Reference material for improving the quality of nutritional composition data for foods

Summary Analytical values for the nutritional composition of foods are required for a range of purposes, in particular, for the construction of nutritional data bases. These provide the basis for estimating nutrient intakes in population groups, and for the nutritional labelling of foods. Both of these uses requires analytical values that accurately represent the composition of the foods. The requisite quality can only be achieved by the institution of a sound quality assurance programme in which reference materials have a vital role.The special features of nutritional analyses and their control with reference materials are reviewed and the criteria for the production of these reference materials discussed.     

Chemometrics and food chemistry: data validation

Chemometrics has often been applied in food chemistry to cluster and classify samples or to produce models for food quality. In recent years, data on food composition have become important for public health protection and food trades. The quality of the available chemical information on foods is a problem; data obtained with the newer analytical methods is scarce and general knowledge about food composition is poor, judged by published tables on food composition. Moreover, agreement between results obtained by different analytical methods is very poor. To overcome this critical problem, several countries have decided to create data banks on food composition. The analytical results to be stored must be validated. Chemometric modelling is useful for this purpose. Interlaboratory studies allow standardization of methods and the preparation of food reference materials. The classical computation of repeatability and reproducibility does not extract all the available information so that a multivariate approach is necessary to improve the quality of a data bank on food composition.     

Predicting hexadecane–air equilibrium partition coefficients (L) using a group contribution approach constructed from high quality data

A group contribution-based quantitative structure–property relationship (QSPR) for the hexadecane–air equilibrium partition coefficients (L) of organic chemicals is developed using the iterative fragment selection (IFS) approach. This new QSPR includes in its training and external validation data sets L values for a large number of structurally complex chemicals measured by the same group using consistent methods. The resulting QSPR has better predictive power than other prediction methods trained primarily using data for chemicals of simpler structures, and measurements of L values from diverse sources. For a subset of chemicals in which the L values have non-additive effects caused by intramolecular hydrogen bonds, the new QSPR gives much better performance in comparison to the most commonly used prediction method.     

Proficiency testing programmes as a tool in food quality assurance: Overview of Italian experiences

Proficiency testing involves the performance of test procedures on routine samples by a number of laboratories. Interlaboratory proficiency testings provide multiple benefits to participants since they play a key-role in the total quality control of laboratory activities. They serve as a means of self-improving, as a mechanism of continuing education and as a source of information for accreditation agencies. This review highlights basic principles, benefits, criteria and capabilities of a proficiency testing programme for food analysis laboratories as well as their role in the implementation of rapidly developing food control legislation.     

Application of differential scanning calorimetry in food research and food quality assurance

Differential scanning calorimetry (DSC) is the most widely used thermal analytical technique in food research and it has a great utility in quality assurance of food. Proteins are the most studied food components by thermal analysis including studies on conformation changes of food proteins as affected by various environmental factors, thermal denaturation of tissue proteins, food enzymes and enzyme preparations for the food industry, as well as effects of various additives on their thermal properties. Freezing-induced denaturation of food proteins and the effect of cryoprotectants are also monitored by DSC. Polymer characterization based on DSC of polysaccharides, gelatinization behaviour of starches and interaction of starch with other food components can be determined, and phase transitions during baking processes can be studied by DSC. Studies on crystallization and melting behaviour of fats observed by DSC indicate changes in lipid composition or help characterizing products. Thermal oxidative decomposition of edible oils examined by DSC can be used for predicting oil stability. Using DSC in the freezing range has a great potential for measuring and modelling frozen food thermal properties, and to estimate the state of water in foods and food ingredients. Research in food microbiology utilizes DSC in better understanding thermoadaptive mechanisms or heat killing of food-borne microorganisms. Isothermic microcalorimetric techniques provide informative data regarding microbial growth and microbial metabolism.     

