Potential of near infrared spectroscopy for the analysis of mycotoxins applied to naturally contaminated red paprika found in the Spanish market

Current and promising strategies to prevent and reduce aflatoxin contamination in grains and food matrices

Mycotoxins are secondary metabolites produced by filamentous fungi that colonise various crops around the world and cause major damage to the agro-industrial sector on a global scale. Considering the estimative of population growth in the next decades, it is of fundamental importance the implementation of practices that help prevent the economics and social impacts of aflatoxin contamination. Even though various approaches have been developed – including physical, chemical and biological approaches – there is not yet one that strikes a balance in terms of safety, food quality and cost, especially when considering large scale application. In this review, we present a compilation of advantages and disadvantages of different strategies for prevention and reduction of aflatoxin contamination. Biological approaches represent the trend in innovations mainly due to their specificity and versatility, since it is possible to consider the utilisation of whole microorganisms, culture supernatants, purified enzymes or even genetic engineering. However, challenges related to improvement of the efficiency of such methods and ensuring safety of treated foods still need to be overcome.

Ganoderma boninense Disease Detection by Near-Infrared Spectroscopy Classification: A Review

Ganoderma boninense (G. boninense) infection reduces the productivity of oil palms and causes a serious threat to the palm oil industry. This catastrophic disease ultimately destroys the basal tissues of oil palm, causing the eventual death of the palm. Early detection of G. boninense is vital since there is no effective treatment to stop the continuing spread of the disease. This review describes past and future prospects of integrated research of near-infrared spectroscopy (NIRS), machine learning classification for predictive analytics and signal processing towards an early G. boninense detection system. This effort could reduce the cost of plantation management and avoid production losses. Remarkably, (i) spectroscopy techniques are more reliable than other detection techniques such as serological, molecular, biomarker-based sensor and imaging techniques in reactions with organic tissues, (ii) the NIR spectrum is more precise and sensitive to particular diseases, including G. boninense, compared to visible light and (iii) hand-held NIRS for in situ measurement is used to explore the efficacy of an early detection system in real time using ML classifier algorithms and a predictive analytics model. The non-destructive, environmentally friendly (no chemicals involved), mobile and sensitive leads the NIRS with ML and predictive analytics as a significant platform towards early detection of G. boninense in the future.

A review on the application of spectroscopy to the condiments detection: from safety to authenticity

Condiments are the magical ingredients that make the food present a richer taste. In recent years, due to the increasing consciousness of food safety and human health, much progress has been made in developing rapid and nondestructive techniques for the evaluation of food condiments safety, authentication, and traceability. The potential of spectroscopy techniques, such as near-infrared (NIR), mid-infrared (MIR), Raman, fluorescence, inductively coupled plasma (ICP), and hyperspectral imaging techniques, has been widely enhanced by numerous applications in this field because of their advantages over other analytical techniques. Following a brief introduction of condiment and safety basics, this review mainly focuses on recent vibrational and atomic spectral applications for condiment nondestructive analysis and evaluation, including (1) chemical hazards detection; (2) microbiological hazards detection; and (3) authenticity concerns. The review shows current spectroscopies to be effective tools that will play indispensable roles for food condiment evaluation. In addition, online/real-time applications of these techniques promise to be a huge growth field in the near future.

Multivariate method for prediction of fumonisins B1 and B2 and zearalenone in Brazilian maize using Near Infrared Spectroscopy (NIR)

