Industrial impact on sustainable dairy farms: Essential elements, hazardous metals and polycyclic aromatic hydrocarbons in forage and cow's milk.

Sustainable dairy farms are characterised by the self-production of forage for animal feed. These farms are sometimes located near industrial areas, entailing a risk of food chain contamination with hazardous metals and polycyclic aromatic hydrocarbons (PAHs). Accordingly, evaluating the impact of pollution on forage and milk is of great interest. In this study, the effects of industrial factors on sustainable forage from 43 dairy farms and possible correlations between inorganic elements and PAHs were studied. Spearman's correlation and principal component analysis (PCA) were performed for the forage and milk. Most of the inorganic elements in the forage were below the maximum residual limits for cadmium (Cd) and lead (Pb), established in EU 2013/1275 and EU 2019/1869, respectively. However, arsenic (As) and mercury (Hg) levels were above their respective limits in the forage (EU 2019/1869). No milk samples exceeded the maximum residual limits for Pb (EU 488/2014) or Cd (EU 1881/2006) in dairy products. Heavy-weight PAHs (HW-PAHs, four or more aromatic rings) were detected in forage but not in milk. In the forage samples, HW-PAHs were positively correlated with Zn and Cd. In addition, some hazardous metals (chromium (Cr), iron (Fe), As, Hg, and Pb) also were positively correlated with Zn and Cd. Interestingly, no correlations were found between forage pollutants and milk, suggesting that these pollutants have a low transfer rate to milk. The PCA results highlighted the predominant contribution of PAHs to the global variance in forage samples collected at different distances from industrial areas. In milk, the contributions of hazardous metals and PAHs were more balanced than in forages. Finally, when distances to potential pollution sources were included in the PCA of forage samples, a negative correlation was observed between the former and the concentrations of HW-PAHs, Cd, and Zn, suggesting that thermal power plants and steel factory emissions were the main sources of polluting forage in this area.

Preliminary Feed Sedimentation Step for the Sensitive and Specific Detection of Processed Animal Proteins by Mass Spectrometry-Based Proteomics.

The circular economy is one of the main building blocks of the European Green Deal. In this context, the use of former foodstuffs containing ruminant gelatin was recently authorized in nonruminant feed. This minor modification makes it more challenging, if not impossible, to interpret the analytical results of the official control for animal proteins. The presence of ruminant DNA from authorized byproducts (i.e., milk and/or gelatin) may hide the use of prohibited byproducts. The objective of this work was to evaluate the use of sedimentation to increase the sensitivity and specificity of bovine-processed animal proteins (PAPs) detection by mass spectrometry-based proteomics. Both approaches (standard versus optimized method) were evaluated by UHPLC-MS/MS on various animal feeds and samples from an interlaboratory study. The optimized method was able to achieve the adulteration level below the level of 0.1% PAPs required by the European Commission. This approach presents a simple and economical solution to improve the method without the need for new equipment or expertise since it is already in place in the control laboratories.

Challenges related to the application of analytical methods to control insect meals in the context of European legislation.

Since their approval for use in aquaculture in 2017, processed insect proteins have been extensively studied for their nutritional quality in animal feed. This new type of meal is highly promising but requires, as for other products used in animal feed, strict sanitary control in accordance with European legislation. Within this legal framework, light microscopy and PCR remain the official methods but have some analytical limitations that other methods could overcome. This paper aims to provide an overview of the European legislation concerning use of processed insect proteins, but also to highlight the advantages and disadvantages of the official methods for their analysis. It also points out other analytical methods, which have already proved their worth for the analysis of processed animal proteins, which could be used as complementary methods.

Modifying sucrose esters oleogels properties using different structuration routes.

