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The most common methods for acrylamide analysis in foods require the use of LC–MS/MS and GC–MS. Although these methods have great analytical performance, they need intensive sample preparation, highly specialised instrumentation, and are time consuming. In this study, portable and handheld infrared spectrometers were evaluated as rapid methods for screening acrylamide in potato chips and their performances were compared to those of benchtop infrared systems. The acrylamide content of 64 commercial potato chips (169–2453 μg/kg) was determined by LC–MS/MS. Spectral data were collected using mid-infrared (MIR) and near-infrared (NIR) spectrometers. Partial least squares regression (PLSR) calibration models were developed to predict acrylamide levels. Overall, good linear correlation was found between the predicted acrylamide levels and actual measured acrylamide concentrations by LC–MS/MS ( r Pred > 0.90 and SEP < 100 μg/kg). Our results indicate that portable and handheld spectrometers can be used as simple and rapid alternatives for acrylamide analysis in potato chips. [ABSTRACT FROM AUTHOR]

Bacillus species may be resistant to processing and sanitation procedures, making their control an important issue in the food industry. The objective of this study was to develop a rapid method for the differentiation of Bacillus cells at the strain level using infrared microspectroscopy and multivariate pattern recognition techniques. Aliquots (10 ml) of vegetative cells (∼10² CFU/ml) from four strains of each of three Bacillus species (B. cereus, B. mycoides, and B. thuringiensis) were filtered onto hydrophobic grid membranes. The membranes were placed on tryptic soy agar and incubated at 42°C for 24 h and then removed from the agar and dried, and the biomass of individual vegetative colonies was directly measured by attenuated total reflectance infrared (ATR-IR) microspectroscopy. Soft independent modeling of class analogy models generated from second derivative transformed spectra in the 1,300 to 900 cm-1 region exhibited clusters that permitted accurate strain-level classification of all isolates. Major discrimination was related to the signal from phosphate-containing compounds, likely phospholipids. Results indicate that a simple ATR-IR microspectroscopy technique combined with multivariate analysis could provide the food industry with a rapid and reagent-free screening procedure to complement more elaborate molecular identification methods. [ABSTRACT FROM AUTHOR]

Detection of pathogenic microorganisms in food is often a tedious and time-consuming exercise. Developing rapid and cost-effective techniques for identifying pathogens to subspecies is critical for tracking causes of foodborne disease outbreaks. The objective of this study was to develop a method for rapid identification and differentiation of Salmonella serovars and strains within these serovars through isolation on hydrophobic grid membrane filters (HGMFs), examination by infrared (IR) spectroscopy and microspectroscopy, and data analysis by multivariate statistical techniques. Salmonella serovars (Anatum, Enteritidis, Heidelberg, Kentucky, Muenchen, and Typhimurium), most of which were represented by multiple strains, were grown in tryptic soy broth (24 h at 42°C), diluted to 10² to 103 CFU/ml, and filtered using HGMFs. The membranes were incubated on Miller-Mallinson agar (24 h at 42°C), and typical Salmonella colonies were sonicated in 50% acetonitrile and centrifuged. Resulting pellets were vacuum dried on a ZnSe crystal and analyzed using IR spectroscopy. Alternatively, the membranes containing Salmonella growth were removed from the agar, vacuum dried, and colonies were analyzed directly by IR microspectroscopy. Soft independent modeling of class analogy (SIMCA) models were developed from spectra. The method was validated by analyzing Salmonella-inoculated tomato juice, eggs, milk, and chicken. Salmonella serovars exhibited distinctive and reproducible spectra in the fingerprint region (1,200 to 900 cm-1) of the IR spectrum. SIMCA permitted distinguishing Salmonella strains from each other through differences in bacterial lipopolysaccharides and other membrane components. The model correctly predicted Salmonella in foods at serovar (100%) and strain (90%) levels. Isolation of Salmonella on HGMF and selective agar followed by IR spectroscopic analysis resulted in rapid and efficient isolation, identification, and differentiation of Salmonella serovars and strains. [ABSTRACT FROM AUTHOR]

