Kinetic modeling of the generation of 2-and 3-methylbutanal in a heated extract of beef liver

Quantitative control of aroma generation during the Maillard reaction presents great scientific and industrial interest. Although there have been many studies conducted in simplified model systems, the results are difficult to apply to complex food systems, where the presence of other components can have a significant impact. In this work, an aqueous extract of defatted beef liver was chosen as a simplified food matrix for studying the kinetics of the Mallard reaction. Aliquots of the extract were heated under different time and temperature conditions and analyzed for sugars, amino acids, and methylbutanals, which are important Maillard-derived aroma compounds formed in cooked meat. Multiresponse kinetic modeling, based on a simplified mechanistic pathway, gave a good fit with the experimental data, but only when additional steps were introduced to take into account the interactions of glucose and glucose-derived intermediates with protein and other amino compounds. This emphasizes the significant role of the food matrix in controlling the Maillard reaction.

Final report on research project PS2010, proof of concept of automated mapping of weeds in arable fields

Many weeds occur in patches but farmers frequently spray whole fields to control the weeds in these patches. Given a geo-referenced weed map, technology exists to confine spraying to these patches. Adoption of patch spraying by arable farmers has, however, been negligible partly due to the difficulty of constructing weed maps. Building on previous DEFRA and HGCA projects, this proposal aims to develop and evaluate a machine vision system to automate the weed mapping process. The project thereby addresses the principal technical stumbling block to widespread adoption of site specific weed management (SSWM). The accuracy of weed identification by machine vision based on a single field survey may be inadequate to create herbicide application maps. We therefore propose to test the hypothesis that sufficiently accurate weed maps can be constructed by integrating information from geo-referenced images captured automatically at different times of the year during normal field activities. Accuracy of identification will also be increased by utilising a priori knowledge of weeds present in fields. To prove this concept, images will be captured from arable fields on two farms and processed offline to identify and map the weeds, focussing especially on black-grass, wild oats, barren brome, couch grass and cleavers. As advocated by Lutman et al. (2002), the approach uncouples the weed mapping and treatment processes and builds on the observation that patches of these weeds are quite stable in arable fields. There are three main aspects to the project. 1) Machine vision hardware. Hardware component parts of the system are one or more cameras connected to a single board computer (Concurrent Solutions LLC) and interfaced with an accurate Global Positioning System (GPS) supplied by Patchwork Technology. The camera(s) will take separate measurements for each of the three primary colours of visible light (red, green and blue) in each pixel. The basic proof of concept can be achieved in principle using a single camera system, but in practice systems with more than one camera may need to be installed so that larger fractions of each field can be photographed. Hardware will be reviewed regularly during the project in response to feedback from other work packages and updated as required. 2) Image capture and weed identification software. The machine vision system will be attached to toolbars of farm machinery so that images can be collected during different field operations. Images will be captured at different ground speeds, in different directions and at different crop growth stages as well as in different crop backgrounds. Having captured geo-referenced images in the field, image analysis software will be developed to identify weed species by Murray State and Reading Universities with advice from The Arable Group. A wide range of pattern recognition and in particular Bayesian Networks will be used to advance the state of the art in machine vision-based weed identification and mapping. Weed identification algorithms used by others are inadequate for this project as we intend to collect and correlate images collected at different growth stages. Plants grown for this purpose by Herbiseed will be used in the first instance. In addition, our image capture and analysis system will include plant characteristics such as leaf shape, size, vein structure, colour and textural pattern, some of which are not detectable by other machine vision systems or are omitted by their algorithms. Using such a list of features observable using our machine vision system, we will determine those that can be used to distinguish weed species of interest. 3) Weed mapping. Geo-referenced maps of weeds in arable fields (Reading University and Syngenta) will be produced with advice from The Arable Group and Patchwork Technology. Natural infestations will be mapped in the fields but we will also introduce specimen plants in pots to facilitate more rigorous system evaluation and testing. Manual weed maps of the same fields will be generated by Reading University, Syngenta and Peter Lutman so that the accuracy of automated mapping can be assessed. The principal hypothesis and concept to be tested is that by combining maps from several surveys, a weed map with acceptable accuracy for endusers can be produced. If the concept is proved and can be commercialised, systems could be retrofitted at low cost onto existing farm machinery. The outputs of the weed mapping software would then link with the precision farming options already built into many commercial sprayers, allowing their use for targeted, site-specific herbicide applications. Immediate economic benefits would, therefore, arise directly from reducing herbicide costs. SSWM will also reduce the overall pesticide load on the crop and so may reduce pesticide residues in food and drinking water, and reduce adverse impacts of pesticides on non-target species and beneficials. Farmers may even choose to leave unsprayed some non-injurious, environmentally-beneficial, low density weed infestations. These benefits fit very well with the anticipated legislation emerging in the new EU Thematic Strategy for Pesticides which will encourage more targeted use of pesticides and greater uptake of Integrated Crop (Pest) Management approaches, and also with the requirements of the Water Framework Directive to reduce levels of pesticides in water bodies. The greater precision of weed management offered by SSWM is therefore a key element in preparing arable farming systems for the future, where policy makers and consumers want to minimise pesticide use and the carbon footprint of farming while maintaining food production and security. The mapping technology could also be used on organic farms to identify areas of fields needing mechanical weed control thereby reducing both carbon footprints and also damage to crops by, for example, spring tines. Objective i. To develop a prototype machine vision system for automated image capture during agricultural field operations; ii. To prove the concept that images captured by the machine vision system over a series of field operations can be processed to identify and geo-reference specific weeds in the field; iii. To generate weed maps from the geo-referenced, weed plants/patches identified in objective (ii).

