93 resultados para Food -- Analysis


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The integration of detailed information on feeding interactions with measures of abundance and body mass of individuals provides a powerful platform for understanding ecosystem organisation. Metabolism and, by proxy, body mass constrain the flux, turnover and storage of energy and biomass in food webs. Here, we present the first food web data for Lough Hyne, a species rich Irish Sea Lough. Through the application of individual-and size-based analysis of the abundance-body mass relationship, we tested predictions derived from the metabolic theory of ecology. We found that individual body mass constrained the flux of biomass and determined its distribution within the food web. Body mass was also an important determinant of diet width and niche overlap, and predator diets were nested hierarchically, such that diet width increased with body mass. We applied a novel measure of predator-prey biomass flux which revealed that most interactions in Lough Hyne were weak, whereas only a few were strong. Further, the patterning of interaction strength between prey sharing a common predator revealed that strong interactions were nearly always coupled with weak interactions. Our findings illustrate that important insights into the organisation, structure and stability of ecosystems can be achieved through the theoretical exploration of detailed empirical data.

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Mass spectrometry (MS)-based metabolomics is emerging as an important field of research in many scientific areas, including chemical safety of food. A particular strength of this approach is its potential to reveal some physiological effects induced by complex mixtures of chemicals present at trace concentrations. The limitations of other analytical approaches currently employed to detect low-dose and mixture effects of chemicals make detection very problematic. Besides this basic technical challenge, numerous analytical choices have to be made at each step of a metabolomics study, and each step can have a direct impact on the final results obtained and their interpretation (i.e. sample preparation, sample introduction, ionization, signal acquisition, data processing, and data analysis). As the application of metabolomics to chemical analysis of food is still in its infancy, no consensus has yet been reached on defining many of these important parameters. In this context, the aim of the present study is to review all these aspects of MS-based approaches to metabolomics, and to give a comprehensive, critical overview of the current state of the art, possible pitfalls, and future challenges and trends linked to this emerging field. (C) 2010 Elsevier Ltd. All rights reserved.

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An LC/MS/MS method was developed and validated for the simultaneous identification, confirmation, and quantification of 12 glucocorticoids in bovine milk. The method was validated in accordance with the criteria defined in Commission Decision 2002/657/EC. The developed method can detect and confirm the presence of dexamethasone, betamethasone, prednisolone, flumethasone, 6 alpha-methylprednisolone, fluorometholone, triamcinolone acetonide, prednisone, cortisone, hydrocortisone, clobetasol propionate, and clobetasol butyrate in bovine milk. Milk samples are extracted with acetonitrile; sodium chloride is subsequently added to aid partition of the milk and acetonitrile mixture. The acetonitrile extract is then subjected to liquid-liquid purification by the addition of hexane. The purified extract is evaporated to dryness and reconstituted in a water acetonitrile mixture, and determination is carried out by LC/MS/MS. The method permits analysis of up to 30 samples in 1 day.

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The means to detect the irradiation of food has been investigated for many years. In recent times radiolytic products, termed 2-alkylcyclobutanones (2-CBs), have been identified as excellent markers of irradiation in lipid-containing foods. An ELISA test was developed, which was capable of detecting a number of these compounds in irradiated chicken meat. A polyclonal antiserum was raised to a 2-CB containing a terminal carboxyl group conjugated to a carrier protein. This antiserum was highly specific for cyclobutanones containing C-10 and C-12 side chains. During assay validation the limit of detection of the assay was calculated to be 0.064 pg of 2-CB per gram of fat, within- and between-assay variations ranged from 6.7 to 18%. During experimental studies, chicken meat irradiated at doses ranging from 2.5 to 10 kGy were assayed and correctly identified as being treated. Quantitative comparisons between the ELISA and CC-MS revealed a good correlation (r(2) = 0.913) between the two methodologies in concentrations of 2-CB detected in irradiated samples.

