Effect of milk fat concentration and gel firmness on syneresis during curd stirring in cheese-making

An experiment was undertaken to investigate the effect of milk fat level (0%, 2.5% and 5.0% w/w) and gel firmness level at cutting (5, 35 and 65 Pa) on indices of syneresis, while curd was undergoing stirring. The curd moisture content, yield of whey, fat in whey and casein fines in whey were measured at fixed intervals between 5 and 75 min after cutting the gel. The casein level in milk and clotting conditions was kept constant in all trials. The trials were carried out using recombined whole milk in an 11 L cheese vat. The fat level in milk had a large negative effect on the yield of whey. A clear effect of gel firmness on casein fines was observed. The best overall prediction, in terms of coefficient of determination, was for curd moisture content using milk fat concentration, time after gel cutting and set-to-cut time (R2 = 0.95).

Enhanced second order non-linear optical properties of silica sol-gel thin films through photo-induced poling

Sol-gel derived inorganic materials are of interest as hosts for non-linear optically active guest molecules and they offer particular advantages in the field of non-linear optics. Orientationally ordered glasses have been prepared using a sol-gel system based on tetramethoxysilane, methyltrimethoxysilane and a non-linear optical chromophore Disperse Red 1. The novel technique of photo-induced poling was used to generate enhanced levels of polar order. The level of enhancement is strongly dependent on the extent of gelation and an optimum preparation time of ∼100 h led to an enhancement factor of ∼5. Films prepared in this manner exhibited a high stability of the polar order.

Calibration and bias correction of climate projections for crop modelling: an idealised case study over Europe

Producing projections of future crop yields requires careful thought about the appropriate use of atmosphere-ocean global climate model (AOGCM) simulations. Here we describe and demonstrate multiple methods for ‘calibrating’ climate projections using an ensemble of AOGCM simulations in a ‘perfect sibling’ framework. Crucially, this type of analysis assesses the ability of each calibration methodology to produce reliable estimates of future climate, which is not possible just using historical observations. This type of approach could be more widely adopted for assessing calibration methodologies for crop modelling. The calibration methods assessed include the commonly used ‘delta’ (change factor) and ‘nudging’ (bias correction) approaches. We focus on daily maximum temperature in summer over Europe for this idealised case study, but the methods can be generalised to other variables and other regions. The calibration methods, which are relatively easy to implement given appropriate observations, produce more robust projections of future daily maximum temperatures and heat stress than using raw model output. The choice over which calibration method to use will likely depend on the situation, but change factor approaches tend to perform best in our examples. Finally, we demonstrate that the uncertainty due to the choice of calibration methodology is a significant contributor to the total uncertainty in future climate projections for impact studies. We conclude that utilising a variety of calibration methods on output from a wide range of AOGCMs is essential to produce climate data that will ensure robust and reliable crop yield projections.

Combined use of two genetic fingerprinting methods, pulsed-field gel electrophoresis and ribotyping, for characterization of Escherichia coli O157 isolates from food animals, retail meats, and cases of human disease

Two genetic fingerprinting techniques, pulsed-field gel electrophoresis (PFGE) and ribotyping, were used to characterize 207 Escherichia coli O157 isolates from food animals, foods of animal origin, and cases of human disease (206 of the isolates were from the United Kingdom). In addition, 164 of these isolates were also phage typed. The isolates were divided into two general groups: (i) unrelated isolates not known to be epidemiologically linked (n = 154) and originating from food animals, foods and the environment, or humans and (ii) epidemiologically related isolates (n = 53) comprised of four related groups (RGs) originating either from one farm plus the abattoir where cattle from that farm were slaughtered or from one of three different English abattoirs. PFGE was conducted with the restriction endonuclease XbaI. while for ribotyping, two restriction endonucleases (PstI and SphI) were combined to digest genomic DNAs simultaneously. The 207 E. coli O157 isolates produced 97 PFGE profiles and 51 ribotypes. The two genetic fingerprinting methods had similar powers to discriminate the 154 epidemiologically unrelated E. coli O157 isolates in the study (Simpson's index of diversity [D] = 0.98 and 0.94 for PFGE typing and ribotyping, respectively). There was no correlation between the source of an isolate (healthy meat or milk animals, retail meats, or cases of human infection) and either particular PFGE or ribotype profiles or clusters. Combination of the results of both genetic fingerprinting methods produced 146 types, significantly more than when either of the two methods was used individually. Consequently, the superior discriminatory performance of the PFGE-ribotyping combination was proven in two ways: (i) by demonstrating that the majority of the E. coli O157 isolates with unrelated histories were indeed distinguishable types and (ii) by identifying some clonal groups among two of the four RGs of E. coli O157 isolates (comprising PFGE types different by just one or two bands), the relatedness of which would have remained unconfirmed otherwise.

