Comparative structural and vibrational investigations between cocoa butter (CB) and cocoa butter equivalent (CBE) by ESI/MALDI-HRMS, XRD, DSC, MIR and Raman spectroscopy.

A high quality chocolate requires not only a shiny surface, a crunchy and pleasant texture, but also a proper resistance to blooming. All these characteristics are influenced by the physical and chemical properties of the components, which are directly related to their crystalline structure. Some works found that the proportion of cocoa butter (CB), cocoa butter equivalent (CBE) and milk fatty acid (AMF) tend to strongly delay the blooming when mixing them. The goal of our research is to determine how the choice of adding CBE to the mixture delays chocolate blooming. ESI/MALDI-HRMS, X-ray, DSC, MIR and Raman investigations were used to analyze the structure features and the vibrational modes of CB and CBE. The comparison of these experimental results between CB and CBE made it possible to highlight markers of differentiation between CB and CBE which seems to explain the impact of CBE in the chocolate blooming. Part of these triglycerides remains in form IV instead. The presence of the latter seems to be a key parameter that favors the transformation deceleration to the form VI, which is responsible for the fat bloom development.

Evaluation of a calibration transfer between a bench top and portable Mid-InfraRed spectrometer for cocaine classification and quantification.

A portable Fourier Transform Mid-InfraRed (FT-MIR) spectrometer using Attenuated Total Reflectance (ATR) sampling is used for daily routine screening of seized powders. Earlier, ATR-FT-MIR combined with Support Vector Machines (SVM) algorithms resulted in a significant improvement of the screening method to a reliable and straightforward classification and quantification tool for both cocaine and levamisole. However, can this tool be transferred to new (hand-held) devices, without loss of the extensive data set? The objective of this study was to perform a calibration transfer between a newly purchased bench top (BT) spectrometer and a portable (P) spectrometer with existing calibration models. Both instruments are from the same brand and have identical characteristics and acquisition parameters (FT instrument, resolution of 4 cm-1 and wavenumber range 4000 to 500 cm-1). The original SVM classification model (n = 515) and SVM quantification model (n = 378) were considered for the transfer trial. Three calibration transfer strategies were assessed: 1) adjustment of slope and bias; 2) correction of spectra from the new instrument BT to P using Piecewise Direct Standardization (PDS) and 3) building a new mixed instrument model with spectra of both instruments. For each approach, additional cocaine powders were measured (n = 682) and the results were compared with GC-MS and GC-FID. The development of a mixed instrument model was the most successful in terms of performance. The future strategy of a mixed model allows applying the models, developed in the laboratory, to portable instruments that are used on-site, and vice versa. The approach offers opportunities to exchange data within a network of forensic laboratories using other FT-MIR spectrometers.

A mass spectrometry method for sensitive, specific and simultaneous detection of bovine blood meal, blood products and milk products in compound feed.

Feed sustainability is one of the biggest challenges for the next few years. Solutions have to be found that take feed quality and safety into account. Animal by-products are one valuable source of proteins. However, since the bovine spongiform encephalopathy (BSE) crisis, their use has been strictly regulated. The objective of this study was to propose a routine, sensitive and specific method using ultra-high performance liquid chromatography coupled to tandem mass spectrometry for the detection of blood-derived products and milk powder in feed. Contaminated aquafeeds were analysed in order to evaluate the sensitivity and specificity of the method. This new method meets both selectivity and sensitivity (0.1% (w/w)) requirements imposed by the European Commission for animal proteins detection methods. It offers an innovative and complementary solution for the simultaneously identification of authorised and unauthorised animal by-products such as processed animal proteins (PAPs).

Standardization of milk mid-infrared spectrometers for the transfer and use of multiple models.

An increasing number of models are being developed to provide information from milk Fourier transform mid-infrared (FT-MIR) spectra on fine milk composition, technological properties of milk, or even cows' physiological status. In this context, and to take advantage of these existing models, the purpose of this work was to evaluate whether a spectral standardization method can enable the use of multiple equations within a network of different FT-MIR spectrometers. The piecewise direct standardization method was used, matching "slave" instruments to a common reference, the "master." The effect of standardization on network reproducibility was assessed on 66 instruments from 3 different brands by comparing the spectral variability of the slaves and the master with and without standardization. With standardization, the global Mahalanobis distance from the slave spectra to the master spectra was reduced on average from 2,655.9 to 14.3, representing a significant reduction of noninformative spectral variability. The transfer of models from instrument to instrument was tested using 3 FT-MIR models predicting (1) the quantity of daily methane emitted by dairy cows, (2) the concentration of polyunsaturated fatty acids in milk, and (3) the fresh cheese yield. The differences, in terms of root mean squared error, between master predictions and slave predictions were reduced after standardization on average from 103 to 17 g/d, from 0.0315 to 0.0045 g/100 mL of milk, and from 2.55 to 0.49 g of curd/100 g of milk, respectively. For all the models, standard deviations of predictions among all the instruments were also reduced by 5.11 times for methane, 5.01 times for polyunsaturated fatty acids, and 7.05 times for fresh cheese yield, showing an improvement of prediction reproducibility within the network. Regarding the results obtained, spectral standardization allows the transfer and use of multiple models on all instruments as well as the improvement of spectral and prediction reproducibility within the network. The method makes the models universal, thereby offering opportunities for data exchange and the creation and use of common robust models at an international level to provide more information to the dairy sector from direct analysis of milk.