Sucrose esters (SE) have been widely studied as emulsifiers to tailor crystallization in fats. Nevertheless, few studies have assessed the potential of SEs as oleogelators to structure oleogels. This study aimed to evaluate alternative routes that would improve the oleogelation capacity of commercial SEs with different Hydrophilic-lipophilic balance (HLB) values and evaluate the physical properties of the oleogels produced by different routes. Four SEs were evaluated (SP10-HLB2, SP30-HLB6, SP50-HLB11, and SP70-HLB15) using three oleogelation routes (traditional or melting, ethanol, and foam-template). Of all evaluated samples, only the SP50 ethanol route with 10 % SE showed a solid-like structure. This sample presented the highest hardness (0.4 ± 0.1 N) and elastic modulus (4589 ± 89 Pa). SP70 showed a potential oleogel after foam-template approach due to the higher oil binding capacity. SP10 was the only directly completely soluble SE in oil, although it formed a very liquid gel. SP30 did not show a potential or oleogel structure for any of the routes tested.

A method for non-destructive determination of cocoa bean fermentation levels based on terahertz hyperspectral imaging.

Fermentation of cocoa is a key process to obtain aromatic chocolate products from raw cocoa beans. Hitherto, the levels of fermentation in cocoa are determined using destructive techniques, for example by a cut-test to manually observe the colour inside the beans, or by quantifying ammonia nitrogen (NH3) in the cocoa powder. In this paper, we present the use of Terahertz hyperspectral imaging as a new way to non-destructively analyse and detect fermented cocoa beans. The study analysed two sets of twenty-two cocoa bean samples with different levels of fermentation from two producers in Brazil. A correlation between fermentation conditions and the outcome results of their THz measurements was observed.

Comparison of Spectroscopic Techniques Combined with Chemometrics for Cocaine Powder Analysis.

Spectroscopic techniques combined with chemometrics are a promising tool for analysis of seized drug powders. In this study, the performance of three spectroscopic techniques [Mid-InfraRed (MIR), Raman and Near-InfraRed (NIR)] was compared. In total, 364 seized powders were analyzed and consisted of 276 cocaine powders (with concentrations ranging from 4 to 99 w%) and 88 powders without cocaine. A classification model (using Support Vector Machines [SVM] discriminant analysis) and a quantification model (using SVM regression) were constructed with each spectral dataset in order to discriminate cocaine powders from other powders and quantify cocaine in powders classified as cocaine positive. The performances of the models were compared with gas chromatography coupled with mass spectrometry (GC-MS) and gas chromatography with flame-ionization detection (GC-FID). Different evaluation criteria were used: number of false negatives (FNs), number of false positives (FPs), accuracy, root mean square error of cross-validation (RMSECV) and determination coefficients (R2). Ten colored powders were excluded from the classification data set due to fluorescence background observed in Raman spectra. For the classification, the best accuracy (99.7%) was obtained with MIR spectra. With Raman and NIR spectra, the accuracy was 99.5% and 98.9%, respectively. For the quantification, the best results were obtained with NIR spectra. The cocaine content was determined with a RMSECV of 3.79% and a R2 of 0.97. The performance of MIR and Raman to predict cocaine concentrations was lower than NIR, with RMSECV of 6.76% and 6.79%, respectively and both with a R2 of 0.90. The three spectroscopic techniques can be applied for both classification and quantification of cocaine, but some differences in performance were detected. The best classification was obtained with MIR spectra. For quantification, however, the RMSECV of MIR and Raman was twice as high in comparison with NIR. Spectroscopic techniques combined with chemometrics can reduce the workload for confirmation analysis (e.g., chromatography based) and therefore save time and resources.

Vibrational Spectroscopy Coupled to a Multivariate Analysis Tiered Approach for Argentinean Honey Provenance Confirmation.

