RESUMEN
Whiskey production originated in Scotland in the 15th century and was based on malted barley. As Scotch-Irish settlers came into the Ohio river valley, they began fermenting and distilling the primary grain of North America, maize. These earlier settlers started a heritage; they created American Whiskey. The bourbon industry in Kentucky had tremendous growth in the last 20 years, and currently, distilleries have a broad increase in product innovation, new raw materials, improved sustainability, efficient processes, and product diversification. Our study presents a new lab-scale method for new-make bourbon whiskey production. It was developed to mimic distilleries' processes; therefore, results can be extrapolated and adopted by commercial distilleries. The method focused on reproducibility with consistency from batch to batch when handled by an operator or small crew in a university lab. The method consisted of a first cooking step to make a "mash", a fermentation phase of 96 h, a first distillation accomplished with a copper pot still to obtain the "low wines" and a second distillation carried out with an air still to collect the "hearts". The method produced a final distillate of 500-700 mL for further sensory analysis and tasting. This lab-scale method showed consistency between samples in the different parameters quantified and will be also used to train students in fermentation and distillation studies.
RESUMEN
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.
