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Tetracycline (TC) is an antibiotic utilized in dairy livestock, which can leave trace residues in milk and other dairy products. Dicyandiamide (DCD), a grassland fertilizer, but also potentially an adulterant to increase milk apparent protein content, has been found in milk products that were subsequently banned. Both these chemicals can pose human health risks via the consumption of dairy foods, and therefore rapid, simple detection methodologies are necessary. Herein, we fabricated a transparent and homogeneous substrate by fabricating silver nanoparticle (Ag NP) arrays based on the anodic aluminum oxide (AAO) template-assisted electrochemical deposition approach. The periodic nanostructure was optimized to obtain high SERS activity by varying nanopore diameters and Ag NP sputtering duration to have Ag NP nanogaps in the sub 10 nm regime so that the high sensitivity was achieved with detecting R6G analytes at the 1 × 10–10 M level. The substrate was also used to detect TC and DCD in milk at low concentration levels of 1 × 10–9 M and 1 × 10–7 M, respectively, with good linear correlation between concentration and intensity (TC R2 = 0.96; DCD R2 = 0.99). The assignments of Raman bands of tetracycline and dicyandiamide were also given by density-functional-theory (DFT) calculations. The advantage of this transparent SERS substrate is that it is especially useful for measurement of analytes at the interface between Ag NP substrate layer and the opaque liquid containing the analytes without special pretreatment of the sample. Thus, this method may provide an alternative practical and reliable platform for rapid detection of contaminants in foods.

The traditional candling methods are very hard to discriminate the infertile chicken eggs from the fertile ones before hatching on the poultry farm. The purpose of this study was to detect infertil...

Problems with “clenbuterol”, a synthetic β2-adrenergic stimulant that includes clenbuterol, ractopamine, and albuterol, have been increasing in recent years. This article focuses on the detection of albuterol, chemically called 3,6-dihydroxy1-methyl-5-oxo-3,5-dihydro-2H-indolium betaine. It is difficult to directly measure the content of clenbuterol in pork due to its messy and uneven composition, which requires a destructive pre-treatment process that takes time and effort. In this study, a method for subsurface food inspection was presented based on a newly developed line-scan spatially scattering Raman spectroscopy technique. A spatially offset Raman spectroscopy system based on line-scan Raman chemical imaging system was built, which was used to collect spatially offset Raman spectra from the samples. Under the condition of one CCD exposure, the spatially offset Raman spectroscopy system can collect a series of Raman spectra simultaneously in a narrow space interval and a wide offset range. Through data analysis, the rare clenbuterol species in the sample can be determined by the position of characteristic peaks. The system was used to collect salbutamol Raman signal, and the results showed that the characteristic peaks of salbutamol were consistent with the standard characteristic peaks, so it was possible to use the system to detect lean meat in meat.

Mixed chain phospholipids containing a saturated fatty acid at sn1 and a polyunsaturated fatty acid in sn2 are common in the specialized biological membranes prevalent in neural, retinal and organ tissues. Particularly important are mixed lipids containing palmitic or stearic acid and arachidonic or docosahexaenoic acid. Gradient temperature Raman spectroscopy (GTRS) applies the temperature gradients utilized in differential scanning calorimetry to Raman spectroscopy, providing a straightforward technique to identify molecular rearrangements and phase transitions. Herein we utilize GTRS for 1-18:0, 2-20:4n-6 PC; 1-18:0 2-22:6n-3 PC; and 1-18:0, 2-18:0 PC from −80 to 50 °C temperatures. 20 Mb three-dimensional data arrays with 0.2 °C increments and first/second derivatives allowed detailed vibrational mode assignment and analysis. Samples were analyzed neat and with molecular hydration. Previously reported phase transitions for hydrated 18:0−20:4PC and 18:0−22:6PC and numerous spectral differences resulting from hydration and the double bond structure were clearly observed. Molecular models showed that the addition of minimal water molecules results in significant structural differences compared to the neat molecules; 18:0−22:6PC is strikingly compact with water when viewed from the hydrophilic end. This precise Raman data cannot be observed in typically utilized fully hydrated vesicle samples, however the improved GTRS will allow for more precise analysis in fully hydrated vesicles because the underlying modes in the unavoidably broadened spectra can be identified.

