A reversed-phased HPLC method that allows the separation and simultaneous determination of the preservatives benzoic (BA) and sorbic acids (SA), methyl- (MP) and propylparabens (PP) is described. The separations were effected by using an initial mobile phase of methanol-acetate buffer (pH 4.4) (35:65) to elute BA, SA and MP and changing the mobile phase composition to methanol-acetate buffer (pH 4.4) (50:50) thereafter. The detector wavelength was set at 254 nm. Under these conditions, separation of the four components was achieved in less than 23 min. Analytical characteristics of the separation such as limit of detection, limit of quantification, linear range and reproducibility were evaluated. The developed method was applied to the determination of 67 foodstuffs (mainly imported), comprising soft drinks, jams, sauces, canned fruits/vegetables, dried vegetables/fruits and others. The range of preservatives found were from not detected (nd)--1260, nd--1390, nd--44.8 and nd--221 mg kg(-1) for BA, SA, MP and PP, respectively.
A study was conducted to detect and quantify lard stearin (LS) content in canola oil (CaO) using differential scanning calorimetry (DSC). Authentic samples of CaO were obtained from a reliable supplier and the adulterant LS were obtained through a fractional crystallization procedure as reported previously. Pure CaO samples spiked with LS in levels ranging from 5 to 15% (w/w) were analyzed using DSC to obtain their cooling and heating profiles. The results showed that samples contaminated with LS at 5% (w/w) level can be detected using characteristic contaminant peaks appearing in the higher temperature regions (0 to 70°C) of the cooling and heating curves. Pearson correlation analysis of LS content against individual DSC parameters of the adulterant peak namely peak temperature, peak area, peak onset temperature indicated that there were strong correlations between these with the LS content of the CaO admixtures. When these three parameters were engaged as variables in the execution of the stepwise regression procedure, predictive models for determination of LS content in CaO were obtained. The predictive models obtained with single DSC parameter had relatively lower coefficient of determination (R(2) value) and higher standard error than the models obtained using two DSC parameters in combination. This study concluded that the predictive models obtained with peak area and peak onset temperature of the adulteration peak would be more accurate for prediction of LS content in CaO based on the highest coefficient of determination (R(2) value) and smallest standard error.
The authentication of food products from the presence of non-allowed components for certain religion like lard is very important. In this study, we used proton Nuclear Magnetic Resonance ((1)H-NMR) spectroscopy for the analysis of butter adulterated with lard by simultaneously quantification of all proton bearing compounds, and consequently all relevant sample classes. Since the spectra obtained were too complex to be analyzed visually by the naked eyes, the classification of spectra was carried out.The multivariate calibration of partial least square (PLS) regression was used for modelling the relationship between actual value of lard and predicted value. The model yielded a highest regression coefficient (R(2)) of 0.998 and the lowest root mean square error calibration (RMSEC) of 0.0091% and root mean square error prediction (RMSEP) of 0.0090, respectively. Cross validation testing evaluates the predictive power of the model. PLS model was shown as good models as the intercept of R(2)Y and Q(2)Y were 0.0853 and -0.309, respectively.
Being the third-largest primate population has not made macaque (Macaca fascicularis sp.) monkeys less exposed to threats and dangers. Despite wildlife protection, they have been widely hunted and consumed in several countries because of their purported nutritional values. In addition to trading as pure bush meats in several places, monkey meat has been sold in meatball and soup products in Indonesia. Thus the possibility of macaque meat trafficking under the label of common meats is quite high. This paper reports the development of a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) assay with the shortest amplicon length for the confirmed detection of monkey meat under compromised states which are known to degrade DNA. We amplified a 120-bp region of d-loop gene using a pair of macaque-specific primers and confirmed their specificity for the target species through cross-challenging against 17 different species using a 141-bp site of an 18 S rRNA gene as an endogenous control for eukaryotes. This eliminated the possibilities of any false-negative detection with complex matrices or degraded specimens. The detection limit was 0.00001 ng DNA in a pure state and 0.1% of meat in mixed matrices and commercial meatball products. RFLP analysis further authenticated the originality of the PCR product and distinctive restriction patterns were found upon AluI and CViKI-1 digestion. A micro-fluidic lab-on-a-chip automated electrophoretic system separated the fragments with high resolution. The assay was validated for screening commercial meatball products with sufficient internal control.