Online detection and quantification of particles of ergot bodies in cereal flour using near-infrared hyperspectral imaging.

The objective of this study is to assess near-infrared (NIR) hyperspectral imaging for the detection of ergot bodies at the particle level in cereal flour. For this study, ground ergot body samples and wheat flour samples as well as mixtures of both from 100 to 500,000 mg kg-1 were analysed. Partial least squares discriminant analysis (PLS-DA) models were developed and applied to spectral images in order to detect the ergot body particles. Ergot was detected in 100% of samples spiked at more than 10,000 mg kg-1 and no false-positives were obtained with non-contaminated samples. A correlation of 0.99 was calculated between the reference values and the values predicted by the PLS-DA model. For the cereal flours containing less than 10,000 mg kg-1 of ergot, it was possible for some samples spiked as low as 100 mg kg-1 to detect enough pixels of ergot to conclude that the sample was contaminated. However, some samples were under- or overestimated, which can be explained by the lack of homogeneity in relation to the sampling issue and the thickness of the sample. This study has demonstrated the potential of NIR hyperspectral imaging combined with chemometrics as an alternative solution for discriminating ergot body particles from cereal flour.

Regression models based on new local strategies for near infrared spectroscopic data.

In this work, a comparative study of two novel algorithms to perform sample selection in local regression based on Partial Least Squares Regression (PLS) is presented. These methodologies were applied for Near Infrared Spectroscopy (NIRS) quantification of five major constituents in corn seeds and are compared and contrasted with global PLS calibrations. Validation results show a significant improvement in the prediction quality when local models implemented by the proposed algorithms are applied to large data bases.

Identification of specific bovine blood biomarkers with a non-targeted approach using HPLC ESI tandem mass spectrometry.

Animal by-products are valuable protein sources in animal nutrition. Among them are blood products and blood meal, which are used as high-quality material for their beneficial effects on growth and health. Within the framework of the feed ban relaxation, the development of complementary methods in order to refine the identification of processed animal proteins remains challenging. The aim of this study was to identify specific biomarkers that would allow the detection of bovine blood products and processed animal proteins using tandem mass spectrometry. Seventeen biomarkers were identified: nine peptides for bovine plasma powder; seven peptides for bovine haemoglobin powder, including six peptides for bovine blood meal; and one peptide for porcine blood. They were not detected in several commercial compound feed or feed materials, such as blood by-products of other animal origins, milk-derived products and fish meal. These biomarkers could be used for developing a species-specific and blood-specific detection method.

Origin identification of dried distillers grains with solubles using attenuated total reflection Fourier transform mid-infrared spectroscopy after in situ oil extraction.

The ban on using processed animal proteins in feedstuffs led the feed sector to look for other sources of protein. Dried distillers grains with solubles (DDGS) could be considered as an important source in this regard. They are imported into Europe mainly for livestock feed. Identifying their origin is essential when labelling is missing and for feed safety, particularly in a crisis situation resulting from contamination. This study investigated applying attenuated total reflection Fourier transform mid-infrared spectroscopy (ATR-FT-MIR) to the oil fraction extracted from samples in situ in order to identify the origin of DDGS. The use of spectroscopic and chemometric tools enabled the botanical and geographical origins of DDGS, as well as the industrial process used to produce them, to be identified. The models developed during the study provided a classification higher than 95% using an external validation set.

Standardization of milk mid-infrared spectra from a European dairy network.

