson. A management strategy of foliar fungicide and (or) ST + foliar fungicide generally produced higher yields with greater stability, particularly for susceptible cultivars in high FHB environments. The results of this study reinforce that integration of FHB-resistant cultivars with appropriate cultural practices is required to reduce the risk of FHB and optimize grain yield, and is further enhanced with a winter vs. spring growth habit.