The bovine milk allergenic protein, 'β-lactoglobulin' is one of the leading causes of milk allergic reaction. In this research, a novel label-free non-faradaic capacitive aptasensor was designed to detect β-lactoglobulin using a Laser Scribed Graphene (LSG) electrode. The graphene was directly engraved into a microgapped (~ 95 µm) capacitor-electrode pattern on a flexible polyimide (PI) film via a simple one-step CO2 laser irradiation. The novel hybrid nanoflower (NF) was synthesized using 1,1'-carbonyldiimidazole (CDI) as the organic molecule and copper (Cu) as the inorganic molecule via one-pot biomineralization by tuning the reaction time and concentration. NF was fixed on the pre-modified PI film at the triangular junction of the LSG microgap specifically for bio-capturing β-lactoglobulin. The fine-tuned CDI-Cu NF revealed the flower-like structures was viewed through field emission scanning electron microscopy. Fourier-transform infrared spectroscopy showed the interactions with PI film, CDI-Cu NF, oligoaptamer and β-lactoglobulin. The non-faradaic sensing of milk allergen β-lactoglobulin corresponds to a higher loading of oligoaptamer on 3D-structured CDI-Cu NF, with a linear range detection from 1 ag/ml to 100 fg/ml and attomolar (1 ag/ml) detection limit (S/N = 3:1). This novel CDI-Cu NF/LSG microgap aptasensor has a great potential for the detection of milk allergen with high-specificity and sensitivity.
Herbal-based products are becoming a widespread production trend among manufacturers for the domestic and international markets. As the production increases to meet the market demand, it is very crucial for the manufacturer to ensure that their products have met specific criteria and fulfil the intended quality determined by the quality controller. One famous herbal-based product is herbal tea. This paper investigates bio-inspired flavour assessments in a data fusion framework involving an e-nose and e-tongue. The objectives are to attain good classification of different types and brands of herbal tea, classification of different flavour masking effects and finally classification of different concentrations of herbal tea. Two data fusion levels were employed in this research, low level data fusion and intermediate level data fusion. Four classification approaches; LDA, SVM, KNN and PNN were examined in search of the best classifier to achieve the research objectives. In order to evaluate the classifiers' performance, an error estimator based on k-fold cross validation and leave-one-out were applied. Classification based on GC-MS TIC data was also included as a comparison to the classification performance using fusion approaches. Generally, KNN outperformed the other classification techniques for the three flavour assessments in the low level data fusion and intermediate level data fusion. However, the classification results based on GC-MS TIC data are varied.
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.
Food forgery has posed considerable risk to public health, religious rituals, personal budget and wildlife. Pig, dog, cat, rat and monkey meat are restricted in most religions, but their sporadic adulteration are rampant. Market controllers need a low-cost but reliable technique to track and trace suspected species in the food chain. Considering the need, here we documented a lab-on-a-chip-based multiplex polymerase chain reaction (PCR) assay for the authentication of five non-halal meat species in foods. Using species-specific primers, 172, 163, 141, 129 and 108-bp sites of mitochondrial ND5, ATPase 6 and cytochrome b genes were amplified to detect cat, dog, pig, monkey and rat species under complex matrices. Species-specificity was authenticated against 20 different species with the potential to be used in food. The targets were stable under extreme sterilisation (121°C at 45 psi for 2.5 h) which severely degrades DNA. The assay was optimised under the backgrounds of various commercial meat products and validated for the analysis of meatballs, burgers and frankfurters, which are popular fast food items across the globe. The assay was tested to detect 0.1% suspected meats under commercial backgrounds of marketed foods. Instead of simplex PCR which detects only one species at a time, such a multiplex platform can reduce cost by at least fivefolds by detecting five different species in a single assay platform.
The present study was undertaken to determine whether Ligularia fischeri leaf extract (LF) is efficacious against collagen-induced arthritis (CIA) in mice. DBA/1J mice were immunized with bovine type II collagen and treated with LF (100 and 200 mg/kg) for 49 days. Mice were assessed regularly for signs of arthritis and the levels of rheumatoid factor, anti-type II collagen antibody, cytokines, AST, ALT, and creatinine in serum were also examined after the animals were killed. The arthritis score and paw edema were markedly suppressed in the groups treated with LF. Moreover, levels of rheumatoid factor, anti-type II collagen antibody, tumor necrosis factor-alpha, interleukin (IL)-1, and IL-6 in sera were reduced by LF administration. These data suggest that L. fischeri might be effective for the treatment of inflammatory arthritis like human rheumatoid arthritis.