The goal of this study was to find a procedure to standardize dairy milk mid-infrared spectra from different Fourier transform mid-infrared spectrophotometers (different brands or models) inside a European dairy network to create new farm-management indicators (e.g., fertility, health, feed, environmental impact) based on milk infrared spectra. This step is necessary to create common spectral databases, allowing the building of statistical tools, to be used by all instruments of the network. The method used was piecewise direct standardization (PDS), which matches slave-instrument spectra on master-instrument spectra. To evaluate the possibility of using common equations on different instruments, the PDS method was tested on a set of milk samples measured on each machine, and an equation predicting fat content of milk is applied on all. Regressions were performed between master and slaves fat predictions, before and after PDS. Bias and root mean square error between predictions were decreased after PDS, respectively, from 0.3781 to 0.0000 and from 0.4609 to 0.0156 (g of fat/100mL of milk). The stability over time of these results was confirmed by an application of the coefficients created by PDS 1 mo later on the slave spectra. These preliminary results showed that the PDS method permits a reduction of the inherent spectral variability between instruments, allowing the merging of Fourier transform mid-infrared milk spectra from different instruments into a common database, the creation of new types of dairy farm management indicators, and the use of these common calibrations for all Fourier transform mid-infrared instruments of the European dairy network.

Determination of the ruminant origin of bone particles using fluorescence in situ hybridization (FISH).

Molecular biology techniques such as PCR constitute powerful tools for the determination of the taxonomic origin of bones. DNA degradation and contamination by exogenous DNA, however, jeopardise bone identification. Despite the vast array of techniques used to decontaminate bone fragments, the isolation and determination of bone DNA content are still problematic. Within the framework of the eradication of transmissible spongiform encephalopathies (including BSE, commonly known as "mad cow disease"), a fluorescence in situ hybridization (FISH) protocol was developed. Results from the described study showed that this method can be applied directly to bones without a demineralisation step and that it allows the identification of bovine and ruminant bones even after severe processing. The results also showed that the method is independent of exogenous contamination and that it is therefore entirely appropriate for this application.

Towards combinatorial spectroscopy: the case of minor milk fatty acids determination.

Chemometrical models for determination of milk fatty acids (FA) are typically developed using spectral data from a single spectroscopy technique, e.g., mid-infrared spectroscopy in milk control. Such models perform poorly in determining minor components and are highly dependent on the spectral data source and on the type of matrix. In milk fat, the unsuccessful determination of minor (fatty acids lower than 1.0 g/100g in total fat) FA is often the result of: (1) the molecular structure similarity between the minor and the major FA within the milk fat matrix (thus the chemical signature specific to individual fatty acids has restricted specificity), and (2) the low signal intensity (detection limit) for specific vibrational modes. To overcome these limitations, data from different types of spectroscopy techniques, which brings additional chemical information in relation to the variation of the FA, could be included in the regression models to improve quantification. Here, Fourier transform (FT) Raman spectra were concatenated with attenuated total reflectance FT infrared (ATR/FTIR) spectra. The new combinatorial models showed up to 25% decrease in the root mean squared error of cross-validation (RMSECV) values, accompanied with a higher Rcv(2) for most individual FA or sums of FA groups, as compared to regression models based on Raman only or ATR/FTIR only spectra. In addition, improved models included less PLS components indicating an increased robustness. Interpretation of the most contributing regression coefficients indicated the value of newly combined spectral regions as carriers of specific chemical information. Although requiring additional spectroscopy instrumentation and prolonged acquisition time, this new combinatorial approach can be automated and is sufficient for semi-routine determination of the milk FA profile.

Validation and transferability study of a method based on near-infrared hyperspectral imaging for the detection and quantification of ergot bodies in cereals.

In recent years, near-infrared (NIR) hyperspectral imaging has proved its suitability for quality and safety control in the cereal sector by allowing spectroscopic images to be collected at single-kernel level, which is of great interest to cereal control laboratories. Contaminants in cereals include, inter alia, impurities such as straw, grains from other crops, and insects, as well as undesirable substances such as ergot (sclerotium of Claviceps purpurea). For the cereal sector, the presence of ergot creates a high toxicity risk for animals and humans because of its alkaloid content. A study was undertaken, in which a complete procedure for detecting ergot bodies in cereals was developed, based on their NIR spectral characteristics. These were used to build relevant decision rules based on chemometric tools and on the morphological information obtained from the NIR images. The study sought to transfer this procedure from a pilot online NIR hyperspectral imaging system at laboratory level to a NIR hyperspectral imaging system at industrial level and to validate the latter. All the analyses performed showed that the results obtained using both NIR hyperspectral imaging cameras were quite stable and repeatable. In addition, a correlation higher than 0.94 was obtained between the predicted values obtained by NIR hyperspectral imaging and those supplied by the stereo-microscopic method which is the reference method. The validation of the transferred protocol on blind samples showed that the method could identify and quantify ergot contamination, demonstrating the transferability of the method. These results were obtained on samples with an ergot concentration of 0.02% which is less than the EC limit for cereals (intervention grains) destined for humans fixed at 0.05%.

