FTIR-ATR Spectroscopy Based Metabolite Fingerprinting as A Direct Determination of Butter Adulterated With Lard

Nondestructive Metabolomic Fingerprinting: FTIR, NIR and Raman Spectroscopy in Food Screening

In recent years, there has been renewed interest in the maintenance of food quality and food safety on the basis of metabolomic fingerprinting using vibrational spectroscopy combined with multivariate chemometrics. Nontargeted spectroscopy techniques such as FTIR, NIR and Raman can provide fingerprint information for metabolomic constituents in agricultural products, natural products and foods in a high-throughput, cost-effective and rapid way. In the current review, we tried to explain the capabilities of FTIR, NIR and Raman spectroscopy techniques combined with multivariate analysis for metabolic fingerprinting and profiling. Previous contributions highlighted the considerable potential of these analytical techniques for the detection and quantification of key constituents, such as aromatic amino acids, peptides, aromatic acids, carotenoids, alcohols, terpenoids and flavonoids in the food matrices. Additionally, promising results were obtained for the identification and characterization of different microorganism species such as fungus, bacterial strains and yeasts using these techniques combined with supervised and unsupervised pattern recognition techniques. In conclusion, this review summarized the cutting-edge applications of FTIR, NIR and Raman spectroscopy techniques equipped with multivariate statistics for food analysis and foodomics in the context of metabolomic fingerprinting and profiling.

A Comparative Study of Milk Fat Extracted from the Milk of Different Goat Breeds in China: Fatty Acids, Triacylglycerols and Thermal and Spectroscopic Characterization

Goat milk (GM) is an excellent alternative to cow milk and has recently been used in commercial infant formula preparation due to its superior fat composition. Here, the fatty acid (FA) composition, triacylglycerol (TAG) molecular species, thermal behavior and infrared spectra of extracted milk fat from the milk of the two main breeds of dairy goat bred in China (Guanzhong GM (GZG) and Xinong Saanen GM (XSG)) are investigated. Gas chromatography, Fourier-transform infrared spectroscopy, differential scanning calorimetry and ultra-performance convergence chromatography with quadrupole time-of-flight mass spectrometry are applied. The obtained results evidence significant fat compositional differences based on the breed that produced the considered GM. The major FAs in both GM fats were capric (C10:0), myristic (C14:0), palmitic (C16:0), stearic (C18:0) and oleic (C18:1 n-9c). GZG presented a higher content of medium-chain saturated FAs, while XSG had higher unsaturated FAs with higher ratios of L/Ln and n-6/n-3. A total of 339 and 359 TAGs were detected and quantified in GZG and XSG, and the major TAGs were those of m/z 740.6712 (14.10 ± 0.27%) and m/z 684.6094 (10.94 ± 0.02%), respectively. Milk TAGs of GZG and XSG showed 24–54 and 26–54 total acyl carbon numbers with a 0–4 and 0–5 double bond number at 68 and 72 various retention times, respectively. Thermal analysis showed that all GM fat samples melted below normal body temperature. Infrared spectra revealed higher absorption values of GZG milk fat. This study provides valuable information to the dairy industry sector about GM fat produced in China, assessing the appropriateness of Chinese GM fat to be applied in Chinese infant formula.

Near-infrared techniques for fraud detection in dairy products: A review

The dairy products sector is an important part of the food industry, and their consumption is expected to grow in the next 10 years. Therefore, the authentication of these products in a faster and precise way is required for the sake of public health. This review proposes the use of near-infrared techniques for the detection of food fraud in dairy products as they are faster, nondestructive, environmentally friendly, do not require sample preparation, and allow multiconstituent analysis. First, we have described frequent forms of food fraud in dairy products and the application of traditional techniques for their detection, highlighting gaps and counterproductive characteristics for the actual global food chain, as longer sample preparation time and use of reagents. Then, the application of near-infrared spectroscopy and hyperspectral imaging for the detection of food fraud mainly in cheese, butter, and yogurt are described. As these techniques depend on model development, the coverage of different dairy products by the literature will promote the identification of food fraud in a faster and reliable way.