Carbon balance of UK peatlands: current state of knowledge and future research challenges

The retention of peatland carbon (C) and the ability to continue to draw down and store C from the atmosphere is not only important for the UK terrestrial carbon inventory, but also for a range of ecosystem services, the landscape value and the ecology and hydrology of ~15% of the land area of the UK. Here we review the current state of knowledge on the C balance of UK peatlands using several studies which highlight not only the importance of making good flux measurements, but also the spatial and temporal variability of different flux terms that characterise a landscape affected by a range of natural and anthropogenic processes and threats. Our data emphasise the importance of measuring (or accurately estimating) all components of the peatland C budget. We highlight the role of the aquatic pathway and suggest that fluxes are higher than previously thought. We also compare the contemporary C balance of several UK peatlands with historical rates of C accumulation measured using peat cores, thus providing a long-term context for present-day measurements and their natural year-on-year variability. Contemporary measurements from 2 sites suggest that current accumulation rates (–56 to –72 g C m–2 yr–1) are at the lower end of those seen over the last 150 yr in peat cores (–35 to –209 g C m–2 yr–1). Finally, we highlight significant current gaps in knowledge and identify where levels of uncertainty are high, as well as emphasise the research challenges that need to be addressed if we are to improve the measurement and prediction of change in the peatland C balance over future decades.

Prediction of moisture, calorific value, ash and carbon content of two dedicated bioenergy crops using near-infrared spectroscopy

The potential of near infrared spectroscopy in conjunction with partial least squares regression to predict Miscanthus xgiganteus and short rotation coppice willow quality indices was examined. Moisture, calorific value, ash and carbon content were predicted with a root mean square error of cross validation of 0.90% (R2 = 0.99), 0.13 MJ/kg (R2 = 0.99), 0.42% (R2 = 0.58), and 0.57% (R2 = 0.88), respectively. The moisture and calorific value prediction models had excellent accuracy while the carbon and ash models were fair and poor, respectively. The results indicate that near infrared spectroscopy has the potential to predict quality indices of dedicated energy crops, however the models must be further validated on a wider range of samples prior to implementation. The utilization of such models would assist in the optimal use of the feedstock based on its biomass properties.

Hyper-parallel tempering Monte Carlo simulations of Ar adsorption in new models of microporous non-graphitizing activated carbon: effect of microporosity

The adsorption of gases on microporous carbons is still poorly understood, partly because the structure of these carbons is not well known. Here, a model of microporous carbons based on fullerene- like fragments is used as the basis for a theoretical study of Ar adsorption on carbon. First, a simulation box was constructed, containing a plausible arrangement of carbon fragments. Next, using a new Monte Carlo simulation algorithm, two types of carbon fragments were gradually placed into the initial structure to increase its microporosity. Thirty six different microporous carbon structures were generated in this way. Using the method proposed recently by Bhattacharya and Gubbins ( BG), the micropore size distributions of the obtained carbon models and the average micropore diameters were calculated. For ten chosen structures, Ar adsorption isotherms ( 87 K) were simulated via the hyper- parallel tempering Monte Carlo simulation method. The isotherms obtained in this way were described by widely applied methods of microporous carbon characterisation, i. e. Nguyen and Do, Horvath - Kawazoe, high- resolution alpha(a)s plots, adsorption potential distributions and the Dubinin - Astakhov ( DA) equation. From simulated isotherms described by the DA equation, the average micropore diameters were calculated using empirical relationships proposed by different authors and they were compared with those from the BG method.

