Multiple‐line cross QTL mapping for grain yield and thousand kernel weight in triticale

Grain yield and its component trait thousand kernel weight are important traits in triticale breeding programmes. Here, we used a large mapping population of 647 doubled haploid lines derived from four families to dissect the genetic architecture underlying grain yield and thousand kernel weight by multiple‐line cross QTL mapping. We identified 3 QTL for grain yield and 13 for thousand kernel weight which cross‐validated explained 5.2% and 48.2% of the genotypic variance, respectively. Both traits showed a positive phenotypic correlation, and we found two QTL overlapping between them. Full two‐dimensional epistasis scans revealed epistatic QTL for both traits, suggesting that epistatic interactions contribute to their genetic architecture. Based on QTL identified in our results, we conclude that the potential for marker‐assisted selection is limited for grain yield but more promising for thousand kernel weight.     

Evaluation of genomic approaches for marker‐based improvement of lodging tolerance in triticale

Lodging tolerance is an important agronomic trait as it can have a severe negative impact on grain yield and quality. Here, we used a large mapping population of 647 doubled haploid triticale lines derived from four families to dissect the genetic architecture underlying lodging tolerance and to assess different approaches for a genomics‐based improvement of the trait. The plants were evaluated for lodging in two environments and genotyped with 1710 genomewide DArT markers. We observed a large genotypic variation for lodging and transgressive segregation in all families. Employing two complementary QTL mapping approaches, we identified both main effect and epistatic QTL. Using cross‐validation, we showed that the proportion of genotypic variance explained by the detected QTL is low, thus limiting the efficiency of marker‐assisted selection to improve this trait. By contrast, the cross‐validated predictive ability of genomic prediction was approximately twice as high as that of the QTL‐based selection approaches. In conclusion, our results show that lodging tolerance is a complex trait that can be improved by classical breeding but also assisted by marker‐based approaches.     

Hybrid breeding for biomass yield in winter triticale: II. Combining ability and hybrid prediction

Accurate hybrid prediction and knowledge about the relative contribution of general (GCA) and specific combining ability (SCA) are of utmost importance for efficient hybrid breeding. We therefore evaluated 91 triticale single-cross hybrids in field trials at seven environments for plant height, heading time, fresh biomass, dry matter content and dry biomass. Fresh and dry biomass showed the highest proportion (23%) of variance due to SCA. Prediction accuracies based on GCA were slightly higher than based on mid-parent values. Utilizing parental kinship information yielded the highest prediction accuracies when both parental lines have been tested in other hybrid combinations, but still moderate-to-low prediction accuracies for two untested parents. Thus, hybrid prediction for biomass traits in triticale is currently promising based on mid-parent values as emphasized by our simulation study, but can be expected to shift to GCA-based prediction with an increasing importance of GCA due to selection in hybrid breeding. Moreover, the performance of potential hybrids between newly developed lines can be predicted with moderate accuracy using genomic relationship information.     

Choice of shrinkage parameter and prediction of genomic breeding values in elite maize breeding populations

Genomic selection (GS) is a promising alternative to marker‐assisted selection particularly for quantitative traits. In this study, we examined the prediction accuracy of genomic breeding values by using ridge regression best linear unbiased prediction in combination with fivefold cross‐validation based on empirical data of a commercial maize breeding programme. The empirical data is composed of 930 testcross progenies derived from 11 segregating families evaluated at six environments for grain yield and grain moisture. Accuracy to predict genomic breeding values was affected by the choice of the shrinkage parameter λ², by unbalanced family size, by size of the training population and to a lower extent by the number of markers. Accuracy of genomic breeding values was high suggesting that the selection gain can be improved implementing GS in elite maize breeding programmes.     

Genetic relatedness and the ratio of subpopulation‐common alleles are related in genomic prediction across structured subpopulations in maize

Genomic prediction (GP), which could predict the breeding value of crop plants genotyped with molecular markers, has been carried out in multiple species. Prediction accuracy (PA) of GP depends on various factors, including genetic relatedness and genetic basis. In this study, we examined the rationale for the low PA of GP when the training and validation populations were distinct using 170 temperate inbred lines and 210 tropical and subtropical inbred lines, respectively. All inbred lines were evaluated for 17 traits and genotyped with 550K high‐density markers. The results show that: (a) the influences of heritability and marker number on PA reflected variations in phenotypic variance captured by the genetic information; (b) the low PA of GP when the training and validation populations represent structured subpopulation is related to the ratio of subpopulation‐common alleles (RSCA) and the genetic relatedness between the two subpopulations; (c) RSCA and PA increased with the increase of genetic relatedness, suggesting that these three factors were related. Our findings would provide references when performing GP, and guidance when designing breeding populations.     

