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Starch consists of a mixture of two α-glucans built mainly upon α-(1,4) linkages: amylose, an essentially linear polymer, and amylopectin, a branched polymer containing 5-6% of α-(1,6) linkages. The aim of the present work was to analyze the structural properties of native starches displaying different amylose-to-amylopectin ratios and arising from different botanical sources, using asymmetrical flow field flow fractionation (A4F) and a combination of hydrodynamic and size-exclusion chromatography (HDC-SEC) coupled with multiangle laser light scattering, online quasi-elastic light scattering, and differential refractive index techniques. The procedure, based upon dimethyl sulfoxide pretreatment and then solubilization in water, generates a representative injected sample without altering the initial degree of polymerization. The amylopectin weight-average molar masses and radii of gyration were around 1.0 × 10(8)-4.8 × 10(8) g mol(-1) and 110-267 nm, respectively. For each starch sample, the hydrodynamic radius (R(H)) distributions and the molar mass distributions obtained from the two fractionation systems coupled with light scattering techniques were analyzed. The size determination scales were extended by means of R(H) calibration curves. HDC-SEC and A4F data could be matched. However, A4F enabled a better separation of amylopectins and therefore an enhanced structural characterization of the starches. The two advantages of this experimental approach are (1) it can directly obtain distributions as a function of both molar mass and size, while taking account of sample heterogeneity, and (2) it is possible to compare the results obtained using the different techniques through the direct application of R(H) distributions.

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Variations in the quality of wheat kernels can be an important problem in the cereal industry. In particular, desiccation conditions play an essential role in both the technological characteristics of the kernel and its ability to sprout. In planta desiccation constitutes a key stage in the determinism of the functional properties of seeds. The impact of desiccation on the endosperm texture of seed is presented in this work. A simple imaging system had previously been developed to acquire multivariate images to characterize the heterogeneity of food materials. A special algorithm for the use under principal component analysis (PCA) was developed to process the acquired multivariate images. Wheat grains were collected at physiological maturity, and were subjected to two types of drying conditions that induced different kinetics of water loss. A data set containing 24 images (dimensioned 702 × 524 pixels) corresponding to the different desiccation stages of wheat kernels was acquired at different wavelengths and then analyzed. A comparison of the images of kernel sections highlighted changes in kernel texture as a function of their drying conditions. Slow drying led to a floury texture, whereas fast drying caused a glassy texture. The automated imaging system thus developed is sufficiently rapid and economical to enable the characterization in large collections of grain texture as a function of time and water content.

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