Preventing carbon contamination of optical devices for X-rays: the effect of oxygen on photon-induced dissociation of CO on platinum

Platinum is one of the most common coatings used to optimize mirror reflectivity in soft X-ray beamlines. Normal operation results in optics contamination by carbon-based molecules present in the residual vacuum of the beamlines. The reflectivity reduction induced by a carbon layer at the mirror surface is a major problem in synchrotron radiation sources. A time-dependent photoelectron spectroscopy study of the chemical reactions which take place at the Pt(111) surface under operating conditions is presented. It is shown that the carbon contamination layer growth can be stopped and reversed by low partial pressures of oxygen for optics operated in intense photon beams at liquidnitrogen temperature. For mirrors operated at room temperature the carbon contamination observed for equivalent partial pressures of CO is reduced and the effects of oxygen are observed on a long time scale.

The economics of enhanced landfill mining: private and societal performance drivers

This paper addresses the economics of Enhanced Landfill Mining (ELFM) both from a private point of view as well as from a society perspective. The private potential is assessed using a case study for which an investment model is developed to identify the impact of a broad range of parameters on the profitability of ELFM. We found that especially variations in Waste-to-Energy (WtE efficiency, electricity price, CO2-price, WtE investment and operational costs) and ELFM support explain the variation in economic profitability measured by the Internal Rate of Return. To overcome site-specific parameters we also evaluated the regional ELFM potential for the densely populated and industrial region of Flanders (north of Belgium). The total number of potential ELFM sites was estimated using a 5-step procedure and a simulation tool was developed to trade-off private costs and benefits. The analysis shows that there is a substantial economic potential for ELFM projects on the wider regional level. Furthermore, this paper also reviews the costs and benefits from a broader perspective. The carbon footprint of the case study was mapped in order to assess the project’s net impact in terms of greenhouse gas emissions. Also the impacts of nature restoration, soil remediation, resource scarcity and reduced import dependence were valued so that they can be used in future social cost-benefit analysis. Given the complex trade-off between economic, social and environmental issues of ELFM projects, we conclude that further refinement of the methodological framework and the development of the integrated decision tools supporting private and public actors, are necessary.

Using proxies to calculate the carbon impact of investment into electricity network assets

Replacement and upgrading of assets in the electricity network requires financial investment for the distribution and transmission utilities. The replacement and upgrading of network assets also represents an emissions impact due to the carbon embodied in the materials used to manufacture network assets. This paper uses investment and asset data for the GB system for 2015-2023 to assess the suitability of using a proxy with peak demand data and network investment data to calculate the carbon impacts of network investments. The proxies are calculated on a regional basis and applied to calculate the embodied carbon associated with current network assets by DNO region. The proxies are also applied to peak demand data across the 2015-2023 period to estimate the expected levels of embodied carbon that will be associated with network investment during this period. The suitability of these proxies in different contexts are then discussed, along with initial scenario analysis to calculate the impact of avoiding or deferring network investments through distributed generation projects. The proxies were found to be effective in estimating the total embodied carbon of electricity system investment in order to compare investment strategies in different regions of the GB network.

Exploring methods to evaluate the carbon impact of network investment deferral

Replacement, expansion and upgrading of assets in the electricity network represents financial investment for the distribution utilities. Network Investment Deferral (NID) is a well discussed benefit of wider adoption of Distributed Generation (DG). There have been many attempts to quantify and evaluate the financial benefit for the distribution utilities. While the carbon benefits of NID are commonly mentioned, there is little attempt to quantify these impacts. This paper explores the quantitative methods previously used to evaluate financial benefits in order to discuss the carbon impacts. These carbon impacts are important for companies owning DG equipment for internal reporting and emissions reductions ambitions. Currently, a GB wide approach is taken as a means for discussing more regional and local methods to be used in future work. By investigating these principles, the paper offers a novel approach to quantifying carbon emissions from various DG technologies.

Intake, water consumption, ruminal fermentation, and stress response of beef heifers fed after different lengths of delays in the daily feed delivery time