Fumonisins (FBs) and zearalenone (ZEN) are mycotoxins which occur naturally in grains and cereals, especially maize, causing negative effects on animals and humans. Along with the need for constant monitoring, there is a growing demand for rapid, non-destructive methods. Among these, Near Infrared Spectroscopy (NIR) has made great headway for being an easy-to-use technology. NIR was applied in the present research to quantify the contamination level of total FBs, i.e., fumonisin B1+fumonisin B2 (FB1+FB2), and ZEN in Brazilian maize. From a total of six hundred and seventy-six samples, 236 were analyzed for FBs and 440 for ZEN. Three regression models were defined: one with 18 principal components (PCs) for FB1, one with 10 PCs for FB2, and one with 7 PCs for ZEN. Partial least square regression algorithm with full cross-validation was applied as internal validation. External validation was performed with 200 unknown samples (100 for FBs and 100 for ZEN). Correlation coefficient (R), determination coefficient (R2), root mean square error of prediction (RMSEP), standard error of prediction (SEP) and residual prediction deviation (RPD) for FBs and ZEN were, respectively: 0.809 and 0.991; 0.899 and 0.984; 659 and 69.4; 682 and 69.8; and 3.33 and 2.71. No significant difference was observed between predicted values using NIR and reference values obtained by Liquid Chromatography Coupled to Tandem Mass Spectrometry (LC-MS/MS), thus indicating the suitability of NIR to rapidly analyze a large numbers of maize samples for FBs and ZEN contamination. The external validation confirmed a fair potential of the model in predicting FB1+FB2 and ZEN concentration. This is the first study providing scientific knowledge on the determination of FBs and ZEN in Brazilian maize samples using NIR, which is confirmed as a reliable alternative methodology for the analysis of such toxins.

Discriminant analysis of pyrrolizidine alkaloid contamination in bee pollen based on near-infrared data from lab-stationary and portable spectrometers

Bee pollen may be contaminated with pyrrolizidine alkaloids (PAs) and their N-oxides (PANOs), which are mainly detected by liquid chromatography coupled to tandem mass spectrometry (LC–MS/MS), even though the use of fast near-infrared (NIR) spectroscopy is an ongoing alternative. Therefore, the main challenge of this study was to assess the feasibility of both a lab-stationary (Foss) and a portable (Polispec) NIR spectrometer in 60 dehydrated bee pollen samples. After an ANOVA-feature selection of the most informative NIR spectral data, canonical discriminant analysis (CDA) was performed to distinguish three quantitative PA/PANO classes (µg/kg): < LOQ (0.4), low; 0.4–400, moderate; > 400, high. According to the LC–MS/MS analysis, 77% of the samples were contaminated with PAs/PANOs and the sum content of the 17 target analytes was higher than 400 µg/kg in 28% of the samples. CDA was carried out on a pool of 18 (Foss) and 22 (Polispec) selected spectral variables and allowed accurate classification of samples from the low class as confirmed by the high values of Matthews correlation coefficient (≥ 0.91) for both NIR spectrometers. Leave-one-out cross-validation highlighted precise recognition of samples characterised by a high PA/PANO content with a low misclassification rate (0.02) as false negatives. The most informative wavelengths were within the < 1000, 1000–1660 and > 2400 nm regions for Foss and > 1500 nm for Polispec that could be associated with cyclic amines, and epoxide chemical structures of PAs/PANOs. In sum, both lab-stationary and portable NIR systems are reliable and fast techniques for detecting PA/PANO contamination in bee pollen.

Detection of mycotoxins and toxigenic fungi in cereal grains using vibrational spectroscopic techniques: a review

Nutrition-rich cereal grains and oil seeds are the major sources of food and feed for human and livestock, respectively. Infected by fungi and contaminated with mycotoxins are serious problems worldwide for cereals and oil seeds before and after harvest. The growth and development activities of fungi consume seed nutrients and destroy seed structures, leading to dramatic declines of crop yield and quality. In addition, the toxic secondary metabolites produced by these fungi pose a well-known threat to both human and animals. The existence of fungi and mycotoxins has been a redoubtable problem worldwide for decades but tends to be a severe food safety issue in developing countries and regions, such as China and Africa. Detection of fungal infection at an early stage and of mycotoxin contaminants, even at a small amount, is of great significance to prevent harmful toxins from entering the food supply chains worldwide. This review focuses on the recent advancements in utilising infrared spectroscopy, Raman spectroscopy, and hyperspectral imaging to detect fungal infections and mycotoxin contaminants in cereals and oil seeds worldwide, with an emphasis on recent progress in China. Brief introduction of principles, and corresponding shortcomings, as well as latest advances of each technique, are also being presented herein.