An amperometric enzyme-electrode was introduced where glucose oxidase (GOD) was immobilized on chitosan membrane via crosslinking, and then fastened on a platinum working electrode. The immobilized enzyme showed relatively high retention activity. The activity of the immobilized enzyme was influenced by its loading, being suppressed when more than 0.6 mg enzyme was used in the immobilization. The biosensor showing the highest response to glucose utilized 0.21 ml/cm2 thick chitosan membrane. The optimum experimental conditions for the biosensors in analysing glucose dissolved in 0.1 M phosphate buffer (pH 6.0) were found to be 35°C and 0.6 V applied potential. The introduced biosensor reached a steady-state current at 60 s. The apparent Michaelis-Menten constant ([Formula: see text]) of the biosensor was 14.2350 mM, and its detection limit was 0.05 mM at s/n > 3, determined experimentally. The RSD of repeatability and reproducibility of the biosensor were 2.30% and 3.70%, respectively. The biosensor was showed good stability; it retained ~36% of initial activity after two months of investigation. The performance of the biosensors was evaluated by determining the glucose content in fruit homogenates. Their accuracy was compared to that of a commercial glucose assay kit. There was no significance different between two methods, indicating the introduced biosensor is reliable.
A total of 126 food samples, categorised into three groups (seafood and seafood products, meat and meat products, as well as milk and dairy products) from Malaysia were analysed for polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs). The concentration of PCDD/Fs that ranged from 0.16 to 0.25 pg WHO05-TEQ g(-1) fw was found in these samples. According to the food consumption data from the Global Environment Monitoring System (GEMS) of the World Health Organization (WHO), the dietary exposures to PCDD/F from seafood and seafood products, meat and meat products, as well as milk and dairy products for the general population in Malaysia were 0.064, 0.183 and 0.736 pg WHO05-TEQ kg(-1) bw day(-1), respectively. However, the exposure was higher in seafood and seafood products (0.415 pg WHO05-TEQ kg(-1) bw day(-1)) and meat and meat products (0.317 pg WHO05-TEQ kg(-1) bw day(-1)) when the data were estimated using the Malaysian food consumption statistics. The lower exposure was observed in dairy products with an estimation of 0.365 pg WHO05-TEQ kg(-1) bw day(-1). Overall, these dietary exposure estimates were much lower than the tolerable daily intake (TDI) as recommended by WHO. Thus, it is suggested that the dietary exposure to PCDD/F does not represent a risk for human health in Malaysia.
A simple visual ethanol biosensor based on alcohol oxidase (AOX) immobilised onto polyaniline (PANI) film for halal verification of fermented beverage samples is described. This biosensor responds to ethanol via a colour change from green to blue, due to the enzymatic reaction of ethanol that produces acetaldehyde and hydrogen peroxide, when the latter oxidizes the PANI film. The procedure to obtain this biosensor consists of the immobilization of AOX onto PANI film by adsorption. For the immobilisation, an AOX solution is deposited on the PANI film and left at room temperature until dried (30 min). The biosensor was constructed as a dip stick for visual and simple use. The colour changes of the films have been scanned and analysed using image analysis software (i.e., ImageJ) to study the characteristics of the biosensor's response toward ethanol. The biosensor has a linear response in an ethanol concentration range of 0.01%-0.8%, with a correlation coefficient (r) of 0.996. The limit detection of the biosensor was 0.001%, with reproducibility (RSD) of 1.6% and a life time up to seven weeks when stored at 4 °C. The biosensor provides accurate results for ethanol determination in fermented drinks and was in good agreement with the standard method (gas chromatography) results. Thus, the biosensor could be used as a simple visual method for ethanol determination in fermented beverage samples that can be useful for Muslim community for halal verification.
