A Markov random field based approach to the identification of meat and bone meal in feed by near-infrared spectroscopic imaging

Contaminated meat and bone meal (MBM) in animal feedstuff has been the source of bovine spongiform encephalopathy (BSE) disease in cattle, leading to a ban in its use, so methods for its detection are essential. In this study, five pure feed and five pure MBM samples were used to prepare two sets of sample arrangements: set A for investigating the discrimination of individual feed/MBM particles and set B for larger numbers of overlapping particles. The two sets were used to test a Markov random field (MRF)-based approach. A Fourier transform infrared (FT-IR) imaging system was used for data acquisition. The spatial resolution of the near-infrared (NIR) spectroscopic image was 25 μm?×?25 μm. Each spectrum was the average of 16 scans across the wavenumber range 7,000-4,000 cm^?1, at intervals of 8 cm^?1. This study introduces an innovative approach to analyzing NIR spectroscopic images: an MRF-based approach has been developed using the iterated conditional mode (ICM) algorithm, integrating initial labeling-derived results from support vector machine discriminant analysis (SVMDA) and observation data derived from the results of principal component analysis (PCA). The results showed that MBM covered by feed could be successfully recognized with an overall accuracy of 86.59 % and a Kappa coefficient of 0.68. Compared with conventional methods, the MRF-based approach is capable of extracting spectral information combined with spatial information from NIR spectroscopic images. This new approach enhances the identification of MBM using NIR spectroscopic imaging.

Quantitative determination of soybean meal content in compound feeds: comparison of near-infrared spectroscopy and real-time PCR

Standard methods for determining the raw material content of compound feed are little exploited, except for the identification of meat and bone meal in feeds. In this work, near-infrared (NIR) spectroscopy and real-time polymerase chain reaction (PCR) were applied in order to establish new and fast methods for quantification of soybean meal content in compound feeds. The best prediction quality was achieved by using a model based on NIR spectroscopy (R ² = 0.9857, standard error of cross-validation 1.1065). Furthermore, a sensitive qualitative detection method by using the real-time PCR was developed (R ² = 0.976, slope −3.7599). Finally, the differences between the real-time PCR result and the NIR spectroscopy result for a given sample were also treated, and we found that the NIR spectroscopy method provided quite accurate results which approach closely those of the real-time PCR method. Hui Li and Xiaowen Lv contributed equally to this work.     

Transferability study of a near-infrared microscopic method for the detection of banned meat and bone meal in feedingstuffs

Near-infrared microscopy (NIRM) has been proved to be a powerful tool for the detection of banned meat and bone meal (MBM) in feed. The identification of MBM traces and its ability to differentiate animal from vegetable feed ingredients is based on the evaluation of near-infrared spectra obtained from individual particles present in the sample. This evaluation is supported by appropriate decision rules for the absorbances at specific wavelengths. Here we show that the method and the corresponding decision rules can be successfully transferred from the laboratory which constructed the decision rules to two independent laboratories that were not involved in the calibration process of the method. The analytical results from blind feed samples containing MBM (positive samples) and feed samples without MBM (negative samples) revealed a very good agreement between the three laboratories, thus demonstrating the transferability of the method.     

Determination of Sulfite in Botanical Medicine Using Headspace Thin-Film Microextraction and Surface Enhanced Raman Spectrometry

A facile method using headspace thin-film microextraction (HS-TFME) coupled with surface enhanced Raman spectrometry (SERS) has been developed for the determination of sulfite in traditional Chinese herbal medicine. The extraction substrate was synthesized by depositing urchin-like ZnO micron particles on glass sheets using chemical liquid phase deposition. Under the optimal conditions, the intensity of the SERS signal at 630–640?cm^?1 provided a good linear relationship with the concentration of sulfite from 25 to 400?mg/kg, and the linear correlation coefficient (R) was 0.996 with a detection limit of 6?mg/kg. The method was employed for the determination of sulfite in herbal medicines, and the results were confirmed by a traditional distillation-titration method. Therefore, this developed HS-TFME-SERS method may play an important role in the rapid, simple, and selective determination of sulfite residues in Chinese herbal medicine and become a potentially universal method for this analyte in various solid samples.     