A new method for detection both external and internal quality attributes of tomato was proposed in this paper. The comprehensive quality detection could be completed by the image and spectra analyses based on the optical sensing system. The images processing method contained three steps: (1) morphological filtering; (2) binarization and (3) circle fitting. The first step was applied to reduce the random noises in the raw images. The second step was aimed to obtain the binary images that contained the contour information of the tomato edge. And the circle fitting algorithm was used to obtain the final diameter information of the tomato samples. The values of R and the RMSE for size prediction results of the tomato samples were 0.9813 and 1.269 mm, respectively. For the spectra analysis, the light scatter effects, including addition coefficient and multiplication coefficient in the raw spectra, were the main reasons for the calibration failure of the multivariate linear model such as PLS, MLR and PCR. Thus, the NSR method was used to eliminate the light scatter effects in this paper. Compared with the other method, NSR method was advantages in higher prediction performance and the simpler calculation. The RMSEP values of the final PLS model were 0.2936 % and 2.0129 a.u. for the SSC and a*, respectively. Thus, the optical sensing system combined with effective information processing method was able to detect the tomato external and internal quality attributes, which could be more suitable to apply in the food processing enterprise in the practice.

Gradient Temperature Raman spectroscopy (GTRS) applies the temperature gradients utilized in differential scanning calorimetry (DSC) to Raman spectroscopy, providing a straightforward technique to identify molecular rearrangements that occur at or near phase transitions. 20 Mb threedimensional data arrays with 1.0 or 0.2°C increments allow complete assignment of solid, liquid and transition state vibrational modes, including low intensity/frequency vibrations that cannot be readily analyzed with conventional Raman. We compared GTRS and DSC data for commercial fish oil supplements that are excellent sources of docosahexaenoic acid (DHA; 22:6n-3) and eicosapentaenoic acid (EPA; 20:5n-3). Krill oils and whole fish and shellfish have nearly all their PUFA contained within phospholipids (PL). Development of any fast-throughput optical identification system for seafood products will require improved PL Raman data. We also analyzed molecularly hydrated PL with DHA and other unsaturated lipids. Each fish oil and PL have a unique, distinctive response to the thermal gradient, which graphically and spectroscopically differentiates them. The entire set or any subset of the any of the contour plots, first derivatives or second derivatives can be utilized to create a graphical standard to quickly authenticate a given product or source material.

Real-time detection of frozen meat freshness without thawing is important. This study investigates inspection of frozen pork quality attributes without thawing using fluorescence hyperspectral imaging (HSI). Partial least squares regression (PLSR) models were developed based on fluorescence spectra for total volatile basic nitrogen (TVB-N), pH, L*, a*, and b*, and compared with PLSR models based on visible/near-infrared (Vis/NIR) HSI of the same samples. Competitive adaptive reweighted sampling was used to select key fluorescence wavelengths related to each indicator. The correlation coefficients of prediction (Rp) of the models established by fluorescence spectra, with optimal pre-treatment for TVB-N, pH, L*, a*, and b*, were 0.9447, 0.9037, 0.6602, 0.8686, and 0.8699, respectively. Except for L*, fluorescence HSI-based model performance was better than that of Vis-NIR HSI. Model performance was further improved using selected key wavelengths. Results demonstrated that fluorescence HSI could determine freshness indicators of frozen pork without thawing.

This study reports a nondestructive detection method using Raman chemical imaging (RCI) technology for the simultaneous determination of multiple veterinary drugs, such as ofloxacin, chloramphenicol, and sulfadimidine, in pork. A line-scan Raman imaging system was employed to acquire images of pure veterinary drugs and pork samples containing single and mixed drugs. Raman characteristic peaks at 1623, 1353, and 1147 cm−1 were identified for ofloxacin, chloramphenicol, and sulfadimidine, respectively. An image processing method was proposed to calculate the “pixel-ratio” values in each feature image, and linear regression models for a single veterinary drug were then established between the “pixel-ratio” values and the actual concentrations. By applying the models to samples with mixed veterinary drugs, the concentrations of the three drugs were predicted with correlation coefficients of 0.978, 0.986, and 0.984. The satisfactory results indicated that along with the proposed “pixel-ratio” method, RCI technology enables the nondestructive quantitation and spatial distribution visualization of multiple veterinary drug residues.