Verification of results to improve the quality of analytical data: a proposal

After some two decades insisting on validation and normalization of methods, the reliability of the results in analytical chemistry continues to be unsatisfactory. Further, the processes involved are too slow, with the effect that frequently the most relevant results are obtained with methods not (yet) validated according to norms. It is time to rethink about how the reliability of the results could be improved. It is proposed to shift some of the control from the validation and normalization of method to the verification of the results, using verification tools built into the procedure: additional standards may enable the calculation of the yield of an extraction or chemical transformation, control the column performance or ensure that the fraction from a preseparation is correctly cut. Such verification tools provide control for every sample. If the correctness of results is verified for every sample, this confirms the adequate performance of the method and could replace a corresponding part of the validation. Examples are shown for a number of methods.     

Detection of genetically modified organisms in food: critical points for quality assurance

 The detection of genetically modified organisms (GMOs) by the polymerase chain reaction (PCR) is a complex multiparameter problem. Therefore, a number of critical issues in respect to quality control need to be considered. For practical purposes, the PCR process itself can be divided into three subprocesses: template isolation and reaction setup (pre-PCR), PCR reaction and detection of amplification products, and data evaluation (post-PCR). Crucial factors for the pre-PCR process are the following: homogeneity of the sample to be analysed, performance of template isolation and purification in terms of yield and purity, standardized process for the estimation of concentrations of genomic DNA and all reagents used in the reaction. For the PCR itself, crucial factors to be controlled are: setup of reactions, batch to batch variations of reagents, temperature-time programs used for the PCR amplification, and the performance of different types of hardware (e.g. different brands of thermocyclers). The crucial factor for the post-PCR process is the detection of the amplification products of the PCR. The tremendous sensitivity of PCR methods requires a careful and consequent separation of the three processes in terms of hardware, laboratory space and sample handling. The avoidance of contamination is one of the most critical factors. The goal of quality assurance measures must be to ensure appropriate results at maximum sensitivity. The complexity of any PCR system used for the detection of GMOs leads to the requirement of a careful validation process for any laboratory using such methods. For qualitative analyses crucial validation parameters are: specificity, selectivity, repeatability, intermediate precision, reproducibility, limit of detection and robustness. Received: 5 October 1998 / Accepted: 22 February 1999     

HTS quality control and data analysis: a process to maximize information from a high-throughput screen

Changes in all aspects of HTS from compound management through to evaluation of hits and leads, strengthened by infrastructure improvements, in both automation and informatics, have made possible increased analysis and implementation of process and quality control throughout HTS. This paper focuses on the process of HTS with an emphasis on quality control, reducing the variability of all the processes that have an impact on the final result, and argue that by increasing the quality of the entire process that data mining of primary screening data is in fact possible and will reduce cycle times to medicinal chemistry.     

Development, validation and data quality assurance of screening methods: a case study

Despite the growing importance of qualitative screening tests in routine laboratories involved in the EU official control, their validation is not as deeply explained in Commission Decision 2002/657/EC as the validation of quantitative confirmatory methods. At the same time, the issue of quality assurance of screening assays defining internal quality control (IQC) procedures as required by accreditation bodies is undoubtedly less developed in this analytical field. As an example the present study describes the development, the validation and the IQC implemented for a commercial enzyme linked immunosorbent assay (ELISA) able to detect 17-α-19-nortestosterone (α-NT) and 17-β-19-nortestosterone (β-NT) isomers in bullock urine. In order to select a suitable sample treatment, two SPE purification protocols were preliminary compared. The chosen method was therefore fully validated determining the mandatory parameters required by Commission Decision 2002/657/EC: specificity, detection capability and robustness. An in-depth discussion was carried out illustrating the possible validation approaches and their implications especially in the assessment of the key performance characteristic: detection capability. Finally, the control charts implemented for continuous method verification during analyses of real samples were reported.     