Energy filtered transmission electron microscopy for the physico-chemical characterization of aquatic submicron colloids

A combination of energy filtered transmission electron microscopic (EF-TEM) procedures is proposed for the non-perturbing physico-chemical characterization of submicron mineral and organic colloids in aquatic systems. Synthetic hematite microparticles and xanthan polysaccharides were used as well-characterized model colloids in order to determine the optimum EF-TEM analysis conditions. In this paper, it is demonstrated that (i) our model colloids are morphologically representative of naturally occurring mineral/organic associations, (ii) EF-TEM allows the detection of fine xanthan ultrastructures without artefacts of conventional staining methods and (iii) submicron hematite particles can be specifically visualized and spectrometrically measured by EF-TEM within a hematite/xanthan mixture. This EF-TEM procedure appears to be appropriate for the characterization of real aquatic samples.     

Statistical evaluation of potash-lime-silica glass weathering

Two potash-lime-silica model glasses with compositions similar to those of medieval stained glass were exposed at 26 test sites all over Europe and in North America for 3–6 years. The objectives of this large-scale field exposure programme were: (a) a qualitative analysis of the weathering products formed on the surface of the samples in the (environmental) scanning electron microscope in combination with energy dispersive X-ray microanalysis (ESEM/EDX or SEM/EDX, respectively); (b) a statistical evaluation of the weathering phenomena by applying a multiple linear regression (MLR) analysis to find correlations between the degree of weathering, which was measured in terms of surface coverage with reaction products, and environmental parameters such as the concentration (c) of the acidifying gases SO₂, NO₂ and O₃, the temperature (T) and the relative humidity (RH); and (c) the calculation of a time-dependence function of the weathering process of these glasses. Mainly sulfates of calcium and potassium such as gypsum (CaSO₄·2 H₂O), arcanite (K₂SO₄) and syngenite (CaSO₄·K₂SO₄·H₂O) could be identified in the SEM and ESEM. Carbonates, nitrates and many particles deposited on the glass surface were found as well. MLR calculations exhibit significant dependencies of the degree of weathering on T, RH, c(NO_x), c(SO₂) and c(O₃). Applying a time-dependence function of the general form y=a·t^b (t=time) results in a value of approximately 0.42 for the exponent b, which comes close to values expected from various studies in the literature.     

Biodiesel classification by base stock type (vegetable oil) using near infrared spectroscopy data

The use of biofuels, such as bioethanol or biodiesel, has rapidly increased in the last few years. Near infrared (near-IR, NIR, or NIRS) spectroscopy (>4000 cm⁻¹) has previously been reported as a cheap and fast alternative for biodiesel quality control when compared with infrared, Raman, or nuclear magnetic resonance (NMR) methods; in addition, NIR can easily be done in real time (on-line). In this proof-of-principle paper, we attempt to find a correlation between the near infrared spectrum of a biodiesel sample and its base stock. This correlation is used to classify fuel samples into 10 groups according to their origin (vegetable oil): sunflower, coconut, palm, soy/soya, cottonseed, castor, Jatropha, etc. Principal component analysis (PCA) is used for outlier detection and dimensionality reduction of the NIR spectral data. Four different multivariate data analysis techniques are used to solve the classification problem, including regularized discriminant analysis (RDA), partial least squares method/projection on latent structures (PLS-DA), K-nearest neighbors (KNN) technique, and support vector machines (SVMs). Classifying biodiesel by feedstock (base stock) type can be successfully solved with modern machine learning techniques and NIR spectroscopy data. KNN and SVM methods were found to be highly effective for biodiesel classification by feedstock oil type. A classification error (E) of less than 5% can be reached using an SVM-based approach. If computational time is an important consideration, the KNN technique (E = 6.2%) can be recommended for practical (industrial) implementation. Comparison with gasoline and motor oil data shows the relative simplicity of this methodology for biodiesel classification.     

