State of the art in the validation of screening methods for the control of antibiotic residues: is there a need for further development?

ABSTRACT

Screening methods are used as a first-line approach to detect the presence of antibiotic residues in food of animal origin. The validation process guarantees that the method is fit-for-purpose, suited to regulatory requirements, and provides evidence of its performance. This article is focused on intra-laboratory validation. The first step in validation is characterisation of performance, and the second step is the validation itself with regard to pre-established criteria. The validation approaches can be absolute (a single method) or relative (comparison of methods), overall (combination of several characteristics in one) or criterion-by-criterion. Various approaches to validation, in the form of regulations, guidelines or standards, are presented and discussed to draw conclusions on their potential application for different residue screening methods, and to determine whether or not they reach the same conclusions. The approach by comparison of methods is not suitable for screening methods for antibiotic residues. The overall approaches, such as probability of detection (POD) and accuracy profile, are increasingly used in other fields of application. They may be of interest for screening methods for antibiotic residues. Finally, the criterion-by-criterion approach (Decision 2002/657/EC and of European guideline for the validation of screening methods), usually applied to the screening methods for antibiotic residues, introduced a major characteristic and an improvement in the validation, i.e. the detection capability (CCβ).

In conclusion, screening methods are constantly evolving, thanks to the development of new biosensors or liquid chromatography coupled to tandem-mass spectrometry (LC-MS/MS) methods. There have been clear changes in validation approaches these last 20 years. Continued progress is required and perspectives for future development of guidelines, regulations and standards for validation are presented here.     

Enhancing assessment of social representations by comparing groups with different cultural and demographic characteristics: A case study on pulses

Culture plays an important role in the construction of social representations about food, influencing choices such as when, where, with whom, and how much to eat. Even within Europe, differences in the consumption of pulses may be observed between neighboring countries, such as France and Spain. Moreover, literature suggests different attitudes towards pulses according to the level of education. The first aim of this study was to carry out an exploratory comparison of the social representations of pulses for French and Spanish consumers, in relation to their level of education. Another goal was to improve social representation assessment through a free word association task focusing on pulses. Methodological improvements to the structural approach were therefore proposed, combining order of citation with frequency and importance, with adapted cut-off points. The polarity index was modified, and the impact of analyzing words (raw data) or word categories was assessed. The main results from the study highlighted that, for both words and categories, there is a common core in the social representations of pulses of the two groups of participants compared, related to five dimensions: health, pulses, nutrition, preparation, and sensory aspects. The study also identified a difference in focus between the two countries: French consumers focused on other foods; Spanish consumers focused on appropriateness and context. Overall, in both France and Spain, participants had a positive attitude towards pulses. The methodological changes proposed in the present study facilitate the comparison of results across different groups of participants. This research project provides valuable insights for researchers and policymakers seeking to understand the impact of culture on consumer food choices.     

Modelling the effect of temperature and water activity in the growth boundaries of Aspergillus ochraceus and Aspergillus parasiticus

The aim of this work was to model the growth of Aspergillus parasiticus and Aspergillus ochraceus, both mycotoxin producers, near to the growth/no growth boundaries and validate those models in sterile maize grain, peanuts and coffee beans. Malt extract agar was adjusted to six different water activities: 0.93, 0.91, 0.89, 0.87, 0.85 and 0.80. Plates were incubated at 10, 15, 20, 25, 30, 37 and 42 °C. For each of the 42 conditions, 10 Petri dishes were inoculated. Both kinetic and probability models were applied to colony growth data. The results of the present study indicate that the developed probability modelling approach could be satisfactorily employed to quantify the combined effect of temperature and water activity on the growth responses of A. ochraceus and A. parasiticus. However, validation of kinetic results led to poor goodness of prediction. In this study, the validation samples were placed near to the expected boundaries of the models in order to test them under the worst situation. Probability of growth prediction under extreme growth conditions was somewhat compromised, but it can be considered acceptable.     