Validation of a near infrared microscopy method for the detection of animal products in feedingstuffs: results of a collaborative study.

The performance characteristics of a near infrared microscopy (NIRM) method, when applied to the detection of animal products in feedingstuffs, were determined via a collaborative study. The method delivers qualitative results in terms of the presence or absence of animal particles in feed and differentiates animal from vegetable feed ingredients on the basis of the evaluation of near infrared spectra obtained from individual particles present in the sample. The specificity ranged from 86% to 100%. The limit of detection obtained on the analysis of the sediment fraction, prepared as for the European official method, was 0.1% processed animal proteins (PAPs) in feed, since all laboratories correctly identified the positive samples. This limit has to be increased up to 2% for the analysis of samples which are not sedimented. The required sensitivity for the official control is therefore achieved in the analysis of the sediment fraction of the samples where the method can be applied for the detection of the presence of animal meal. Criteria for the classification of samples, when fewer than five spectra are found, as being of animal origin needs to be set up in order to harmonise the approach taken by the laboratories when applying NIRM for the detection of the presence of animal meal in feed.

Online detection and quantification of ergot bodies in cereals using near infrared hyperspectral imaging.

The occurrence of ergot bodies (sclerotia of Claviceps purpurea) in cereals presents a high toxicity risk for animals and humans due to the alkaloid content. To reduce this risk, the European Commission fixed an ergot concentration limit of 0.1% in all feedstuffs containing unground cereals, and a limit of 0.05% in 'intervention' cereals destined for humans. This study sought to develop a procedure based on near infrared hyperspectral imaging and multivariate image analysis to detect and quantify ergot contamination in cereals. Hyperspectral images were collected using an NIR hyperspectral line scan combined with a conveyor belt. All images consisted of lines of 320 pixels that were acquired at 209 wavelength channels (1100-2400 nm). To test the procedure, several wheat samples with different levels of ergot contamination were prepared. The results showed a correlation higher than 0.99 between the predicted values obtained using chemometric tools such as partial least squares discriminant analysis or support vector machine and the reference values. For a wheat sample with a level of ergot contamination as low as 0.01 %, it was possible to identify groups of pixels detected as ergot to conclude that the sample was contaminated. In addition, no false positives were obtained with non-contaminated samples. The limit of detection was found to be 145 mg/kg and the limit of quantification 341 mg/kg. The reproducibility tests of the measurements performed over several weeks showed that the results were always within the limits allowed. Additional studies were done to optimise the parameters in terms of number of samples analysed per unit of time or conveyor belt speed. It was shown that ergot can be detected using a speed of 1-100 mm/s and that a sample of 250 g can be analysed in 1 min.

[Detection of processed animal protein: European experience and perspectives]. / Détection des protéines animales transformées: expérience et perspectives européennes.

European Commission Regulation (EC) No. 152/2009 imposes optical microscopy as the reference method for official controls to detect traces of animal protein in animal feed. Since 1 July 2004, the one-solvent technique has been the only authorised variant of optical microscopy. Its detection limit is 0.1% of meat-and-bone meal. Other techniques--using molecular biology (polymerase chain reaction, immunology), microscopy or near-infrared imaging--have been developed in the past ten years to supplement the official method, which has certain limitations. This paper compares and discusses the different techniques, highlighting the strengths of each technique in order to propose a feasible control scheme to improve the sensitivity and specificity of the technique for the detection of processed animal protein in livestock feed.

Comparison of various chemometric approaches for large near infrared spectroscopic data of feed and feed products.

In the present study, different multivariate regression techniques have been applied to two large near-infrared data sets of feed and feed ingredients in order to fulfil the regulations and laws that exist about the chemical composition of these products. The aim of this paper was to compare the performances of different linear and nonlinear multivariate calibration techniques: PLS, ANN and LS-SVM. The results obtained show that ANN and LS-SVM are very powerful methods for non-linearity but LS-SVM can also perform quite well in the case of linear models. Using LS-SVM an improvement of the RMS for independent test sets of 10% is obtained in average compared to ANN and of 24% compared to PLS.

Analysis of milk odd- and branched-chain fatty acids using Fourier transform (FT)-Raman spectroscopy.

