Recent Progress on Techniques in the Detection of Aflatoxin B1 in Edible Oil: A Mini Review

Contamination of agricultural products and foods by aflatoxin B1 (AFB1) is becoming a serious global problem, and the presence of AFB1 in edible oil is frequent and has become inevitable, especially in underdeveloped countries and regions. As AFB1 results from a possible degradation of aflatoxins and the interaction of the resulting toxic compound with food components, it could cause chronic disease or severe cancers, increasing morbidity and mortality. Therefore, rapid and reliable detection methods are essential for checking AFB1 occurrence in foodstuffs to ensure food safety. Recently, new biosensor technologies have become a research hotspot due to their characteristics of speed and accuracy. This review describes various technologies such as chromatographic and spectroscopic techniques, ELISA techniques, and biosensing techniques, along with their advantages and weaknesses, for AFB1 control in edible oil and provides new insight into AFB1 detection for future work. Although compared with other technologies, biosensor technology involves the cross integration of multiple technologies, such as spectral technology and new nano materials, and has great potential, some challenges regarding their stability, cost, etc., need further studies.

A feasibility study on nondestructive classification of frozen Atlantic salmon (Salmo salar) fillets based on temperature history at the logistics using NIR spectroscopy

Temperature fluctuation commonly occurs in the cold chain leading to complete or partial thawing and refreezing of frozen products resulting in a multifrozen product. Such oscillation of temperature could cause significant quality reduction compared to single frozen products. This study was designed to differentiate frozen Atlantic salmon fillets based on the level of temperature fluctuation. Near-infrared spectroscopy (NIRS) coupled with chemometrics was used to classify the frozen fillets stored at no fluctuation (NF), low fluctuation (LF), high fluctuation (HF), and very high fluctuation (VF) temperature. Using spectral profiles obtained at both frozen and thawed states, fillets were classified based on the level of temperature fluctuation by partial least squares discriminant analysis (PLS-DA). The thawed samples showed better classification accuracy (71%) than frozen samples (66%) in a four-class model. Considering the small variation within the first two (NF, LF) and the last two (HF, VF) groups, a two-class classification model was developed using thawed samples, and the obtained model correctly classified the two groups ([NF, LF] and [HF, VF]) with 100 % classification accuracy. Protein- and water-related changes were found important to distinguish the fillets. Based on these findings, the four-class prediction model is found insufficient to be used for nondestructive determination of temperature history of frozen fillets. However, the two-class prediction model with further external validation can be applied to determine the level of temperature fluctuation particularly using fillets scanned at thawed state. PRACTICAL APPLICATION: NIR spectroscopy can be used to evaluate the degree of temperature fluctuation and thus related quality loss throughout the logistics of frozen Atlantic salmon fillets. Researchers, food control authorities, and the retail industry could be the primary beneficiaries of this research output.

Rapid Differentiation of Unfrozen and Frozen-Thawed Tuna with Non-Destructive Methods and Classification Models: Bioelectrical Impedance Analysis (BIA), Near-Infrared Spectroscopy (NIR) and Time Domain Reflectometry (TDR)

The performances of three non-destructive sensors, based on different principles, bioelectrical impedance analysis (BIA), near-infrared spectroscopy (NIR) and time domain reflectometry (TDR), were studied to discriminate between unfrozen and frozen-thawed fish. Bigeye tuna (Thunnus obesus) was selected as a model to evaluate these technologies. The addition of water and additives is usual in the fish industry, thus, in order to have a wide range of possible commercial conditions, some samples were injected with different water solutions (based on different concentrations of salt, polyphosphates and a protein hydrolysate solution). Three different models, based on partial least squares discriminant analysis (PLS-DA), were developed for each technology. This is a linear classification method that combines the properties of partial least squares (PLS) regression with the classification power of a discriminant technique. The results obtained in the evaluation of the test set were satisfactory for all the sensors, giving NIR the best performance (accuracy = 0.91, error rate = 0.10). Nevertheless, the classification accomplished with BIA and TDR data resulted also satisfactory and almost equally as good, with accuracies of 0.88 and 0.86 and error rates of 0.14 and 0.15, respectively. This work opens new possibilities to discriminate between unfrozen and frozen-thawed fish samples with different non-destructive alternatives, regardless of whether or not they have added water.

