Effects of nitrogen and sulfur fertilization on free amino acids, sugars, and acrylamide-forming potential in potato

Nitrogen (N) fertilizer is used routinely in potato (Solanum tuberosum) cultivation to maximize yield. However, it also affects sugar and free amino acid concentrations in potato tubers, and this has potential implications for food quality and safety because free amino acids and reducing sugars participate in the Maillard reaction during high-temperature cooking and processing. This results in the formation of color, aroma, and flavor compounds, but also some undesirable contaminants, including acrylamide, which forms when the amino acid that participates in the final stages of the reaction is asparagine. Another mineral, sulfur (S), also has profound effects on tuber composition. In this study, 13 varieties of potato were grown in a field trial in 2010 and treated with different combinations of N and S. Potatoes were analyzed immediately after harvest to show the effect of N and S fertilization on concentrations of free asparagine, other free amino acids, sugars, and acrylamide-forming potential. The study showed that N application can affect acrylamide-forming potential in potatoes but that the effect is type- (French fry, chipping, and boiling) and variety-dependent, with most varieties showing an increase in acrylamide formation in response to increased N but two showing a decrease. S application reduced glucose concentrations and mitigated the effect of high N application on the acrylamide-forming potential of some of the French fry-type potatoes.

A general-method for tracking analysis and its application to meteorological data

Recent interest in the validation of general circulation models (GCMs) has been devoted to objective methods. A small number of authors have used the direct synoptic identification of phenomena together with a statistical analysis to perform the objective comparison between various datasets. This paper describes a general method for performing the synoptic identification of phenomena that can be used for an objective analysis of atmospheric, or oceanographic, datasets obtained from numerical models and remote sensing. Methods usually associated with image processing have been used to segment the scene and to identify suitable feature points to represent the phenomena of interest. This is performed for each time level. A technique from dynamic scene analysis is then used to link the feature points to form trajectories. The method is fully automatic and should be applicable to a wide range of geophysical fields. An example will be shown of results obtained from this method using data obtained from a run of the Universities Global Atmospheric Modelling Project GCM.

Storm prediction research and its application to the oil/gas industry

The accurate prediction of storms is vital to the oil and gas sector for the management of their operations. An overview of research exploring the prediction of storms by ensemble prediction systems is presented and its application to the oil and gas sector is discussed. The analysis method used requires larger amounts of data storage and computer processing time than other more conventional analysis methods. To overcome these difficulties eScience techniques have been utilised. These techniques potentially have applications to the oil and gas sector to help incorporate environmental data into their information systems

British Nutrition Foundation annual lecture: chips with everything? Nutritional genomics and the application of diet in disease prevention

The development of high throughput techniques ('chip' technology) for measurement of gene expression and gene polymorphisms (genomics), and techniques for measuring global protein expression (proteomics) and metabolite profile (metabolomics) are revolutionising life science research, including research in human nutrition. In particular, the ability to undertake large-scale genotyping and to identify gene polymorphisms that determine risk of chronic disease (candidate genes) could enable definition of an individual's risk at an early age. However, the search for candidate genes has proven to be more complex, and their identification more elusive, than previously thought. This is largely due to the fact that much of the variability in risk results from interactions between the genome and environmental exposures. Whilst the former is now very well defined via the Human Genome Project, the latter (e.g. diet, toxins, physical activity) are poorly characterised, resulting in inability to account for their confounding effects in most large-scale candidate gene studies. The polygenic nature of most chronic diseases offers further complexity, requiring very large studies to disentangle relatively weak impacts of large numbers of potential 'risk' genes. The efficacy of diet as a preventative strategy could also be considerably increased by better information concerning gene polymorphisms that determine variability in responsiveness to specific diet and nutrient changes. Much of the limited available data are based on retrospective genotyping using stored samples from previously conducted intervention trials. Prospective studies are now needed to provide data that can be used as the basis for provision of individualised dietary advice and development of food products that optimise disease prevention. Application of the new technologies in nutrition research offers considerable potential for development of new knowledge and could greatly advance the role of diet as a preventative disease strategy in the 21st century. Given the potential economic and social benefits offered, funding for research in this area needs greater recognition, and a stronger strategic focus, than is presently the case. Application of genomics in human health offers considerable ethical and societal as well as scientific challenges. Economic determinants of health care provision are more likely to resolve such issues than scientific developments or altruistic concerns for human health.

The modelling of electrical current NDT methods and its application to weld testing

Discussion of the numerical modeling of NDT methods based on the potential drop and the disruption of power lines to describe the nature, importance and application of modeling. La 1ère partie est consacrée aux applications aux contrôles par courants de Foucault. The first part is devoted to applications for inspection by eddy currents.