[Display omitted] • Lesser mealworm protein concentrate (LMPC) and polyphenols were conjugated by alkaline method. • Tannic acid exhibits higher binding affinity for LMPC than chlorogenic acid. • The conjugation with polyphenols enhanced the antioxidant activity of LMPC. • The oxidative stability of flaxseed oil emulsions improved when using conjugates. • The conjugates presented potential to be used as dual-functional ingredients. Lesser mealworm protein concentrate (LMPC) was conjugated with chlorogenic acid (CA) or tannic acid (TA) using an alkaline method. The impact of polyphenol type and concentration on the physicochemical and structural characteristics, antioxidant, interfacial, and emulsifying properties of the LMPC-polyphenol conjugates were investigated. Under the conditions tested, TA demonstrated higher affinity for LMPC compared to CA. The conjugation of LMPC induced conformational changes as showed by intrinsic fluorescence and FT-MIR raw spectra analysis. The surface hydrophobicity of the conjugates was reduced, leading to increased interfacial tension values for LMPC-TA conjugates without impairment of the emulsifying activity. The antioxidant properties were significantly improved by the conjugation. Flaxseed oil-in-water (O/W) emulsions stabilized by the conjugates and LMPC remained physically stable for 12 days at 50 °C with a notable reduction of secondary oxidation products when conjugates were used. LMPC-TA and LMPC-CA exhibited potential to be used as novel antioxidant emulsifiers in O/W emulsions. [ABSTRACT FROM AUTHOR]

Highlights: [•] FT-IR coupled with chemometrics correctly discriminated grape juices based on grape variety. [•] A predictive model was constructed using 7 factors with an internal error of 4.6%. [•] Predictions on an external validation set of grape juices were accurate within 5.6% error. [•] FT-IR is rapid, simple, and has many possible applications for authentication within industry. [ABSTRACT FROM AUTHOR]

Monitoring the ripening process by prevalent analytic methods is laborious, expensive, and time consuming. Our objective was to develop a rapid and simple method based on vibrational spectroscopic techniques to understand the biochemical changes occurring during the ripening process of Turkish white cheese and to generate predictive algorithms for the determination of the content of key cheese quality and ripening indicator compounds. Turkish white cheese samples were produced in a pilot plant scale and ripened for 100 d, and samples were analyzed at 20 d intervals during storage. The collected spectra (Fourier-transform infrared, Raman, and near-infrared) correlated with major composition characteristics (fat, protein, and moisture) and primary products of the ripening process and analyzed by pattern recognition to generate prediction (partial least squares regression) and classification (soft independent analysis of class analogy) models. The soft independent analysis of class analogy models classified cheese samples based on the unique biochemical changes taking place during the ripening process. partial least squares regression models showed good correlation (R Pre = 0.87 to 0.98) between the predicted values by vibrational spectroscopy and the reference values, giving low standard errors of prediction (0.01 to 0.57). Portable and handheld vibrational spectroscopy units can be used as a rapid, simple, and in situ technique for monitoring the quality of cheese during aging and provide real-time tools for addressing deviations in manufacturing. [ABSTRACT FROM AUTHOR]

Our aim was to develop a rapid non-targeted approach to authenticate commercial honey combining Raman spectroscopy and pattern recognition analysis. Honey samples (n = 97) were collected from local and global grocery stores and online vendors. Spectra were collected by handheld and compact benchtop Raman systems equipped with a 1064 nm excitation laser and analyzed by pattern recognition techniques (Soft Independent Model of Class Analogies, SIMCA) to develop classification algorithms. High-performance liquid chromatography (HPLC-RI, AOAC#977.20) was used to verify the authenticity of honeys. Both Raman systems formed distinct SIMCA clusters for the samples associated with their unique sugar profile. Evaluation of store-bought commercial samples indicated adulteration in 16 samples (17%); all samples predicted by the Raman algorithms as non-authentic were confirmed by HPLC-RI. Raman technology provides analytical features for ingredient verification, offering the industry and regulatory agencies valuable resources to ensure accurate labeling of honey products. • SIMCA combined with Raman spectroscopy data confirmed the authenticity of commercial honeys. • From the total evaluated 97 store bought honeys, 17% were determined as tainted. • The type of Raman instrument (handheld or compact benchtop) did not compromise classification accuracies. [ABSTRACT FROM AUTHOR]