Genome-wide association mapping and genomic prediction of Fusarium head blight resistance,heading stage and plant height in winter rye (Secale cereale)

Rye is a multi-purpose cereal crop grown in Central and Eastern Europe as well as in Western Canada. Fusarium head blight (FHB) is one of the diseases that have a severe negative impact on rye, but knowledge about FHB resistance at the genomic level is totally missing in rye. The objective of this study was to elucidate the genetic architecture of FHB resistance in winter rye using genome-wide association (GWA) mapping complemented by genomic prediction (GP) in comparison with marker-assisted selection (MAS). Additionally, plant height and heading stage were analysed. A panel of 465 S₁-inbred lines of winter rye was phenotyped in three environments (location–year combinations) for FHB resistance by inoculation with Fusarium culmorum and genotyped with a 15k SNP array. Significant genotypic variation and high heritabilities were found for FHB resistance, heading stage and plant height. FHB did not correlate with heading stage, but was moderately correlated with plant height (r = −.52, p < .001) caused by some susceptible short inbred lines. The GWA scan identified 15 QTL for FHB resistance that jointly explained 74% of the genotypic variance. In addition, we detected 11 QTL for heading stage and 8 QTL for plant height, explaining 26% and 14% of the genotypic variance, respectively. A genome-wide prediction approach resulted in 44% higher prediction abilities than marker-assisted selection for FHB resistance. In conclusion, genomic approaches appear promising to improve and accelerate breeding for complex traits in winter rye.     

Hybrid breeding for biomass yield in winter triticale: I. Hybrid performance,trait correlations and heterosis

Triticale (×Triticosecale Wittmack) holds great potential as a source for biomass production for industrial applications in Central Europe and hybrid breeding in particular appears promising owing to the higher vigour of hybrids compared to lines. In this study, a set of 178 winter triticale genotypes, including 91 hybrids, their 10 male and 23 female parental lines, as well as 54 varieties were evaluated for biomass yield and other agronomically relevant traits in 2 years at five locations in Germany. We observed a large variation of dry biomass yield as well as significant genotypic variances and high heritabilities for all traits. For the hybrids, a moderate correlation was observed between biomass and plant height and between biomass and grain yield. Mid‐parent heterosis of biomass yield ranged from ?13.6 to 16.5% with an average of 4.8%, and the maximum commercial heterosis was 9.1%. Taken together, our results illustrate the potential of hybrid breeding of triticale for biomass yield to diversify our portfolio of crops for biomass production.     

Genomic prediction of grain yield in commercial Finnish oat (Avena sativa) and barley (Hordeum vulgare) breeding programmes

Genomic selection has been adopted in many plant breeding programmes. In this paper, we cover some aspects of information necessary before starting genomic selection. Spring oat and barley breeding data sets from commercial breeding programmes were studied using single, multitrait and trait-assisted models for predicting grain yield. Heritabilities were higher when estimated using multitrait models compared to single-trait models. However, no corresponding increase in prediction accuracy was observed in a cross-validation scenario. On the other hand, forward prediction showed a slight, but not significant, increase in accuracy of genomic estimated breeding values for breeding cohorts when a multitrait model was applied. When a correlated trait was used in a trait-assisted model, on average the accuracies increased by 9%–14% for oat and by 11%–28% for barley compared with a single-trait model. Overall, accuracies in forward validation varied between breeding cohorts and years for grain yield. Forward prediction accuracies for multiple cohorts and multiple years’ data are reported for oat for the first time.     

Effects of photoperiod sensitivity genes Ppd‐B1 and Ppd‐D1 on spike fertility and related traits in bread wheat

Increasing grain yield is a key breeding goal in bread wheat. Several authors have suggested that a spike fertility index (SF), that is the quotient between grain number per unit spike (GNS) and spike chaff dry weight (SCDW), could be used as a yield‐related selection criterion, especially if molecular markers were available. Here, the effects of Ppd‐B1 and Ppd‐D1 genes on SFm, GNSm and SCDWm (measured at maturity) and the relationship between these variables were analysed in field experiments carried out during three crop seasons at Balcarce, Argentina, on an association mapping population of 100 bread wheat cultivars of diverse origin released in Argentina between 1927 and 2010. Results show that both Ppd‐B1 and Ppd‐D1 are associated with SFm with similar effects. Cultivars with insensitive alleles at both genes showed a mean SFm 9.2% greater than those with sensitive alleles at both genes; at each gene, difference in SFm between insensitive and sensitive alleles was ~4.5%. In turn, each gene showed a differential effect on GNSm and SCDWm, as Ppd‐B1 was more related to SCDWm, whereas Ppd‐D1 was only related to GNSm. Although more research needs to be carried out in order to ascertain the physiological pathway by which these genes affect spike fertility, this study represents a first approximation in order to elucidate the molecular and genetic basis underlying SF and related physiological traits.     