Shortwave Near-Infrared Spectroscopy for Rapid Detection of Aflatoxin B1 Contamination in Polished Rice

The objective of this research was to apply near-infrared spectroscopy, with a short-wavelength range of 950 to 1,650 nm, for the rapid detection of aflatoxin B₁ (AFB₁) contamination in polished rice samples. Spectra were obtained by reflection mode for 105 rice samples: 90 samples naturally contaminated with AFB₁ and 15 samples artificially contaminated with AFB₁. Quantitative calibration models to detect AFB₁ were developed using the original and pretreated absorbance spectra in conjunction with partial least squares regression with prediction testing and full cross-validation. The statistical model from the external validation process developed from the treated spectra (standard normal variate and detrending) was most accurate for prediction, with a correlation coefficient (r) of 0.952, a standard error of prediction of 3.362 μg/kg, and a bias of -0.778 μg/kg. The most predictive models according to full cross-validation were developed from the multiplicative scatter correction pretreated spectra (r = 0.967, root mean square error in cross-validation [RMSECV] = 2.689 μg/kg, bias = 0.015 μg/kg) and standard normal variate pretreated spectra (r = 0.966, RMSECV = 2.691 μg/kg, bias = 0.008 μg/kg). A classification-based partial least squares discriminant analysis model of AFB₁ contamination classified the samples with 90% accuracy. The results indicate that the near-infrared spectroscopy technique is potentially useful for screening polished rice samples for AFB₁ contamination.

Current methods for mycotoxins analysis and innovative strategies for their reduction in cereals: an overview

Mycotoxins are secondary metabolites produced by moulds in food that are considered a substantial issue in the context of food safety, due to their acute and chronic toxic effects on animals and humans. Therefore, new accurate methods for their identification and quantification are constantly developed in order to increase the performance of extraction, improve the accuracy of identification and reduce the limit of detection. At the same time, several industrial practices have shown the ability to reduce the level of mycotoxin contamination in food. In particular, a decrease in the amount of mycotoxins could result from standard processes naturally used for food processing or by procedures strategically introduced during processing, with the specific aim of reducing the amount of mycotoxins. In this review, the current methods adopted for accurate analyses of mycotoxins in cereals (aflatoxins, ochratoxins, trichothecenes, fumonisins) are discussed. In addition, both conventional and innovative strategies adopted to obtain safer finished products from common cereals intended for human consumption will be explored and analysed. © 2018 Society of Chemical Industry.

Qualitative and quantitative analysis of endophyte alkaloids in perennial ryegrass using near-infrared spectroscopy

BACKGROUND

Near-infrared reflectance spectroscopy (NIRS) has been widely used in forage quality control because it is faster, cleaner and less expensive than conventional chemical procedures. In Lolium perenne (perennial ryegrass), one of the most important forage grasses, the infection by asymptomatic Epichloë fungal endophytes alters the plant nutritional quality due to the production of alkaloids. In this research, we developed a rapid method based on NIRS to detect and quantify endophyte alkaloids (peramine, lolitrem B and ergovaline) using a heterogeneous set of L. perenne plants obtained from wild grasslands and cultivars.

RESULTS

NIR spectra from dried grass samples were recorded and classified according to the absence or presence of alkaloids, based on reference methods. The best discriminant equations for detection of alkaloids classified correctly 94.4%, 87.5% and 92.9% of plants containing peramine, lolitrem B and ergovaline, respectively. The quantitative NIR equations obtained by modified partial least squares (MPLS) algorithm had coefficients of correlation of 0.93, 0.41, and 0.76 for peramine, lolitrem B and ergovaline respectively.