Red rice is a fermented product of Monascus spp. It is widely consumed by Malaysian Chinese who believe in its pharmacological properties. The traditional method of red rice preparation disregards safety regulation and renders red rice susceptible to fungal infestation and mycotoxin contamination. A preliminary study was undertaken aiming to determine the occurrence of mycotoxigenic fungi and mycotoxins contamination on red rice at consumer level in Selangor, Malaysia. Fifty red rice samples were obtained and subjected to fungal isolation, enumeration, and identification. Citrinin, aflatoxin, and ochratoxin-A were quantitated by ELISA based on the presence of predominant causal fungi. Fungal loads of 1.4 × 10(4) to 2.1 × 10(6) CFU/g exceeded Malaysian limits. Monascus spp. as starter fungi were present in 50 samples (100%), followed by Penicillium chrysogenum (62%), Aspergillus niger (54%), and Aspergillus flavus (44%). Citrinin was present in 100% samples (0.23-20.65 mg/kg), aflatoxin in 92% samples (0.61-77.33 μg/kg) and Ochratoxin-A in 100% samples (0.23-2.48 μg/kg); 100% citrinin and 76.09% aflatoxin exceeded Malaysian limits. The presence of mycotoxigenic fungi served as an indicator of mycotoxins contamination and might imply improper production, handling, transportation, and storage of red rice. Further confirmatory analysis (e.g., HPLC) is required to verify the mycotoxins level in red rice samples and to validate the safety status of red rice.
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.
In this study, a rapid, specific and sensitive multi-residue method based on acetonitrile extraction followed by dispersive solid-phase extraction (d-SPE) clean-up was implemented and validated for multi-class pesticide residues determination in palm oil for the first time. Liquid-liquid extraction followed by low-temperature precipitation procedure was evaluated in order to study the freezing-out clean-up efficiency to obtain high recovery yield and low co-extract fat residue in the final extract. For clean-up step, d-SPE was carried out using a combination of anhydrous magnesium sulphate (MgSO(4)), primary secondary amine, octadecyl (C(18)) and graphitized carbon black. Recovery study was performed at two concentration levels (10 and 100 ng g(-1)), yielding recovery rates between 74.52% and 97.1% with relative standard deviation values below 10% (n = 6) except diuron. Detection and quantification limits were lower than 5 and 9 ng g(-1), respectively. In addition, soft matrix effects (≤±20%) were observed for most of the studied pesticides except malathion that indicated medium (20-50%) matrix effects. The proposed method was successfully applied to the analysis of suspected palm oil samples.
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.
This paper reports the application of hexamethyldisilazane-trimethylsilyl trifluoromethanesulfonate (HMDS-TMSOTf) for the simultaneous silylation of 3-monochloro-1,2-propanediol (3-MCPD) and 1,3-dicholoropropanol (1,3-DCP) in solid and liquid food samples. 3-MCPD and 1,3-DCP are chloropropanols that have been established as Group 2B carcinogens in clinical testing. They can be found in heat-processed food, especially when an extended high-temperature treatment is required. However, the current AOAC detection method is time-consuming and expensive. Thus, HMDS-TMSOTf was used in this study to provide a safer, and cost-effective alternative to the HFBI method. Three important steps are involved in the quantification of 3-MCPD and 1,3-DCP: extraction, derivatization and quantification. The optimization of the derivatization process, which involved focusing on the catalyst volume, derivatization temperature, and derivatization time was performed based on the findings obtained from both the Box-Behnken modeling and a real experimental set up. With the optimized conditions, the newly developed method was used for actual food sample quantification and the results were compared with those obtained via the standard AOAC method. The developed method required less samples and reagents but it could be used to achieve lower limits of quantification (0.0043mgL(-1) for 1,3-DCP and 0.0011mgL(-1) for 3-MCPD) and detection (0.0028mgL(-1) for 1,3-DCP and 0.0008mgL(-1) for 3-MCPD). All the detected concentrations are below the maximum tolerable limit of 0.02mgL(-1). The percentage of recovery obtained from food sample analysis was between 83% and 96%. The new procedure was validated with the AOAC method and showed a comparable performance. The HMDS-TMSOTf derivatization strategy is capable of simultaneously derivatizing 1,3-DCP and 3-MCPD at room temperature, and it also serves as a rapid, sensitive, and accurate analytical method for food samples analysis.
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.
This paper outlines the methodology to add glycaemic index (GI) and glycaemic load (GL) functionality to food DietPLUS, a Microsoft Excel-based Malaysian food composition database and diet intake calculator. Locally determined GI values and published international GI databases were used as the source of GI values. Previously published methodology for GI value assignment was modified to add GI and GL calculators to the database. Two popular local low GI foods were added to the DietPLUS database, bringing up the total number of foods in the database to 838 foods. Overall, in relation to the 539 major carbohydrate foods in the Malaysian Food Composition Database, 243 (45%) food items had local Malaysian values or were directly matched to International GI database and another 180 (33%) of the foods were linked to closely-related foods in the GI databases used. The mean ± SD dietary GI and GL of the dietary intake of 63 women with previous gestational diabetes mellitus, calculated using DietPLUS version3 were, 62 ± 6 and 142 ± 45, respectively. These values were comparable to those reported from other local studies. DietPLUS version3, a simple Microsoft Excel-based programme aids calculation of diet GI and GL for Malaysian diets based on food records.