Diagnosis and treatment of fibromyalgia (FM) remains a challenge owing to the lack of reliable biomarkers. Our objective was to develop a rapid biomarker-based method for diagnosing FM by using vibrational spectroscopy to differentiate patients with FM from those with rheumatoid arthritis (RA), osteoarthritis (OA), or systemic lupus erythematosus (SLE) and to identify metabolites associated with these differences. Blood samples were collected from patients with a diagnosis ofFM(n=50),RA (n = 29), OA (n = 19), or SLE (n = 23). Bloodspot samples were prepared, and spectra collected with portable FT-IR and FTRaman microspectroscopy and subjected to metabolomics analysis by ultra-HPLC (uHPLC), coupled to a photodiode array (PDA) and tandem MS/MS. Unique IR and Raman spectral signatures were identified by pattern recognition analysis and clustered all study participants into classes (FM, RA, and SLE) with no misclassifications (p < 0.05, and interclass distances > 2.5). Furthermore, the spectra correlated (r = 0.95 and 0.83 for IR and Raman, respectively) with FM pain severity measured with fibromyalgia impact questionnaire revised version (FIQR) assessments. Protein backbones and pyridine-carboxylic acids dominated this discrimination and might serve as biomarkers for syndromes such as FM. uHPLC-PDA-MS/MS provided insights into metabolites significantly differing among the disease groups, not only in molecular m/z+ and m/z- values but also in UV-visible chromatograms. We conclude that vibrational spectroscopy may provide a reliable diagnostic test for differentiating FM from other disorders and for establishing serologic biomarkers of FM-associated pain. [ABSTRACT FROM AUTHOR]

A study was conducted to investigate and model kinetic degradation of ascorbic acid in freshly prepared pineapple juice subjected to various pressure (0.1, 300,450 and 600 MPa)-thermal (30, 75, 85 and 95 °C) treatment combinations. Experiments were conducted using a semi-custom made high pressure kinetic tester as well as an aluminum thermal kinetic tester. Thermal degradation of ascorbic acid was described with simple first order kinetics. The thermal rate constants ( k 75 -95 ◦C, 0.1 MPa ) and activation energy ( E a ) for ascorbic acid degradation reaction varied in the range of 0.004–0.006 per min and 14.22–29.78 kJ/mol, respectively. Within the experimental conditions of the study (300–600 MPa at 30 °C for holding times up to 15 min) high pressure processing did not alter ascorbic acid content (535.5–564.5 mg/kg). Combined pressure-thermal treatment (300–600 MPa at 75–95 °C) degraded ascorbic acid with increasing thermal intensity and was modeled using first order fractional conversion kinetics model. The lower asymptote value ( [ A ] ∞ [ A ] 0 ), rate constants ( k 75 -95 ◦C, 600 MPa ) and E a were in the range of 77–85%, 0.108 to 0.138 per min and 17.4–43.8 kJ/mol, respectively. Similarly, pressure sensitivity ( Δ V ≠ ) was ∼0 and −2.99 cm 3 /mol at 30 and 95 °C, respectively. Knowledge gained from the study can be useful for food processors to optimize high pressure treatment conditions for pineapple juice products. [ABSTRACT FROM AUTHOR]

Formulating whey protein beverages at acidic pH provides better clarity but the beverages typically develop an unpleasant and astringent flavor. Our aim was to evaluate the application of infrared spectroscopy and chemometrics in predicting astringency of acidic whey protein beverages. Whey protein isolate (WPI), whey protein concentrate (WPC), and whey protein hydrolysate (WPH) from different manufacturers were used to formulate beverages at pH ranging from 2.2 to 3.9. Trained panelists using the spectrum method of descriptive analysis tested the beverages providing astringency scores. A portable Fourier transform infrared spectroscopy attenuated total reflectance spectrometer was used for spectra collection that was analyzed by multivariate regression analysis (partial least squares regression) to build calibration models with the sensory astringency scores. Beverage astringency scores fluctuated from 1.9 to 5.2 units and were explained by pH, protein type (WPC, WPI, or WPH), source (manufacturer), and their interactions, revealing the complexity of astringency development in acidic whey protein beverages. The WPC and WPH beverages showed an increase in astringency as the pH of the solution was lowered, but no relationship was found for WPI beverages. The partial least squares regression analysis showed strong relationship between the reference astringency scores and the infrared predicted values (correlation coefficient >0.94), giving standard error of cross-validation ranging from 0.08 to 0.12 units, depending on whey protein type. Major absorption bands explaining astringency scores were associated with carboxylic groups and amide regions of proteins. The portable infrared technique allowed rapid prediction of astringency of acidic whey protein beverages, providing the industry a novel tool for monitoring sensory characteristics of whey-containing beverages. [ABSTRACT FROM AUTHOR]