Maximizing overall liking results in a superior product to minimizing deviations from ideal ratings: An optimization case study with coffee-flavored milk

In just-about-right (JAR) scaling and ideal scaling, attribute delta (i.e., “Too Little” or “Too Much”) reflects a subject’s dissatisfaction level for an attribute relative to their hypothetical ideal. Dissatisfaction (attribute delta) is a different construct from consumer acceptability, operationalized as liking. Therefore, we hypothesized minimizing dissatisfaction and maximizing liking would yield different optimal formulations. The objective of this research was to compare product optimization strategies, i.e., maximizing liking vis-à-vis minimizing dissatisfaction.Coffee-flavored dairy beverages (n = 20) were formulated using a fractional mixture design that constrained the proportions of coffee extract, milk, sucrose, and water. Participants (n = 388) were randomly assigned to one of three research conditions, where they evaluated 4 of the 20 samples using an incomplete block design. Samples were rated for overall liking and for intensity of the attributes sweetness, milk flavor, thickness and coffee flavor. Where appropriate, measures of overall product quality (Ideal_Delta and JAR_Delta) were calculated as the sum of the absolute values of the four attribute deltas. Optimal formulations were estimated by: (a) maximizing liking; (b) minimizing Ideal_Delta; or (c) minimizing JAR_Delta. A validation study was conducted to evaluate product optimization models.Participants indicated a preference for a coffee-flavored dairy beverage with more coffee extract and less milk and sucrose in the dissatisfaction model compared to the formula obtained by maximizing liking. That is, when liking was optimized, participants generally liked a weaker, milkier and sweeter coffee-flavored dairy beverage. Predicted liking scores were validated in a subsequent experiment, and the optimal product formulated to maximize liking was significantly preferred to that formulated to minimize dissatisfaction by a paired preference test. These findings are consistent with the view that JAR and ideal scaling methods both suffer from attitudinal biases that are not present when liking is assessed. That is, consumers sincerely believe they want ‘dark, rich, hearty’ coffee when they do not. This paper also demonstrates the utility and efficiency of a lean experimental approach.     

Research on factors allowing a risk assessment of spore-forming pathogenic bacteria in cooked chilled foods containing vegetables: a FAIR collaborative project

Vegetables are frequent ingredients of cooked chilled foods and are frequently contaminated with spore-forming bacteria (SFB). Therefore, risk assessment studies have been carried out, including the following: hazard identification and characterisation — from an extensive literature review and expertise of the participants, B. cereus and C. botulinum were identified as the main hazards; exposure assessment — consisting of determination of the prevalence of hazardous SFB in cooked chilled foods containing vegetables and in unprocessed vegetables, and identification of SFB representative of the bacterial community in cooked chilled foods containing vegetables, determination of heat-resistance parameters and factors affecting heat resistance of SFB, determination of the growth kinetics of SFB in vegetable substrate and of the influence of controlling factors, validation of previous work in complex food systems and by challenge testing and information about process and storage conditions of cooked chilled foods containing vegetables. The paper illustrates some original results obtained in the course of the project. The results and information collected from scientific literature or from the expertise of the participants are integrated into the microbial risk assessment, using both a Bayesian belief network approach and a process risk model approach, previously applied to other foodborne hazards.     

Application of Near-Infrared Spectroscopy for the Detection of Metanil Yellow in Turmeric Powder

Turmeric (Curcumina Longa) is a globally traded commodity which is subjected to economically motivated chemically unsafe adulteration, namely metanil yellow. In this work, we report a simplistic and convenient approach to find the adulteration of turmeric with metanil yellow by near-infrared (NIR) spectroscopy coupled with chemometrics. Pure turmeric sample was prepared in the laboratory and spiked with different concentrations of metanil yellow. The reflectance spectra of 248 pure turmeric, metanil yellow, and adulterated samples (1–25%) (w/w) were collected using NIR spectroscopy. The calibration models based on NIR spectra of 144 samples were built for two different regression models, principal component analysis (PCR), and partial least square (PLSR) methods. Another 72 samples were used for external validation. The coefficient of determination (R ²) and root mean square error of calibration for validation and prediction were found to be 0.96–0.99, 0.44–0.91, respectively, for most of the results depending upon different pre-processing techniques and mathematical models used. The original reflectance spectra, the 1st derivative plot, the plot of PLSR regression coefficient (β), and the first three principal component loadings revealed metanil-related absorption regions. To verify the robustness of the models, the figures of merit (FOM) of the models were calculated with the help of net analyte signal (NAS) theory. Overall, it was found that PLSR yielded superior results as compared to the PCR technique. These methods can be applied to other spices also to detect the adulteration rapidly and without any prior sample preparations and with low cost.     

