Abstract

It is surprising that not even today do germination data seem fully integrated with malting data in barley quality evaluation. In order to implement such an integration, pattern recognition multivariate data analysis (chemometrics) is essential. Inspired by the results from chemometric analyses of whole germination curves we tested a two-dimensional classification plot of barley samples based on separate estimates for “vigour” (g%1) germination energy (GE) as abscissa with limits at 70% and 30% and “viability” (g%3) as ordinate with limits at 98% and 92%. The seven barley classes obtained visualise the quality differences in a consistent and instructive way clearly differencing and ordering malting barleys with falling extract% and increasing wort β-glucan (mg/l) according to a subsequent validation analysis. “Vigour” g%1 could surprisingly be predicted by Partial Least Squares Regression (PLSR) correlation by Near Infrared Transmission (NIT) and by a separate set of ten physical-chemical analyses. Samples with “viability” g%3 lower than 92% were outliers. It was concluded that germination speed is connected with the structure of the seed, which regulates the availability of substrate for germ growth near connected to the speed of malt modification. It is suggested that a NIT PLSR prediction model for “vigour” can be used directly “on-line” for quality control in the grain industry and by plant breeders. A fast germinative classification plot can be established with NIT spectroscopy for “vigour” and the Tetrazolium germ-staining test for “viability” within two hours.    

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call