Surface-enhanced Raman spectroscopy (SERS) is an emerging new analytical tool that boasts the feature of high detection sensitivity and molecular fingerprint specificity, attracting increased attention and showing promise for various applications in many areas including food industry. But in practice, special pretreatments of samples are generally required and to some extent have restricted the extension of its applications, particularly in examining analytes in opaque food. In this work, we put forward a new approach to fabrication of transparent SERS substrates which could be used to probe residual ractopamine on pork meat directly without pretreatment of the meat samples. The SERS substrate was fabricated based on anodic aluminum oxide (AAO) template, from which a conical-pore-AAO template with regularly ordered Al2O3 nanotips on the surface was formed after multistep process of anodization and etching, followed by removal of remaining aluminum and sputtering silver nanoparticles (Ag NPs) on the nanotips on the surface. The as-fabricated transparent SERS substrate could detect ractopamine in solution with a detection limit as low as 10−8 M, which is lower than the provision of the international standard concentration of 10 μg/L, and was confirmed to be sensitive enough for detecting trace ractopamine on meat directly. Therefore, this work not only demonstrates an easy approach to fabrication of a novel transparent SERS substrate for detection of residual ractopmine in meat but also may provide a convenient and effective solution to the problem of directly measuring trace chemicals on the surface of opaque food.

Ganoderma lingzhi (G. lingzhi), G. sinense, G. applanatum, etc. belongs to the Ganoderma genus of polypore mushrooms which contain rich polysaccharides valuable for nutrition and positive medicinal effects. In order to evaluate polysaccharide content in Ganoderma mycelia obtained in the fermentation process quickly and accurately, in this work we employed infrared spectroscopy to examine different Ganoderma stains of samples from diversified sources. Through mid-infrared (mid-IR) spectroscopy, we could identify the most relevant spectral bands required for polysaccharide evaluation, and through near-infrared (NIR) spectroscopy, we could establish the quantification model for making satisfactory prediction of polysaccharide ingredient content. As such, we have achieved an effective and convenient approach to quantitative assessment of the total polysaccharides in Ganoderma mycelia but also demonstrated that infrared spectroscopy can be a powerful tool for quality control of Ganoderma polysaccharides obtained from industrial production.

Specialized pro-resolving mediators provide promising targets for new drugs and natural products. Much work has been accomplished on the structure/ function of the lipoxygenase and cyclooxygenase enzymes but not on the substrates. A better visualization of three-dimensional lipid structures will allow increased refinement of the interactions that produce the pro-resolving mediators, and lead to improvements in synthetic pathways. We present systematic analysis of oleic (18:1n-9), linoleic (18:2n-6), alpha-linolenic (18:3n-3), arachidonic (20:4n-6), docosapentaenoic (22:5n-3), and docosahexaenoic (22:6n-3) acids. Continuous gradient temperature Raman spectroscopy (GTRS) applies the temperature gradients utilized in differential scanning calorimetry to Raman spectroscopy. GTRS can identify and differentiate specific carbon chain sites, finally allowing Raman analysis to explain why the long-chain polyunsaturated fatty acids (LC-PUFA) exhibit such extreme functional differences despite minimal changes in chemical structure. Detailed vibrational analysis of the important frequency ranges 1450 - 1200 cm-1 (includes CH2 bending and twisting) and 1750 - 1425 cm-1 (includes C=C stretching and C-C stretching plus H-C in-plane rocking) shows for the first time that each molecule has its own characteristic set of modes with only some redundancy/commonality. The number and frequency of modes correlates with three-dimensional molecular structure, not the degree of unsaturation. The high degree of specificity of lipoxygenase and cyclooxygenase enzymes should be reconsidered in light of the fact that individual sites on the polyunsaturated fatty acid chain are nonequivalent, and each LC-PUFA molecule has an individual, specific three dimensional structure incorporating torsion.