In dairy product sector, butter is one of the potential sources of fat soluble vitamins, namely vitamin A, D, E, K; consequently, butter is taken into account as high valuable price from other dairy products. This fact has attracted unscrupulous market players to blind butter with other animal fats to gain economic profit. Animal fats like mutton fat (MF) are potential to be mixed with butter due to the similarity in terms of fatty acid composition. This study focused on the application of FTIR-ATR spectroscopy in conjunction with chemometrics for classification and quantification of MF as adulterant in butter. The FTIR spectral region of 3910-710 cm⁻¹ was used for classification between butter and butter blended with MF at various concentrations with the aid of discriminant analysis (DA). DA is able to classify butter and adulterated butter without any mistakenly grouped. For quantitative analysis, partial least square (PLS) regression was used to develop a calibration model at the frequency regions of 3910-710 cm⁻¹. The equation obtained for the relationship between actual value of MF and FTIR predicted values of MF in PLS calibration model was y = 0.998x + 1.033, with the values of coefficient of determination (R²) and root mean square error of calibration are 0.998 and 0.046% (v/v), respectively. The PLS calibration model was subsequently used for the prediction of independent samples containing butter in the binary mixtures with MF. Using 9 principal components, root mean square error of prediction (RMSEP) is 1.68% (v/v). The results showed that FTIR spectroscopy can be used for the classification and quantification of MF in butter formulation for verification purposes.
A simple and selective RP-HPLC-UV method with SPE was developed and validated for the quantification of cefotaxime in all-in-one total parenteral nutrition (AIO-TPN) admixtures. Chromatographic separation was achieved on a 5 pm particle size C18 DB column (250 x 4.6 mm id) using the mobile phase ammonium acetate (25 mM, pH 4.0)-50% acetonitrile in methanol (80 + 20, v/v). The flow rate was 0.9 mL/min and the detection wavelength was 254 nm. The analyte was extracted from AIO-TPN admixtures by means of an SPE method. The cefotaxime calibration curve was linear over a concentration range of 100-1400 microg/mL with a correlation coefficient of > or = 0.9994. The intraday accuracy and precision for cefotaxime were < or = -3.15 and < or = 3.08%, respectively, whereas the interday accuracy and precision were < or = -2.48 and < or = 2.25%, respectively. The method was successfully applied to stability studies of cefotaxime in the presence of micronutrients together with low and high concentrations of macronutrients in AIO-TPN admixtures. Cefotaxime was degraded by 13.00 and 26.05% at room temperature (25 +/- 2 degrees C) after 72 h in low and high macronutrient concentration formulations of AIO-TPN admixtures, respectively. The values of cefotaxime degradation rates for low and high macronutrient concentration formulations of AIO-TPN admixtures were -0.164 and -0.353, respectively. These results indicated that there was a higher rate of degradation in the AIO-TPN admixture formulations containing high concentrations of macronutrients.
Gelatin is a highly purified animal protein of pig, cow, and fish origins and is extensively used in food, pharmaceuticals, and personal care products. However, the acceptability of gelatin products greatly depends on the animal sources of the gelatin. Porcine and bovine gelatins have attractive features but limited acceptance because of religious prohibitions and potential zoonotic threats, whereas fish gelatin is welcomed in all religions and cultures. Thus, source authentication is a must for gelatin products but it is greatly challenging due to the breakdown of both protein and DNA biomarkers in processed gelatins. Therefore, several methods have been proposed for gelatin identification, but a comprehensive and systematic document that includes all of the techniques does not exist. This up-to-date review addresses this research gap and presents, in an accessible format, the major gelatin source authentication techniques, which are primarily nucleic acid and protein based. Instead of presenting these methods in paragraph form which needs much attention in reading, the major methods are schematically depicted, and their comparative features are tabulated. Future technologies are forecasted, and challenges are outlined. Overall, this review paper has the merit to serve as a reference guide for the production and application of gelatin in academia and industry and will act as a platform for the development of improved methods for gelatin authentication.