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Regulatory authorities, the food industry and the consumer demand reliable determination of chemical contaminants present in foods. A relatively new analytical technique that addresses this need is an immunobiosensor based on surface plasmon resonance (SPR) measurements. Although a range of tests have been developed to measure residues in milk, meat, animal bile and honey, a considerable problem has been encountered with both serum and plasma samples. The high degree of non-specific binding of some sample components can lead to loss of assay robustness, increased rates of false positives and general loss of assay sensitivity. In this paper we describe a straightforward precipitation technique to remove interfering substances from serum samples to be analysed for veterinary anthelmintics by SPR. This technique enabled development of an assay to detect a wide range of benzimidazole residues in serum samples by immunobiosensor. The limit of quantification was below 5 ng/ml and coefficients of variation were about 2%.

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With the introduction of budget airlines and greater competitiveness amongst all airlines, air travel has now become an extremely popular form of travel, presenting its own unique set of risks from food poisoning. Foodborne illness associated with air travel is quite uncommon in the modern era. However, when it occurs, it may have serious implications for passengers and when crew are affected, has the potential to threaten safety. Quality, safe, in-flight catering relies on high standards of food preparation and storage; this applies at the airport kitchens (or at subcontractors' facilities), on the aircraft and in the transportation vehicles which carry the food from the ground source to the aircraft. This is especially challenging in certain countries. Several foodborne outbreaks have been recorded by the airline industry as a result of a number of different failures of these systems. These have provided an opportunity to learn from past mistakes and current practice has, therefore, reached such a standard so as to minimise risk of failures of this kind. This review examines: (i) the origin of food safety in modern commercial aviation; (ii) outbreaks which have occurred previously relating to aviation travel; (iii) the microbiological quality of food and water on board commercial aircraft; and (iv) how Hazard Analysis Critical Control Points may be employed to maintain food safety in aviation travel.

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Mass spectrometric methods were developed and validated for the analysis in chicken muscle of a range of antibiotic growth promoters: spiramycin, tylosin, virginiamycin and bacitracin, and separately for two marker metabolites of carbadox (quinoxaline-2-carboxylic acid and 1,4-bisdesoxycarbadox), and a marker metabolite of olaquindox (3-methyl-quinoxaline-2-carboxylic acid). The use of these compounds as antibiotic growth promoters has been banned by the European Commission. This study aimed to develop methods to detect their residues in muscle samples as a means of checking for the use of these drugs during the rearing of broiler chickens. When fed growth-promoting doses for 6 days, spiramycin (31.4 mu g kg(-1)), tylosin (1.0 mu g kg(-1)), QCA (6.5 mu g kg(-1)), DCBX (71.2 mu g kg(-1)) and MQCA (0.2 mu g kg(-1)) could be detected in the muscle 0 days after the withdrawal of fortified feed. Only spiramycin could consistently be detected beyond a withdrawal period of 1 day. All analytes showed stability commercial cooking process, therefore raw or cooked muscle could be used for monitoring purposes.

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A study was undertaken to examine a range of sample preparation and near infrared reflectance spectroscopy (NIPS) methodologies, using undried samples, for predicting organic matter digestibility (OMD g kg(-1)) and ad libitum intake (g kg(-1) W-0.75) of grass silages. A total of eight sample preparation/NIRS scanning methods were examined involving three extents of silage comminution, two liquid extracts and scanning via either external probe (1100-2200 nm) or internal cell (1100-2500 nm). The spectral data (log 1/R) for each of the eight methods were examined by three regression techniques each with a range of data transformations. The 136 silages used in the study were obtained from farms across Northern Ireland, over a two year period, and had in vivo OMD (sheep) and ad libitum intake (cattle) determined under uniform conditions. In the comparisons of the eight sample preparation/scanning methods, and the differing mathematical treatments of the spectral data, the sample population was divided into calibration (n = 91) and validation (n = 45) sets. The standard error of performance (SEP) on the validation set was used in comparisons of prediction accuracy. Across all 8 sample preparation/scanning methods, the modified partial least squares (MPLS) technique, generally minimized SEP's for both OMD and intake. The accuracy of prediction also increased with degree of comminution of the forage and with scanning by internal cell rather than external probe. The system providing the lowest SEP used the MPLS regression technique on spectra from the finely milled material scanned through the internal cell. This resulted in SEP and R-2 (variance accounted for in validation set) values of 24 (g/kg OM) and 0.88 (OMD) and 5.37 (g/kg W-0.75) and 0.77 (intake) respectively. These data indicate that with appropriate techniques NIRS scanning of undried samples of grass silage can produce predictions of intake and digestibility with accuracies similar to those achieved previously using NIRS with dried samples. (C) 1998 Elsevier Science B.V.