Phenotypic and genotypic analyses of diversity and breeding progress in European triticale (× Triticosecale Wittmack)

Knowledge of the extent of phenotypic variability, genetic diversity and the realized breeding progress is central for the optimum design of breeding programmes, but little information is available for triticale (× Triticosecale Wittmack). In this study, a collection of 885 diverse European triticale lines was evaluated in multilocation field trials in 2 years. We observed significant genotypic variances and high heritabilities for several agronomic and morphological traits and significant correlations among different traits including grain yield. Based on a subset of the population of 121 varieties registered in Europe between 1983 and 2014, we observed a substantial breeding progress for grain yield with a significant rate of increase of 53 kg/ha or 0.67% per year. All lines were genotyped by a genotyping‐by‐sequencing approach yielding 58 888 polymorphic markers. Our analyses revealed the absence of major population structure but a certain grouping of lines according to their origin. Taken together, our results on triticale germplasm and its breeding history provide important information for breeding programmes and future selection gain in this crop.     

Designing optimal training sets for genomic prediction using adversarial validation with probit regression

Genomic selection (GS) is a disruptive methodology that is revolutionizing animal and plant breeding. However, its practical implementation is challenging since many times there is a mismatch in the distribution of the training and testing sets. Adversarial validation is an approach popular in machine learning to detect and address the difference between the training and testing distributions. For this reason, the adversarial validation method in this research was implemented using probit regression to detect the mismatch in distributions and also to select an optimal training set. We evaluated the proposed method with 14 datasets, and the results were benchmarked regarding of using the whole reference population and simple random samples. We found that the proposed method is effective for detecting the mismatch in distributions and outperformed in prediction accuracy by 11.67% (in terms of mean square error) and by 5.35% (in terms of normalized mean square error) when the whole reference population was used as training sets. Also, in general, this outperformed some existing methods for optimal training designs in the context of GS.     

The effect of interplot competition on yield assessment in triticale trials

Summary A series of experiments was carried out to investigate the effects of interplot competition on grain yield among hexaploid triticale cultivars of widely differing heights grown in 1.5 m wide plots. Three experiments in 1982 tested four triticale cultivars, ranging in final height from 63 to 104 cm, with four wheat standards, 62 to 82 cm in height, using a design balanced for nearest neighbours. Two further experiments in 1983 with the same design included eight triticale cultivars ranging in final height from 92 to 183 cm. In four of the five experiments, plot yields of both wheat and triticale were decreased by between one and two grammes per square metre for every centimetre by which the plot was exceeded by the mean height of its two neighbours. Plots which were taller than their neighbours showed a similar increase in yield. Such systematic biases in cultivar means are not reduced by randomisation and increased replication. Hence, in breeding trials, every effort should be made to group genotypes according to their final height so that competition effects between plots are reduced. For the final evaluation of varieties differing widely in height, where an estimate of error is required for variety comparisons and varietal differences are likely to be small, guard plots should be grown on either side of each experimental plot or harvesting should be restricted to the centre of larger plots.     

Optimum allocation of test resources and relative efficiency of alternative procedures of within‐family selection in hybrid breeding

Selection within families can be conducted as family deviation (FDS) or strict within‐family selection (WFS). Our objectives were to (i) investigate two breeding schemes combining selection among families with FDS or WFS and (ii) compare the optimum allocation of test resources for these breeding schemes. We focused on selection among S₁ families and doubled haploid (DH) lines within S₁ families and used Monte Carlo simulations to determine the selection gain (Δ?), its standard deviation (SD_Δ?), and the average coefficient of coancestry among the selected DH lines (). For breeding schemes focusing only on within‐family selection, as employed in animal breeding, the maximum Δ?, its SD_Δ?, and were larger for FDS than for WFS. However, for breeding schemes combining among‐ and within‐family selection, as employed commonly in plant breeding programmes, the maximum Δ?, SD_Δ?, and were almost equal for FDS and WFS. Furthermore, the optimum allocation of test resources was similar for FDS and WFS. We conclude that FDS and WFS are equally suited for short‐ and long‐term success in breeding schemes where among‐family selection is followed by within‐family selection.     