In the present work, the provenance discrimination of Argentinian honeys was used as case study to compare the capabilities of three spectroscopic techniques as fast screening platforms for honey authentication purposes. Multifloral honeys were collected among three main honey-producing regions of Argentina over four harvesting seasons. Each sample was fingerprinted by FT-MIR, NIR and FT-Raman spectroscopy. The spectroscopic platforms were compared on the basis of the classification performance achieved under a supervised chemometric approach. Furthermore, low- mid- and high-level data fusion were attempted in order to enhance the classification results. Finally, the best-performing solution underwent to SIMCA modelling with the purpose of reproducing a food authentication scenario. All the developed classification models underwent to a "year-by-year" validation strategy, enabling a sound assessment of their long-term robustness and excluding any issue of model overfitting. Excellent classification scores were achieved by all the technologies and nearly perfect classification was provided by FT-MIR. All the data fusion strategies provided satisfying outcomes, with the mid- and high-level approaches outperforming the low-level data fusion. However, no significant advantage over the FT-MIR alone was obtained. SIMCA modelling of FT-MIR data produced highly sensitive and specific models and an overall prediction ability improvement was achieved when more harvesting seasons were used for the model calibration (86.7% sensitivity and 91.1% specificity). The results obtained in the present work suggested the major potential of FT-MIR for fingerprinting-based honey authentication and demonstrated that accuracy levels that may be commercially useful can be reached. On the other hand, the combination of multiple vibrational spectroscopic fingerprints represents a choice that should be carefully evaluated from a cost/benefit standpoint within the industrial context.

Dataset of visible-near infrared handheld and micro-spectrometers - comparison of the prediction accuracy of sugarcane properties.

In the dataset presented in this article, sixty sugarcane samples were analyzed by eight visible / near infrared spectrometers including seven micro-spectrometers. There is one file per spectrometer with sample name, wavelength, absorbance data [calculated as log10 (1/Reflectance)], and another file for reference data, in order to assess the potential of the micro-spectrometers to predict chemical properties of sugarcane samples and to compare their performance with a LabSpec spectrometer. The Partial Least Square Regression (PLS-R) algorithm was used to build calibration models. This open access dataset could also be used to test new chemometric methods, for training, etc.

Official Feed Control Linked to the Detection of Animal Byproducts: Past, Present, and Future.

In the context of the expansion of the human population, availability of food, and in extension of animal feed, is a big issue. Favoring a circular economy by the valorization of byproducts is a sustainable way to be more efficient. Animal byproducts are an interesting source of feed materials due to their richness in proteins of high nutritional value. Prevention and control efforts have allowed a gradual lifting of the feed ban regarding the use of animal byproducts. Nevertheless, the challenge remains the development of analytical methods enabling a distinction between authorized and unauthorized feed materials. This Review focuses on the historical and epidemiological context of the official control, the evaluation of current and foreseen legislation, and the available methods of analysis for the detection of constituents of animal origin in feedingstuffs. It also underlines the analytical limitations of the approach and discusses some prospects of novel methods to ensure food and feed safety.

Local anomaly detection and quantitative analysis of contaminants in soybean meal using near infrared imaging: The example of non-protein nitrogen.

The melamine scandal indicates that traditional targeted detection methods only detect the specifically listed forms of contamination, which leads to the failure to identify new adulterants in time. In order to deal with continually changing forms of adulterations in food and feed and make up for the inadequacy of targeted detection methods, an untargeted detection method based on local anomaly detection (LAD) using near infrared (NIR) imaging was examined in this study. In the LAD method, with a particular size of window filter and at a 99% level of confidence, a specific value of Global H (GH, modified Mahalanobis distance) can be used as a threshold for anomalous spectra detection and quantitative analysis. The results showed an acceptable performance for the detection of contaminations with the advantage of no need of building a 'clean' library. And, a high coefficient of determination (R2LAD = 0.9984 and R2PLS-DA = 0.9978) for the quantitative analysis of melamine with a limit of detection lower than 0.01% was obtained. This indicates that the new strategy of untargeted detection has the potential to move from passive to active for food and feed safety control.

Deep-sea sharks: Relation between the liver's buoyancy and red aerobic muscle volumes, a new approach.

