One-class model with two decision thresholds for the rapid detection of cashew nuts adulteration by other nuts

A green screening method to determine cashew nut adulteration with Brazilian nut, pecan nut, macadamia nut and peanut was proposed. The method was based on the development of a one-class soft independent modelling of class analogy (SIMCA) model for non-adulterated cashew nuts using near-infrared (NIR) spectra obtained with portable equipment. Once the model is established, the assignment of unknown samples depends on the threshold established for the authentic class, which is a key aspect in any screening approach. The authors propose innovatively to define two thresholds: lower model distance limit and upper model distance limit. Samples with distances below the lower threshold are assigned as non-adulterated with a 100% probability; samples with distance values greater than the upper threshold are assigned as adulterated with a 100% probability; and samples with distances within these two thresholds will be considered uncertain and should be submitted to a confirmatory analysis. Thus, the possibility of error in the sample assignment significantly decreases. In the present study, when just one threshold was defined, values greater than 95% for the optimized threshold were obtained for both selectivity and specificity. When two class thresholds were defined, the percentage of samples with uncertain assignment changes according to the adulterant considered, highlighting the case of peanuts, in which 0% of uncertain samples was obtained. Considering all adulterants, the number of samples that were submitted to a confirmatory analysis was quite low, 5 of 224 adulterated samples and 3 of 56 non-adulterated samples.

Effect of thermal processing on the antigenicity of allergenic milk, egg and soy proteins

The detection of allergenic proteins and the influence of processing on the structure and antigenicity of these proteins are relevant topics. Using commercial enzyme-linked immunosorbent assay kits, this study aimed to evaluate the degradation profiles of milk, egg and soy proteins during the processing of semisweet biscuits. The formulations were baked under different conditions according to a complete factorial experiment that included a three-level temperature factor and a six-level time factor. β-lactoglobulin and egg white proteins were severely degraded, the degradation of casein was intermediate, and soy proteins were the most stable. Complete allergen protein degradation was found under only the extreme baking conditions, which resulted in products that were not sensorily acceptable. Residual levels of the proteins were detected after baking, indicating that this thermal processing reduced but did not eliminate the antigenicity of these proteins; thus, baking cannot be considered a strategy to protect allergic consumers.

Lead in Brazilian food: Exposure assessment and risk characterization

A risk assessment was performed to estimate the lead (Pb) dietary intake in the Brazilian population. Data on Pb concentration in food were obtained through a systematic review with meta-analyses and from the GEMS/Food database, both involving data through 2018. Food consumption data were obtained from a Brazilian official dietary survey. Pb dietary intakes were estimated by a deterministic approach. Risk characterisation was conducted using the margin of exposure approach (MOE). The total Pb intake in the Brazilian population ranged from 1.53 to 2.01 μg/kg bw/day. Major contributors to Pb dietary exposure were the vegetable and vegetable products and beverage categories. From the results obtained, a risk of increased systolic pressure, nephrotoxicity and decrease of 0.5 point intelligence quotient can be expected, MOE<1, with greater magnitudes of risk observed for men in rural areas and in the Midwest, Southeast and South Brazilian regions. The dietary risk assessment indicates a health concern for the Brazilian population associated with Pb dietary intake.

Lead contamination in food consumed and produced in Brazil: Systematic review and meta-analysis

This systematic review (SR) evaluated evidence of lead (Pb) levels in foods consumed or produced in Brazil. Seventy-seven publications were included in this review, corresponding to a total of 8466 food samples that were grouped into 12 food categories with similar characteristics (infant food; sugar; beverages; meat and meat products; nuts, cocoa and products; fruits and fruit products; grains, cereals and products; milk and milk products; eggs; oil and fat spreads; vegetables and vegetable products and other foods). The random model was used to establish levels of Pb in food categories. We used the software R® to perform the meta-analysis. The overall occurrence of Pb was estimated at 0.0541 mg/kg, and ranged from 0.0004 mg/kg to 0.4842 mg/kg. The SR and meta-analysis presented relevant results about Pb contamination on foods, despite the high heterogeneity. They were understood as a viable strategy to answer questions regarding prevalence of Pb which is necessary for the risk assessment of Pb intake in foods.

Variable selection for multivariate classification aiming to detect individual adulterants and their blends in grape nectars

During the quality inspection control of fruit beverages, some types of adulterations can be detected, such as the addition or substitution with less expensive fruits. To determine whether grape nectars were adulterated by substitution with apple or cashew juice or by a mixture of both, a methodology based on attenuated total reflectance Fourier transform mid infrared spectroscopy (ATR-FTIR) and multivariate classification methods was proposed. Partial least squares discriminant analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA) models were developed as multi-class methods (classes unadulterated, adulterated with cashew and adulterated with apple) with the full-spectra. PLS-DA presented better performance parameters than SIMCA in the classification of samples with just one adulterant, while poor results were achieved for samples with blends of two adulterants when using both classification methods. Three variable selection methods were tested in order to improve the effectiveness of the classification models: interval partial least squares (iPLS), variable importance in projection scores (VIP scores) and a genetic algorithm (GA). Variable selection methods improved the performance parameters for the SIMCA and PLS-DA methods when they were used to predict samples with only one adulterant. Only PLS-DA coupled with iPLS was able to classify samples with blends of two adulterants, providing sensitivity values between 100% and 83% at 100% specificity for the three studied classes.

