Inaugural Addresses (Food Science)

Permanent URI for this collection

https://scholar.sun.ac.za/handle/10019.1/541

Browse

Browsing Inaugural Addresses (Food Science) by Author "Du Toit, Gerida"

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Near infrared hyperspectral imaging and chemometrics for exploration and classification of whole wheat kernels
    (Stellenbosch : University of Stellenbosch, 2009-12) Du Toit, Gerida; Manley, Marena; Geladi, Paul; University of Stellenbosch. Faculty of Agrisciences. Dept. of Food Science.
    ENGLISH ABSTRACT: Near infrared (NIR) hyperspectral imaging together with multivariate image analysis was evaluated as a non-destructive method to distinguish between whole wheat kernels differing in hardness; and also to track the diffusion of conditioning water into whole wheat kernels of different hardness over a conditioning period of 36 hours. Wheat kernels of varying hardness were imaged using a Spectral Dimensions MatrixNIR imaging system with a wavelength range of 960-1662 nm. Principal component analysis (PCA) was applied to clean the image, which entailed removal of bad pixels (background, shading, curvature errors, dead pixels and outliers). PCA also proved effective in the identification and classification of clusters in the score plot, relating to different hardness wheat endosperm (durum, hard and soft). PC 2 differentiated soft endosperm form hard and durum endosperm; while PC 3 distinguished durum endosperm from hard and soft endosperm. The loading line plot of PC 2 indicated absorbance peaks at 1195, 1450 and 1570 nm associated with starch, moisture and protein; while the loading line plot of PC 3 indicated absorbance peaks at 1195 and 1450 nm associated with starch and moisture. Partial least squares discriminant analysis (PLS-DA) was used to determine the ability to discriminate between different hardness endosperm classes using NIR hyperspectral imaging. The model of soft versus (vs) durum endosperm obtained a classification accuracy of 100%; the model of soft vs hard endosperm 98% classification accuracy; and the model of hard vs durum endosperm model classification accuracy up to 96%. NIR hyperspectral images were acquired using the sisuChema SWIR (short wave infrared) imaging system with a wavelength range of 1000 to 2500 nm. Images of wheat conditioned with water (H2O) and deuterium oxide (D2O), respectively, were acquired at regular intervals between 0 and 36 hours. PCA proved effective in cleaning the image. The score images of PC 3 for wheat conditioned with H2O indicated an increase in intensity over conditioning time. The loading line plots of PC 3 for wheat conditioned with H2O indicated the variation in PC 3 due to bound moisture (1940 nm). Comparing the results from the score images and loading line plots, a conclusion could be made that the diffusion of conditioning water into soft wheat kernels reaches equilibrium after 18 hours, 24 hours for hard wheat and 36 hours for very hard wheat. The score images of wheat conditioned with D2O indicated an increase in intensity within either PC 3 or PC 5; intensity increases were between 0 and 6 hours with no further increase up to 36 hours conditioning. The loading line plots of PC 3 and PC 5 indicated variation in these PCs due to D2O (1954 nm). In contrast to results obtained with H2O, D2O did not diffuse into the wheat endosperm as expected. NIR hyperspectral imaging proved effective in differentiating between whole wheat kernels differing in hardness; and also in tracking the diffusion of conditioning water into whole wheat kernels