Clenbuterol (CLB) is an antibiotic and illegal growth promoter drug that has a long half-life and easily remains as residue and contaminates the animal-based food product that leads to various health problems. In this work, electrochemical immunosensor based on poly(3,4-ethylenedioxythiophene)/graphene oxide (PEDOT/GO) modified screen-printed carbon electrode (SPCE) for CLB detection was developed for antibiotic monitoring in a food product. The modification of SPCE with PEDOT/GO as a sensor platform was performed through electropolymerization, while the electrochemical assay was accomplished while using direct competitive format in which the free CLB and clenbuterol-horseradish peroxidase (CLB-HRP) in the solution will compete to form binding with the polyclonal anti-clenbuterol antibody (Ab) immobilized onto the modified electrode surface. A linear standard CLB calibration curve with R² = 0.9619 and low limit of detection (0.196 ng mL-1) was reported. Analysis of milk samples indicated that this immunosensor was able to detect CLB in real samples and the results that were obtained were comparable with enzyme-linked immunosorbent assays (ELISA).
Recent foodborne outbreaks in multiple locations necessitate the continuous development of highly sensitive and specific biosensors that offer rapid detection of foodborne biological hazards. This work focuses on the development of a reduced graphene oxide‑titanium dioxide (rGO-TiO2) nanocomposite based aptasensor to detect Salmonella enterica serovar Typhimurium. A label-free aptamer was immobilized on a rGO-TiO2 nanocomposite matrix through electrostatic interactions. The changes in electrical conductivity on the electrode surface were evaluated using electroanalytical methods. DNA aptamer adsorbed on the rGO-TiO2 surface bound to the bacterial cells at the electrode interface causing a physical barrier inhibiting the electron transfer. This interaction decreased the DPV signal of the electrode proportional to decreasing concentrations of the bacterial cells. The optimized aptasensor exhibited high sensitivity with a wide detection range (108 to 101 cfu mL-1), a low detection limit of 101 cfu mL-1 and good selectivity for Salmonella bacteria. This rGO-TiO2 aptasensor is an excellent biosensing platform that offers a reliable, rapid and sensitive alternative for foodborne pathogen detection.
The influence of temperature-time combinations on non-volatile compound and taste traits of beef semitendinosus muscles tested by the electronic tongue was studied. Single-stage sous-vide at 60 and 70 °C (6 and 12 h), and two-stage sous-vide that sequentially cooked at 45 °C (3 h) and 60 °C (either 3 or 9 h) were compared with traditional cooking at 70 °C (30 min). Umami was better explained in the given model of partial least squares regression than astringency, sourness, saltiness, bitterness, and richness. Sous-vide at 70 °C for 12 h characterized the most umami, likely adenosine-5'-monophosphate (AMP) and guanosine-5'-monophosphate (GMP) as significant contributors. Two-stage sous-vide projected higher histidine, leucine, inosine, and hypoxanthine with the astringent and sour taste significant after 6 and 12 h cooking, respectively. Equivalent umami concentration (EUC) between umami amino acids and umami nucleotides showed a strong relationship to umami taste assessed by the electronic tongue.
The Malayan box turtle (Cuora amboinensis) (MBT) is a vulnerable and protected species widely used in exotic foods and traditional medicines. Currently available polymerase chain reaction (PCR) assays to identify MBT lack automation and involve long targets which break down in processed or denatured tissue. This SYBR Green duplex real-time PCR assay has addressed this research gap for the first time through the combination of 120- and 141-bp targets from MBT and eukaryotes for the quantitative detection of MBT DNA in food chain and herbal medicinal preparations. This authentication ensures better security through automation, internal control and short targets that were stable under the processing treatments of foods and medicines. A melting curve clearly demonstrated two peaks at 74.63 ± 0.22 and 78.40 ± 0.31°C for the MBT and eukaryotic products, respectively, under pure, admixed and commercial food matrices. Analysis of 125 reference samples reflected a target recovery of 93.25-153.00%, PCR efficiency of 99-100% and limit of detection of 0.001% under various matrices. The quantification limits were 0.00001, 0.00170 ± 0.00012, 0.00228 ± 0.00029, 0.00198 ± 0.00036 and 0.00191 ± 0.00043 ng DNA for the pure meat, binary mixtures, meatball, burger and frankfurter products, respectively. The assay was used to screen 100 commercial samples of traditional Chinese herbal jelly powder from eight different brands; 22% of them were found to be MBT-positive (5.37 ± 0.50-7.00 ± 0.34% w/w), which was reflected through the Ct values (26.37 ± 0.32-28.90 ± 0.42) and melting curves (74.63-78.65 ± 0.22°C) of the amplified MBT target (120 bp), confirming the speculation that MBT materials are widely used in Chinese herbal desserts, exotic dishes consumed with the hope of prolonging life and youth.