Tailoring Size and Coverage Density of Silver Nanoparticles on Monodispersed Polymer Spheres as Highly Sensitive SERS Substrates

Silver nanoparticles (AgNPs) were deposited onto the monodispersed carboxylic polystyrene (CPS) spheres by an improved in situ reduction method. The size and coverage density of the AgNPs on the surface of CPS spheres could be easily tailored by tuning the concentrations of carboxylic functional groups and silver precursor. The morphologies and structures of the resulting CPS/Ag hybrid particles were studied by scanning electron microscopy (SEM), transmission electron microscopy (TEM), X‐ray diffraction (XRD), UV‐Vis‐NIR spectrometer and X‐ray photoelectron spectroscopy (XPS), etc. The surface enhanced Raman scattering (SERS) performances of the resulting uniform CPS/Ag hybrid particles were investigated using 4‐aminobenzenethiol (4‐ABT) as the probe molecule. The optimized CPS/Ag hybrid particles show high enhancement factor (EF) of 2.71×10⁷, low limit of detection (LOD) of 10^?10 m and good reproducibility with relative standard deviation (RSD) of 9.64 %. The good SERS improvement properties demonstrate these hybrid particles could be employed as simple and effective substrates in the SERS spectroscopy.     

Preparation of dummy‐imprinted polymers by Pickering emulsion polymerization for the selective determination of seven bisphenols from sediment samples

The dummy molecularly imprinted polymers were prepared by Pickering emulsion polymerization. 4,4′‐(1‐Phenylethylidene) bisphenol was selected as the dummy template to avoid the leakage of the target bisphenols. The microsphere particles were characterized by scanning electron microscopy and nitrogen adsorption–desorption measurements, demonstrating that the regular‐shaped and medium‐sized particles (40–70 μm) were obtained with a specific surface area of 355.759 m²/g and a total pore volume of 0.561 cm³/g. The molecular imprinting properties of the particles were evaluated by static adsorption and chromatographic evaluation experiments. The association constant and maximum adsorption amount of bisphenol A were 0.115 mmol/L and 3.327 μmol/g using Scatchard analysis. The microsphere particles were then used as a solid‐phase extraction sorbent for selective extraction of seven bisphenols. The method of dummy molecularly imprinted solid‐phase extraction coupled with high‐performance liquid chromatography and diode array detection was successfully established for the extraction and determination of seven bisphenols from environmental sediment samples with method detection limits of 0.6–1.1 ng/g. Good recoveries (75.5–105.2%) for sediment samples at two spiking levels (500 and 250 ng/g) and reproducibility (RSDs < 7.7%, n = 3) were obtained.     

Emulsion copolymerization of styrene and methyl methacrylate

Chain transfer constants to monomer have been measured by an emulsion copolymerization technique at 44°C. The monomer transfer constant (ratio of transfer to propagation rate constants) is 1.9 × 10^?5 for styrene polymerization and 0.4 × 10^?5 for the methyl methacrylate reaction. Cross-transfer reactions are important in this system; the sum of the cross-transfer constants is 5.8 × 10^?5. Reactivity ratios measured in emulsion were r₁ (styrene) = 0.44, r₂ = 0.46. Those in bulk polymerizations were r₁ = 0.45, r₂ = 0.48. These sets of values are not significantly different. Monomer feed compcsition in the polymerizing particles is the same as in the monomer droplets in emulsion copolymerization, despite the higher water solubility of methyl methacrylate. The equilibrium monomer concentration in the particles in interval-2 emulsion polymerization was constant and independent of monomer feed composition for feeds containing 0.25–1.0 mole fraction styrene. Radical concentration is estimated to go through a minimum with increasing methyl methacrylate content in the feed. Rates of copolymerization can be calculated a priori when the concentrations of monomers in the polymer particles are known.     