The United States Pharmacopeial Convention has led an international collaborative project to develop a toolbox of screening methods and reference standards for the detection of milk powder adulteration. During the development of adulterated milk powder reference standards, blending methods used to combine melamine and milk had unanticipated strong effects on the near-infrared (NIR) spectrum of melamine. The prominent absorbance band at 1468 nm of melamine was retained when it was dry-blended with skim milk powder but disappeared in wet-blended mixtures, where spray-dried milk powder samples were prepared from solution. Analyses using polarized light microscopy, Raman spectroscopy, dielectric relaxation spectroscopy, X-ray diffraction, and mass spectrometry indicated that wet blending promoted reversible and early Maillard reactions with lactose that are responsible for differences in melamine NIR spectra between wet- and dry-blended samples. Targeted detection estimates based solely on dry-blended reference standards are likely to overestimate NIR detection capabilities in wet-blended samples as a result of previously overlooked matrix effects arising from changes in melamine hydrogen-bonding status, covalent complexation with lactose, and the lower but more homogeneous melamine local concentration distribution produced in wet-blended samples. Techniques used to incorporate potential adulterants can determine the suitability of milk reference standards for use with rapid detection methods.

A partial least squares regression (PLSR) model to map internal soluble solids content (SSC) of apples using visible/near-infrared (VNIR) hyperspectral imaging was developed. The reflectance spectra of sliced apples were extracted from hyperspectral absorbance images obtained in the 400–1000 nm range. Prediction models for SSC mapping were developed for three different measurement/sampling designs that varied in the number and size of the regions of interest (ROIs) used for apple SSC measurement and spectral averaging. Case 1 used 29 small ROIs per apple, Case II used 9 moderate-size ROIs per apple, and Case III used 5 large ROIs per apple. The optimal pre-treatment of the spectra extracted from the hyperspectral images was investigated to enhance the performance of the prediction models. The coefficients of determination and root mean square errors of the best-performing models were, respectively, 0.802 and ±0.674 °Brix for Case I, 0.871 and ±0.524 °Brix for Case II, and 0.876 and ±0.514 °Brix for Case III. The accuracy of the PLSR models was enhanced by using the spectra and SSC measured/averaged from the fewer but larger areas of the apples rather than from more numerous but smaller areas. PLS images of SSC showed the predicted internal distribution of SSC within the apples. The overall results demonstrate that hyperspectral absorbance imaging techniques may be useful for mapping internal soluble solids content of apples.

Since the 1950's, the broad-spectrum, organochlorine insecticide endosulfan (6,7,8, 9,10,10-hexachloro-1,5,5a,6,9,9a-hexahydro-6,9-methano-2,4,3-benzodioxathiepine-3-oxide) has been used on numerous crops. Due to its persistence, bioaccumulation, long-range transport, and adverse effects to human health and ecosystems, it was officially identified as a persistent organic pollutant (POP) in 2011. The last uses in the United States were phased out in 2016. Endosulfan consists of two diastereomers, α-endosulfan and β-endosulfan, and while the α-isomer exists as two asymmetrical, twist-chair enantiomers which interchange, the β-isomer is a symmetrical-chair conformation. In addition, the β-isomer was found to isomerize to the α-isomer. Gradient Temperature Raman Spectroscopy (GTRS) enables identification the molecular sites at which bending vibrational modes becomes twisting or wagging vibrational modes. Previous studies using GTRS and chemical calculations afforded evidence for specific bond movements and the irreversibility of the isomerization mechanism. However, not all of the vibrational modes observed in the spectra could be explained. Thus, new analyses of the GTRS data were conducted to examine the effects of torsional forces on the bond movement, which allowed for the identification of all the peaks. These newly-identified torsional forces provide further confirmation of the isomerization mechanism and its irreversibility. Finally, this isomerization explains why β-endosulfan is rarely detected in the atmosphere.