Technical note: simultaneous identification of CSN1S2 A, B, C, and E alleles in goats by polymerase chain reaction-single strand conformation polymorphism

Most variability in goat caseins originates from the high number of genetic polymorphisms often affecting the specific protein expression, with strong effects on milk composition traits and technological properties. At least 7 alleles have been found in the goat α_S2-CN gene (CSN1S2). Five of them (CSN1S2*A, CSN1S2*B, CSN1S2*C, CSN1S2*E, and CSN1S2*F) are widespread in most breeds, whereas the other 2 (CSN1S2*D and CSN1S2*0) are rarer alleles. Four different PCR-RFLP tests are needed to detect all of these variants at the DNA level. The objective of this study was to develop and validate a rapid method for typing 4 of the 5 most-common goat CSN1S2 alleles by means of PCR-single strand conformation polymorphism (SSCP). The method was validated by analyzing 37 goat samples at the protein and DNA level, respectively, by milk isoelectrofocusing and PCR-RFLP methods already described. The genotypes obtained using the PCR-SSCP approach were in full agreement with those obtained by the validation analyses. The newly developed PCR-SSCP approach provides an accurate and inexpensive assay highly suitable for genotyping goat CSN1S2.     

A simultaneous triplex TaqMan real-time PCR approach for authentication of caprine and bovine meat,milk and cheese

Goat foodstuffs are considered as healthy foods with high nutritional value. This study demonstrated the development and validation of a triplex real-time PCR on the basis of species-specific and species-conservative TaqMan probes for the simultaneous identification of caprine and bovine DNA in meats, milk and cheeses with a prerequisite designed endogenous control. In this research, caprine and bovine meat, milk and cheese were specifically identified via developed primers and probes, and the limits of detection of this methodology were 0.005 and 0.01 ng DNA of milk and cheese from goat, and 0.01 and 0.05 ng DNA of milk and cheese from cow. Taken together, this approach was elaborated to address dairy adulteration issues to eliminate the fraud of economically motivated goat milk and cheese adulteration by adding cow milk.     

Segmentation in projective mapping

Projective mapping (PM) or napping® has attained much attention in recent literature as a method for fast sensory profiling and measurement of consumer perception. However, little work has been done to understand the consumer’s individual differences in these experiments. In this work, segmentation criteria based on the Procrustes distance are explored. The Procrustes distance can be applied with hierarchical clustering using the Proclustrees method, which consists of doing hierarchical clustering on the pairwise Procrustes distance between consumers. An alternative strategy called sequential clusterwise rotations (SCR) is proposed. SCR extracts clusters by a sequentially partitioning obtained by combining fuzzy clustering techniques and general Procrustes analysis. The methods were tested on simulated and real data and compared with clustering based on MFA results. The simulations show that the MFA approach was outperformed by the other methods when the underlying classes were of same size and there are noise configurations present in the data. For the real data, all methods provided at last one cluster similar to the consensus but differed with respect to the number of clusters identified as well as the interpretation of the clusters. Differences between the methodologies point out the need for external cluster validation in such experiments.     

The comparability of consumers’ behavior in virtual reality and real life: A validation study of virtual reality based on a ranking task

The comparability or similarity of consumers’ behavior in virtual reality (VR) and in real life (RL) is indispensable to successfully take advantage of VR technology in consumer behavior (CB) research. This study investigated the comparability of participants’ behavior in a virtual environment and in RL to validate VR for data acquisition in CB research. Participants (N = 98) were randomly assigned to a RL condition or a VR condition in which the settings were chosen to mimic a RL environment as closely as possible. In both conditions, participants ranked 20 types of commercial breakfast cereal by their perceived healthiness from healthy to unhealthy. We observed that the perceived healthiness of the 20 cereals in the VR and RL conditions were highly correlated (r_s = 0.91, p < .001, N = 20). The information-seeking behavior was not different between the two conditions, t (96) = −1.11, p = .27. Furthermore, the attributes employed by the participants to evaluate the healthiness of the cereals did not vary between the two conditions. The presence level of the participants in the virtual environment was also examined. The results illustrate that the participants’ behavior in the virtual environment and in the real world were comparable, which provides robust evidence for the validity of VR as a beneficial and promising tool for data acquisition in CB research.     