Langmur monolayers of cerebroside with different head groups originated from sea cucumber: Binary systems with dipalmitoylphosphatidylcholine (DPPC)

Surface properties (Langmuir monolayer) of two different cerebrosides which are extracted from the sea cucumber (Bohadschia argus) were investigated. A main difference in chemical structure of cerebroside between BAC-2a and BAC-4 is their head groups (glucose and galactose, respectively). Furthermore, miscibility and interaction between dipalmitoylphosphatidylcholine (DPPC) and cerebrosides (BAC-2a and BAC-4) in the monolayer have been systematically examined. The surface pressure (π)−area (A), the surface potential (ΔV)−A, and the dipole moment (μ)−A isotherms for monolayers of DPPC, cerebrosides, and their binary combinations have been measured using the Wilhelmy method and the ionizing electrode method. BAC-4 forms a stable liquid-expanded (LE) monolayer, whereas BAC-2a has a first-order phase transition from the LE phase to the liquid-condensed (LC) state on 0.15 M NaCl at 298.2 K. The fundamental properties for each cerebroside monolayer were elucidated in terms of the surface dipole moment based on the three-layer model [R.J. Demchak, T. Fort Jr., J. Colloid Interface Sci. 46 (1974) 191–202] for both cerebrosides and the apparent molar quantity change (Δs^γ, Δh^γ, and Δu^γ) for BAC-2a. In addition, their miscibility with DPPC was examined by the variation of the molecular areas and the surface potentials as a function of cerebroside mole fractions, the additivity rule. The miscibility was also confirmed by constructing the two-dimensional phase diagrams. The phase diagrams for the both binary systems were of negative azeotropic type. That is, the two-component DPPC/BAC-2a and DPPC/BAC-4 monolayers are miscible. Furthermore, the Joos equation for the analysis of the collapse pressure of binary monolayers allowed calculation of the interaction parameter and the interaction energy between the DPPC and cerebroside monolayers. The miscibility in the monolayer state was also confirmed by the morphological observation with Brewster angle microscopy (BAM), fluorescence microscopy (FM), and atomic force microscopy (AFM).     

Silica gel surface modified with sulfanilamide for selective solid-phase extraction of Cu(II), Zn(II) and Ni(II)

A new chelating matrix has been prepared by immobilising sulfanilamide (SA) on silica gel (SG) surface modified with 3-chloropropyltrimethoxysilane as a sorbent for the solid-phase extraction (SPE) Cu(II), Zn(II) and Ni(II). The determination of metal ions in aqueous solutions was carried out by inductively coupled plasma optical emission spectrometry (ICP-OES). Experimental conditions for effective sorption of trace levels of Cu(II), Zn(II) and Ni(II) were optimised with respect to different experimental parameters using the batch and column procedures. The presence of common coexisting ions does not affect the sorption capacities. The maximum sorption capacity of the sorbent at optimum conditions was found to be 34.91, 19.07 and 23.62 mg g^?1 for Cu(II), Zn(II) and Ni(II), respectively. The detection limit of the method defined by IUPAC was found to be 1.60, 0.50 and 0.61 µg L^?1 for Cu(II), Zn(II) and Ni(II), respectively. The relative standard deviation (RSD) of the method under optimum conditions was 4.0% (n = 8). The method was applied to the recovery of Cu(II), Zn(II) and Ni(II) from the certified reference material (GBW 08301, river sediment) and to the simultaneous determination of these cations in different water samples with satisfactory results.     

Determination of anionic surfactant in surface water by resonance light-scattering technology

A sensitive and rapid method, without any extraction procedure, for the determination of the anionic surfactant expressed in the terms of sodium dodecyl benzene sulfonate (SDBS) by the resonance light scattering (RLS) technique is described in this paper. In the pH value 3.0 Britton-Robinson (BR) buffer, Victoria blue B (VBB) reacted with SDBS and produced large particles which resulted in the remarkable enhancement of the RLS intensity of VBB. The enhanced RLS intensity of the assay system was proportional to the concentration of SDBS in the range of 0.08–3.0 mg L^–1 and the correlation coefficient was r = 0.9996. The detection limit was 0.013 mg L^–1. This method was applied to determine the anionic surfactant in the surface water samples and satisfactory results were obtained. The reaction mechanism was also studied and the interaction between VBB and SDBS was mainly governed by electrostatic effect and the π–π stacking effect.     