Subsurface inspection of food and agricultural products is challenging for optical-based sensing techniques due to complex interactions between light and heterogeneous or layered samples. In this study, a method for subsurface food inspection was presented based on a newly developed line-scan spatially offset Raman spectroscopy (SORS) technique. A 785 nm point laser was used as a Raman excitation source. The line-shape SORS data from the sample was collected in a wavenumber range of 0–2815 cm −1 using a detection module consisting of an imaging spectrograph and a CCD camera. Two layered samples, one by placing a 1 mm thick plastic sheet cut from original container on top of cane sugar and the other by placing a 5 mm thick carrot slice on top of melamine powder, were created to test the subsurface food inspection method. For each sample, a whole set of SORS data was acquired using one CCD exposure in an offset range of 0–36 mm (two sides of the incident laser point) with a spatial interval of 0.07 mm. Raman spectra from the cane sugar under the plastic sheet and the melamine powder under the carrot slice were successfully resolved using self-modeling mixture analysis (SMA) algorithms, demonstrating the potential of the technique for authenticating foods and ingredients through packaging and evaluating internal food safety and quality attributes. The line-scan SORS measurement technique provides a rapid and nondestructive method for subsurface inspection of food safety and quality.

Both surface and subsurface food inspection is important since interesting safety and quality attributes can be at different sample locations. This paper presents a multipurpose line-scan Raman platform for food safety and quality research, which can be configured for Raman chemical imaging (RCI) mode for surface inspection and spatially offset Raman spectroscopy (SORS) mode for subsurface inspection. In the RCI mode, macro-scale imaging was achieved using a 785 nm line laser up to 24 cm long with a push-broom method. In the SORS mode, a 785 nm point laser was used and a complete set of SORS data was collected in an offset range of 0–36 mm with a spatial interval of 0.07 mm using one CCD exposure. The RCI and SORS modes share a common detection module including a dispersive imaging spectrograph and a CCD camera, covering a Raman shift range from −674 to 2865 cm−1. A pork shoulder and an orange carrot were used to test large-field-of-view (230 mm wide) and high-spatial-resolution (0.07 mm/pixel) settings of the RCI mode for food surface evaluation. Fluorescence-corrected images at selected Raman peak wavenumbers were used to view Raman-active analytes on the whole sample surfaces (e.g., fat on the pork shoulder and carotenoids over the carrot cross section). Also, three layered samples, which were created by placing carrot slices with thicknesses of 2, 5, and 8 mm on top of melamine powder, were used to test the SORS mode for subsurface food evaluation. Raman spectra from carrot and melamine were successfully resolved for all three layered samples using self-modeling mixture analysis. The line-scan Raman imaging and spectroscopy platform provides a new tool for surface and subsurface inspection for food safety and quality.

Docosahexaenoic acid (DHA, 22:6n-3) is exclusively utilized in fast signal processing tissues such as retinal, neural and cardiac. N-3 docosapentaenoic acid (n-3DPA, 22:5n-3), with just one less double bond, is also found in the marine food chain yet cannot substitute for DHA. Gradient temperature Raman spectroscopy (GTRS) applies the temperature gradients utilized in differential scanning calorimetry (DSC) to Raman spectroscopy, providing a straightforward technique to identify molecular rearrangements that occur near and at phase transitions. Herein we apply GTRS and both conventional and modulated DSC to n-3DPA and DHA from -100 to 20°C. Three-dimensional data arrays with 0.2°C increments and first derivatives allowed complete assignment of solid, liquid and transition state vibrational modes. Melting temperatures n-3DPA (-45°C) and DHA (-46°C) are similar and show evidence for solid-state phase transitions not seen in n-6DPA (-27°C melt). The C6H2 site is an elastic marker for temperature perturbation of all three lipids, each of which has a distinct three dimensional structure. N-3 DPA shows the spectroscopic signature of saturated fatty acids from C1 to C6. DHA does not have three aliphatic carbons in sequence; n-6DPA does but they occur at the methyl end, and do not yield the characteristic signal. DHA appears to have uniform twisting from C6H2 to C12H2 to C18H2 whereas n-6DPA bends from C12 to C18, centered at C15H2. For n-3DPA, twisting is centered at C6H2 adjacent to the C2-C3-C4-C5 aliphatic moiety. These molecular sites are the most elastic in the solid phase and during premelting.