Fourier transform (FT)-Raman spectra of pure C13:0, C15:0, C17:0, iso C14:0, iso C15:0, and ante C15:0 fatty acid methyl ester standards (FAMESs) and 75 milk fat samples from 6 different dietary experiments were acquired at room temperature (RT) and immediately after freezing at -80 °C (FT). The latter generally included much more well-defined and sharper scattering bands than those obtained at RT. Further, the spectra at FT revealed additional acuate bands in the vicinity of peculiar wavenumber regions, as well as an increase of Raman scattering intensity, which was sometimes associated with a shift of the peak. Partial least-squares (PLS) regression models based on either selected regions or the full spectra and using two pretreatment methods [multiplicative scatter correction (MSC, using raw spectra of milk fat only) and modified MSC (MMSC, a combination of pure FAMESs and milk fat spectra)] with cross-validation were used to evaluate the different types of milk fat FT-Raman spectra for the predictions of individual odd- and branched-chain fatty acids (OBCFAs) and their sums. In general, most individual (C15:0, ante C15:0, iso C17:0, and ante C17:0) and grouped (ODD, ANTE, and total OBCFAs) fatty acids were favorably (coefficient of determination, R(2) > 0.65) predicted using models with FT spectra only or a combination of RT and FT spectra (RFT), when compared to models with spectra analyzed at RT only. The results indicate the interest to use FT-Raman spectra collected at different temperatures for the prediction of narrow concentrations of saturated OBCFAs in milk fat.

Development of a real-time PCR protocol for the species origin confirmation of isolated animal particles detected by NIRM.

At present, European legislation prohibits totally the use of processed animal proteins in feed for all farmed animals (Commission Regulation (EC) No. 1234/2003-extended feed ban). A softening of the feed ban for non-ruminants would nevertheless be considered if alternative methods could be used to gain more information concerning the species origin of processed animal proteins than that which can be provided by classical optical microscopy. This would allow control provisions such as the ban of feeding animals with proteins from the same species or intra-species recycling (Regulation (EC) No. 1774/2002). Two promising alternative methods, near-infrared microscopy (NIRM) and real-time polymerase chain reaction (PCR), were combined to authenticate, at the species level, the presence of animal particles. The paper describes the improvements of the real-time PCR method made to the DNA extraction protocol, allowing five PCR analyses to be performed with the DNA extracted from a single particle.

New approach for the quantification of processed animal proteins in feed using light microscopy.

A revision of European Union's total feed ban on animal proteins in feed will need robust quantification methods, especially for control analyses, if tolerance levels are to be introduced, as for fishmeal in ruminant feed. In 2006, a study conducted by the Community Reference Laboratory for Animal Proteins in feedstuffs (CRL-AP) demonstrated the deficiency of the official quantification method based on light microscopy. The study concluded that the method had to be revised. This paper puts forward an improved quantification method based on three elements: (1) the preparation of permanent slides with an optical adhesive preserving all morphological markers of bones necessary for accurate identification and precision counting; (2) the use of a counting grid eyepiece reticle; and (3) new definitions for correction factors for the estimated portions of animal particles in the sediment. This revised quantification method was tested on feeds adulterated at different levels with bovine meat and bone meal (MBM) and fishmeal, and it proved to be effortless to apply. The results obtained were very close to the expected values of contamination levels for both types of adulteration (MBM or fishmeal). Calculated values were not only replicable, but also reproducible. The advantages of the new approach, including the benefits of the optical adhesive used for permanent slide mounting and the experimental conditions that need to be met to implement the new method correctly, are discussed.

Key parameters for the development of a NIR microscopic method for the quantification of processed by-products of animal origin in compound feedingstuffs.

The aim of this work is to show new advances in the analytical methods developed in the frame of the ban of processed animal by-products in compound feed that is currently applied within the European Union. With this aim, studies to develop a quantitative near infrared microscopy (NIRM) approach have been undertaken in order to fulfil future requirements of European legislation like the introduction of tolerance levels that would require for official control purposes the availability of specific quantitative methods. The capabilities of the NIRM method have been improved; no sample preparation is required and the acquisition parameters are optimised. Both the gross and the fine fractions of the samples are considered; the reflexion mode was used to analyse the gross raw fraction and the transmission mode was chosen to analyse the fine raw fraction. Parameters for reflexion analyses were already fixed in our previous studies while those of transmission mode have been determined in the present study. Because particles are too small, it is difficult to mark them; spectra were collected using the mapping technique. Quantitative analyses have been carried out for different percentages of adulteration (0.5, 1, 2 and 5%). Results were depending on the particle size distribution of the feed and of the fish meal which led to experimental values of adulteration varying between 0.13-0.92%, 0.93-3.7%, 2.42-5.83% and 1.95-9.39% for theoretical percentages of adulteration equal to 0.5, 1, 2 and 5%, respectively. The established protocol with the key parameters proposed has to be considered for the development of an accurate method of quantification.