Use of denaturing gradient gel electrophoresis to detect Actinobacteria associated with the human faecal microbiota

With the exceptions of the bifidobacteria, propionibacteria and coriobacteria, the Actinobacteria associated with the human gastrointestinal tract have received little attention. This has been due to the seeming absence of these bacteria from most clone libraries. In addition, many of these bacteria have fastidious growth and atmospheric requirements. A recent cultivation-based study has shown that the Actinobacteria of the human gut may be more diverse than previously thought. The aim of this study was to develop a denaturing gradient gel electrophoresis (DGGE) approach for characterizing Actinobacteria present in faecal samples. Amount of DNA added to the Actinobacteria-specific PCR used to generate strong PCR products of equal intenstity from faecal samples of five infants, nine adults and eight elderly adults was anti-correlated with counts of bacteria obtained using fluorescence in situ hybridization probe HGC69A. A nested PCR using Actinobacteria-specific and universal PCR-DGGE primers was used to generate profiles for the Actinobacteria. Cloning of sequences from the DGGE bands confirmed the specificity of the Actinobacteria-specific primers. In addition to members of the genus Bifidobacterium, species belonging to the genera Propionibacterium, Microbacterium, Brevibacterium, Actinomyces and Corynebacterium were found to be part of the faecal microbiota of healthy humans.

Toward vicarious calibration of microwave remote-sensing satellites in arid environments

The Soil Moisture and Ocean Salinity (SMOS) satellite marks the commencement of dedicated global surface soil moisture missions, and the first mission to make passive microwave observations at L-band. On-orbit calibration is an essential part of the instrument calibration strategy, but on-board beam-filling targets are not practical for such large apertures. Therefore, areas to serve as vicarious calibration targets need to be identified. Such sites can only be identified through field experiments including both in situ and airborne measurements. For this purpose, two field experiments were performed in central Australia. Three areas are studied as follows: 1) Lake Eyre, a typically dry salt lake; 2) Wirrangula Hill, with sparse vegetation and a dense cover of surface rock; and 3) Simpson Desert, characterized by dry sand dunes. Of those sites, only Wirrangula Hill and the Simpson Desert are found to be potentially suitable targets, as they have a spatial variation in brightness temperatures of <4 K under normal conditions. However, some limitations are observed for the Simpson Desert, where a bias of 15 K in vertical and 20 K in horizontal polarization exists between model predictions and observations, suggesting a lack of understanding of the underlying physics in this environment. Subsequent comparison with model predictions indicates a SMOS bias of 5 K in vertical and 11 K in horizontal polarization, and an unbiased root mean square difference of 10 K in both polarizations for Wirrangula Hill. Most importantly, the SMOS observations show that the brightness temperature evolution is dominated by regular seasonal patterns and that precipitation events have only little impact.

A cross-calibration of GMS-5 thermal channels against ATSR-2

Motivated by the importance to weather and climate of the Indo-Pacific seas, we present a new calibration of the Visible Infrared Spin-Scan Radiometer (VISSR) on the geostationary meteorological satellite, GMS-5. VISSR imagery has significant potential for exploring the dynamics of the ocean and air–sea interactions in this poorly characterized region, by virtue of the VISSR's surface temperature retrieval capability and hourly sampling. However, the calibration of the thermal imagery supplied by the Japanese Meteorological Agency (JMA) is inconsistent with the spectral characteristics of the channels, and published details of the JMA calibration procedure are scant. We use the well-characterized Along-Track Scanning Radiometer 2 (ATSR-2) as a reference, and determine calibration corrections for GMS-5 VISSR. We obtain more credible VISSR brightness temperatures and demonstrate sea surface temperature (SST) retrieval that validates well against in situ measurements (bias ∼0.3 and scatter ∼0.4 K). Comparison with a widely used sea surface temperature analysis shows that the GMS-5 VISSR SST fields capture important spatial structure, absent in the analysis.