The major compounds in honey are carbohydrates such as monosaccharides and disaccharides. The same compounds are found in cane-sugar concentrates. Unfortunately when sugar concentrate is added to honey, laboratory assessments are found to be ineffective in detecting this adulteration. Unlike tracing heavy metals in honey, sugar adulterated honey is much trickier and harder to detect, and traditionally it has been very challenging to come up with a suitable method to prove the presence of adulterants in honey products. This paper proposes a combination of array sensing and multi-modality sensor fusion that can effectively discriminate the samples not only based on the compounds present in the sample but also mimic the way humans perceive flavours and aromas. Conversely, analytical instruments are based on chemical separations which may alter the properties of the volatiles or flavours of a particular honey. The present work is focused on classifying 18 samples of different honeys, sugar syrups and adulterated samples using data fusion of electronic nose (e-nose) and electronic tongue (e-tongue) measurements. Each group of samples was evaluated separately by the e-nose and e-tongue. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were able to separately discriminate monofloral honey from sugar syrup, and polyfloral honey from sugar and adulterated samples using the e-nose and e-tongue. The e-nose was observed to give better separation compared to e-tongue assessment, particularly when LDA was applied. However, when all samples were combined in one classification analysis, neither PCA nor LDA were able to discriminate between honeys of different floral origins, sugar syrup and adulterated samples. By applying a sensor fusion technique, the classification for the 18 different samples was improved. Significant improvement was observed using PCA, while LDA not only improved the discrimination but also gave better classification. An improvement in performance was also observed using a Probabilistic Neural Network classifier when the e-nose and e-tongue data were fused.
The performance of gas chromatography (GC) combined with a hybrid quadrupole time-of-flight (QTOF) mass spectrometry (MS) system for the determination of volatile and semi-volatile compounds in honey samples is evaluated. After headspace (HS) solid-phase microextraction (SPME) of samples, the accurate mass capabilities of the above system were evaluated for compounds identification. Accurate scan electron impact (EI) MS spectra allowed discriminating compounds displaying the same nominal masses, but having different empirical formulae. Moreover, the use of a mass window with a width of 0.005 Da provided highly specific chromatograms for selected ions, avoiding the contribution of interferences to their peak areas. Additional information derived from positive chemical ionization (PCI) MS spectra and ion product scan MS/MS spectra permitted confirming the identity of novel compounds. The above possibilities are illustrated with examples of honey aroma compounds, belonging to different chemical classes and containing different elements in their molecules. Examples of compounds whose structures could not be described are also provided. Overall, 84 compounds, from a total of 89 species, could be identified in 19 honey samples from 3 different geographic areas in the world. The suitability of responses measured for selected ions, corresponding to above species, for authentication purposes is assessed through principal components analysis.
INTRODUCTION: There is a lack of information on the trans fatty acid (TFA) content in Malaysian foods. The objective of this study is to determine the TFA content of bakery products, snacks, dairy products, fast foods, cooking oils and semisolid fats, and breakfast cereals and Malaysian fast foods. This study also estimated the quantity of each isomer in the foods assayed.
METHODS: The trans fatty acid content of each food sample was assessed in duplicate by separating the fatty acid methyl esters (FAME) in a gas chromatography system equipped with HP-88 column (USA: split ratio 10: 1) for cis/trans separation. Five major TFA isomers, palmitoelaidic acid (16: 1t9), petroselaidic acid (18:1t6), elaidic acid (18:1t9), vaccenic acid (18: 1t11) and linoelaidic acid (18:2t9, 12), were measured using gas chromatography (GC) and the data were expressed in unit values of g/100 g lipid or g/100 g food.
