Sean X. Liu

Utilisation of corn (Zea mays) bran and corn fiber in the production of food components

The milling of corn for the production of food constituents results in a number of low-value co-products. Two of the major co-products produced by this operation are corn bran and corn fiber, which currently have low commercial value. This review focuses on current and prospective research surrounding the utilization of corn fiber and corn bran in the production of potentially higher-value food components. Corn bran and corn fiber contain potentially useful components that may be harvested through physical, chemical or enzymatic means for the production of food ingredients or additives, including corn fiber oil, corn fiber gum, cellulosic fiber gels, xylo-oligosaccharides and ferulic acid. Components of corn bran and corn fiber may also be converted to food chemicals such as vanillin and xylitol. Commercialization of processes for the isolation or production of food products from corn bran or corn fiber has been met with numerous technical challenges, therefore further research that improves the production of these components from corn bran or corn fiber is needed.

Content and Molecular Weight Distribution of Oat β-Glucan in Oatrim, Nutrim, and C-Trim Products

ABSTRACT The soluble fiber, β-glucan, in oat products is an active hypolipidemic component that is responsible for lowering plasma lipids. Quantitative analysis of β-glucan in oat hydrocolloids such as Oatrim, Nutrim, and C-Trim was performed to measure the total β-glucan content and molecular weight distribution. For the measurement of total β-glucan content, both modified flow-injection analysis (FIA) method and the standard AACC enzymatic method were employed. FIA method uses the enhanced fluorescence produced when β-glucan forms complexes with Calcofluor. Experimental results of both the modified FIA method and the standard AACC enzymatic method revealed very good coincidence with each other. This result confirms the applicability of either technique for the quantitative evaluation of β-glucan in hydrocolloids. Molecular weight (MW) distribution of β-glucan was determined by size-exclusion chromatography with postcolumn detection. Experimental results revealed that the molecular weight of β-glucan in ...

Viscoelastic properties of oat β-glucan-rich aqueous dispersions.

C-trim is a healthy food product containing soluble dietary fibre β-glucan. The dispersion of C-trim in water is a hydrocolloid biopolymer. The linear and non-linear rheological properties of dispersions of C-trim biopolymers were investigated. The linear viscoelastic behaviours for C-trim dispersions were dependent on the β-glucan that C-trim contained. The C-trim20 and C-trim30, which have about 20% and 30% β-glucan, respectively, exhibited more fluid-like behaviours. The C-trim50 and C-trim95, which contain about 50% and 95% β-glucan, respectively, showed solid viscoelastic properties. The power law model fitting, as well as spectra, for the linear dynamic frequency sweep and stress relaxation of C-trim dispersions, suggested that the C-trim dispersions were composed of physical entanglement networks instead of chemical cross ones. The non-linear steady shearing studies for C-trim dispersions indicated that all four of the C-trim dispersions exhibited shear-thinning behaviours, which could be best described by the power law model.

Detection of Corn Adulteration in Brazilian Coffee (Coffea arabica) by Tocopherol Profiling and Near-Infrared (NIR) Spectroscopy

Coffee is a high-value commodity that is a target for adulteration, leading to loss of quality and causing significant loss to consumers. Therefore, there is significant interest in developing methods for detecting coffee adulteration and improving the sensitivity and accuracy of these methods. Corn and other lower value crops are potential adulterants, along with sticks and coffee husks. Fourteen pure Brazilian roasted, ground coffee bean samples were adulterated with 1-20% of roasted, ground corn and were analyzed for their tocopherol content and profile by HPLC. They were also analyzed by near-infrared (NIR) spectroscopy. Both proposed methods of detection of corn adulteration displayed a sensitivity of around 5%, thus representing simple and fast analytical methods for detecting adulteration at likely levels of contamination. Further studies should be conducted to verify the results with a much larger sample size and additional types of adulterants.