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Increasing fruit and vegetable (FV) consumption is associated with reduced risk of major diseases. However, it is unclear if health benefits are related to increased micronutrient intake or to improvements in overall diet profile. This review aimed to assess if increasing FV consumption had an impact on diet profile. In the systematic review, twelve studies revealed increases in micronutrient intakes, whilst the meta-analysis confirmed macronutrient findings from the systematic review showing no significant difference between the intervention and control groups in energy (kcals) in seven studies (mean difference = 1 kcals [95% CI = -115, 117]; P = 0.98), significant decreases in total fat (% energy) in 5 studies (Mean difference = -4% [95% CI = -5, -3]; P = <0.00001) and significant increases in fibre in 6 studies (Mean difference = 5.36 grams [95% CI = 4, 7]; P = <0.00001) and total carbohydrate (% energy) in 4 studies (Mean = 4% [95% CI = 2, 5]; P = <0.00001). In conclusion, results indicate that increased FV consumption increases micronutrient, carbohydrate and fibre intakes and possibly reduces fat intake, with no overall effect on energy intake. Therefore health benefits may act through an improvement in overall diet profile alongside increased micronutrient intakes.

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After years of emphasis on leanness and responsiveness businesses are now experiencing their vulnerability to supply chain disturbances. Although more literature is appearing on this subject, there is a need for an integrated framework to support the analysis and design of robust food supply chains. In this chapter we present such a framework. We define the concept of robustness and classify supply chain disturbances, sources of food supply chain vulnerability, and adequate redesign principles and strategies to achieve robust supply chain performances. To test and illustrate its applicability, the research framework is applied to a meat supply chain.

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High effectiveness and leanness of modern supply chains (SCs) increase their vulnerability, i.e. susceptibility to disturbances reflected in non-robust SC performances. Both the SC management literature and SC professionals indicate the need for the development of SC vulnerability assessment tools. In this article, a new method for vulnerability assessment, the VULA method, is presented. The VULA method helps to identify how much a company would underperform on a specific Key Performance Indicator in the case of a disturbance, how often this would happen and how long it would last. It ultimately informs the decision about whether process redesign is appropriate and what kind of redesign strategies should be used in order to increase the SC's robustness. The applicability of the VULA method is demonstrated in the context of a meat SC using discrete-event simulation to conduct the performance analysis.

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A prototype fluorescent based biosensor has been developed for the antibody based detection of food related contaminants. Its performance was characterised and showed a typical antibody binding signal of 200-2000 mV, a short term noise of 9.1 mV, and baseline slope of -0.016 mV/s over 4 h. Bulk signal detection repeatability (n=23) and reproducibility (n=3) were less than 2.4%CV. The biosensor detection unit was evaluated using two food related model systems proving its ability to monitor both binding using commercial products and inhibition through the development of an assay. This assay development potential was evaluated by observing the biosensor's performance whilst appraising several labelled antibody and glass slide configurations. The molecular interaction between biotin and an anti-biotin antibody was shown to be inhibited by 41% due to the presence of biotin in a sample. A food toxin (domoic acid) calibration curve was produced, with %CVs ranging from 2.7 to 7.8%, and a midpoint of approximately 17 ng/ml with further optimisation possible. The ultimate aim of this study was to demonstrate the working principles of this innovative biosensor as a potential portable tool with the opportunity of interchangeable assays. The biosensor design is applicable for the requirements of routine food contaminant analysis, with respect to performance, functionality and cost. (C) 2012 Elsevier B.V. All rights reserved.