CONCLUSION

NIRS is a suitable tool for qualitative analysis of endophyte alkaloids in grasses and for the accurate quantification of peramine and ergovaline. © 2017 Society of Chemical Industry.

Development of Methods for Determination of Aflatoxins

Aflatoxins can cause damage to the health of humans and animals. Several institutions around the world have established regulations to limit the levels of aflatoxins in food, and numerous analytical methods have been extensively developed for aflatoxin determination. This review covers the currently used analytical methods for the determination of aflatoxins in different food matrices, which includes sampling and sample preparation, sample pretreatment methods including extraction methods and purification methods of aflatoxin extracts, separation and determination methods. Validation for analysis of aflatoxins and safety considerations and precautions when doing the experiments are also discussed.

Simultaneous determination of aflatoxins B1, B2, G1, G2, and M1 in dairy products by high-performance liquid chromatography/fluorescence

A fast and reliable method was established for the simultaneous detection of aflatoxins in dairy products by HPLC–FLD coupled with the optimized chromatographic conditions.

Quantitative Determination of Fusarium proliferatum Concentration in Intact Garlic Cloves Using Near-Infrared Spectroscopy

Fusarium proliferatum is considered to be a pathogen of many economically important plants, including garlic. The objective of this research was to apply near-infrared spectroscopy (NIRS) to rapidly determine fungal concentration in intact garlic cloves, avoiding the laborious and time-consuming procedures of traditional assays. Preventive detection of infection before seeding is of great interest for farmers, because it could avoid serious losses of yield during harvesting and storage. Spectra were collected on 95 garlic cloves, divided in five classes of infection (from 1-healthy to 5-very highly infected) in the range of fungal concentration 0.34-7231.15 ppb. Calibration and cross validation models were developed with partial least squares regression (PLSR) on pretreated spectra (standard normal variate, SNV, and derivatives), providing good accuracy in prediction, with a coefficient of determination (R²) of 0.829 and 0.774, respectively, a standard error of calibration (SEC) of 615.17 ppb, and a standard error of cross validation (SECV) of 717.41 ppb. The calibration model was then used to predict fungal concentration in unknown samples, peeled and unpeeled. The results showed that NIRS could be used as a reliable tool to directly detect and quantify F. proliferatum infection in peeled intact garlic cloves, but the presence of the external peel strongly affected the prediction reliability.

Application of visible/near-infrared reflectance spectroscopy for predicting internal and external quality in pepper

BACKGROUND

The characterization of internal (°Brix, pH, malic acid, total phenolic compounds, ascorbic acid and total carotenoid content) and external (color, firmness and pericarp wall thickness) pepper quality is necessary to better understand its possible applications and increase consumer awareness of its benefits. The main aim of this work was to examine the feasibility of using visible/near-infrared reflectance spectroscopy (VIS-NIRS) to predict quality parameters in different pepper types. Commercially available spectrophotometers were evaluated for this purpose: a Polychromix Phazir spectrometer for intact raw pepper, and a scanning monochromator for freeze-dried pepper.

RESULTS

The RPD values (ratio of the standard deviation of the reference data to the standard error of prediction) obtained from the external validation exceeded a value of 3 for chlorophyll a and total carotenoid content; values ranging between 2.5 < RPD < 3 for total phenolic compounds; between 1.5 < RPD <2.5 for °Brix, pH, color parameters a* and h* and chlorophyll b; and RPD values below 1.5 for fruit firmness, pericarp wall thickness, color parameters C*, b* and L*, vitamin C and malic acid content.

CONCLUSION

The present work has led to the development of multi-type calibrations for pepper quality parameters in intact and freeze-dried peppers. The majority of NIRS equations obtained were suitable for screening purposes in pepper breeding programs. Components such as pigments (xanthophyll, carotenes and chlorophyll), glucides, lipids, cellulose and water were used by modified partial least-squares regression for modeling the predicting equations. © 2015 Society of Chemical Industry.