Four rumen-fistulated Holstein heifers (134 +/- 1 kg initial BW) were used in a 4 x 4 Latin square design to determine the effects of delaying daily feed delivery time on intake, ruminal fermentation, behavior, and stress response. Each 3-wk experimental period was preceded by 1 wk in which all animals were fed at 0800 h. Feed bunks were cleaned at 0745 h and feed offered at 0800 h (T0, no delay), 0900 (T1), 1000 (T2), and 1100 (T3) from d1 to 21 with measurements taken during wk 1 and 3. Heifers were able to see each other at all times. Concentrate and barley straw were offered in separate compartments of the feed bunks, once daily and for ad libitum intake. Ruminal pH and saliva cortisol concentrations were measured at 0, 4, 8, and 12 h postfeeding on d 3 and 17 of each experimental period. Fecal glucocorticoid metabolites were measured on d 17. Increasing length of delay in daily feed delivery time resulted in a quadratic response in concentrate DMI (low in T1 and T2; P = 0.002), whereas straw DMI was greatest in T1 and T3 (cubic P = 0.03). Treatments affected the distribution of DMI within the day with a linear decrease observed between 0800 and 1200 h but a linear increase during nighttimes (2000 to 0800 h), whereas T1 and T2 had reduced DMI between 1200 and 1600 h (quadratic P = 0.04). Water consumption (L/d) was not affected but decreased linearly when expressed as liters per kilogram of DMI (P = 0.01). Meal length was greatest and eating rate slowest in T1 and T2 (quadratic P <= 0.001). Size of the first meal after feed delivery was reduced in T1 on d 1 (cubic P = 0.05) and decreased linearly on d 2 (P = 0.01) after change. Concentrate eating and drinking time (shortest in T1) and straw eating time (longest in T1) followed a cubic trend (P = 0.02). Time spent lying down was shortest and ruminating in standing position longest in T1 and T2. Delay of feeding time resulted in greater daily maximum salivary cortisol concentration (quadratic P = 0.04), which was greatest at 0 h in T1 and at 12 h after feeding in T2 (P < 0.05). Daily mean fecal glucocorticoid metabolites were greatest in T1 and T3 (cubic P = 0.04). Ruminal pH showed a treatment effect at wk 1 because of increased values in T1 and T3 (cubic P = 0.01). Delaying feed delivery time was not detrimental for rumen function because a stress response was triggered, which led to reduced concentrate intake, eating rate, and size of first meal, and increased straw intake. Increased salivary cortisol suggests that animal welfare is compromised.

Historical carbon budget of the brazilian ethanol program

This work models the carbon neutralization capacity of Brazil`s ethanol program since 1975. In addition to biofuel, we also assessed the mitigation potential of other energy products, such as, bioelectricity, and CO(2) emissions captured during fermentation of sugar cane`s juice. Finally, we projected the neutralization capacity of sugar cane`s bio-energy system over the next 32 years. The balance between several carbon stocks and flows was considered in the model, including the effects of land-use change. Our results show that the neutralization of the carbon released due to land-use change was attained only in 1992, and the maximum mitigation potential of the sugar cane sector was 128 tonnes Of CO(2) per ha in 2006. An ideal reconstitution of the deployment of the sugar cane sector, including the full exploitation of bio-electricity`s potential, plus the capture Of CO(2) released during fermentation, shows that the neutralization of land-use change emissions would have been achieved in 1988, and its mitigation potential would have been 390 tCO(2)/ha. Finally, forecasts of the sector up to 2039 shows that the mitigation potential in 2039 corresponds to 836 tCO(2)/ha, which corresponds to 5.51 kg Of CO(2) per liter of ethanol produced, or 55% above the negative emission level. (C) 2009 Elsevier Ltd. All rights reserved.

THE CARBON EMISSIONS OF THE BOSTON RED SOX

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The Carbon Emissions of the Boston Red Sox

The Boston Red Sox emit a great deal of carbon throughout the regular baseball season because of flights to the home fields of their opponents. Knowing that air travel is one of the biggest transportation-based contributors to global climate change, the Boston Red Sox (and all major league teams) should be encouraged to offset their carbon emissions from regular season travel. Using ArcGIS to map the flight paths along great circle routes, the distance of flights to opponents’ cities was calculated to total the number of miles traveled in the 2008 season. The price of offsetting this carbon was estimated using the calculators of carbon offset retailers, such as Native Energy, a Vermont-based retailer. This project provides the potential costs of offsetting the carbon emitted from Red Sox air travel. To take the lead in the future of the Northeast, the Red Sox should begin to consider their contribution to climate change.

Characterization of Escherichia coli isolated from carcasses of beef cattle during their processing at an abattoir in Brazil

Beef carcass sponge samples collected between March 2003 and August 2005 at an abattoir in Brazil were surveyed for the presence of Shiga toxin-producing Escherichia coli (STEC). Only one carcass among the 80 tested showed a STEC, stx2-encoding gene by PCR amplification. The frequency of carcass contamination by E. coli during processing was tested at three situations, respectively: preevisceration, postevisceration and postprocessing, during the rain and dry seasons. The prevalence of E. coli at the three points was of 30.0%, 70.0%, 27.5% in the rain season and of 22.5%, 55.0%, 17.5% during the dry season, respectively. The E. coli isolates exhibited a high level (45.0%) of multidrug resistance to two or more antimicrobial agents. (c) 2006 Elsevier B.V. All rights reserved.