Identification of inhibitors of pinellic acid generation in whole wheat bread

Bitterness is a common aversive flavor attribute of foods associated with low consumer acceptance. Untargeted LC-MS flavoromic profiling was utilized to identify endogenous compounds that influence the generation of the bitter compound 9,12,13-trihydroxy-trans-10-octadecenoic acid (pinellic acid) during bread making. A diverse sample set of wheat germplasm was chemically profiled. The corresponding pinellic acid concentrations after dough formation were modeled by orthogonal partial least squares (OPLS) with good fit (R²Y = 0.8) and predictive ability (Q² = 0.6). The most predictive feature (negatively correlated), postulated to interfere with the biosynthetic pathway, was identified as schaftoside, an apigenin di-C-glycoside. Recombination experiments involving the addition of schaftoside to flour prior to breadmaking resulted in a 26% decrease in pinellic acid formation and significantly lower perceived bitterness intensity in whole wheat bread. This work provides novel understanding of bitter generation pathways in wheat products and new strategies to improve flavor profiles and consumer acceptability.

Rapid detection and quantification of sucrose adulteration in cow milk using Attenuated total reflectance-Fourier transform infrared spectroscopy coupled with multivariate analysis

Adulteration of milk to gain economic benefit has become a common practice in recent years. Sucrose is illegally added in milk to reconstitute its compositional requirement by improving the total solid contents. The present study is aimed to use FTIR spectroscopy in combination with multivariate chemometric modelling for the differentiation and quantification of sucrose in cow milk. Pure milk and adulterated milk spectra (0.5-7.5% w/v) were observed in the spectral region 4000-400 cm^-1. Principal component analysis (PCA) was used for the discrimination of pure milk and adulterated milk. Soft independent modelling of class analogy (SIMCA) was able to classify test samples with a classification efficiency of 100%. Partial least square regression (PLS-R) and principle component regression (PCR) models were established for normal spectra, 1st derivative and 2nd derivative for the quantification of sucrose in milk. PLS-R model (normal spectra) in the combined wavenumber range of 1070-980 cm^-1 showed the best prediction based on parameters like coefficient of determination (R²) (Cal: 0.996; Val: 0.993), RMSE (Cal: 0.15% w/v; Val: 0.20% w/v), RE% (Cal: 4.9% w/v; Val: 5.1% w/v) and RPD (13.40). This method has a detection level of 0.5% w/v sucrose adulteration.

A review of Fourier Transform Infrared (FTIR) spectroscopy used in food adulteration and authenticity investigations

The increasing demand for food and the globalisation of the supply chain have resulted in a rise in food fraud, and recent high profile cases, such as the Chinese milk scandal in 2008 and the EU horsemeat scandal in 2013 have emphasised the vulnerability of the food supply system to adulteration and authenticity frauds. Fourier Transform Infrared (FTIR) spectroscopy is routinely used in cases of suspected food fraud as it offers a rapid, easy and reliable detection method for these investigations. In this review, we first present a brief summary of the concepts of food adulteration and authenticity as well as a discussion of the current legislation regarding these crimes. Thereafter, we give an extensive overview of FTIR as an analytical technique and the different foods where FTIR analysis has been employed for food fraud investigations as well as the subsequent multivariate data analyses that have been applied successfully to investigate the case of adulteration or authenticity. Finally, we give a critical discussion of the applications and limitations of FTIR, either as a standalone technique or incorporated in a test battery, in the fight against food fraud.

Current and Future Perspectives on the Structural Identification of Small Molecules in Biological Systems

Although significant advances have been made in recent years, the structural elucidation of small molecules continues to remain a challenging issue for metabolite profiling. Many metabolomic studies feature unknown compounds; sometimes even in the list of features identified as "statistically significant" in the study. Such metabolic "dark matter" means that much of the potential information collected by metabolomics studies is lost. Accurate structure elucidation allows researchers to identify these compounds. This in turn, facilitates downstream metabolite pathway analysis, and a better understanding of the underlying biology of the system under investigation. This review covers a range of methods for the structural elucidation of individual compounds, including those based on gas and liquid chromatography hyphenated to mass spectrometry, single and multi-dimensional nuclear magnetic resonance spectroscopy, and high-resolution mass spectrometry and includes discussion of data standardization. Future perspectives in structure elucidation are also discussed; with a focus on the potential development of instruments and techniques, in both nuclear magnetic resonance spectroscopy and mass spectrometry that, may help solve some of the current issues that are hampering the complete identification of metabolite structure and function.