Shark's buoyancy depends on two types of force: (i) the hydrostatic force which is mainly provided by their liver filled with low density lipids and (ii) the hydrodynamic force which is provided by the morphology of their body and fins. Shallow-water shark species are usually negatively buoyant, whereas deep-sea shark species have been suggested to display neutral buoyancy. It has been suggested that species that are close to the neutrality would have less red aerobic muscle fibers. Here, we investigated several liver features (the hepatosomatic index, the oil content and the lipid composition) playing a major role regarding the buoyancy of three deep-sea shark species (Etmopterus molleri, Etmopterus spinax and Isistius brasiliensis) and one shallow-water counterpart (Galeus melastomus). We used FT-Raman and FT-MIR spectroscopy to qualify/quantify the lipid composition of their liver. Our results showed that most deep-sea shark species studied have liver features providing more buoyancy than their shallow-water counterparts, appart from E. molleri which shows liver's features that resemble more shallow-water shark species (e.g. G. melastomus). Finally, data regarding liver features of several deep-sea shark species from the literature were added and the red aerobic muscle distribution/proportion of nine species was measured, to reveal how these parameters might be related. Our results showed that sharks characterized by a liver providing more hydrostatic force possess proportionally less red aerobic muscles than sharks having a liver that contributes less to their buoyancy. Therefore, our results i.e. deep-sea shark displaying less red aerobic muscle with a liver providing more buoyancy, support low metabolic rates hence slow swimming speed.

Synchronous fluorescence spectroscopy for detecting blood meal and blood products.

Fluorescence spectroscopy is a powerful method for protein analysis. Its sensitivity and selectivity allow its use for the detection of blood meal and blood products. This study proposes a novel approach for the detection of hemoglobin in animal feed by synchronous fluorescence spectroscopy (SFS). The objective was to develop a fast and easy method to detect hemoglobin powder and blood meal. Analyses were carried out on standard reference material (hemoglobin and albumin) in order to optimize SFS method conditions for hemoglobin detection. The method was then applied to protein extracts of commercial feed material and compound feed. The results showed that SFS spectra of blood meal and blood products (hemoglobin powder and plasma powder) could be used to characterize hemoglobin. Principal component analysis (PCA) applied to area-normalized SFS spectra of artificially adulterated samples made it possible to define a limit of detection of hemoglobin powder or blood meal of 0.5-1% depending on the feed material. The projection in the PCA graphs of SFS spectra of real commercial compound feeds known to contain or to be free from blood-derived products showed that it was possible to discriminate samples according to the presence of hemoglobin. These results confirmed that SFS is a promising screening method for the detection of hemoglobin in animal feed.

Analytical methods used for the authentication of food of animal origin.

Since adulteration can have serious consequences on human health, it affects market growth by destroying consumer confidence. Therefore, authentication of food is important for food processors, retailers and consumers, but also for regulatory authorities. However, a complex nature of food and an increase in types of adulterants make their detection difficult, so that food authentication often poses a challenge. This review focuses on analytical approaches to authentication of food of animal origin, with an emphasis put on determination of specific ingredients, geographical origin and adulteration by virtue of substitution. This review highlights a current overview of the application of target approaches in cases when the compound of interest is known and non-target approaches for screening issues. Papers cited herein mainly concern milk, cheese, meat and honey. Moreover, advantages, disadvantages as well as challenges regarding the use of both approaches in official food control but also in food industry are investigated.

Collaborative study on the effect of grinding on the detection of bones from processed animal proteins in feed by light microscopy.

Bone fragments are essential structures for the detection of processed animal proteins (PAPs) in feed by light microscopy for official controls according to Annex VI of European Union Regulation EC/152/2009. The preparation of samples submitted for analysis requires a grinding step to make them suitable for microscopic slide preparation and observation. However, there are no technical guidelines set down for this step despite the fact that it can lead to an increase in bone numbers due to fragmentation. This was demonstrated by an in-house study carried out by the Irish National Reference Laboratory (NRL) for animal protein detection. The present collaborative study investigated the possible effects of three different grinding conditions on the final result for a feed adulterated with 0.05 and 0.01% (w/w) of PAP. The microscopic analysis either combined or not with an Alizarin Red staining was carried out by 10 different laboratories. The results demonstrated that although a large variation in the numbers of bone fragments was noted, five of the six different grinding/staining combinations applied at two levels of PAP adulteration did not significantly (at p = 0.05) differ from one another. The only exception occurred when grinding the feed containing 0.05% of PAP with a rotor mill equipped with a 0.5-mm sieve and combined with a staining which resulted in a greater number of bone fragments by forced fragmentation. Overall, the impact of the grinding/staining combinations on the final results was shown to be negligible when considering the regulatory limit of detection (LOD) requirement for the method and the current rules of implementation of the light microscopic method. From a total of 180 analyses carried out on the feed matrix containing 0.05% of PAP no false-negative result was observed, and at a level of 0.01% PAP only 10 false-negative results occurred.