Decision trees in selection of featured determined food quality

The determination of food quality, authenticity and the detection of adulterations are problems of increasing importance in food chemistry. Recently, chemometric classification techniques and pattern recognition analysis methods for wine and other alcoholic beverages have received great attention and have been largely used. Beer is a complex mixture of components: on one hand a volatile fraction, which is responsible for its aroma, and on the other hand, a non-volatile fraction or extract consisting of a great variety of substances with distinct characteristics. The aim of this study was to consider parameters which contribute to beer differentiation according to the quality grade. Chemical (e.g. pH, acidity, dry extract, alcohol content, CO(2) content) and sensory features (e.g. bitter taste, color) were determined in 70 beer samples and used as variables in decision tree techniques. This pattern recognition techniques applied to the dataset were able to extract information useful in obtaining a satisfactory classification of beer samples according to their quality grade. Feature selection procedures indicated which features are the most discriminating for classification.     

Improving the quality of the ion beam exiting a quadrupole ion guide

The effect of fringing fields on the divergence of the ion beam exiting an RF quadrupole ion guide was studied using a computer simulation. It was shown that reducing the strength of the RF field towards the ion guide exit reduces ion beam divergence. Further improvement was demonstrated when creating a DC gradient towards the exit. The results of the numerical simulation were verified experimentally using a time-of-flight (TOF) mass analyzer with orthogonal acceleration. Decreasing the ion beam divergence resulted in considerably improved mass resolution of the instrument.     

Review of European Union requirements: quality standards for food analysis laboratories

 The European Union has prescribed strict quality standards for official food laboratories and the methods of analysis to be used in laboratories when carrying out official food control work. These requirements, which are based on accreditation, participation in proficiency testing schemes and using validated methods of analysis, are described in detail. The similar approach being taken within the Codex Alimentarius Commission is also outlined. The procedures prescribed will ensure that official food control laboratories have in place the measures to ensure that consistently reliable data can be produced. Received: 29 November 1995 Accepted: 8 January 1996     

Acrylamide formation in food: a mechanistic perspective

Earliest reports on the origin of acrylamide in food have confirmed asparagine as the main amino acid responsible for its formation. Available evidence suggests that sugars and other carbonyl compounds play a specific role in the decarboxylation process of asparagine, a necessary step in the generation of acrylamide. It has been proposed that Schiff base intermediate formed between asparagine and the sugar provides a low energy alternative to the decarboxylation from the intact Amadori product through generation and decomposition of oxazolidin-5-one intermediate, leading to the formation of a relatively stable azomethine ylide. Literature data indicate the propensity of such protonated ylides to undergo irreversible 1,2-prototropic shift and produce, in this case, decarboxylated Schiff bases which can easily rearrange into corresponding Amadori products. Decarboxylated Amadori products can either undergo the well known beta-elimination process initiated by the sugar moiety to produce 3-aminopropanamide and 1-deoxyglucosone or undergo 1,2-elimination initiated by the amino acid moiety to directly generate acrylamide. On the other hand, the Schiff intermediate can either hydrolyze and release 3-aminopropanamide or similarly undergo amino acid initiated 1,2-elimination to directly form acrylamide. Other thermolytic pathways to acrylamide--considered marginal at this stage--via the Strecker aldehyde, acrolein, and acrylic acid, are also addressed. Despite significant progress in the understanding of the mechanistic aspects of acrylamide formation, concrete evidence for the role of the different proposed intermediates in foods is still lacking.     

Analytical quality assurance in the german food contamination monitoring programme

Summary The general and analytical strategy for a monitoring project for various chemical elements, nitrate and some halogenated organic compounds in milk, beef, pork, potatoes, lettuce, cabbage, apples and strawberries within the activities of official food control in the Federal Republic of Germany is outlined.

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Analytische Qualitätssicherung im Rahmen eines deutschen Programms zur Überwachung von Lebensmittelverunreinigungen

     

模式识别在食品质量控制方面的应用进展

本文介绍了食品质量研究中常用的一些化学模式识别方法的基本原理,并介绍了模式识别结合红外、原子吸收、原子发射、气相色谱、液相色谱、质谱、电子鼻传感器等检测技术在食品质量控制中的应用.对化学计量学在食品质量控制中的应用前景作了展望.     