The modelling of electrical current NDT methods and its application to weld testing

Control by voltage drop DC. Contrôle par chute de potentiel de courant alternatif. Control by voltage drop AC.

Measuring productivity growth when technological change is biased - a new index and an application to UK agriculture

Productivity growth is conventionally measured by indices representing discreet approximations of the Divisia TFP index under the assumption that technological change is Hicks-neutral. When this assumption is violated, these indices are no longer meaningful because they conflate the effects of factor accumulation and technological change. We propose a way of adjusting the conventional TFP index that solves this problem. The method adopts a latent variable approach to the measurement of technical change biases that provides a simple means of correcting product and factor shares in the standard Tornqvist-Theil TFP index. An application to UK agriculture over the period 1953-2000 demonstrates that technical progress is strongly biased. The implications of that bias for productivity measurement are shown to be very large, with the conventional TFP index severely underestimating productivity growth. The result is explained primarily by the fact that technological change has favoured the rapidly accumulating factors against labour, the factor leaving the sector. (C) 2004 Elsevier B.V. All rights reserved.

Splanchnic metabolism of nutrients and hormones in steers fed alfalfa under conditions of increased absorption of ammonia and L-arginine supply across the portal-drained viscera

Effects of increased ammonia and/or arginine absorption on net splanchnic (portal-drained viscera [PDV] plus liver) metabolism of nonnitrogenous nutrients and hormones in cattle were examined. Six Hereford x Angus steers (501 +/- 1 kg BW) prepared with vascular catheters for measurements of net flux across the splanchnic bed were fed a 75% alfalfa:25% (as-fed basis) corn and soybean meal diet (0.523 MJ of ME/[kg BW(0.75.)d]) every 2 h without (27.0 g of N/kg of DM) and. with 20 g of urea/kg of DM (35.7 g of N/kg of DM) in a split-plot design. Net flux measurements were made immediately before and after a 72-h mesenteric vein infusion Of L-arginine (15 mmol/h). There were no treatment effects on PDV or hepatic 02 consumption. Dietary urea had no effect on splanchnic metabolism of glucose or L-lactate, but arginine infusion decreased net hepatic removal Of L-lactate when urea was fed (P < 0.01). Net PDV appearance of n-butyrate was increased by arginine infusion (P < 0.07), and both dietary urea (P < 0.09) and arginine infusion (P < 0.05) increased net hepatic removal of n-butyrate. Dietary urea also increased total splanchnic acetate output (P < 0.06), tended to increase arterial glucagon concentration (P < 0.11), and decreased arterial ST concentration (P < 0.03). Arginine infusion increased arterial concentration (P < 0.07) and net PDV release (P < 0.10) and tended to increase hepatic removal (P < 0.11) of insulin, as well as arterial concentration (P < 0.01) and total splanchnic output (P < 0.01) of glucagon. Despite changes in splanchnic N metabolism, increased ammonia and arginine absorption had little measurable effect on splanchnic metabolism of glucose and other nonnitrogenous components of splanchnic energy metabolism.

Parametric accelerated failure time models with random effects and an application to kidney transplant survival

Accelerated failure time models with a shared random component are described, and are used to evaluate the effect of explanatory factors and different transplant centres on survival times following kidney transplantation. Different combinations of the distribution of the random effects and baseline hazard function are considered and the fit of such models to the transplant data is critically assessed. A mixture model that combines short- and long-term components of a hazard function is then developed, which provides a more flexible model for the hazard function. The model can incorporate different explanatory variables and random effects in each component. The model is straightforward to fit using standard statistical software, and is shown to be a good fit to the transplant data. Copyright (C) 2004 John Wiley Sons, Ltd.

Synthesis of multicarboxylic acid appended imidazolium ionic liquids and their application in palladium-catalyzed selective oxidation of styrene

A series of multicarboxylic acid appended imidazolium ionic liquids ( McaILs) with chloride [ Cl](-) or bromide [ Br](-) as anions have been synthesized and characterized. Deprotonation of these ionic acids gives the corresponding zwitterions. Re-protonation of the zwitterions with strong Bronsted acids gives a series of new ionic acid-adducts, many of which remained as room-temperature ionic liquids. A new catalytic system, McaIL/PdCl2 for the selective catalytic oxidation of styrene to acetophenone with hydrogen peroxide as an oxidant has been attempted. In the presence of McaILs, it is found that the quantity of palladium chloride PdCl2 used can be greatly reduced while the activity ( TOF) and selectivity towards acetophenone are enhanced sharply. It is also shown that the catalytic properties of this system could be finely tuned through the molecular design of the McaILs. The best TOF value obtained so far is 146 h(-1) with 100% conversion of styrene at 93% selectivity to acetophenone. In addition, the catalytic activity has been maintained for at least ten catalytic cycles.