The use of the so-called 'superchilling' technique for the transport of fresh fishery products

Superchilling entails lowering the fish temperature to between the initial freezing point of the fish and about 1-2°C lower. The temperature of superchilled fresh fishery products (SFFP) in boxes without ice was compared to that of products subject to the currently authorised practice in boxes with ice (CFFP) under the same conditions of on-land storage and/or transport. A heat transfer model was developed and made available as a tool to identify under which initial configurations of SFFP the fish temperature, at any time of storage/transport, is lower or equal to CFFP. A minimum degree of superchilling, corresponding to an ice fraction in the fish matrix of SFFP equal or higher than the proportion of ice added per mass of fish in CFFP, will ensure with 99-100% certainty (almost certain) that the fish temperature of SFFP and the consequent increase of relevant hazards will be lower or equal to that of CFFP. In practice, the degree of superchilling can be estimated using the fish temperature after superchilling and its initial freezing point, which are subject to uncertainties. The tool can be used as part of 'safety-by-design' approach, with the reliability of its outcome being dependent on the accuracy of the input data. An evaluation of methods capable of detecting whether a previously frozen fish is commercially presented as 'superchilled' was carried out based on, amongst others, their applicability for different fish species, ability to differentiate fresh fish from fish frozen at different temperatures, use as a stand-alone method, ease of use and classification performance. The methods that were considered 'fit for purpose' are Hydroxyacyl-coenzyme A dehydrogenase (HADH) test, α-glucosidase test, histology, ultraviolet-visible-near-infrared (UV-VIS/NIR) spectroscopy and hyperspectral imaging. These methods would benefit from standardisation, including the establishment of threshold values or classification algorithms to provide a practical routine test.

Emerging Techniques for Differentiation of Fresh and Frozen-Thawed Seafoods: Highlighting the Potential of Spectroscopic Techniques

Fish and other seafood products have a limited shelf life due to favorable conditions for microbial growth and enzymatic alterations. Various preservation and/or processing methods have been developed for shelf-life extension and for maintaining the quality of such highly perishable products. Freezing and frozen storage are among the most commonly applied techniques for this purpose. However, frozen–thawed fish or meat are less preferred by consumers; thus, labeling thawed products as fresh is considered a fraudulent practice. To detect this kind of fraud, several techniques and approaches (e.g., enzymatic, histological) have been commonly employed. While these methods have proven successful, they are not without limitations. In recent years, different emerging methods have been investigated to be used in place of other traditional detection methods of thawed products. In this context, spectroscopic techniques have received considerable attention due to their potential as being rapid and non-destructive analytical tools. This review paper aims to summarize studies that investigated the potential of emerging techniques, particularly those based on spectroscopy in combination with chemometric tools, to detect frozen–thawed muscle foods.

NIR spectroscopic method for the detection of calcium carbide in artificial ripening of mangoes (Magnifera indica)

The present study presents a novel method employing Near Infrared Spectroscopy (NIR) for detection of the use of calcium carbide in artificial ripening of mangoes. Use of calcium carbide has been banned in artificial ripening of fruits as it contains traces of arsenic. Mango samples were ripened artificially using calcium carbide and compared with naturally ripened mangoes using NIR spectroscopic wavelength ranging from 600 to 1100 nm. The captured NIR spectra from mango samples were analysed using multivariate methods including principal component analysis, particle least square and successive projection algorithm. The obtained results showed distinguishing zones for naturally and artificially ripened mangoes. Furthermore, the arsenic content was obtained through ICP-MS analysis, and it was found that mangoes ripened artificially using calcium carbide have a higher content of arsenic. Hence, arsenic was used as a principal component in the analysis. The developed method is not unique to samples that were grown in any particular region or year as it and can be used universally as NIR will give the distinguishing comparison between naturally- and artificially ripened mangoes. This method is simple, non-invasive, non-destructive and rapid for detection of use of calcium carbide in the artificial ripening of mangoes.

Approaching Authenticity Issues in Fish and Seafood Products by Qualitative Spectroscopy and Chemometrics

The intrinsically complex nature of fish and seafood, as well as the complicated organisation of the international fish supply and market, make struggle against counterfeiting and falsification of fish and seafood products very difficult. The development of fast and reliable omics strategies based on spectroscopy in conjunction with multivariate data analysis has been attracting great interest from food scientists, so that the studies linked to fish and seafood authenticity have increased considerably in recent years. The present work has been designed to review the most promising studies dealing with the use of qualitative spectroscopy and chemometrics for the resolution of the key authenticity issues of fish and seafood products, with a focus on species substitution, geographical origin falsification, production method or farming system misrepresentation, and fresh for frozen/thawed product substitution. Within this framework, the potential of fluorescence, vibrational, nuclear magnetic resonance, and hyperspectral imaging spectroscopies, combined with both unsupervised and supervised chemometric techniques, has been highlighted, each time pointing out the trends in using one or another analytical approach and the performances achieved.