Emerging food contaminants: a review

Governments throughout the world are intensifying their efforts to improve food safety. These efforts come as a response to an increasing number of food-safety problems and increasing consumer concerns. In addition, the variety of toxic residues in food is continuously increasing as a consequence of industrial development, new agricultural practices, environmental pollution, and climate change. This paper reviews a selection of emerging contaminants in food, including the industrial organic pollutants perfluorinated compounds (PFCs), polybrominated diphenyl ethers (PBDEs), and nanomaterials; the pharmaceutical residues antibiotics and coccidiostats; and emerging groups of marine biotoxins. The main analytical approaches for their detection and quantification in food will be presented and discussed with special emphasis on biological techniques, when these are feasible. In the last section, a summary of recent publications reporting the concentrations of these compounds in food will be presented and discussed.     

The distribution of interlaboratory comparison data: response to the contribution by K. Heydorn

The distribution of interlaboratory results can often be successfully modeled as a mixture of distributions: a “majority” population of results from laboratories of high and roughly equal competence and a (hopefully) minority “contaminant” population from laboratories of lesser competence. Approximating the majority population as a normal distribution and the contaminant as a uniform distribution can be and has been used to produce mixture populations that have realistically “heavy-tails” (i.e., leptokurtic). Papers published in this section do not necessarily reflect the opinion of the Editors, the Editorial Board and the Publisher.     

Microprocessor-based data processing and quality control in hematology

Routine hematological determinations with Coulter Counter model S instruments benefit from electronic data processing, and appropriate quality control is essential. The system described here is based on an INTEL 8008 microprocessor provided with options for handling sample identification numbers, duplicate print-out of results on self-adhesive labels, and zero-level quality control functions which utilize both patient samples and quality-control samples. The arithmetical means of the results of ten patient samples are calculated in real time for four parameters in whole blood. The running mean values of two of these parameters (MCVand MCHC) are suitable for zero-level process control. together with signalling of extremes. Daily mean values of patiant samples and quality-control samples are also calculated to check the stability from day to day. The microprocessor-based system is adequate for these functions and is relatively simple and inexpensive.     

Instrumental intelligent test of food sensory quality as mimic of human panel test combining multiple cross-perception sensors and data fusion

Instrumental test of food quality using perception sensors instead of human panel test is attracting massive attention recently. A novel cross-perception multi-sensors data fusion imitating multiple mammal perception was proposed for the instrumental test in this work. First, three mimic sensors of electronic eye, electronic nose and electronic tongue were used in sequence for data acquisition of rice wine samples. Then all data from the three different sensors were preprocessed and merged. Next, three cross-perception variables i.e., color, aroma and taste, were constructed using principal components analysis (PCA) and multiple linear regression (MLR) which were used as the input of models. MLR, back-propagation artificial neural network (BPANN) and support vector machine (SVM) were comparatively used for modeling, and the instrumental test was achieved for the comprehensive quality of samples. Results showed the proposed cross-perception multi-sensors data fusion presented obvious superiority to the traditional data fusion methodologies, also achieved a high correlation coefficient (>90%) with the human panel test results. This work demonstrated that the instrumental test based on the cross-perception multi-sensors data fusion can actually mimic the human test behavior, therefore is of great significance to ensure the quality of products and decrease the loss of the manufacturers.     

Quality assurance for the analytical data of micro elements in food

The micro element content of food is an important quality index due to the action of these elements on human health. In this article, we discuss how to ensure the reliability of analytical data on micro elements in order to truly represent the condition of food. Sampling, treatment of the analytical sample, selection of the analytical method, standard solution, and certified reference material, blank test, calibration of the instrument and equipment, application of the quality control chart, assessment of the final analytical result, and quality assurance system are briefly described. Received: 5 July 2001 Accepted: 19 November 2001