Inaugural Addresses (Food Science)

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    Characterisation of "glassiness" in commercially processed french fried potatoes
    (Stellenbosch : University of Stellenbosch, 2005-03) Sadie, Louise; Witthuhn, R. C.; Dalton, A.; Manley, M.; University of Stellenbosch. Faculty of Agrisciences. Dept. of Food Science.
    The relationship between the “glassiness” defect in frozen French fries and the moisture, starch and reducing sugar content of the affected potato tuber was investigated. The effect of soil water quality, cultivar, soil depth, storage duration, specific gravity and blanching conditions during French fry production on the occurrence of “glassiness” was determined. Fourier transform near infrared (FT-NIR) spectroscopy was used to identify possible classifications of defected tubers. No significant difference occurred between the moisture (p=0.10, trial 1 and p=0.15, trial 2), starch (p=0.76, trial 1 and p=0.70, trial 2) or reducing sugar (p=0.05, trial 1 and p=0.51, trial 2) content of potato sample with and without the “glassiness” defect. Samples of the cultivar Herta (Her) showed the lowest occurrence of the defect (23%, trial 1 and 0%, trial 2), while the cultivar Columbus (Col) showed the highest occurrence (70%, trial 1 and 84%, trial 2). The soil water quality prevailing in the area of cultivation contributed to the amount of “glassiness” occurring in the samples of the cultivar Col. Col obtained from the Parys area (electrical capacity (EC) = 145 mS.m-1) showed a 21% occurrence of “glassiness”. Col obtained from the Uitvlug (EC = 57 mS.m-1) and Zandrug (EC = 25 mS.m-1) areas showed a 91% occurrence of the defect. All samples cultivated in the Parys area during trial 1 showed a significantly lower occurrence of “glassiness” (p=0.01) than samples obtained from the areas Uitvlug and Zandrug. During trial 2 all samples obtained from the Thaaibos area (EC = 82 mS.m-1) showed a lower occurrence of the defect than samples obtained from the area Witklip (EC = 178 mS.m-1) although this difference was not statistically significant (p=0.06). Soil depth, specific gravity and storage duration did not contribute to a significant difference in the occurrence of “glassiness” between samples. Modified blanching conditions of 62ºC for 25 min instead of 80ºC for 20 min during frozen French fry processing had a reducing effect on the occurrence of the defect in the cultivars Fianna (Fia) (p=0.06), Pentland Dell (Pen) (p=0.05) and Col (p<0.01). The modified blanching conditions improved the texture uniformity in the French fry strip, reducing oil absorption during frying and prevented fry strips from breaking during subsequent processing steps. FT-NIR calibration models could not be successfully developed for the prediction of the moisture, starch and reducing sugar content in a potato sample. Principal component analysis (PCA) indicated no classification between potato samples affected by the “glassiness” defect and samples without the defect. The calibration models for moisture, starch and reducing sugar content yielded a standard error of prediction (SEP) of 1.62%, 2.28% and 0.07%, respectively. The respective correlation coefficients of these calibration models were 0.46, 0.42 and 0.41. The “glassiness” defect was most prominent in the cultivar Col. The occurrence of the defect was reduced and French fry quality improved by adjusting blanching parameters to 25 min at 62ºC. FT-NIR spectroscopy is not recommended for screening of potato quality prior to processing.
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    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