Mitigating the impact of selective phenotyping in training populations on the prediction ability by multi-trait pedigree and genomic selection models

Training populations for pedigree and genomic prediction in plant breeding programmes are largely updated with superior genotypes from multi-environment trials, where they are tested with the goal of variety development. Such a selective phenotyping has, however, a negative impact on prediction abilities, especially when only a subset of breeding lines can be tested, as for laborious and costly to phenotype traits. This study focused, thus, on investigating the impact of selective phenotyping in the training population of an applied wheat breeding programme, and assessing the potential to mitigate this impact by pedigree and genomic multi-trait prediction models as well as bi-directionally selected training populations for several baking quality parameters. Combining both pedigree and genomic information in multi-trait prediction models with pre-existing phenotypic information for protein content and sedimentation value compensated for the observed loss in prediction ability, while entering few inferior breeding lines into the training population further mitigated the impact of selective phenotyping and even led to a slight increase of prediction ability in comparison to a randomly chosen training population.     

Relationship between grain yield and grain nitrogen concentration in winter triticale

Summary Ten hexaploid winter triticale lines were grown for two cropping periods at three locations in western Switzerland. Averaged across the six environments, the differences between lines were statistically significant (P=0.05) for grain yield, above-ground biomass, N uptake, grain N yield, nitrogen harvest index, grain N concentration and straw N concentration. There were significant line x environment interactions for all traits. Grain yield and grain N concentration were inversely related (r=–0.74^**). Diagrams in which grain yields were plotted against grain N concentration were used to identify lines with a consistently unusual combination of grain yield and grain N concentration. Despite comparable grain yields, Line 3 had a high grain N concentration, while that of Line 7 was low. Line 3 was superior to Line 7 in both N uptake and N harvest index. Averaged across environments and lines, the N harvest index was 0.73 which corresponds to N harvest indices reported for bread wheat in the same region. We considered the feasibility of developing triticale lines which would outperform the best recent ones in N uptake and partitioning. However, we doubted that this would bring about a marked increase in grain N concentration, because, in the long run, the expected genetic progress in grain yield will lead to a dilution of grain protein by grain carbohydrate increments.Abbreviations GNC grain N concentration - GNY grain N yield - GY grain yield - HI above-ground dry matter harvest index - NHI nitrogen harvest index - SNC straw N concentration - TB total above-ground biomass - TPN total plant N     

Root System Size Influences Water‐Nutrient Uptake and Nitrate Leaching Potential in Wheat

Environmental and economic considerations require the effective use of water and nutrients to elevate grain production in bread wheat (Triticum aestivum L.) with concomitant reduction in nitrate leaching to minimize contamination of underground water. We determined the effect of the root system on leaching fraction, leachate N concentration, and N, P and K uptake using bread wheat ‘Pavon 76’ and its three near‐isogenic translocation lines: Pavon 1RS.1AL, Pavon 1RS.1BL and Pavon 1RS.1DL. These genotypes were grown in sand‐tube experiments under optimum and low level of nutrients for 2 years. Root, stem and leaves, and grain N, P, and K content, and agronomic characters were measured. Leaching fraction and leachate nitrate concentration were measured at early tillering, booting and early grain filling. Significant main effects for year, nutrient level and genotype were found for the characters. Genotype × N interaction was significant only for root P content. Genotype × year interaction was significant only for plant N content, root P content and plant P content. Genotype × year × N interaction was significant only for root N uptake efficiency. Thus, genotypic means averaged across years and nutrient levels are reported. Low levels of nutrients (1330, 235 and 793 mg vs. 1915, 375 and 1268 mg N, P and K, respectively) reduced mean root biomass, plant biomass and grain yield by 27 %, 25 %, and 19 %, respectively. The translocation lines produced 31–46 % more root biomass, 11–14 % heavier grains and 6–8 % greater grain yield than Pavon 76. Leaching fraction was higher under low level of nutrient at booting and grain filling. Leaching fraction at tillering, booting, and grain filling was 67%, 42% and 25%, respectively. Leaching fraction at early tillering was lower for Pavon 1RS.1AL (39 %) and Pavon 1RS.1DL (40.5 %) than for Pavon 76 (45.3 %). Leachate nitrate concentration was lower for two translocation lines at all three stages of plant growth compared to Pavon 76. The correlation coefficient between plant N content and root biomass, between plant N content and plant biomass, and between grain yield and root biomass was positive and significant. Significant positive correlation was found between root biomass and P and K uptake. Multiple small applications of N fertilizer during early plant growth with adequate irrigation water are recommended. Wheat genotypes with superior root characteristics for efficient nutrient uptake, especially during tillering and booting, should be developed in breeding programmes to increase grain yield and to minimize the nitrate leaching.     