Deliberate chemical contamination of food powders has become a major food safety concern worldwide. This study used Raman imaging and FT-IR spectroscopy to detect Sudan Red and white turmeric adulteration in turmeric powder. While Sudan Red Raman spectral peaks were identifiable in turmeric-Sudan Red samples, Sudan Red false positive detection was observed in binary Raman images, limiting effective quantitative detection. In addition, white turmeric Raman spectral peaks were unidentifiable in turmeric-white turmeric mixtures. However, IR spectra of turmeric-Sudan Red and turmeric-white turmeric samples provided discrete identifier peaks for both the adulterants. Partial least squares regression models were developed using IR spectra for each mixture type. The models estimated Sudan Red and white turmeric concentrations with correlation coefficients of 0.97 and 0.95, respectively. Priority should be given to developing an IR imaging system and incorporating it with Raman system to simultaneously measure of food samples for detection of adulterants.

Fipronil is a phenylpyrazole insecticide commonly used in agriculture and residential applications. In this paper, we reported a novel label-free surface-enhanced Raman spectroscopy (SERS) method for detection of fipronil residues in chicken eggs (mostly accumulated on the egg membrane). We fabricated the SERS substrates composed of the SiO

Commercial Raman systems generally conduct imaging and spectroscopy measurements at subcentimeter scales. Such small spatial ranges cannot be used to inspect food samples with large surface areas (e.g., tomato fruit and beef steak), which is not convenient for food experiments. A line-scan macro-scale Raman system has been developed using a 785 nm line laser to implement high-throughput Raman chemical imaging (RCI) for food safety and quality research. A one-axis positioning table is used to move the samples to accumulate hyperspectral data using a pushbroom method. A dispersive Raman spectrograph is used in the system, which can be configured to backscattering RCI mode for surface inspection and spatially offset Raman spectroscopy (SORS) mode for subsurface inspection. In-house developed LabVIEW software is used to fulfill functions for system control, hardware parameterization, and data transfer. The systems is flexible and versatile for food test, and it has been used to evaluate safety and quality of various food and agricultural products, such as detecting chemical adulterants mixed in food powders, mapping carotenoid content on carrot cross section, imaging whole surface of pork shoulder, and authenticating foods and ingredients through packages.

Turmeric powder (Curcuma longa L.) is known for its use in foods, in medicine, and as a cosmetic. In recent years, economically driven contamination of turmeric powder with different chemicals is increasing. This study used a 1064 nm hyperspectral Raman imaging system for detection of Sudan Red G dye contamination in turmeric powder. Sudan Red was mixed with turmeric powder at five concentration levels (1%, 5%, 10%, 15%, and 20%- w/w). Each mixture sample was packed in a sample container. A Raman chemical image of each sample was acquired across the 7.5 mm x 7.5 mm surface area using a 0.25 mm step size. The spectral fingerprint of turmeric and Sudan Red were identified and used to obtain a binary image from the Raman chemical image of each sample. A simple threshold method was applied to convert the contaminant pixels into white pixels and turmeric pixels into the black (background) pixels. The detected Sudan Red pixels were correlated with the actual concentration in the sample. The result shows that the Sudan Red pixels in the sample image is linearly correlated (R2 = 0.99) with the actual concentration of the sample. This study demonstrated the 1064 nm hyperspectral Raman imaging system as a potential tool to detect chemical contaminants in turmeric powder.

A nondestructive and sensitive method is developed to determine mixed pesticides of acetamiprid, chlorpyrifos and carbendazim in apple samples by surface-enhanced Raman spectroscopy (SERS). Self-modeling mixture analysis (SMA) was used to identify and extract the Raman signals of each pesticide from the spectra of apples contaminated with mixed pesticides. Results indicate that the obtained SERS signal intensities of each pesticide in their mixture have no obvious difference to the signal intensities of the corresponding pure pesticide at a low concentration. The lowest detectable level of acetamiprid, chlorpyrifos and carbendazim in apple are 0.0054 mg/kg, 0.064 mg/kg and 0.014 mg/kg, respectively, which are sensitive enough for identifying apple contaminated with pesticides above the maximum residue limit. The predicted values of each pesticide in their mixture are obtained using the prediction model based on the Raman signal of the single pesticide. The correlation coefficients of predicted values and actual values are 0.893 for acetamiprid, 0.926 for chlorpyrifos and 0.938 for carbendazim, respectively. The method presents the ultrasensitive SERS performance for quantifying residual pesticides in apple samples without sample pre-treatment, showing great potential to serve as a useful means for monitoring pesticide residues used in mixed state. Copyright © 2016 John Wiley & Sons, Ltd.

