Food composition database (FCD) provides the nutritional composition of foods. Reliable and up-to date FCD is important in many aspects of nutrition, dietetics, health, food science, biodiversity, plant breeding, food industry, trade and food regulation. FCD has been used extensively in nutrition labelling, nutritional analysis, research, regulation, national food and nutrition policy. The choice of method for the analysis of samples for FCD often depends on detection capability, along with ease of use, speed of analysis and low cost. Sample preparation is the most critical stage in analytical method development. Samples can be prepared using numerous techniques; however it should be applicable for a wide range of analytes and sample matrices. There are quite a number of significant improvements on sample preparation techniques in various food matrices for specific analytes highlighted in the literatures. Improvements on the technology used for the analysis of samples by specific instrumentation could provide an alternative to the analyst to choose for their laboratory requirement. This review provides the reader with an overview of recent techniques that can be used for sample preparation and instrumentation for food analysis which can provide wide options to the analysts in providing data to their FCD.
Chicken is known to be the most common meat type involved in food mislabeling and adulteration. Establishing a method to authenticate chicken content precisely and identifying chicken breeds as declared in processed food is crucial for protecting consumers' rights. Categorizing the authentication method into their respective omics disciplines, such as genomics, transcriptomics, proteomics, lipidomics, metabolomics, and glycomics, and the implementation of bioinformatics or chemometrics in data analysis can assist the researcher in improving the currently available techniques. Designing a vast range of instruments and analytical methods at the molecular level is vital for overcoming the technical drawback in discriminating chicken from other species and even within its breed. This review aims to provide insight and highlight previous and current approaches suitable for countering different circumstances in chicken authentication.
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.
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.
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.
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.
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.
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).
Food-derived bioactive proteins and peptides have gained acceptance among researchers, food manufacturers and consumers as health-enhancing functional food components that also serve as natural alternatives for disease prevention and/or management. Bioactivity in food proteins and peptides is determined by their conformations and binding characteristics, which in turn depend on their primary and secondary structures. To maintain their bioactivities, the molecular integrity of bioactive peptides must remain intact, and this warrants the study of peptide form and structure, ideally with robust, highly specific and sensitive techniques. Short single-stranded nucleic acids (i.e. aptamers) are known to have high affinity for cognate targets such as proteins and peptides. Aptamers can be produced cost-effectively and chemically derivatized to increase their stability and shelf life. Their improved binding characteristics and minimal modification of the target molecular signature suggests their suitability for real-time detection of conformational changes in both proteins and peptides. This review discusses the developmental progress of systematic evolution of ligands by exponential enrichment (SELEX), an iterative technology for generating cost-effective aptamers with low dissociation constants (Kd) for monitoring the form and structure of bioactive proteins and peptides. The review also presents case studies of this technique in monitoring the structural stability of bioactive peptide formulations to encourage applications in functional foods. The challenges and potential of aptamers in this research field are also discussed. Graphical abstract Advancing bioactive proteins and peptide functionality via aptameric ligands.
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.
Porcine gelatine is a common adulterant found in edible bird's nests (EBNs) used to increase the net weight prior to sale. This study aimed to develop indirect enzyme-linked immunosorbent assays (ELISAs) for porcine gelatine adulteration using anti-peptide polyclonal antibodies. Three indirect ELISAs were developed (PAB1, 2 and 3), which had limits of detection (LODs) of 0.12, 0.10 and 0.11 µg g(-1), respectively. When applied to standard solutions of porcine gelatine, the inter- and intra-assays showed coefficients of variation (CVs) less than 20% and were able to detect at least 0.5 ng µg(-1) (0.05%) porcine gelatine in spiked samples. The proposed ELISA offers attractions for quality control in the EBN industry.
Authentication of meat products is critical in the food industry. Meat adulteration may lead to religious apprehensions, financial gain and food-toxicities such as meat allergies. Thus, empirical validation of the quality and constituents of meat is paramount. Various analytical methods often based on protein or DNA measurements are utilized to identify meat species. Protein-based methods, including electrophoretic and immunological techniques, are at times unsuitable for discriminating closely related species. Most of these methods have been replaced by more accurate and sensitive detection methods, such as DNA-based techniques. Emerging technologies like DNA barcoding and mass spectrometry are still in their infancy when it comes to their utilization in meat detection. Gold nanobiosensors have shown some promise in this regard. However, its applicability in small scale industries is distant. This article comprehensively reviews the recent developments in the field of analytical methods used for porcine identification.
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.
Allele Specific Amplification with four primers (External Antisense Primer, External Sense Primer, Internal Nonfragrant Sense Primer, and Internal Fragrant Antisense Primer) and sensory evaluation with leaves and grains were executed to identify aromatic rice genotypes and their F1 individuals derived from different crosses of 2 Malaysian varieties with 4 popular land races and 3 advance lines. Homozygous aromatic (fgr/fgr) F1 individuals demonstrated better aroma scores compared to both heterozygous nonaromatic (FGR/fgr) and homozygous nonaromatic (FGR/FGR) individuals, while, some F1 individuals expressed aroma in both leaf and grain aromatic tests without possessing the fgr allele. Genotypic analysis of F1 individuals for the fgr gene represented homozygous aromatic, heterozygous nonaromatic and homozygous nonaromatic genotypes in the ratio 20:19:3. Genotypic and phenotypic analysis revealed that aroma in F1 individuals was successfully inherited from the parents, but either molecular analysis or sensory evaluation alone could not determine aromatic condition completely. The integration of molecular analysis with sensory methods was observed as rapid and reliable for the screening of aromatic genotypes because molecular analysis could distinguish aromatic homozygous, nonaromatic homozygous and nonaromatic heterozygous individuals, whilst the sensory method facilitated the evaluation of aroma emitted from leaf and grain during flowering to maturity stages.
This study was conducted to evaluate the total carotene content (TCC) and beta carotene (BC) in the selected underutilized tropical fruits. TCC of underutilized fruits estimated by spectrophotometric method was in the range of 1.4-19.8 mg/100 g edible portion. The TCC of these fruits decreased in the order: Jentik-jentik > Durian Nyekak 2 > Durian Nyekak 1 > Cerapu 2 > Cerapu 1 > Tampoi Kuning > Bacang 1 > Kuini > Jambu Mawar > Bacang 2 > Durian Daun > Bacang 3 > Tampoi Putih > Jambu Susu. BC contents estimated by HPLC method were highest in Jentik-jentik, followed by Cerapu 2, Durian Nyekak 2, Tampoi Kuning, Durian Nyekak 1, and Cerapu 1, which had a range of 68-92% of BC in TCC. These underutilized fruits have an acceptable amount of carotenoids that are potential antioxidant fruits.
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.
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 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.
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.