Towards radiocarbon calibration beyond 28ka using speleothems from the Bahamas

We present a new speleothem record of atmospheric Δ14C between 28 and 44 ka that offers considerable promise for resolving some of the uncertainty associated with existing radiocarbon calibration curves for this time period. The record is based on a comprehensive suite of AMS 14C ages, using new low-blank protocols, and U–Th ages using high precision MC-ICPMS procedures. Atmospheric Δ14C was calculated by correcting 14C ages with a constant dead carbon fraction (DCF) of 22.7 ± 5.9%, based on a comparison of stalagmite 14C ages with the IntCal04 (Reimer et al., 2004) calibration curve between 15 and 11 ka. The new Δ14C speleothem record shows similar structure and amplitude to that derived from Cariaco Basin foraminifera (Hughen et al., 2004, 2006), and the match is further improved if the latter is tied to the most recent Greenland ice core chronology (Svensson et al., 2008). These data are however in conflict with a previously published 14C data set for a stalagmite record from the Bahamas — GB-89-24-1 (Beck et al., 2001), which likely suffered from 14C analytical blank subtraction issues in the older part of the record. The new Bahamas speleothem ∆14C data do not show the extreme shifts between 44 and 40 ka reported in the previous study (Beck et al., 2001). Causes for the observed structure in derived atmospheric Δ14C variation based on the new speleothem data are investigated with a suite of simulations using an earth system model of intermediate complexity. Data-model comparison indicates that major fluctuations in atmospheric ∆14C during marine isotope stage 3 is primarily a function of changes in geomagnetic field intensity, although ocean–atmosphere system reorganisation also played a supporting role.

Toward seamless prediction: calibration of climate change projections using seasonal forecasts

The CWRF is developed as a climate extension of the Weather Research and Forecasting model (WRF) by incorporating numerous improvements in the representation of physical processes and integration of external (top, surface, lateral) forcings that are crucial to climate scales, including interactions between land, atmosphere, and ocean; convection and microphysics; and cloud, aerosol, and radiation; and system consistency throughout all process modules. This extension inherits all WRF functionalities for numerical weather prediction while enhancing the capability for climate modeling. As such, CWRF can be applied seamlessly to weather forecast and climate prediction. The CWRF is built with a comprehensive ensemble of alternative parameterization schemes for each of the key physical processes, including surface (land, ocean), planetary boundary layer, cumulus (deep, shallow), microphysics, cloud, aerosol, and radiation, and their interactions. This facilitates the use of an optimized physics ensemble approach to improve weather or climate prediction along with a reliable uncertainty estimate. The CWRF also emphasizes the societal service capability to provide impactrelevant information by coupling with detailed models of terrestrial hydrology, coastal ocean, crop growth, air quality, and a recently expanded interactive water quality and ecosystem model. This study provides a general CWRF description and basic skill evaluation based on a continuous integration for the period 1979– 2009 as compared with that of WRF, using a 30-km grid spacing over a domain that includes the contiguous United States plus southern Canada and northern Mexico. In addition to advantages of greater application capability, CWRF improves performance in radiation and terrestrial hydrology over WRF and other regional models. Precipitation simulation, however, remains a challenge for all of the tested models.

Calibration of structure in a distributed forecasting model for a semiarid flash flood: dynamic surface storage and channel roughness