Heterosis and combining ability for grain yield and other agronomic traits in winter triticale

Hybrid breeding is a widely discussed alternative for triticale. Heterosis as well as general (GCA) and specific combining ability (SCA) effects were estimated for eight agronomic traits. The experiment comprised 24 F₁ hybrids, produced by a chemical hybridizing agent, together with their six female and four male parents, grown in drilled plots in two locations. In comparison with the mid‐parent values, hybrids averaged a 6.4 dt/ha (10.1%) higher grain yield, 8.4% more kernels per spike, a 6.8% higher 1000‐kernel weight, 9.7% lower falling number (FN) and 4.4% greater plant height. SCA effects for grain yield were significant and ranged from 4.5 to 6.9 dt/ha for grain yield. Together with GCA x location interactions, they explained most of the variation. For 1000‐kernel weight, GCA effects were predominant. SCA and interactions with location accounted for most of the variation in FN, whereas interactions were negligible for plant height. Correlations between mid‐parent and hybrid performance and between GCA and per se performance of parents were tight for all traits except grain yield, which allows for pre‐selection of parental lines. Although the amount of heterosis in triticale at present is closer to wheat than to rye, by selecting parents for combining ability and identifying heterotic patterns, grain yield heterosis of up to 20% appears sufficiently encouraging to embark on hybrid breeding.     

The potential of genomic‐assisted breeding to improve Fusarium head blight resistance in winter durum wheat

Durum wheat is the most important tetraploid wheat mainly used for semolina and pasta production, but is notorious for its high susceptibility to Fusarium head blight (FHB). Our objectives were to identify and characterize quantitative trait loci (QTL) in winter durum and to evaluate the potential of genomic approaches for the improvement of FHB resistance. Here, we employed an international panel of 170 winter and 14 spring durum lines, phenotyped for Fusarium culmorum resistance at five environments. Heading date, plant height and mean FHB severity showed significant genotypic variation with high heritabilities and FHB resistance was negatively correlated with both heading date and plant height. The dwarfing gene Rht‐B1 significantly affected FHB resistance and the genome‐wide association scan identified eight additional QTL affecting FHB resistance, explaining between 1% and 14% of the genotypic variation. A genome‐wide prediction approach yielded only a slightly improved predictive ability compared to marker‐assisted selection based on the four strongest QTL. In conclusion, FHB resistance in durum wheat is a highly quantitative trait and in breeding programmes may best be tackled by classical high‐throughput recurrent phenotypic selection that can be assisted by genomic prediction if marker profiles are available.     

Estimation of deoxynivalenol (DON) content by symptom rating and exoantigen content for resistance selection in wheat and triticale

Fusarium head blight (FHB) in wheat and triticale leads to contamination of the grain with the mycotoxin deoxynivalenol (DON) that is harmful to animal and man. A fast, low-cost, and reliable method for quantification of the DON content in the grain is essential for selection. We analysed 113 wheat and 55 triticale genotypes for their symptom development on spikes, Fusarium exoantigen (ExAg) and DON content in the grain after artificial inoculation with a highly aggressive isolate of F. culmorum in three (wheat) and six (triticale) location-by-year combinations. Additionally, in triticale the amount of Fusarium damaged kernels (FDK) was assessed. ExAg content was analysed by a newly developed Fusarium-specific plate-trapped antigen enzyme-linked immunosorbent assay (PTA-ELISA) and DON content by an immunoassay. A moderate disease severity resulted in an ExAg content of 0.87 optical density (OD) units in wheat and 1.02 OD in triticale. DON content ranged from 12.0 to 105.2 mg kg^–1 in wheat and from 24.2 to 74.0 mg kg^–1 in triticale. Genotypic and genotype-by-environment interaction variances were significant (P < 0.01). Coefficient of phenotypic correlation between DON content analysed by the immunoassay and ExAg content was r = 0.86 for wheat and r = 0.60 for triticale. The highest correlation between DON content and symptom rating was found by FHB rating in wheat (r = 0.77) and by FDK rating in triticale (r = 0.71). In conclusion, selection for reduced FHB symptoms should lead to a correlated selection response in low fungal biomass and low DON content in the grain.