Efficient selection of potato varieties with enhanced nutritional quality requires simple, accurate and cost effective assays to obtain tuber chemical composition information. In this study, 75 Andean native potato samples from 7 Solanum species with different colors were characterized and quantified for their anthocyanin, phenolics and sugar content using traditional reference methods. IR (infrared) spectra of potato extracts were collected using a portable infrared system and partial least squares regression (PLSR) calibration models were developed. These models were validated using both full cross-validation and an independent sample set giving strong linear correlation coefficients of prediction (rPred) > 0.91 and standard error of prediction (SEP) of 24 mg/100 g phenolics, 7 mg/100 g monomeric anthocyanins, 0.1 g/100 g reducing sugars and 0.12 g/100 g sucrose. Overall, portable infrared system with PLSR showed great potential to facilitate potato breeding and certain aspects of crop management, material selection for potato processing and related research by providing alternative prediction models. [ABSTRACT FROM AUTHOR]

In this study, a novel portable infrared spectrometer was evaluated for rapid and simultaneous determination of glucose, fructose, total reducing sugars, soluble solids (°Brix), serum viscosity, Bostwick consistency, predicted paste Bostwick value and pH. A total of 350 hot-break juices from two consecutive years (2013 and 2014) including 66 different varieties grown in 6 counties of California, USA, were used in this study. Duplicate spectra for each tomato juice were collected using the transmission accessory of the portable infrared spectrometer at 50 μm fixed path length. Samples were randomly divided into calibration (n = 280) and external validation (n = 70) sets and partial least squares (PLS) regression was used to develop calibration models to predict all the variables (quality traits) in the validation samples based on the tomato juice spectral data (r pred > 0.82). Overall, our validated chemometric models allowed rapidly (∼2 min) predicting all the quality traits in tomato juice samples with no sample preparation. [ABSTRACT FROM AUTHOR]

Abstract: Near infrared spectroscopy (NIRS) has been widely used to determine food chemical composition and to a lesser extent to evaluate sensory properties. Because sample preparation is relatively simple, NIRS is especially useful in situations where many samples must be analysed, such as gene-bank characterization or breeding. We aimed to assess the feasibility of using NIRS to predict aroma, flavour, mealiness, seed-coat perception, seed-coat brightness, and seed-coat roughness in common beans. Spectra of raw, undried cooked and dried cooked common bean seeds of 55 accessions were registered. Partial least squares (PLS) regression equations were developed between spectra absorbance and sensory properties scored by eleven trained panellists. Spectra registered on dried cooked samples generally yielded the best predictions. The relative ability of prediction (RAP) values were greater than 0.8 for flavour and mealiness and between 0.5 and 0.7 for seed-coat roughness and brightness. However, a suitable model to estimate the seed-coat perception was not found. These results make it possible to screen for samples that are close to the target sensory properties and thus substantially reduce the number of panel sessions needed for gene-bank evaluation or breeding. [Copyright &y& Elsevier]

Abstract: Infrared spectroscopy (IR) is a well-established technique for determining component levels in foods. New portable technology offers versatility and ruggedness by reducing the size and weight of the spectroscopy systems without compromising performance and reproducibility. The aim of this work was to evaluate the performance of regression models developed by dispersive NIR, FT-NIR and MIR using laboratory benchtops and portable instruments for determination of the main components in ground endosperm of common beans (protein, starch, and amylose). In order to increase the speed of data collection and prevent cross-contamination between samples, NIR spectra of samples in a polystyrene bag were taken. Endosperms of 54 different genotypes cultivated in different locations in Catalonia and Asturias (Spain) were analyzed by standard chemistry (reference) methods and their spectra were collected using benchtop and portable systems on dispersive NIR, FT-NIR and MIR. Partial least squares regression (PLSR) was used to correlate the spectra matrix with the reference value and the regression model was validated by full-cross-validation. Ratio of performance to deviation (RPD) value was used to test the regression model performance, with the FT-NIR benchtop system giving the best RPD values of 3.7, 3.2 and 2.8 for protein, starch and amylose levels, respectively. Handheld NIR and MIR portable systems showed good predictability with RPD values of 3.5, 2.9 and 2.6 for protein, starch and amylose levels, respectively. NIR spectral collection using polystyrene bags had detrimental impact in the PLSR models in terms of reduction of the models goodness of fit and RPD values. Portable infrared units may provide the plant breeder and germplasm banks with an efficient method for simple, rapid and high throughput quantification of quality parameters in common beans. [Copyright &y& Elsevier]