We analyzed the unsaturated fatty acids oleic (OA, 18:1n-9) and linoleic (LA, 18:2n-3), and a 3:1 LA:OA mixture from −100 to 50 °C with continuous gradient temperature Raman spectroscopy (GTRS). The 20 Mb three-dimensional data arrays with 0.2 °C increments and first/second derivatives allowed rapid, complete assignment of solid, liquid, and transition state vibrational modes. For OA, large spectral and line width changes occurred in the solid state γ to α transition near −4 °C, and the melt (13 °C) over a range of only 1 °C. For LA, major intensity reductions from 200 to 1750 cm−1 and some peak shifts marked one solid state phase transition at −50 °C. A second solid state transition (−33 °C) had minor spectral changes. Large spectral and line width changes occurred at the melt transition (−7 °C) over a narrow temperature range. For both molecules, melting initiates at the diene structure, then progresses towards the ends. In the 3:1 LA:OA mixture, some less intense and lower frequencies present in the individual lipids are weaker or absent. For example, modes assignable to C8 rocking, C9H–C10H wagging, C10H–C11H wagging, and CH3 rocking are present in OA but absent in LA:OA. Our data quantify the concept of lipid premelting and identify the flexible structures within OA and LA, which have characteristic vibrational modes beginning at cryogenic temperatures.

Since 2008, the detection of the adulterant melamine (2,4,6-triamino-1,3,5-triazine) in food products has become the subject of research due to several food safety scares. Near-infrared (NIR) hyperspectral imaging offers great potential for food safety and quality research because it combines the features of vibrational spectroscopy and digital imaging. In this study, NIR hyperspectral imaging was investigated for quantitative evaluation of melamine particles in nonfat and whole milk powders. Melamine was mixed into milk powders in a concentration range of 0.02–1.00% (w/w). A NIR hyperspectral imaging system was used to acquire images (938–1654 nm) of melamine powder, whole milk powder, nonfat milk powder, and mixtures of melamine and each of the milk powders. Two optimal bands (1447 nm and 1466 nm) were selected by a linear correlation algorithm with pure milk and pure melamine. Band ratio (B1447/1466) images coupled with a single threshold were used to create resultant images to visualize identification and distribution of the melamine adulterant particles in milk powders. The identification results were verified by spectral feature comparison between separated mean spectra of melamine pixels and milk pixels. Linear correlations (r) were found between the number of pixels identified as containing melamine and melamine concentration in nonfat milk and whole milk powders, which were 0.980 and 0.970 or higher, respectively. The study demonstrated that the combination of NIR hyperspectral imaging and simple band ratioing was promising for rapid quantitative analysis of melamine in milk powders.

Raman spectroscopy has proven to be a reliable method for detection of chemical contaminants in food ingredients and products. To detect each contaminant particle in a food sample, it is important to determine the effective depth of penetration of the laser through the food sample and the corresponding laser intensity required for the penetration. It is also important to determine the effective spatial resolution needed to detect each contaminant particle in the mixture. This study examined the depth of penetration of a 785 nm laser through tapioca starch and wheat flour when using three different laser intensities. Melamine, known to exhibit identifiable Raman spectral peaks, was selected as a subsurface reference material for determining the depth of laser penetration through the food powder samples. The food powders were layered in five depths between 1 and 5 mm over a Petri dish packed with melamine. It was observed that the 785 nm laser could penetrate to 3 mm depth in starch; however, the penetration depth was limited to 2 mm in flour. These depths were achieved using laser intensities of 200 and 100 mW for starch and flour, respectively. The selected depth and laser intensity parameters were next used to examine the effective spatial resolution required for detection of maleic acid in starch and benzoyl peroxide in flour, which was selected to be 0.5 mm. Finally, an experiment was conducted to demonstrate the use of these parameters for quantitative Raman imaging-based detection of these contaminants prepared in mixtures at 0.1%, 0.3%, and 0.5% (w/w) concentrations.