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Food webs are the complex networks of trophic interactions that stoke the metabolic fires of life. To understand what structures these interactions in natural communities, ecologists have developed simple models to capture their main architectural features. However, apparently realistic food webs can be generated by models invoking either predator-prey body-size hierarchies or evolutionary constraints as structuring mechanisms. As a result, this approach has not conclusively revealed which factors are the most important. Here we cut to the heart of this debate by directly comparing the influence of phylogeny and body size on food web architecture. Using data from 13 food webs compiled by direct observation, we confirm the importance of both factors. Nevertheless, phylogeny dominates in most networks. Moreover, path analysis reveals that the size-independent direct effect of phylogeny on trophic structure typically outweighs the indirect effect that could be captured by considering body size alone. Furthermore, the phylogenetic signal is asymmetric: closely related species overlap in their set of consumers far more than in their set of resources. This is at odds with several food web models, which take only the view-point of consumers when assigning interactions. The echo of evolutionary history clearly resonates through current food webs, with implications for our theoretical models and conservation priorities.

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In conventional milling, the aleurone layer is combined with the bran fraction. Studies indicate that the bran fraction of wheat contains the majority of the phytonutrients betaine and choline, with relatively minor concentrations in the refined flour. This present study suggests that the wheat aleurone layer (Triticum aestivum L. cv. Tiger) contains the greatest concentration of both betaine and choline (1553.44 and 209.80 mg/100 g of sample, respectively). The bran fraction contained 866.94 and 101.95 mg/100 g of sample of betaine and choline, respectively, while the flour fraction contained 23.30 mg/100 g of sample (betaine) and 28.0 mg/100 g of sample (choline). The betaine content for
the bran was lower, and the choline content was higher compared to previous studies, although it is known that there is large variation in betaine and choline contents between wheat cultivars. The ratio of betaine/choline in the aleurone fraction was approximately 7:1; in the bran, the ratio was approximately 8:1; and in the flour fraction, the ratio was approximately 1:1. The study further
emphasizes the superior phytonutrient composition of the aleurone layer.
INTRODUCTION
Wheat is a valuable source of betaine, choline (1, 2), B
vitamins, vitamin E, and a number of minerals, including iron,
zinc, magnesium, and phosphorus (3). Epidemiological studies
indicate that whole-grain consumption is protective against
several chronic diseases (4-12). It has not been fully elucidated
how whole-grain cereals or specific fractions (13) exert their
protective effect, but it is thought to be due to their content of
several nutrients associated with the reduced risk of disease.
Conventionally, whole grain is separated during milling into
bran, germ, and flour (14). The nutrient composition of these
fractions differ markedly; refined wheat flour contains approximately
50% less vitamins and minerals than whole-grain
flour (