Freshness Evaluation in Chub Mackerel (Scomber japonicus) Using Near-Infrared Spectroscopy Determination of the Cadaverine Content

We analyzed the volatile basic nitrogen content, pH, total viable cell count, and biogenic amine contents in chub mackerel (Scomber japonicus) stored at 5 and 25°C to examine changes in freshness. Among the various parameters, we found the volatile basic nitrogen content had the highest correlation with cadaverine content (r² = 0.72 to 0.88). We also tried to measure cadaverine contents at different times during storage by using near-infrared (NIR) spectroscopy. However, because of the high water content in the fish, we could not obtain meaningful results. Next, we prepared samples for NIR spectroscopy by dilution with 0.1 N HCl, ultrafiltration (3 or 10 kDa) with a glass filter, and dehydration. The samples prepared with the 3-kDa filter had peaks in the NIR spectra between 1,379.3 and 1,388.9 nm, and those prepared with the 10-kDa filter had peaks in the spectra between 1,897.3 and 1,898.6 nm. The correlation coefficient (r²) between the NIR spectroscopy and high-performance liquid chromatography with cadaverine results was 0.98 to 0.99. We concluded that the biogenic amine content could be used to evaluate freshness in fish products, and that NIR measurements could be used to rapidly and accurately determine freshness.

Determination of soybean routine quality parameters using near-infrared spectroscopy

Large differences in quality existed between soybean samples. In order to rapidly detect soybean quality between samples from different areas, we have developed near-infrared spectroscopy (NIRS) models for the moisture, crude fat, and protein content of soybeans, based on 360 soybean samples collected from different areas. Compared with whole kernels, soybean powder with particle sizes of 60 mesh was more suitable for modeling of moisture, crude fat, and protein content. To increase the reproducibility of the prediction model, uniform particle sizes of soybeans were prepared by grinding and sieving soybeans with different sizes and colors. Modeling analysis showed that the internal cross-validation correlation coefficients (Rcv) for the moisture, crude fat, and protein content of soybeans were .965, .941, and .949, respectively, and the determination coefficients (R2) were .966, .958, and .958. NIRS performed well as a rapid method for the determination of routine quality parameters and provided reference data for the analysis of soybean quality using FT-NIRS.

Applications of near-infrared spectroscopy in food safety evaluation and control: a review of recent research advances

Food safety is a critical public concern, and has drawn great attention in society. Consequently, developments of rapid, robust, and accurate methods and techniques for food safety evaluation and control are required. As a nondestructive and convenient tool, near-infrared spectroscopy (NIRS) has been widely shown to be a promising technique for food safety inspection and control due to its huge advantages of speed, noninvasive measurement, ease of use, and minimal sample preparation requirement. This review presents the fundamentals of NIRS and focuses on recent advances in its applications, during the last 10 years of food safety control, in meat, fish and fishery products, edible oils, milk and dairy products, grains and grain products, fruits and vegetables, and others. Based upon these applications, it can be demonstrated that NIRS, combined with chemometric methods, is a powerful tool for food safety surveillance and for the elimination of the occurrence of food safety problems. Some disadvantages that need to be solved or investigated with regard to the further development of NIRS are also discussed.

Differentiation of fresh and frozen/thawed fish, European sea bass (Dicentrarchus labrax), gilthead seabream (Sparus aurata), cod (Gadus morhua) and salmon (Salmo salar), using volatile compounds by SPME/GC/MS

BACKGROUND

A simple method based on solid phase microextraction/gas chromatography/mass spectrometry (SPME/GC/MS) was applied for studying the volatile profiles of whole fish samples of European sea bass (Dicentrarchus labrax) and gilthead seabream (Sparus aurata) and fillets of cod (Gadus morhua) and salmon (Salmo salar) during frozen storage in order to be able to differentiate a fresh product from one that has been frozen. Analysis of volatile compounds was performed on these two product types, fresh and after freezing/thawing following storage at - 20 °C for 30 and 90 days.

RESULTS

More than a hundred volatile compounds were found by SPME/GC/MS. Statistical processing by principal component analysis and ascending hierarchical classification was used to classify the samples into categories and verify the possibility of separating fresh samples from those that had been frozen and thawed. The compounds to be used as differentiators were identified. Four compounds were common to all species: dimethyl sulfide, 3-methylbutanal, ethyl acetate and 2-methylbutanal. Not only were they found in larger quantities after thawing but they also increased with the duration of storage at - 20 °C.

CONCLUSION

These four compounds can therefore be considered as potential markers of differentiation between a fresh product and one that has been frozen.