Functionality of lipase and emulsifiers in low-fat cakes with inulin

The functional effects of lipase (0.003 and 0.006 g/100 g of flour) and emulsifier (0.5 and 1 g/100 g of flour) on fat-replaced (0%, 50% and 70%) batters and cakes with inulin (0, 7.5 and 10 g/100 g/of flour, respectively) were studied. Emulsifier addition significantly lowered the relative density of the batter. Emulsifier incorporation increased the viscoelastic properties of the batter. In contrast, lipase incorporation decreased the degree of system structuring. The evolution of the dynamic moduli and complex viscosity with rising temperatures were studied. Batters with 1 g/100 g emulsifier displayed a significantly lower complex viscosity during heating, resulting in collapsed cakes. Differential scanning calorimetry results revealed that the thermal setting in the control cakes occurred at higher temperatures, and accordingly, greater cake expansion was observed. Cakes with 0.003 g/100 g lipase or 0.5 g/100 g emulsifier displayed volume and crumb cell structure that were similar to those of control cakes. Higher concentrations of both improvers gave rise to cakes with lower volume, higher hardness and lower springiness. During storage time, cakes with lipase displayed lower hardness. Both improvers, at low concentrations, could improve certain physical characteristics, such as crumb structure, of fat-replaced cakes with inulin.

Improving the TanDEM-X Digital Elevation Model for flood modelling using flood extents from Synthetic Aperture Radar images

The topography of many floodplains in the developed world has now been surveyed with high resolution sensors such as airborne LiDAR (Light Detection and Ranging), giving accurate Digital Elevation Models (DEMs) that facilitate accurate flood inundation modelling. This is not always the case for remote rivers in developing countries. However, the accuracy of DEMs produced for modelling studies on such rivers should be enhanced in the near future by the high resolution TanDEM-X WorldDEM. In a parallel development, increasing use is now being made of flood extents derived from high resolution Synthetic Aperture Radar (SAR) images for calibrating, validating and assimilating observations into flood inundation models in order to improve these. This paper discusses an additional use of SAR flood extents, namely to improve the accuracy of the TanDEM-X DEM in the floodplain covered by the flood extents, thereby permanently improving this DEM for future flood modelling and other studies. The method is based on the fact that for larger rivers the water elevation generally changes only slowly along a reach, so that the boundary of the flood extent (the waterline) can be regarded locally as a quasi-contour. As a result, heights of adjacent pixels along a small section of waterline can be regarded as samples with a common population mean. The height of the central pixel in the section can be replaced with the average of these heights, leading to a more accurate estimate. While this will result in a reduction in the height errors along a waterline, the waterline is a linear feature in a two-dimensional space. However, improvements to the DEM heights between adjacent pairs of waterlines can also be made, because DEM heights enclosed by the higher waterline of a pair must be at least no higher than the corrected heights along the higher waterline, whereas DEM heights not enclosed by the lower waterline must in general be no lower than the corrected heights along the lower waterline. In addition, DEM heights between the higher and lower waterlines can also be assigned smaller errors because of the reduced errors on the corrected waterline heights. The method was tested on a section of the TanDEM-X Intermediate DEM (IDEM) covering an 11km reach of the Warwickshire Avon, England. Flood extents from four COSMO-SKyMed images were available at various stages of a flood in November 2012, and a LiDAR DEM was available for validation. In the area covered by the flood extents, the original IDEM heights had a mean difference from the corresponding LiDAR heights of 0.5 m with a standard deviation of 2.0 m, while the corrected heights had a mean difference of 0.3 m with standard deviation 1.2 m. These figures show that significant reductions in IDEM height bias and error can be made using the method, with the corrected error being only 60% of the original. Even if only a single SAR image obtained near the peak of the flood was used, the corrected error was only 66% of the original. The method should also be capable of improving the final TanDEM-X DEM and other DEMs, and may also be of use with data from the SWOT (Surface Water and Ocean Topography) satellite.

Improving power and accuracy of genome-wide association studies via a multi-locus mixed linear model methodology

Genome-wide association studies (GWAS) have been widely used in genetic dissection of complex traits. However, common methods are all based on a fixed-SNP-effect mixed linear model (MLM) and single marker analysis, such as efficient mixed model analysis (EMMA). These methods require Bonferroni correction for multiple tests, which often is too conservative when the number of markers is extremely large. To address this concern, we proposed a random-SNP-effect MLM (RMLM) and a multi-locus RMLM (MRMLM) for GWAS. The RMLM simply treats the SNP-effect as random, but it allows a modified Bonferroni correction to be used to calculate the threshold p value for significance tests. The MRMLM is a multi-locus model including markers selected from the RMLM method with a less stringent selection criterion. Due to the multi-locus nature, no multiple test correction is needed. Simulation studies show that the MRMLM is more powerful in QTN detection and more accurate in QTN effect estimation than the RMLM, which in turn is more powerful and accurate than the EMMA. To demonstrate the new methods, we analyzed six flowering time related traits in Arabidopsis thaliana and detected more genes than previous reported using the EMMA. Therefore, the MRMLM provides an alternative for multi-locus GWAS.

Astringency reduction in red wine by whey proteins

Whey is a by-product of cheese manufacturing and therefore investigating new applications of whey proteins will contribute towards the valorisation of whey and hence waste reduction. This study shows for the first time a detailed comparison of the effectiveness of gelatin and β-lactoglobulin (β-LG) as fining agents. Gelatin was more reactive than whey proteins to tannic acid as shown by both the astringency method (with ovalbumin as a precipitant) and the tannins determination method (with methylcellulose as a precipitant). The two proteins showed similar selectivity for polyphenols but β-LG did not remove as much catechin. The fining agent was removed completely or to a trace level after centrifugation followed by filtration which minimises its potential allergenicity. In addition, improved understanding of protein–tannin interactions was obtained by fluorescence, size measurement and isothermal titration calorimetry (ITC). Overall this study demonstrates that whey proteins have the potential of reducing astringency in red wine and can find a place in enology.