Light microscopy with differential staining techniques for the characterisation and discrimination of insects versus marine arthropods processed animal proteins.

The aim of this study was to evaluate the use of light microscopy with differential staining techniques for the discrimination of insect material from marine arthropods - classified as fishmeal. Specifically, three samples of single-species insect material, Hermetia illucens (HI), Bombyx mori (BM) and Tenebrio molitor (TM), and two samples of marine arthropods, shrimp material and krill, were analysed and compared after staining by two reagents to enhance fragment identification. Alizarin Red (AR) and Chlorazol Black (CB), which react respectively with calcium salts and chitin, were tested for their potential efficacy in distinguishing between insect and marine materials. Results indicated that AR failed to stain HI, BM and TM materials. By contrast, the three insect species materials tested were stained by CB. When shrimp fragments and krill were considered, AR and CB stained marine materials reddish-pink and light blue to black, respectively. By combining these results, it can be suggested that CB staining may efficiently be used to mark insect materials; AR does stain shrimp fragments but does not stain the tested insect material, indicating a possible approach for discriminating between insects and marine arthropods. However, since the present study was performed on pure materials and a small set of samples, possible implementation of this technique still needs to be confirmed in complex matrices such as compound feed.

Determination by near infrared microscopy of the nitrogen and carbon content of tomato (Solanum lycopersicum L.) leaf powder.

Near infrared microscopy (NIRM) has been developed as a rapid technique to predict the chemical composition of foods, reduce analytical costs and time and ease sample preparation. In this study, NIRM has been evaluated as an alternative to classical chemical analysis to determine the nitrogen and carbon content of small samples of tomato (Solanum lycopersicum L.) leaf powder. Near infrared spectra were obtained by NIRM for independent leaf samples collected on 216 plants grown under six different levels of nitrogen. From these, 30 calibration and 30 validation samples covering the spectral range of the whole set were selected and their nitrogen and carbon contents were determined by a reference method. The calibration model obtained for nitrogen content proved to be excellent, with a coefficient of determination in calibration (R(2)c) higher than 0.9 and a ratio of performance to deviation (RPDc) higher than 3. Statistical indicators of prediction using the validation set were also very high (R(2)p values > 0.90). However, the calibration model obtained for carbon content was much less satisfactory (R(2)c < 0.50). NIRM appears as a promising and suitable tool for a rapid, non-destructive and reliable determination of nitrogen content of tiny samples of tomato leaf powder.

In situ analysis of lipid oxidation in oilseed-based food products using near-infrared spectroscopy and chemometrics: The sunflower kernel paste (tahini) example.

