ABSTRACT
ANOVA-simultaneous component analysis (ASCA) was applied to short-wave infrared spectral fingerprints of 5 malting barley varieties collected using a hyperspectral imaging system to determine the effect of germination, the influence of time and the influence of barley by means of a full factorial experimental design. ASCA indicated that there was a significant (p < 0.0001) effect of the germination status, the germination time and interaction on the spectral data for all varieties. The biochemical and physiological modification of the samples were characterised by visualisation of the longitudinal scores obtained from simultaneous component analysis for the germination time factor. This resulted in the visualisation and explanation of biochemical change over the course of barley germination as a factor of time. The relevant loadings indicated a significant change to the proteome, lipid and starch structure as driven by the uptake of water over time. The ASCA model were extrapolated to include the effect of barley variety to the already mentioned germination status and germination time factors, resulting once again in all the effects being significant (p < 0.0001). Here it was shown that all the barley varieties are significantly different from one another pre- and post-modification, based on the molecular vibrations observed in the short wave-infrared (SWIR) spectra, suggesting that the detection of biotic stress factors, such as pre-harvest germination, also differ for each variety, by indicating that the germination profile of each barley variety varies as a function of germination time. Thus, also the malting performance, germinative energy and chemical profile of each barley variety tested will vary before, during and after imbibition and germination - indicating the importance of malting commercial barley malt true to variety. These results indicate that (SWIR) spectral imaging instrumentation can possibly be used to monitor controlled germination of barley grain. Due to the shown ability of SWIR spectral imaging to detect small biochemical changes over time of barley grain during germination.
ABSTRACT
ANOVA-simultaneous component analysis (ASCA) was used to investigate the effect of roasting and wheat type on shortwave-infrared (SWIR) spectra of whole wheat and flour through assessment of statistical significance and characterisation of the contributing spectral features. The full factorial experimental design included two wheat types, three roasting temperatures and three roasting frequencies. SWIR spectral images were collected from the two roasted wheat types and their two milled samples. Three ASCA models, one for each wheat conformation (kernel, whole wheat flour, white flour) were investigated. It was evidenced that all factors and interaction in the whole wheat flour model had a significant (p ≤ 0.05) effect on spectral data. Only the factor roasting frequency was not significant in white flour model and only the interaction between roasting frequency and wheat type was not significant for the kernel model. The main variations in the loading line plots were identified and characterised by chemical structural differences that occur within the sample. The effect of roasting frequency had a more adverse effect on protein stability, moisture evaporation, water soluble carbohydrates and aromatic amino acids, compared to roasting temperature. A Rapid Visco-Analyser (RVA) was used to further investigate difference in wheat type as almost all spectral data sets differed significantly. The most prominent difference between the two wheat types was observed as differences in amylase activity and presence of lipids. ASCA applied to SWIR whole wheat and flour spectral data effectively characterised the significant effect of roasting on wheat starch and protein structures.