NIR studies of the surface modification in silica fillers

Methods of estimating the degree of condensation of the surface silanol groups of silica due to its modification by silane coupling agents are reported.Also, a procedure for estimating the surface silanol groups for the pre- and post-modified silicas for the NIR 7326 cm^–1 band is given.Using electron microscope studies and heats of immersion of silica surfaces, the silane effect on agglomeration of silica particles and, thus, on the physicochemical properties of its surface has been demonstrated.     

Determination of synthetic musks in the sediment of the Taihu lake by using accelerated solvent extraction (ASE) and GC/MS

Synthetic musks, substitutes for natural musks, are widely distributed in environment. They have been detected in water, sludge, fish, shrimp, mussels and other aquatic animals, and even in human's adipose tissue, blood and breast milk. In this study, a new extraction procedure, based on the accelerated solvent extraction (ASE) and in cell clean-up technique was developed and successfully coupled with gas chromatography-mass spectrometry (GC/MS) for the analysis of musks in sediment samples. With this method, the limits of detection as low as 0.03–0.05?ng?g^?1 and the recovery rate of 86.0%–104% are achieved. When compared with soxhlet extraction (SE) and ultrasonic extraction (USE), ASE not only has the best extraction efficiency but also has advantage in extraction time and solvent consumption. Eight synthetic musks, including six polycyclic musks (Tonalide (AHTN), Galaxolide (HHCB), Phantolide (AHDI), Traseolide (ATII), Cashmeran (DPMI) and Celestolide (ADBI)) and two nitro musks (musk xylene (MX) and musk ketone (MK)), were evaluated in sediment samples collected from 15 selected locations of the Taihu lake, one of the largest freshwater lakes in China. The contents of synthetic musks in sediment samples range from 0.336 to 3.10?ng?g^?1 for HHCB, 0.184 to 1.21?ng?g^?1 for AHTN, below detection limit (BDL) to 0.349?ng?g^?1 for MX, and BDL to 0.0786?ng?g^?1 for MK. The contents of DPMI, ADBI, AHMI and ATII are below detection limit in all samples. The results reflect current status of fragrance compound pollution in this area, and provide basic data for environmental policy making.     

A Polypyrrole‐Imprinted Electrochemical Sensor Based on Nano‐SnO2/Multiwalled Carbon Nanotubes Film Modified Carbon Electrode for the Determination of Oleanolic Acid

A sensitive molecularly imprinted electrochemical sensor with specific recognition ability for oleanolic acid was synthesized by modification of multiwalled carbon nanotubes (MWNTs) decorated with tin oxide nanoparticles (nano‐SnO₂/MWNTs) and polypyrrole‐imprinted polymer on a carbon electrode. The morphology and electrochemical performance of the imprinted sensor were investigated by using scanning electron microscope (SEM), X‐ray diffraction (XRD), cyclic voltammetry (CV), linear sweep voltammetry (LSV) and amperometric i–t curve. The results showed that the imprinted sensor displayed excellent selectivity toward oleanolic acid. A linear relationship between the response currents and oleanolic acid concentrations ranging from 5.0×10^?8 g/L to 2.0×10^?5 g/L was obtained for the imprinted sensor. The limit of detection (LOD) of the imprinted sensor toward oleanolic acid was calculated as 8.6×10^?9 g/L at a signal to noise ratio (S/N) of 3. This imprinted sensor was successfully applied to the determination of oleanolic acid in Acitinidia deliciosa root samples.     