Fourier Transform Near-Infrared Spectroscopy to Predict the Gross Energy Content of Food Grade Legumes

The feasibility of Fourier transform near-infrared reflectance spectroscopy (FT-NIRS) for determining gross energy content in different food legumes has been investigated. Eighty food-grade legume samples were obtained from different retailers and local markets in Hungary and they included 42 common beans (Phaseolus vulgaris L.), 20 peas (Pisum sativum L.), 10 lentils (Lens culinaris L.), and 8 soya beans (Glycine max L.) both as full fat food and defatted. The samples were analyzed by an adiabatic bomb calorimeter and then scanned in a Bruker MPA FT-NIR Analyzer (800–2,500 nm). Two algorithms for spectral selection of calibration and validation samples, which represent variability encountered in the full population, were tested. Partial least squares regression were developed for the prediction of gross energy using four different spectral preprocessing methods (first and second derivative alone and combined with standard normal variation and multiplicative scatter correction). The results show that first derivative produced the most accurate results with very high coefficient of determinations in validation (<93 %) and with very low standard errors of validation (<0.025 kcal/g) as compared to the standard error of the reference method (0.204 kcal/g).     

Which front-of-pack nutrition label is the most efficient one? The results of an eye-tracker study

Different labeling systems that should help consumers make more balanced food decisions have been proposed and are currently in use. In the present study, the effectiveness of three different formats, the nutrition table format, the guideline daily amounts (GDAs) format, and the traffic light (TL) format, was examined. The eye-tracking method was combined with an experimental approach. The participants (N = 98) were randomly assigned to one of the three formats, and they were asked to evaluate the healthiness of five foods from different food categories. The eye-tracking data suggest that the participants needed more time to process the GDA format in comparison to the traffic light format and the nutrition table format. Moreover, the participants processed the traffic light format more efficiently than the nutrition table. In regard to information processing, the traffic light format was better than the other two formats. The participants were asked how they perceived the healthiness of the food products. The GDA, the TL and the nutrition table formats did not result in substantially different evaluations of the products. From an information processing perspective, the TL format has advantages over the other two formats. The TL format is a consumer-friendly way of communicating nutrition information.     

Development of a single nucleotide polymorphism genotyping microarray platform for the identification of bovine milk protein genetic polymorphisms

The objective of this study was to develop and validate a fast method for typing the main mutations of bovine milk protein genes by using microarray technology. An approach based on the ligation detection reaction (LDR) and a universal array (UA) was used. Polymorphisms in both the coding and noncoding sequences of α_S1-casein, β-casein, κ-casein, and β-lactoglobulin genes were considered because of their well-known effects on milk composition and cheese production. A total of 22 polymorphic sites, corresponding to 21 different variants, were included in the diagnostic microarray. First, a multiplex PCR was developed to amplify all the DNA target sequences simultaneously. Second, the LDR-UA assay was implemented. The method was validated by analyzing 100 Italian Friesian DNA samples, which were also genotyped by conventional methods both at the protein level by means of milk isoelectrofocusing and at the molecular level using PCR-RFLP and PCR-single strand conformation polymorphism techniques. The genotypes obtained using the LDR-UA approach were in full agreement with those obtained by the conventional analyses. An important result of the LDR-UA assay was a more accurate genotyping of the different milk protein alleles than was found with conventional typing methods. At the κ-casein gene, in fact, 4 samples were heterozygous (3 reference samples and 1 validation sample) for an allele coding for Thr₁₃₆ and Ala₁₄₈. This variant, which can be considered as the wild type of the genus Bos, is not usually identifiable by the conventional typing methods used. The multiplex PCR-LDR-UA approach developed provides for an accurate, inexpensive, and high-throughput assay that does not exhibit false positive or false negative signals, thus making it highly suitable for animal genotyping.     

Consumer acceptability and purchase intent of traditional Korean soup in the United States and Japan

Samgyetang and yukgaejang are relatively unknown to US and Japanese consumers. This study was conducted 1) to identify how flavor modification and previous consumption affect foreign consumer liking of these foods, and 2) to examine the effect of information on purchase intent. Traditional and modified types were prepared based on focus group interviews that included 13 US and 16 Japanese consumers residing in Korea. A consumer test was then conducted with 104 participants for samgyetang and 106 participants for yukgaejang in the US, and 100 participants for both foods in Japan. Liking scores for these new foods were mainly influenced by flavor modification, with a strong preference for the modified types over the traditional types. Liking of foods that were more familiar to consumers was influenced more by previous consumption experience. The purchase intent was increased after information about the foods was provided.     