Detection of adulterants in grape nectars by attenuated total reflectance Fourier-transform mid-infrared spectroscopy and multivariate classification strategies

There is no any doubt about the importance of food fraud control, as it has implications in food safety and in consumer health. Focusing on fruit beverages, some types of adulterations have been detected more frequently, such as substitution with less expensive fruits. A methodology based on attenuated total reflectance Fourier-transform mid-infrared spectroscopy (ATR-FTIR) and multivariate classification was applied to detect whether grape nectars were adulterated by substitution with apple juice or cashew juice. A total of 126 samples were obtained and analyzed. Two strategies were proposed: one-class and multiclass approaches. Soft independent modeling of class analogy (SIMCA), partial least squares discriminant analysis (PLS-DA) and partial least squares density modeling (PLS-DM) were used to build the models. Among them, PLS-DA presented the best performance with a sensitivity and specificity of nearly 100%. The multiclass strategy was preferred if the adulterants to be studied are known because it provides additional information.

Determination of main fruits in adulterated nectars by ATR-FTIR spectroscopy combined with multivariate calibration and variable selection methods

Grape, orange, peach and passion fruit nectars were formulated and adulterated by dilution with syrup, apple and cashew juices at 10 levels for each adulterant. Attenuated total reflectance Fourier transform mid infrared (ATR-FTIR) spectra were obtained. Partial least squares (PLS) multivariate calibration models allied to different variable selection methods, such as interval partial least squares (iPLS), ordered predictors selection (OPS) and genetic algorithm (GA), were used to quantify the main fruits. PLS improved by iPLS-OPS variable selection showed the highest predictive capacity to quantify the main fruit contents. The selected variables in the final models varied from 72 to 100; the root mean square errors of prediction were estimated from 0.5 to 2.6%; the correlation coefficients of prediction ranged from 0.948 to 0.990; and, the mean relative errors of prediction varied from 3.0 to 6.7%. All of the developed models were validated.

Accelerated solvent extraction method for the quantification of polycyclic aromatic hydrocarbons in cocoa beans by gas chromatography-mass spectrometry

An accelerated solvent extraction (ASE) procedure for use with gas chromatography-mass spectrometry (GC-MS) was optimized for the determination of eight polycyclic aromatic hydrocarbons (PAHs) in cocoa beans. Plackett-Burman and rotatable central composite design (RCCD) indicated that three variables affected the recoveries of PAHs during the extraction and purification steps: agitation time in the second liquid-liquid partition, weight of silica gel in the column, and volume of hexane for PAH elution from the column. After obtaining the optimal conditions, a single laboratory method validation was performed. Linearity was demonstrated for benzo[a]pyrene in the concentration range from 0.5 to 8.0mgkg^-1 of sample, corresponding to 1.25-20.0μgkg^-1 of cocoa on a fat basis. For the other analytes, linearity was observed from 0.75 to 8.0μgkg^-1 of sample (1.88-20.0μgkg^-1 of cocoa on a fat basis). Significant matrix effects were found for chrysene and benzo[b]fluoranthene. The precision of the method was verified with relative standard deviations (RSDs) ranging from 2.57 to 14.13% and from 4.36 to 19.77% under repeatability and intermediate precision conditions, respectively. The average recoveries of the eight PAHs ranged from 74.99 to 109.73%. These parameters, limits and measurement uncertainties met the performance criteria established by European Union regulations, except for the theoretical limit of detection for chrysene. The method was applied to the analysis of samples of Brazilian cocoa beans, and only one sample was found to have a PAH content above the maximum limit defined by the European Union legislation. This optimized and validated method is intended to be used as part of the official Brazilian monitoring programs investigating contaminants and residues in food.

An appropriate and systematized procedure for validating qualitative methods: its application in the detection of sulfonamide residues in raw milk

The lack of well-established references for the validation of qualitative analyses and the increasing demand for reliable binary responses were the main motivating factors for this study. A detailed procedure for single-laboratory validation of qualitative methods is proposed. The experimental design and the tools for data analysis were based on the theoretical background, as well as the aspects of efficiency, convenience and simplicity. Four experimental steps were defined, as follows: (i) preliminary tests for the determination of the concentration range, (ii) a study of the rates, unreliability region, detection limit, and the accordance and concordance values, (iii) a study of the selectivity in the presence of known interferences, and (iv) a study of robustness. The applicability of the procedure was demonstrated by the validation of a qualitative commercial kit for detecting sulfonamide residues in raw milk using both the visual and instrumental reading techniques. Reliability rates of 100% were obtained for the blank samples. For the samples spiked with sulfamethazine at 10.8 and 108 μg L(-1) and with sulfadimethoxine or sulfathiazole at 10 and 100 μg L(-1), the reliability rates ranged from 93.3 to 100%. Selectivity was demonstrated using trimethoprim as a potential interferent. The method was considered robust for the factors of the temperature (54 and 58°C) and time (6 and 10 min) for incubating the test strips. The estimated detection limits and unreliability regions confirmed the suitability of the kit for this purpose, based on the legislated residue limits.