Nanowire sensors offer great potential as highly sensitive electrochemical and electronic biosensors because of their small size, high aspect ratios, and electronic properties. Nevertheless, the available methods to fabricate carbon nanowires in a controlled manner remain limited to expensive techniques. This paper presents a simple fabrication technique for sub-100 nm suspended carbon nanowire sensors by integrating electrospinning and photolithography techniques. Carbon Microelectromechanical Systems (C-MEMS) fabrication techniques allow fabrication of high aspect ratio carbon structures by patterning photoresist polymers into desired shapes and subsequent carbonization of resultant structures by pyrolysis. In our sensor platform, suspended nanowires were deposited by electrospinning while photolithography was used to fabricate support structures. We have achieved suspended carbon nanowires with sub-100 nm diameters in this study. The sensor platform was then integrated with a microfluidic chip to form a lab-on-chip device for label-free chemiresistive biosensing. We have investigated this nanoelectronics label-free biosensor's performance towards bacterial sensing by functionalization with Salmonella-specific aptamer probes. The device was tested with varying concentrations of Salmonella Typhimurium to evaluate sensitivity and various other bacteria to investigate specificity. The results showed that the sensor is highly specific and sensitive in detection of Salmonella with a detection limit of 10 CFU mL-1. Moreover, this proposed chemiresistive assay has a reduced turnaround time of 5 min and sample volume requirement of 5 µL which are much less than reported in the literature.
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.
This paper reports a computational approach for analysis of FTIR spectra where peaks are detected, assigned and matched across samples to produce a peak table with rows corresponding to samples and columns to variables. The algorithm is applied on a dataset of 103 spectra of a broad range of edible oils for exploratory analysis and variable selection using Self Organising Maps (SOMs) and t-statistics, respectively. Analysis on the resultant peak table allows the underlying patterns and the discriminatory variables to be revealed. The algorithm is user-friendly; it involves a minimal number of tunable parameters and would be useful for analysis of a large and complicated FTIR dataset.
This paper reports the design of an electronic nose (E-nose) prototype for reliable measurement and correct classification of beverages. The prototype was developed and fabricated in the laboratory using commercially available metal oxide gas sensors and a temperature sensor. The repeatability, reproducibility and discriminative ability of the developed E-nose prototype were tested on odors emanating from different beverages such as blackcurrant juice, mango juice and orange juice, respectively. Repeated measurements of three beverages showed very high correlation (r > 0.97) between the same beverages to verify the repeatability. The prototype also produced highly correlated patterns (r > 0.97) in the measurement of beverages using different sensor batches to verify its reproducibility. The E-nose prototype also possessed good discriminative ability whereby it was able to produce different patterns for different beverages, different milk heat treatments (ultra high temperature, pasteurization) and fresh and spoiled milks. The discriminative ability of the E-nose was evaluated using Principal Component Analysis and a Multi Layer Perception Neural Network, with both methods showing good classification results.
Murraya koenigii leaf extract antioxidant potentials were evaluated in palm olein using accelerated oxidation storage and deep-frying studies at 180 degrees C for up to 40 h. The extracts (0.2%) retarded oil oxidation and deterioration significantly (P<0.05), slightly less effectively than 0.02% butylated hydroxytoluene in tests such as the peroxide value, anisidine value, iodine value, free fatty acid, Oxidative Stability Index, and polar and polymer compound content. Sensory evaluation on French fries indicated that the extract was useful in improving colour, flavour and overall acceptability and the quality of the fried product. All samples were more acceptable by panellists, especially after the 40th hour frying, compared with those similarly fried in the control oils and the oil containing butylated hydroxytoluene. M. koenigii leaf extract, had a polyphenol content of 109.5+/-0.3 mg gallic acid equivalents/g extract, and contain a heat-stable antioxidant that could be a natural alternative to synthetic antioxidants for the industry.
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.
The authentication of food products is essential for food quality and safety. Authenticity assessments are important to ensure that the ingredients or contents of food products are legitimate and safe to consume. The metabolomics approach is an essential technique that can be utilized for authentication purposes. This study aimed to summarize food authentication through the metabolomics approach, to study the existing analytical methods, instruments, and statistical methods applied in food authentication, and to review some selected food commodities authenticated using metabolomics-based methods. Various databases, including Google Scholar, PubMed, Scopus, etc., were used to obtain previous research works relevant to the objectives. The review highlights the role of the metabolomics approach in food authenticity. The approach is technically implemented to ensure consumer protection through the strict inspection and enforcement of food labeling. Studies have shown that the study of metabolomics can ultimately detect adulterant(s) or ingredients that are added deliberately, thus compromising the authenticity or quality of food products. Overall, this review will provide information on the usefulness of metabolomics and the techniques associated with it in successful food authentication processes, which is currently a gap in research that can be further explored and improved.