Flash floods pose a significant danger for life and property. Unfortunately, in arid and semiarid environment the runoff generation shows a complex non-linear behavior with a strong spatial and temporal non-uniformity. As a result, the predictions made by physically-based simulations in semiarid areas are subject to great uncertainty, and a failure in the predictive behavior of existing models is common. Thus better descriptions of physical processes at the watershed scale need to be incorporated into the hydrological model structures. For example, terrain relief has been systematically considered static in flood modelling at the watershed scale. Here, we show that the integrated effect of small distributed relief variations originated through concurrent hydrological processes within a storm event was significant on the watershed scale hydrograph. We model these observations by introducing dynamic formulations of two relief-related parameters at diverse scales: maximum depression storage, and roughness coefficient in channels. In the final (a posteriori) model structure these parameters are allowed to be both time-constant or time-varying. The case under study is a convective storm in a semiarid Mediterranean watershed with ephemeral channels and high agricultural pressures (the Rambla del Albujón watershed; 556 km 2 ), which showed a complex multi-peak response. First, to obtain quasi-sensible simulations in the (a priori) model with time-constant relief-related parameters, a spatially distributed parameterization was strictly required. Second, a generalized likelihood uncertainty estimation (GLUE) inference applied to the improved model structure, and conditioned to observed nested hydrographs, showed that accounting for dynamic relief-related parameters led to improved simulations. The discussion is finally broadened by considering the use of the calibrated model both to analyze the sensitivity of the watershed to storm motion and to attempt the flood forecasting of a stratiform event with highly different behavior.

Phase calibration of the EISCAT Svalbard Radar interferometer using optical satellite signatures

The link between natural ion-line enhancements in radar spectra and auroral activity has been the subject of recent studies but conclusions have been limited by the spatial and temporal resolution previously available. The next challenge is to use shorter sub-second integration times in combination with interferometric programmes to resolve spatial structure within the main radar beam, and so relate enhanced filaments to individual auroral rays. This paper presents initial studies of a technique, using optical and spectral satellite signatures, to calibrate the received phase of a signal with the position of the scattering source along the interferometric baseline of the EISCAT Svalbard Radar. It is shown that a consistent relationship can be found only if the satellite passage through the phase fringes is adjusted from the passage predicted by optical tracking. This required adjustment is interpreted as being due to the vector between the theoretical focusing points of the two antennae, i.e. the true radar baseline, differing from the baseline obtained by survey between the antenna foot points. A method to obtain a measurement of the true interferometric baseline using multiple satellite passes is outlined.

A traceable physical calibration of the vertical advection-diffusion equation for modelling ocean heat uptake

The classic vertical advection-diffusion (VAD) balance is a central concept in studying the ocean heat budget, in particular in simple climate models (SCMs). Here we present a new framework to calibrate the parameters of the VAD equation to the vertical ocean heat balance of two fully-coupled climate models that is traceable to the models’ circulation as well as to vertical mixing and diffusion processes. Based on temperature diagnostics, we derive an effective vertical velocity w∗ and turbulent diffusivity k∗ for each individual physical process. In steady-state, we find that the residual vertical velocity and diffusivity change sign in mid-depth, highlighting the different regional contributions of isopycnal and diapycnal diffusion in balancing the models’ residual advection and vertical mixing. We quantify the impacts of the time-evolution of the effective quantities under a transient 1%CO2 simulation and make the link to the parameters of currently employed SCMs.

Scene understanding for auto-calibration of surveillance cameras

In the last decade, several research results have presented formulations for the auto-calibration problem. Most of these have relied on the evaluation of vanishing points to extract the camera parameters. Normally vanishing points are evaluated using pedestrians or the Manhattan World assumption i.e. it is assumed that the scene is necessarily composed of orthogonal planar surfaces. In this work, we present a robust framework for auto-calibration, with improved results and generalisability for real-life situations. This framework is capable of handling problems such as occlusions and the presence of unexpected objects in the scene. In our tests, we compare our formulation with the state-of-the-art in auto-calibration using pedestrians and Manhattan World-based assumptions. This paper reports on the experiments conducted using publicly available datasets; the results have shown that our formulation represents an improvement over the state-of-the-art.

Advances in the stochastic modelling of satellite-derived rainfall estimates using a sparse calibration dataset

As satellite technology develops, satellite rainfall estimates are likely to become ever more important in the world of food security. It is therefore vital to be able to identify the uncertainty of such estimates and for end users to be able to use this information in a meaningful way. This paper presents new developments in the methodology of simulating satellite rainfall ensembles from thermal infrared satellite data. Although the basic sequential simulation methodology has been developed in previous studies, it was not suitable for use in regions with more complex terrain and limited calibration data. Developments in this work include the creation of a multithreshold, multizone calibration procedure, plus investigations into the causes of an overestimation of low rainfall amounts and the best way to take into account clustered calibration data. A case study of the Ethiopian highlands has been used as an illustration.