A new near-infrared (NIR) spectroscopic method was developed for the analytical measurement of lipid oxidation in sunflower kernel paste (tahini), which was chosen as an example of a complex oilseed-based food product. The NIR spectra of sunflower tahini were acquired for the extracted fat phase (EFP) and for the intact sunflower tahini (IST) samples during controlled storage. The best peroxide value (PV) calibration models were considered suitable for quality control (ratio of performance of deviation [RPD]>5). The best PV partial least squares (PLS) model result for EFP (RPD 6.36) was obtained when using standard normal variate (SNV) and the Savitzky-Golay first derivative in the 1140-1184nm, 1388-1440nm and 2026-2194nm regions. In the case of IST spectra, the best PV models (RPD 5.23) were obtained when either multiple scattering correction (MSC) or SNV were followed by the Savitzky-Golay second derivative for the 1148-1180nm and 2064-2132nm regions. There were poor correlations between the NIR-predicted values and the reference data of the p-anisidine value (pAV) for both EFP and IST. Overall, the results obtained showed that NIR spectroscopy is an appropriate analytical tool for monitoring sunflower paste PV in situ. Due to the nonexistence of the extraction step, it demonstrates a unique and substantial advantage over presently known methods. Based on these results it is strongly recommended that, when using NIR PLS models to assess lipid oxidation in situ in similar oilseed-based food products (e.g., sesame tahini, hazelnut and cocoa liquor used for chocolate production, peanut butter, hazelnut, almond, pistachio spreads), suitable calibration sets containing samples of different particle sizes and stored at different temperatures be selected.

Linseed oil presents different patterns of oxidation in real-time and accelerated aging assays.

This study aimed at verifying if the hypothesis that one day at 60°C is equivalent to one month at 20°C could be confirmed during linseed oil aging for 6months at 20°C and 6days at 60°C using the "Schaal oven stability test". Tests were conducted with linseed oil supplemented or not with myricetin or butyl-hydroxytoluene as antioxidants. Oxidation was evaluated with the peroxide and p-anisidine values, as well as the content in conjugated dienes and aldehydes. All four indicators of oxidation showed very different kinetic behaviors at 20 and 60°C. The hypothesis is thus not verified for linseed oil, supplemented or not with antioxidant. In the control oil, the conjugated dienes and the peroxide value observed were respectively of 41.8±0.8 Absorbance Unit (AU)/g oil and 254.3±5.8meq.O2/kg oil after 6months at 20°C. These values were of 18.2±1.3AU/g oil and 65.2±20.3meq.O2/kg after 6days at 60°C.

Origin authentication of distillers' dried grains and solubles (DDGS)--application and comparison of different analytical strategies.

In the context of products from certain regions or countries being banned because of an identified or non-identified hazard, proof of geographical origin is essential with regard to feed and food safety issues. Usually, the product labeling of an affected feed lot shows origin, and the paper documentation shows traceability. Incorrect product labeling is common in embargo situations, however, and alternative analytical strategies for controlling feed authenticity are therefore needed. In this study, distillers' dried grains and solubles (DDGS) were chosen as the product on which to base a comparison of analytical strategies aimed at identifying the most appropriate one. Various analytical techniques were investigated for their ability to authenticate DDGS, including spectroscopic and spectrometric techniques combined with multivariate data analysis, as well as proven techniques for authenticating food, such as DNA analysis and stable isotope ratio analysis. An external validation procedure (called the system challenge) was used to analyze sample sets blind and to compare analytical techniques. All the techniques were adapted so as to be applicable to the DDGS matrix. They produced positive results in determining the botanical origin of DDGS (corn vs. wheat), and several of them were able to determine the geographical origin of the DDGS in the sample set. The maintenance and extension of the databanks generated in this study through the analysis of new authentic samples from a single location are essential in order to monitor developments and processing that could affect authentication.

NIR fingerprint screening for early control of non-conformity at feed mills.

The objective of this work was to devise a complete procedure based on chemometrics and the use NIR spectroscopy at the entrance of a feed mill to provide early evidence of non-conformity and unusual ingredients and thus help to achieve cost-savings. The procedure was validated at laboratory level and was adapted for application at the Cargill Animal Nutrition feed mill. The study focused on the characterisation of pure soybean meal with the aim of creating an early control system for detecting and quantifying any unusual ingredient that might be present in the soybean meal, such as melamine, cyanuric acid or whey powder (milk serum). The study results showed that the use of NIR, combined with some simple chemometric tools based on distances and residuals from regression equations, is appropriate for authenticating important feed products (in this case, soybean meal) and detecting the presence of abnormal samples or impurities in both the laboratory and at the feed mill.