Mid-infrared spectroscopy coupled with chemometrics to identify spectral variability in Australian barley samples from different production regions

Abstract

Mid-infrared spectroscopy coupled with chemometrics was used to identify spectral differences in malt barley associated with region (e.g. rainfall, temperature and sunlight). The observed differences in the MIR spectra confirmed that different environmental conditions of the region they are grown, explain or modulate changes in the chemical composition of the grain. Principal component analysis (PCA) was performed to identify underlying patterns and correlations in the data set. Partial least squares (PLS) regression with cross-validation was applied to develop models to predict the regions using the weather variables, the MIR fingerprint region and a combination of both. The PLS model with the combined data predicted the growing location with the standard error of cross-validation (SECV) of 3.38%, an R 2 value of 0.53, a slope of 0.52 and a bias of 0.23. The exploratory approach demonstrated the usefulness of chemometrics to identify differences and similarities based on the MIR spectra. The results provided a solid foundation for hypothesising the overall degree of biochemical similarity and or difference among the samples and a quantifiable method to screen samples for further analysis.

Profiling the varietal antioxidative contents and macrochemical composition in Australian faba beans (Vicia faba L.)

“…PLS discriminant analysis (PLS‐DA) has previously been highlighted as a powerful tool for the discrimination and authentication of grains of different origins (Gordon et al, ). Hence, PLS‐DA was performed on the second derivative of the faba bean spectra.…”

Antioxidative properties and macrochemical composition of five commercial mungbean varieties in Australia

“…There was a reasonable amount of visible differences between mungbean varieties in the band of 1,670–900 cm −1 , very similar to the band of 1,600–800 cm −1 that Cozzolino et al () reported to display spectral variation between barley varieties. The spectra band on the rightmost side of the graph, between 400 and 800 cm −1 , corresponds to the fingerprint region of the spectra and is difficult to attribute to specific bonds (Gordon et al, ; Lai et al, ).…”

“…Air was used as a reference background; the background measurement was performed prior to analysis. Cross‐contamination of samples was minimised by cleaning and drying the platform with isopropyl alcohol and laboratory Kimwipes® (Kimberly Clark; Sydney, Australia) between samples (Gordon et al, ).…”

“…MIR spectra were analysed with the Unscrambler X software Version 10.5 (Camo ASA, Oslo, Norway). Based on previous work on barley seed (Gordon et al, ), the spectra were preprocessed to the second derivative using a Savitzky‐Golay algorithm at a polynomial number of 2 and a smoothing window of 41 points (Savitzky & Golay, ). Using the second derivative removes spectral variations in the baseline and slope (Savitzky & Golay, ), minimising differences due to noncompositional variables such as the pressure and contact with the reflection module.…”

Nutritional Quality and Bioactive Constituents of Six Australian Plum Varieties

“…A Bruker Alpha Fourier transform infrared spectrophotometer (Bruker Optics Gmbh, Ettlingen, Germany) fitted with a platinum diamond ATR single reflection module was used for the midinfrared (MIR) spectroscopy analysis. Cross-contamination of samples was minimized by cleaning and drying the platform with isopropyl alcohol and laboratory Kimwipes® between samples (Gordon et al, 2019). MIR spectra between 4000 and 400 cm −1 were recorded using the OPUS software version 7.5 (Bruker Optics Gmbh, Ettlingen, Germany) as the average of 24 scans at a resolution of 4 cm −1 .…”