The sensitivity ofPolygonum aviculareL. seeds to the dormancy-breaking effect of cycle-doses of fluctuating temperature changes as seeds lose dormancy due to storage under stratification temperatures. Sensitivity changes during seed stratification were characterized by a decrease in the number of cycles required to saturate the germination response, and by a progressive loss of the requirement for temperature fluctuations for dormancy breakage in increasing fractions of the seed population. The rate of these changes was dependent on the temperature at which seeds were stored for stratification; lower storage temperatures produced higher rates of change than higher storage temperatures. Germination curves, obtained in response to the effect of fluctuating temperature cycle-doses for seeds stratified at variable temperatures and times of storage, were brought to a common stratification thermal time (Stt) scale by accumulating thermal time units under a threshold temperature for dormancy loss to occur. Results showed that those seeds that had accumulated similarSttunits during stratification under different storage temperatures presented a similar germination response. Therefore, response-curve functions were adjusted to germination data of exhumed seeds that had accumulated similarStt, obtaining a family of germination response curves in relation toSttaccumulation during storage. Based on these results, a simulation model was constructed relating dynamic changes in the parameters that determine germination response curves in relation toSttaccumulation. The model was tested against independent data, showing a good description of the dynamics of changes in the fraction of the seed population requiring temperature fluctuation for dormancy breakage as dormancy release progressed.

Fusarium head blight (FHB) is a devastating disease in cereals around the world. Because it is quantitatively inherited and technically difficult to reproduce, breeding to increase resistance in wheat germplasm is difficult and slow. Genomic selection (GS) is a form of marker-assisted selection (MAS) that simultaneously estimates all locus, haplotype, or marker effects across the entire genome to calculate genomic estimated breeding values (GEBVs). Since its inception, there have been many studies that demonstrate the utility of GS approaches to breeding for disease resistance in crops. In this study, the Uniform Northern (NUS) and Uniform Southern (SUS) soft red winter wheat scab nurseries (a total 452 lines) were evaluated as possible training populations (TP) to predict FHB traits in breeding lines of the UK (University of Kentucky) wheat breeding program. DON was best predicted by the SUS; Fusarium damaged kernels (FDK), FHB rating, and two indices, DSK index and DK index were best predicted by NUS. The highest prediction accuracies were obtained when the NUS and SUS were combined, reaching up to 0.5 for almost all traits except FHB rating. Highest prediction accuracies were obtained with bigger TP sizes (300-400) and there were not significant effects of TP optimization method for all traits, although at small TP size, the PEVmean algorithm worked better than other methods. To select for lines with tolerance to DON accumulation, a primary breeding target for many breeders, we compared selection based on DON BLUES with selection based on DON GEBVs, DSK GEBVs, and DK GEBVs. At selection intensities (SI) of 30-40%, DSK index showed the best performance with a 4-6% increase over direct selection for DON. Our results confirm the usefulness of regional nurseries as a source of lines to predict GEBVs for local breeding programs, and shows that an index that includes DON, together with FDK and FHB rating could be an excellent choice to identify lines with low DON content and an overall improved FHB resistance.

Fusarium head blight (FHB), caused by Fusarium graminearum (Schwabe), is an economically important disease of wheat (Triticum aestivum L.). After epidemics in the USA during the 1990s, a resistance‐breeding effort was undertaken focusing initially on the transfer of Type II resistance from unadapted Chinese cultivars. The objective of this study was to determine the magnitude and heritability of resistance in populations derived from adapted parents. Three soft red winter (SRW) wheat populations of 40 families each were artificially inoculated with Fusarium graminearum under mist irrigation in 2003 and 2004 at Lexington and Princeton, KY. Traits measured included anthesis date, plant height, disease severity, Fusarium‐damaged kernels (FDK) and deoxynivalenol (DON) concentration. Broad sense heritability (BSH) estimates were generated from entry means over the four environments. Heritability of severity was approximately 0.30 in all populations; heritability of FDK ranged from 0.16 to 0.20. In 2003, a selection intensity of 20% was imposed on all populations, and the eight lowest severity families were advanced and evaluated at Lexington and Princeton in 2004. Direct selection response, averaged over both locations, ranged from 1.9 to 4.1% reduction in severity. Correlated reduction in FDK ranged from 0.4 to 6.5%; there was also a correlated increase in plant height of 1.7 to 4.1 cm after one cycle of selection. Progress in FHB resistance breeding in the absence of major QTL is likely to be constrained by low heritability and genotype × environment (G × E) interaction.

Genomic selection (GS) is being applied routinely in wheat breeding programs. For the evaluation of preliminary lines, this tool is becoming important because preliminary lines are generally evaluated in few environments with no replications due to the minimal amount of seed available to the breeder. A total of 816 breeding lines belonging to advanced or preliminary yield trials were included in the study. We designed different training populations (TP) to predict lines in preliminary yield trials (PYT) consisting of: (i) advanced lines of the breeding program; (ii) 50% of the preliminary lines set belonging to many families; (iii) only full sibs, consisting of 50% of lines of each family. Results showed that the strategy of splitting the preliminary set in half, phenotyping only half of the lines to serve as the TP showed the most consistent results for the different traits. For a subset of the population of lines, we observed accuracies ranging from 0.49–0.65 for yield, 0.59–0.61 for test weight, 0.70–0.72 for heading date, and 0.49–0.50 for height. Accuracies decreased with the other training population designs, and were inconsistent across preliminary line sets and traits. From a breeder’s perspective, a prediction accuracy of 0.65 meant, at 0.2 selection intensity, 75% of the best yielding lines based on phenotypic information were correctly selected by the GS model. Our results demonstrate that, despite the small family size, an approach that includes lines from the same family in both the TP and VP, together with half sibs and more distant lines, and only phenotyping the lines included in the TP, could be a useful, efficient design for establishing a GS scheme to predict lines entering first year yield trials.

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