Spectrophotometric determination of total protein in serum using a novel near-infrared cyanine dye, 5,5′-dicarboxy-1,1′-disulfobutyl-3,3,3′,3′-tetramethylindotricarbocyanine

The application of near-infrared (NIR) dyes (λ _em > 750 nm) to the analysis of biological samples shows much promise, because the long emission wavelengths of such dyes allow interferences from biomolecule matrices to be minimized. In this paper, a novel NIR dye, 5,5′-dicarboxy-1,1′-disulfobutyl-3,3,3′,3′-tetramethylindotricarbocyanine (DCDSTCY) has been developed for the spectrophotometric determination of total protein in serum. Under acidic conditions, the binding of DCDSTCY to proteins caused a new peak at 878 nm, the height of which was proportional to the concentration of protein. The linear range of the method was found to be 0.04–0.5 μg mL⁻¹ for bovine serum albumin (BSA) and human serum albumin (HSA), and detection limits of 5 ng mL⁻¹ were obtained for these substances. The maximum binding number of BSA with DCDSTCY was measured to be 133. The method proposed here has been applied to the quantitation of total protein in serum, and recoveries of 96.6–104% were achieved. Figure Near-infrared probe for protein determination     

Effective PCR detection of animal species in highly processed animal byproducts and compound feeds

In this paper we present a polymerase chain reaction (PCR)-based method for detecting meat and bone meal (MBM) in compound feedingstuffs. By choosing adequate DNA targets from an appropriate localisation in the genome, the real-time PCR method developed here proved to be robust to severe heat treatment of the MBM, showing high sensitivity in the detection of MBM. The method developed here permits the specific detection of processed pig and cattle materials treated at 134 °C in various feed matrices down to a limit of detection of about 0.1%. This technique has also been successfully applied to well-characterised MBM samples heated to as high as 141 °C, as well as to various blind feed samples with very low MBM contents. Finally, the method also passed several official European ring trials.     

Ultrasensitive Cu sensing by near-infrared-emitting CdSeTe alloyed quantum dots

The near-infrared (NIR)-emitting CdSeTe alloyed quantum dots (AQdots) that capped with l-cysteine were applied for ultrasensitive Cu²⁺ sensing. The sensing approach was based on the fluorescence of the AQdots selectively quenched in the presence of Cu²⁺. Experimental results showed a low interference response towards other metal ions. The possible quenching mechanism was discussed on the basis of the binding between l-cysteine and the metal ions. In addition, biomolecules have low effect on the fluorescence due to the minimized interferences in NIR region. The response of the NIR optical sensor was linearly proportional to the concentration of Cu²⁺ ranging from 2 × 10⁻⁸ to 2 × 10⁻⁶ mol L⁻¹. Furthermore, it has been successfully applied to the detection of Cu²⁺ in vegetable samples.     

Selective solid phase extraction of trace cadmium(II) and lead(II) from biological and natural water samples by ofloxacin-modified-silica gel

Ofloxacin was successfully used as a chemical modifier to improve the reactivity of silica gel in terms of selective binding and extraction of heavy metal ions. This new functionalised silica gel (SG-ofloxacin) was as an effective sorbent for the solid-phase extraction (SPE) of Cd(II) and Pb(II) in biological and natural water samples and their determination by inductively coupled plasma optical emission spectrometry (ICP-OES). Experimental conditions for effective adsorption of trace levels of Cd(II) and Pb(II) were optimised with respect to different experimental parameters using the batch and column procedures. The time for 70% sorption for Cd(II) and Pb(II) was less than 2 min. Complete elution of the adsorbed metal ions from the SG-ofloxacin was carried out using 2.0 mL of 0.5 mol L^?1 of HCl. Common coexisting ions did not interfere with the separation and determination at pH 4.0. The maximum static adsorption capacity of the sorbent at optimum conditions was found to be 39.17 and 48.69 mg g^?1 for Cd(II) and Pb(II), respectively. The detection limits of the method were found to be 0.29 and 0.13 ng mL^?1 for Cd(II) and Pb(II), respectively. The relative standard deviation (RSD) of the method under optimum conditions was lower than 3.0% (n = 5). The method was applied to the recovery of Cd(II) and Pb(II) from the certified reference material (GBW 08301, river sediment) and to the simultaneous determination of these cations in different water and biological samples with satisfactory results and yielding 100-folds enrichment factor.