Abstract: Consumption of omega-3 fatty acids (ω-3’s), whether from fish oils, flax or supplements, can protect against cardiovascular disease. Finding plant-based sources of the essential ω-3’s could provide a sustainable, renewable and inexpensive source of ω-3’s, compared to fish oils. Our objective was to develop a rapid test to characterize and detect adulteration in sacha inchi oils, a Peruvian seed containing higher levels of ω-3’s in comparison to other oleaginous seeds. A temperature-controlled ZnSe ATR mid-infrared benchtop and diamond ATR mid-infrared portable handheld spectrometers were used to characterize sacha inchi oil and evaluate its oxidative stability compared to commercial oils. A soft independent model of class analogy (SIMCA) and partial least squares regression (PLSR) analyzed the spectral data. Fatty acid profiles showed that sacha inchi oil (44% linolenic acid) had levels of PUFA similar to those of flax oils. PLSR showed good correlation coefficients (R 2 >0.9) between reference tests and spectra from infrared devices, allowing for rapid determination of fatty acid composition and prediction of oxidative stability. Oils formed distinct clusters, allowing the evaluation of commercial sacha inchi oils from Peruvian markets and showed some prevalence of adulteration. Determining oil adulteration and quality parameters, by using the ATR-MIR portable handheld spectrometer, allowed for portability and ease-of-use, making it a great alternative to traditional testing methods. [Copyright &y& Elsevier]

Abstract: Fourier-transform infrared (FTIR) spectroscopy was used to monitor amino acids, organic acids, and changes during ripening. Twelve Cheddar cheese samples were ripened for 73 days and samples were drawn periodically. Water-soluble fractions of samples were analyzed by gas chromatography (20 amino acids), liquid chromatography (three organic acids), and FTIR spectroscopy (4000–700 cm−1). Spectra were correlated with chromatographic data and ripening events and analyzed by multivariate statistics to develop prediction and classification models. Most models showed a good fit (correlation coefficient ≥0.89) and could predict the levels of amino acids and organic acids and age of the cheese in less than 20 min. Lactic acid, leucine, glutamic acid, asparagine, phenylalanine, and valine were present in significantly high concentrations. Samples could be classified based on their age due to the differences in spectral region 1800–900 cm−1. Some of the changes in the FTIR spectra of WSF during ripening were also characterized. [Copyright &y& Elsevier]

Abstract: An efficient and rapid protocol for profiling tomato carotenoids based on their specific vibrational spectroscopic signatures was developed. Twenty-four tomato varieties that included eight distinct combinations of genes affecting carotenoid concentration and content were grown and harvested in a replicated trial. Hexane was used to extract the lipid fraction from samples, and the extract was applied directly onto an ATR ZnSe crystal plate for spectra acquisition and injected in a reverse-phase HPLC system for carotenoid separation. Soft independent modelling of class analogy (SIMCA) was used to classify tomatoes based on unique infrared spectral signatures. Models exhibited tight and well-separated clusters (inter-class distances >3.0) that correlated well with the HPLC information, and demonstrated the capability of grouping the tomato varieties based on their carotenoid profile. Classification of lipid fractions was primarily based on the presence of trans-double bonds and their cis and trans conjugations. Major discriminating bands at 957 and 964cm−1 were associated with bending trans HC-plane deformation vibrations. ATR-IR and multivariate analysis provided a simple and rapid tool for the identification of dietary carotenoids. This technique will facilitate the effective selection of tomato varieties with specific pigment content, improving the screening process for carotenoid-rich products. [Copyright &y& Elsevier]

Abstract: Salmonella enterica serovars are prevalent foodborne pathogens responsible for high numbers of salmonellosis each year. Complex Fourier-transform infrared (FTIR) spectra offer unique biochemical fingerprints of bacteria with bands due to major cellular components. Growth media effects on discrimination of Salmonella serovars by FTIR spectroscopy were investigated and a novel sample preparation technique was developed. S. enterica strains from six serovars were grown on xylose lysine desoxycholate (XLD), Miller–Mallinson (MM), and plate count (PCA) agar as a control (37 °C, 24 h). Isolated colonies were suspended in 50% acetonitrile and centrifuged; the remaining pellet was placed on an AMTIR (attenuated total reflectance) crystal and dried under vacuum. Classification models (Soft Independent Modeling of Class Analogy, SIMCA), generated from derivatized infrared spectra (1300–900 cm− 1 or 1200–900 cm− 1), successfully discriminated among Salmonella strains with major discrimination from 1000–970 cm− 1 associated to stretching modes of O-specific polysaccharide chains of lipopolysaccharides. Sample treatment with acetonitrile enhanced safe handling of the bacteria, removed interfering signals and improved the discriminating ability of SIMCA. All media were able to discriminate the S. enterica strains studied, varying in discriminating peaks and class distances in SIMCA classification. This methodology, with the production of large libraries of pathogenic bacteria, could be applied for the rapid monitoring of bacterial contamination in food with minimal sample manipulation. [Copyright &y& Elsevier]