A new proposed validation method for low energy electron beam processing of dry spices

Food processing with ionizing technologies must comply with validation requirements laid out by national regulatory bodies and international standards. This paper describes a new proposed method to meet the requirements for microbial decontamination treatment of spices and herbs with low-energy electron beam (LEEB) processing. The demonstration of robust process and product qualification protocols is necessary for regulatory approval and adoption of LEEB process in the food industry. The bulk flow of loose seeds was measured and optimized for treatment, a dosimetry system implemented, and methods for assessing Salmonella spp. reduction were developed combining high- and low-energy electron beam microbial inactivation data. Data is presented indicating 5-log reduction of Salmonella enterica serovar Rissen on black peppercorns, demonstrating the effectiveness of the LEEB treatment. The validation method described in this paper is applicable to most loose, dry, whole spices and herbs.     

Simultaneous determination of ascorbic and dehydroascorbic acids in vegetables and fruits by liquid chromatography with tandem-mass spectrometry

This work describes an analytical method using liquid chromatography coupled with tandem-mass spectrometry (LC–MS/MS) with triple quadrupole in selective reaction monitoring mode for the simultaneous determination of ascorbic acid (AA) and dehydroascorbic acid (DHAA) in pepper, tomato, orange and lemon. The negative ion mode of ESI and MS/MS transitions of m/z 173→143 and m/z 173→71 were used for AA and m/z 175→115 and m/z 175→87 for DHAA. All the validation parameters were found to be within the range of acceptance for both compounds. Different matrix effects were observed in the studied vegetables and samples were quantified by the standard addition approach. The proposed method was suitable for simultaneously determining AA and DHAA with no need for oxidation/reduction or derivatisation steps. The main advantages of this method are its simplicity (little sample preparation), speed (total analysis time does not exceed 5 min) and excellent sensitivity (limits of detection (LODs) of 13 and 11 ng/ml for AA and DHAA, respectively).     

Just-about-right and ideal scaling provide similar insights into the influence of sensory attributes on liking

Just-about-right (JAR) scaling is criticized for measuring attribute intensity and acceptability simultaneously. Using JAR scaling, an attribute is evaluated for its appropriateness relative to one’s hypothetical ideal level that is pre-defined at the middle of a continuum. Alternatively, ideal scaling measures these two constructs separately. Ideal scaling allows participants to rate their ideal freely on the scale (i.e., without assuming the “Too Little” and “Too Much” regions are equal in size). We hypothesized that constraining participants’ ideal to the center point, as is done in the JAR scale, may cause a scaling bias and, thereby, influence the magnitude of “Too Little” and “Too Much”. Furthermore, we hypothesized that the magnitude of “Too Little” and “Too Much” would influence liking to different extents.Coffee-flavored dairy beverages (n = 20) were formulated using a fractional, constrained-mixture design that varied the ratio of water, milk, coffee extract, and sucrose. Participants tasted 4 of 20 prototypes that were served in a monadic sequential order using a balanced incomplete block design. Data reported here are for participants randomly assigned to one of two research conditions: ideal scaling (n = 129) or JAR scaling (n = 132). For both conditions, participants rated overall liking using a 9-point hedonic scale. Four attributes (sweetness, milk flavor, coffee flavor and thickness) were evaluated. The reliability of an individual participant’s ideal rating for an attribute was evaluated using the standard deviation of their ideal ratings (n = 4). All data from a participant were eliminated from further analyses when his/her standard deviation of the ideal ratings for any of the four rated attributes was identified as a statistical outlier. This resulted in the elimination of 15 of 129 (12%) of participants in the ideal scaling group. Multiple linear regression was employed to model liking as a function of “Too Little” or “Too Much” attribute intensities.Mean ideal ratings (averaged across participants) for all four attributes were significantly different from the central point of the scale (i.e., 50). However, coffee flavor was the only attribute for which the mean ideal rating (57.2) fell outside the central 10% (45.0–55.0). Even so, the magnitude of “Too Little” and “Too Much” was not affected by the scaling method. The influence of the magnitude of “Too Little” and “Too Much” on liking was asymmetrical. Both scaling methods agreed that sweetness and coffee flavor were the main sensory attributes affecting liking. Overall, JAR scaling and ideal scaling were comparable for measuring “Too Little” and “Too Much”, and identifying the main factors affecting liking.     