Soy 11S Globulin Acid Subunits as the Novel Food Polymer Carrier

Aflatoxins were conjugated with soy 11S globulins acid subunits and the hapten-specific monoclonal antibodies (McAbs) cross-reactive with four major aflatoxins were achieved using indirect competitive ELISA screening procedure. The two antibodies (clones 1B2 and 2D3) had similar reaction efficiency with aflatoxins B1, B2, and G1 but showed a weak cross-reaction to G2. The clone 4C5 exhibited the highest sensitivity for all four aflatoxins. The concentrations of aflatoxins B1, B2, G1, and G2 at 50% inhibition for 4C5 were 1.1, 1.2, 2.1, and 17.6 pg mL−1. The results indicated that soy 11S globulin acid subunits were suitable novel carriers for aflatoxin antigen in immunization experiments and clone 4C5 could be used for simultaneous analysis of total aflatoxins.

Rapid analysis of deoxynivalenol in durum wheat by FT-NIR spectroscopy

Fourier-transform-near infrared (FT-NIR) spectroscopy has been used to develop quantitative and classification models for the prediction of deoxynivalenol (DON) levels in durum wheat samples. Partial least-squares (PLS) regression analysis was used to determine DON in wheat samples in the range of <50–16,000 µg/kg DON. The model displayed a large root mean square error of prediction value (1,977 µg/kg) as compared to the EU maximum limit for DON in unprocessed durum wheat (i.e., 1,750 µg/kg), thus making the PLS approach unsuitable for quantitative prediction of DON in durum wheat. Linear discriminant analysis (LDA) was successfully used to differentiate wheat samples based on their DON content. A first approach used LDA to group wheat samples into three classes: A (DON ≤ 1,000 µg/kg), B (1,000 < DON ≤ 2,500 µg/kg), and C (DON > 2,500 µg/kg) (LDA I). A second approach was used to discriminate highly contaminated wheat samples based on three different cut-off limits, namely 1,000 (LDA II), 1,200 (LDA III) and 1,400 µg/kg DON (LDA IV). The overall classification and false compliant rates for the three models were 75%–90% and 3%–7%, respectively, with model LDA IV using a cut-off of 1,400 µg/kg fulfilling the requirement of the European official guidelines for screening methods. These findings confirmed the suitability of FT-NIR to screen a large number of wheat samples for DON contamination and to verify the compliance with EU regulation.

Near- and mid-infrared spectroscopy as efficient tools for detection of fungal and mycotoxin contamination in agricultural commodities

In the last decade, near-infrared (NIR) and mid-infrared (MIR) spectroscopy have proven to be most promising tools for the detection of fungal contamination and estimation of mycotoxins in agricultural commodities, particularly of cereals. Owing to significant economic losses incurred from fungal contamination of foodstuffs, producers and processors are looking for fast, reliable, and less-expensive methods for the detection of fungal damage. In this context, NIR and MIR spectroscopy offer a fast, less-expensive, non-destructive, and relatively simple analytical method. Results from published studies indicate that NIR and MIR spectroscopy can be successfully applied to identifying fungal contamination and estimating specific mycotoxins. This review will focus on the applications of NIR and MIR spectroscopy to the classification of fungal contamination and the determination of specific mycotoxin contamination levels, and to compare this technology with traditional analytical methods.

Efficiency of DNA typing methods for detection of smoked paprika "pimenton de la vera" adulteration used in the elaboration of dry-cured Iberian pork sausages

The purpose of this work was to develop a PCR method for the identification of smoked paprika "Pimentón de la Vera" adulteration with paprika elaborated from varieties of pepper foreign to the la Vera region, in central western Spain. Three autochthonous varieties of pepper, Jaranda, Jariza, and Bola, and the varieties Papri Queen, Papri King, Sonora, PS9794, and Papri Ace, foreign to the La Vera region, were used in the study. Analyses of the ITS and 5.8S rDNA, RAPD-PCR, SSR, and ISSR were tested. RAPD-PCR, SSR, and ISSR analyses allowed differentiation among the varieties of paprika analyzed. There was no difference in the sequence of ITS1-5.8S rDNA-ITS2. In addition, with the RAPD-PCR primers S13 and S22, two molecular markers were obtained of 641 and 704 bp, respectively, which allowed all of the smoked paprika varieties to be differentiated from paprikas elaborated with the five foreign varieties. These two molecular markers were investigated as a basis for detecting the adulteration of smoked paprika with paprika elaborated from foreign varieties of pepper.

