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.
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.
Surface enhanced Raman scattering (SERS) DNA biosensing is an ultrasensitive, selective, and rapid detection technique with the ability to produce molecule-specific distinct fingerprint spectra. It supersedes the long amplicon based PCR assays, the fluorescence and spectroscopic techniques with their quenching and narrow spectral bandwidth, and the electrochemical detection techniques using multiplexing. However, the performance of the SERS DNA biosensor relies on the DNA probe length, platform composition, both the presence and position of Raman tags and the chosen sensing strategy. In this context, we herein report a SERS biosensor based on dual nanoplatforms with a uniquely designed Raman tag (ATTO Rho6G) intercalated short-length DNA probe for the sensitive detection of the pig species Sus scrofa. In the design of the signal probe (SP), a Raman tag was incorporated adjacent to the spacer arm, followed by a terminal thiol modifier, which consequently had a strong influence on the SERS signal enhancement. The detection strategy involves the probe-target DNA hybridization mediated coupling of the two platforms, i.e., the graphene oxide-gold nanorod (GO-AuNR) functionalized capture probe (CP) and SP-conjugated gold nanoparticles (AuNPs), consequently enhancing the SERS intensity by both the electromagnetic hot spots generated at the junctions or interstices of the two platforms and the chemical enhancement between the AuNPs and the adsorbed intercalated Raman tag. This dual platform based SERS DNA biosensor exhibited outstanding sensitivity in detecting pork DNA with a limit of detection (LOD) of 100 aM validated with DNA extracted from a pork sample (LOD 1 fM). Moreover, the fabricated SERS biosensor showed outstanding selectivity and specificity for differentiating the DNA sequences of six closely related non-target species from the target DNA sequences with single and three nucleotide base-mismatches. Therefore, the developed short-length DNA linked dual platform based SERS biosensor could replace the less sensitive traditional methods of pork DNA detection and be adopted as a universal detection approach for the qualitative and quantitative detection of DNA from any source.
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.
A vortex-assisted liquid-liquid-liquid microextraction method followed by high performance liquid chromatography-diode array detection for the determination of fourteen phenolic acids (cinnamic, m-coumaric, chlorogenic, syringic, ferulic, o-coumaric, p-coumaric, vanillic, p-hydroxybenzoic, caffeic, 2, 4-dihydroxybenzoic, sinapic, gentisic and gallic acids) in honey, iced tea and canned coffee drink samples has been developed. The separation was achieved using a Poroshell 120-EC-C18 column under a gradient elution at a flow rate of 0.6mLmin-1 and mobile phase composed of methanol and acetic acid (1%, v/v). Under the optimum chromatographic conditions, the fourteen phenolic acids were separated in less than 32min. The extraction was performed using a small volume (400µL) of ternary organic solvents (1-pentanol, propyl acetate and 1-hexanol) dispersed into the aqueous sample (10mL) and assisted by vortex agitation (2500rpm for 45s), the analytes were next back-extracted from the organic solvent using 0.02M KOH (40µL) with vortex speed and time of 2500rpm and 60s, respectively. Under these conditions, enrichment factors of 30-193-fold were achieved. The limits of detection (LODs) were 0.05-0.68µgL-1. Recoveries in honey, iced tea and canned coffee drinks were in the range 72.2-112%. The method was successfully applied for the determination of the phenolic acids in honey, iced tea and canned coffee drinks.
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.
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.
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.
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).
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.
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.
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.
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.
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 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.
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.
The content of 12 elements in Cambodian dried striped snakehead fish was determined using inductively coupled plasma mass spectrometry. The present study compares the level of the trace toxic metals and nutritional trace elements in the fish processed using solar drying system (SDS) and open sun drying (OSD). The skin of SDS fish has lower level of As, Pb, and Cd compared to the OSD sample. As such, the flesh of the fish accumulated higher amount of toxic metals during OSD compared to SDS. However, arsenic was detected in both samples within the safe limit. The nutritional elements (Fe, Mn, Mg, Se, Mo, Cu, Ni, and Cr) were higher in the skin sample SDS fish compared to OSD fish. These beneficial metals were not accumulated in the flesh sample SDS fish demonstrating lower level compared to drying under conventional system. The reddish coloration of the SDS fish was due to the presence of high Cu content in both the skin and flesh samples which possibly account for no mold formation 5 days after packaging. As conclusion, drying of Cambodian C. striata using solar-assisted system has proven higher content of the nutritious elements compared to using the conventional system despite only slight difference in the toxic metals level between the two systems.