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.

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.

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.

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.

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.

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.

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.

Monitoring of the oxidation of the oil from sacha inchi (

This work focuses on the characterization of the oxidation of the oil from sacha inchi seeds (Plukenetia volubilis) under accelerated conditions at 60 ºC for 15 days. Five samples were monitored: three supplemented with 200 ppm of non-hydrolyzed or partially hydrolyzed (for 4 and 9 hours) extracts from tara (Caesalpinia spinosa) pods, one without antioxidant and one with 200 ppm of BHT. Several conventional tech­niques (induction time, peroxide value, conjugated dienoic acid, p-anisidine value, total unsaturated fatty acids and α-linolenic acid contents) and the MIR spectroscopy coupled with chemometric tools were used and com­pared. The results revealed that whatever the antioxidant added, the oil from sacha inchi is fairly stable over time. The results also pointed out that extracts from tara pods, mainly those partially hydrolyzed, were more efficient than BHT against oil oxidation for up to 7 days. Finally, this paper shows that MIR spectroscopy pres­ents an interesting alternative technique for the monitoring of the oxidation of the oil from sacha inchi.

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.

Determination of Processed Animal Proteins, Including Meat and Bone Meal, in Animal Feed

An intercomparison study was conducted to determine the presence of processed animal proteins (PAPs), including meat and bone meal (MBM) from various species, in animal feed. The performances of different methods, such as microscopy, polymerase chain reaction (PCR), immunoassays, and a protocol based on iquid chromatography (LC), were compared. Laboratories were asked to analyze for PAPs from all terrestrial animals and fish (total PAPs); mammalian PAPs; ruminant PAPs; and porcine PAPs. They were free to use their method of choice. In addition, laboratories using microscopy were asked to determine the presence of PAPs from terrestrial animals, which is applicable only to microscopy. For total PAPs microscopy, LC and some immunoassays showed sufficient results at a concentration as low as 0.1% MBM in the feed. In contrast, PCR was not fit for purpose. In differentiating between MBM from terrestrial animals and fishmeal, microscopy detected 0.5% of terrestrial MBM in feed in the presence of 5% fishmeal, but was less successful when the concentration of MBM from terrestrial animals was 0.1%. The animal-specific determination of MBM from mammals or, more specifically from either ruminants or pigs, by PCR showed poor results, as indicated by a high number of false-positive and false-negative results. The only PCR method that scored quite well was applied by a member of the organizer team of the study. Immunoassays scored much better than PCR, showing sufficient sensitivity but some deficiency in terms of specificity. The results also demonstrated that the reliable determination of MBM from ruminants has not been resolved, especially for low concentrations of MBM (0.1%) in feed. Comparison of the results for mammalian MBM from all methods indicated that, for control purposes, the immunoassay method, especially when applied as dipsticks, could be used as a rapid screening method combined with microscopy to confirm the positive samples. However, implementation of such a system would require that the immunoassays were previously validated to demonstrate that this approach is fit for purpose. The determination of ruminant or porcine PAPs by immunoassays was more difficult, partly because the MBM in this study contained about 50% bovine and porcine material, thereby reducing the target concentration level to 0.05%.

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.

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.

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.

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.

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.

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.

Evaluation of the overall quality of olive oil using fluorescence spectroscopy

The fluorescence spectra of some olive oils were examined in their natural and oxidised state, with wavelength range emissions of 300-800 nm and 300-400 nm used as excitation radiation. The fluorescence emissions were measured and an assessment was made of the relationship between them and the main quality parameters of olive oils, such as peroxide value, K232, K270 and acidity. These quality parameters (peroxide value, K232, K270 and acidity) are determined by laboratory methods, which though not too sophisticated, they are required solvents and materials as well as time consuming and sample preparation; there is a need for rapid analytical techniques and a low-cost technology for olive oil quality control. The oxidised oils studied had a strong fluorescence band at 430-450 nm. Extra virgin olive oil gave a different but interesting fluorescence spectrum, composed of three bands: one low intensity doublet at 440 and 455 nm; one strong band at 525 nm; and one of medium intensity at 681 nm. The band at 681 nm was identified as the chlorophyll band. The band at 525 nm was derived, at least partially, from vitamin E. The results presented demonstrate the ability of the fluorescence technique, combined with multivariate analysis, to characterise olive oils on the basis of all the quality parameters studied. Prediction models were obtained using various methods, such as partial least squares (PLS), N-way PLS (N-PLS) and external validation, in order to obtain an overall evaluation of oil quality. The best results were obtained for predicting K270 with a root mean square (RMS) prediction error of 0.08 and a correlation coefficient obtained with the external validation of 0.924. Fluorescence spectroscopy facilitates the detection of virgin olive oils obtained from defective or poorly maintained fruits (high acidity), fruits that are highly degraded in the early stages (with a high peroxide value) and oils in advanced stages of oxidation, with secondary oxidation compounds (high K232 and K270). The results indicate the potential of a spectrofluorimetric method combined with multivariate analysis to differentiate, and even quantify, the levels of oil quality. The proposed methodology could be used to accelerate analysis, is inexpensive and allows a comprehensive assessment to be made of olive oil quality.

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.

Evaluation of FT-NIR and ATR-FTIR spectroscopy techniques for determination of minor odd- and branched-chain saturated and trans unsaturated milk fatty acids

Determination of nutritionally important trans MUFA, CLA, and OBCFA milk fatty acids (often present in amounts lower than 1.0 g/100 g of total fat) using fast and nondestructive analytical methods would enhance their use as diagnostic tools in dairy herd and human health management. Here, PLS regression using ATR/FTIR spectra indicated potential for determination of trans-11 C18:1 and trans-12 C18:1 (Rcv² ≥ 0.80), and trans-9 C18:1 in very minor concentration (Rcv² > 0.82), as well as anteiso C15:0 (Rcv² = 0.57) and iso C17:0 (Rcv² = 0.61). Furthermore, the main cis-9,trans-11 CLA isomer was predicted well despite the high trans MUFA concentration. Differentiation between the CLA and the trans MUFA signals was evident (based on specific cis/trans bands), and branched-chain saturated fatty acid methyl esters revealed specific iso and anteiso ATR/FTIR absorbance bands. None of the minor FA PLS results with FT-NIR showed interesting potential, except satisfactory predictions for trans-9 C18:1 and cis-9,trans-11 CLA. Overall, ATR/FTIR resulted in better calibrations and provided more specific information for determination of minor milk fatty acids.

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.

Non-destructive measurement of vitamin C, total polyphenol and sugar content in apples using near-infrared spectroscopy

BACKGROUND

The vitamin C and polyphenol content of apples constitute quality and nutritional parameters of great interest for consumers, especially in terms of health. They are commonly measured using laborious reference methods. The purpose of this study was to evaluate the potential of near-infrared (NIR) spectroscopy as a rapid and non-destructive method to determine the sugar, vitamin C and total polyphenol content in apples.

RESULTS

The quality parameters of more than 150 apple genotypes were analyzed using NIR and reference methods. The results obtained using the least squares support vector machine regression method showed good to very good prediction performance. Low standard error of prediction values, in addition to relatively high ratio to prediction (RPD) values, demonstrated the precision of the models, especially for polyphenol and sugar content. High RPD values (5.1 and 4.3 for polyphenol and sugar, respectively) indicated that an accurate classification of apples based on their content could be achieved.

CONCLUSION

NIR spectroscopy coupled with the multivariate calibration technique could be used to accurately measure the quality parameters of apples. In addition, in the case of breeding programs, NIR spectroscopy can be considered an interesting tool for sorting varieties according to a range of concentrations.