Developments in mycotoxin analysis: an update for 2008-2009

This review highlights developments in mycotoxin analysis and sampling over a period between mid-2008 and mid-2009. It covers the major mycotoxins: aflatoxins, alternaria toxins, cyclopiazonic acid, fumonisins, ochratoxin, patulin, trichothecenes and zearalenone. Developments in mycotoxin analysis continue, with emphasis on novel immunological methods and further description of LC-MS and LC-MS/MS, particularly as multimycotoxin applications for different ranges of mycotoxins. Although falling outside the main emphasis of the review, some aspects of natural occurrence have been mentioned, especially if linked to novel method developments.

Biosensors for mycotoxin analysis: recent developments and future prospects

The toxicity and prevalence of mycotoxins in commodities and foods has necessitated the development of rapid methods in order to ensure the protection of human food and animal feed supplies. Testing for mycotoxins can be accomplished by many techniques that range from determinative tests in which the presence of the toxin is confirmed, to presumptive tests in which the presence of the toxin is inferred from the presence of markers. This review focuses on tests that fall into a third category, namely indirect assays, where the presence of the toxin is established by it's interaction with an intermediary. Such intermediaries include biological materials that bind mycotoxins, such as antibodies, as well as synthetic materials such as polymers and man-made peptides. The diversity of assays within this category is extraordinary and includes assays based upon traditional microwell formats, microbeads, membranes, electrodes, wave-guides, and solution-phase assays. The microbead format includes platforms as diverse as flow injection immunoassays, tandem column immunoassays, and immunoaffinity columns. The membrane-based formats include flow-through as well as lateral-flow assays. The electrode-based formats incorporate miniaturised immunoassays with electrochemical endpoints. The wave-guide-based devices include formats such as surface plasmon resonance, and fluorescence array biosensors, and the solution phase formats include homogeneous assays such as fluorescence polarisation immunoassay. The breadth of technologies brought to bear upon solving the need for rapid, accurate, detection of mycotoxins is impressive and includes technologies currently available commercially and those which appear poised to enter the marketplace.

An overview of conventional and emerging analytical methods for the determination of mycotoxins

Mycotoxins are a group of compounds produced by various fungi and excreted into the matrices on which they grow, often food intended for human consumption or animal feed. The high toxicity and carcinogenicity of these compounds and their ability to cause various pathological conditions has led to widespread screening of foods and feeds potentially polluted with them. Maximum permissible levels in different matrices have also been established for some toxins. As these are quite low, analytical methods for determination of mycotoxins have to be both sensitive and specific. In addition, an appropriate sample preparation and pre-concentration method is needed to isolate analytes from rather complicated samples. In this article, an overview of methods for analysis and sample preparation published in the last ten years is given for the most often encountered mycotoxins in different samples, mainly in food. Special emphasis is on liquid chromatography with fluorescence and mass spectrometric detection, while in the field of sample preparation various solid-phase extraction approaches are discussed. However, an overview of other analytical and sample preparation methods less often used is also given. Finally, different matrices where mycotoxins have to be determined are discussed with the emphasis on their specific characteristics important for the analysis (human food and beverages, animal feed, biological samples, environmental samples). Various issues important for accurate qualitative and quantitative analyses are critically discussed: sampling and choice of representative sample, sample preparation and possible bias associated with it, specificity of the analytical method and critical evaluation of results.