Quantification of Fishmeal in Compound Feed Using NIR Spectroscopy

Analysis of fishmeal concentrations in feedstuff is critical to quality control and ingredient statement of commercial feed. Near-infrared reflectance spectroscopy (NIRS) determination for fishmeal was established through the spectral data processed by mean center, normalization, Savitzky–Golay first, partial least square 1 and cross validation. The coefficient of determination (R ²) of NIRS calibration model, the standard error estimated by cross validation (SECV) were 0.9554 and 0.9541, respectively. At the same time, the coefficient of determination of validation was 0.9867. Moreover, it has been proven to be directly correlated between the fishmeal spectra and the loading of the second principal components, and the coefficient of determination of the spectra of the calibration model. These results support our theory that the NIRS method constructed in our study could be used to quantify fishmeal in compound feeds.     

Analysis of non-fat soybean powder for the mass fractions of three elements: Copper and zinc by isotope dilution ICP–MS and calcium by ICP–AES

Isotope dilution inductively coupled plasma–mass spectrometry with “approximate match” approach was developed for the measurement of mass fractions of Cu and Zn. An “approximate match” (within 10%) was made between calibration and sample blends. The method was validated against two certified reference materials, namely NIST SRM 1515 (Apple Leaves) and IAEA-359 (Cabbage). Inductively coupled plasma-atomic emission spectrometry with bracketing technique was developed for the measurement of mass fraction of Ca. NIST RM 8412 (Corn Stalk) was employed for method validation purposes. The validated methods were applied to the measurement of Cu, Zn and Ca in a sample of non-fat soybean pertaining to the international comparison CCQM-P64. The results submitted for the comparison were in excellent agreement with the mean values of all participants’ results. Relative standard uncertainties of about 4% (k = 2, which gives a level of confidence of approximately 95%) were achieved in the measurement of the three elements concerned.     

Ergebnisse, Schlussfolgerungen und Empfehlungen aus zwei Ringversuchen zum Nachweis und zur Isolierung von Shiga (Vero) Toxin bildenden Escherichia coli (STEC) aus Hackfleischproben

For quality assurance the National Reference Laboratory for Escherichia coli at the Federal Institute for Risk Assessment had organized two ring trials in 2008 and 2009 (called RV2008 and RV2009) on the detection and isolation of Shiga toxin producing Escherichia coli (STEC) from minced beef samples. There were 23 (RV2008) and 26 (RV2009) participants from institutions dealing with the microbiological control of food. For the analysis, the participants received five samples of minced meat containing STEC and four samples without STEC. By comparing the results, a significant improvement of detection sensitivity and specificity was observed for RV2009. In RV2008, only 4 (17.4%) of the participants had identified all STEC-positive samples, compared to 14 (53.8%) in RV2009. The number of false-positive findings decreased from 17.4% (RV2008) to 3.8% (RV2009). Statistically significant differences between the participating laboratories were found by determination of concordance odds ratios. Most participants used methods for detection and isolation of STEC based on protocols that are officially recommended in Germany (§64 LFGB), such as Shiga toxin (Stx) ELISA/Colony Immunoblot, or stx-PCR/DNA colony hybridization. A strikingly low sensitivity when using the Stx-ELISA as detection method was observed for RV2008. This finding could be attributed to the use of a commercial Stx-ELISA (Novitek Veterinär) that showed deficiencies for identification of Stx1 and some variants of Stx2. It is recommended to use only detection systems that have been independently evaluated for their specificity and sensitivity. Real-time stx-PCR as a new method has been increasingly used and proved to be promising. The detection of enterohaemorrhagic E. coli O157: [H7] as the most common cause of Haemorrhagic Colitis (HC) and Haemolytic Uraemic Syndrome (HUS) should be improved by introduction of specific procedures (ISO16654), since only 2 of 26 participants successfully isolated this agent from a minced meat sample that contained two STEC strains.