RESULTS: The total TFA contents in the studied foods were < 0.001 g-8.77 g/100 g lipid or < 0.001 g-5.79 g/100 g foods. This value falls within the standard and international recommendation level for TFA. The measured range of specific TFA isomers were as follows: palmitoelaidic acid (< 0.001 g-0.26 g/100 g lipid), petroselaidic acid (< 0.001 g - 3.09 g/100 g lipid), elaidic acid (< 0.001 g-0.87 g/100 g lipid), vaccenic acid (< 0.001 g-0.41 g/100 g lipid) and linoelaidic acid (< 0.001 g-6.60 g/100 g lipid).
CONCLUSION: These data indicate that most of the tested foods have low TFA contents (< 1 g/100 g lipid).
A new extraction and cleanup procedure with gas chromatography was developed for the sensitive determination of acephate, dimethoate, malathion, diazinon, quinalphos, chlorpyrifos, profenofos, alpha-endosulfan, beta-endosulfan, chlorothalonil and carbaryl using 1-chloro-4-fluorobenzene as an internal standard in fruits and vegetables. Several extracting and eluting solvents for solid-phase extraction were investigated. The overall extracting solvent with a mixture of acetone:ethyl acetate:hexane (10:80:10, v/v/v) and a eluting solvent of 5% acetone in hexane used with the RPC18 cartridge gave the best recovery for all of the investigated pesticides, and minimized the interference from co-extractants. Under the optimal extraction and clean-up conditions, recoveries of 85 - 99% with RSD < 5.0% (n = 3) for most of the pesticides at the 0.02 - 0.5 mg/kg level were obtained. The limit of detection was between 0.005 - 0.01 mg/kg and the limit of quantification was 0.01 mg/kg. This analytical procedure was characterized with high accuracy and acceptable sensitivity to meet requirements for monitoring pesticides in crops.
Fourier transform infrared spectroscopy (FTIR) combined with multivariate calibration of partial least square (PLS) was developed and optimized for the analysis of Nigella seed oil (NSO) in binary and ternary mixtures with corn oil (CO) and soybean oil (SO). Based on PLS modeling performed, quantitative analysis of NSO in binary mixtures with CO carried out using the second derivative FTIR spectra at combined frequencies of 2977-3028, 1666-1739, and 740-1446 cm(-1) revealed the highest value of coefficient of determination (R (2), 0.9984) and the lowest value of root mean square error of calibration (RMSEC, 1.34% v/v). NSO in binary mixtures with SO is successfully determined at the combined frequencies of 2985-3024 and 752-1755 cm(-1) using the first derivative FTIR spectra with R (2) and RMSEC values of 0.9970 and 0.47% v/v, respectively. Meanwhile, the second derivative FTIR spectra at the combined frequencies of 2977-3028 cm(-1), 1666-1739 cm(-1), and 740-1446 cm(-1) were selected for quantitative analysis of NSO in ternary mixture with CO and SO with R (2) and RMSEC values of 0.9993 and 0.86% v/v, respectively. The results showed that FTIR spectrophotometry is an accurate technique for the quantitative analysis of NSO in binary and ternary mixtures with CO and SO.
Graphene-magnetite composite (G-Fe3O4) was successfully synthesized and applied as adsorbent for magnetic solid phase extraction (MSPE) of two phenolic acids namely 4-hydroxybenzoic acid (4-HB) and 3,4-dihydroxybenzoic acid (3,4-DHB) from stingless bee honey prior to analysis using high performance liquid chromatography with ultraviolet-visible detection (HPLC-UV/Vis). Several MSPE parameters affecting extraction of these two acids were optimized. Optimum MSPE conditions were 50 mg of G-Fe3O4 adsorbent, 5 min extraction time at 1600 rpm, 30 mL sample volume, sample solution pH 0.5, 200 µL methanol as desorption solvent (5 min sonication assisted) and 5% w/v NaCl. The LODs (3 S/N) calculated for 4-HB and 3,4-DHB were 0.08 and 0.14 µg/g, respectively. Good relative recoveries (72.6-110.6%) and reproducibility values (RSD