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The operation of supply chains (SCs) has for many years been focused on efficiency, leanness and responsiveness. This has resulted in reduced slack in operations, compressed cycle times, increased productivity and minimised inventory levels along the SC. Combined with tight tolerance settings for the realisation of logistics and production processes, this has led to SC performances that are frequently not robust. SCs are becoming increasingly vulnerable to disturbances, which can decrease the competitive power of the entire chain in the market. Moreover, in the case of food SCs non-robust performances may ultimately result in empty shelves in grocery stores and supermarkets.
The overall objective of this research is to contribute to Supply Chain Management (SCM) theory by developing a structured approach to assess SC vulnerability, so that robust performances of food SCs can be assured. We also aim to help companies in the food industry to evaluate their current state of vulnerability, and to improve their performance robustness through a better understanding of vulnerability issues. The following research questions (RQs) stem from these objectives:
RQ1: What are the main research challenges related to (food) SC robustness?
RQ2: What are the main elements that have to be considered in the design of robust SCs and what are the relationships between these elements?
RQ3: What is the relationship between the contextual factors of food SCs and the use of disturbance management principles?
RQ4: How to systematically assess the impact of disturbances in (food) SC processes on the robustness of (food) SC performances?
To answer these RQs we used different methodologies, both qualitative and quantitative. For each question, we conducted a literature survey to identify gaps in existing research and define the state of the art of knowledge on the related topics. For the second and third RQ, we conducted both exploration and testing on selected case studies. Finally, to obtain more detailed answers to the fourth question, we used simulation modelling and scenario analysis for vulnerability assessment.
Main findings are summarised as follows.
Based on an extensive literature review, we answered RQ1. The main research challenges were related to the need to define SC robustness more precisely, to identify and classify disturbances and their causes in the context of the specific characteristics of SCs and to make a systematic overview of (re)design strategies that may improve SC robustness. Also, we found that it is useful to be able to discriminate between varying degrees of SC vulnerability and to find a measure that quantifies the extent to which a company or SC shows robust performances when exposed to disturbances.
To address RQ2, we define SC robustness as the degree to which a SC shows an acceptable performance in (each of) its Key Performance Indicators (KPIs) during and after an unexpected event that caused a disturbance in one or more logistics processes. Based on the SCM literature we identified the main elements needed to achieve robust performances and structured them together to form a conceptual framework for the design of robust SCs. We then explained the logic of the framework and elaborate on each of its main elements: the SC scenario, SC disturbances, SC performance, sources of food SC vulnerability, and redesign principles and strategies.
Based on three case studies, we answered RQ3. Our major findings show that the contextual factors have a consistent relationship to Disturbance Management Principles (DMPs). The product and SC environment characteristics are contextual factors that are hard to change and these characteristics initiate the use of specific DMPs as well as constrain the use of potential response actions. The process and the SC network characteristics are contextual factors that are easier to change, and they are affected by the use of the DMPs. We also found a notable relationship between the type of DMP likely to be used and the particular combination of contextual factors present in the observed SC.
To address RQ4, we presented a new method for vulnerability assessments, the VULA method. The VULA method helps to identify how much a company is underperforming on a specific Key Performance Indicator (KPI) in the case of a disturbance, how often this would happen and how long it would last. It ultimately informs the decision maker about whether process redesign is needed and what kind of redesign strategies should be used in order to increase the SC’s robustness. The VULA method is demonstrated in the context of a meat SC using discrete-event simulation. The case findings show that performance robustness can be assessed for any KPI using the VULA method.
To sum-up the project, all findings were incorporated within an integrated framework for designing robust SCs. The integrated framework consists of the following steps: 1) Description of the SC scenario and identification of its specific contextual factors; 2) Identification of disturbances that may affect KPIs; 3) Definition of the relevant KPIs and identification of the main disturbances through assessment of the SC performance robustness (i.e. application of the VULA method); 4) Identification of the sources of vulnerability that may (strongly) affect the robustness of performances and eventually increase the vulnerability of the SC; 5) Identification of appropriate preventive or disturbance impact reductive redesign strategies; 6) Alteration of SC scenario elements as required by the selected redesign strategies and repeat VULA method for KPIs, as defined in Step 3.
Contributions of this research are listed as follows. First, we have identified emerging research areas - SC robustness, and its counterpart, vulnerability. Second, we have developed a definition of SC robustness, operationalized it, and identified and structured the relevant elements for the design of robust SCs in the form of a research framework. With this research framework, we contribute to a better understanding of the concepts of vulnerability and robustness and related issues in food SCs. Third, we identified the relationship between contextual factors of food SCs and specific DMPs used to maintain robust SC performances: characteristics of the product and the SC environment influence the selection and use of DMPs; processes and SC networks are influenced by DMPs. Fourth, we developed specific metrics for vulnerability assessments, which serve as a basis of a VULA method. The VULA method investigates different measures of the variability of both the duration of impacts from disturbances and the fluctuations in their magnitude.
With this project, we also hope to have delivered practical insights into food SC vulnerability. First, the integrated framework for the design of robust SCs can be used to guide food companies in successful disturbance management. Second, empirical findings from case studies lead to the identification of changeable characteristics of SCs that can serve as a basis for assessing where to focus efforts to manage disturbances. Third, the VULA method can help top management to get more reliable information about the “health” of the company.
The two most important research opportunities are: First, there is a need to extend and validate our findings related to the research framework and contextual factors through further case studies related to other types of (food) products and other types of SCs. Second, there is a need to further develop and test the VULA method, e.g.: to use other indicators and statistical measures for disturbance detection and SC improvement; to define the most appropriate KPI to represent the robustness of a complete SC. We hope this thesis invites other researchers to pick up these challenges and help us further improve the robustness of (food) SCs.