A review of the analytical methods coupled with chemometric tools for the determination of the quality and identity of dairy products

There is an increasing demand of the consumers and actors of the food industry sector to have means of measurement allowing the characterisation of raw materials or food. Dairy products (milk, ice cream, yogurt, butter, cheese, etc.) are in considerable demand, command premium prices and are, therefore, vulnerable to economic adulteration. Authenticity of these products is an important issue for food processors, retailers, regulatory authorities and consumers. It is also valuable for ensuring fair competition and as a mean of protecting consumers against fraud due to mislabelling. Conventional chemical methods are not able to determine the regional provenance of dairy products unambiguously. Therefore, alternative techniques such as spectroscopic techniques i.e., near infrared (NIR), mid infrared (MIR), front face fluorescence spectroscopy (FFFS), stable isotope and nuclear magnetic resonance (NMR)-coupled with chemometric tools have many potential advantages as tools for the evaluation of the identity of such products. This review article discusses the potential of destructive and non-destructive techniques for the determination of the quality and the authenticity of dairy products.     

Grape and wine analysis - enhancing the power of spectroscopy with chemometrics.

Spectroscopic techniques offer the potential to simplify and reduce analytical times for a range of grape and wine analytes. It is this aspect, together with the ability to simultaneously measure several analytes, which was the impetus for developing spectroscopic methods. The Australian Wine Research Institute (AWRI) has long used spectroscopic analysis of wines in the ultraviolet (UV) and visible (Vis) wavelengths, and since 1998 has been investigating applications of spectroscopic techniques in the near infrared (NIR) and mid-infrared (MIR) wavelength regions of the electromagnetic spectrum for the rapid analysis and quality control of both grapes and wine by the Australian wine industry. This paper reviews the use of several spectroscopic techniques, including NIR, MIR, and Vis, combined with chemometrics, to assess grape and wine composition in the Australian wine industry. The achievements, current research, and proposed further applications of different spectroscopic techniques are discussed in studies into the assessments of red grape composition and of fungal diseases in grapes, monitoring phenolic compounds during red wine fermentations, quality grading of red, white and fortified wine styles, monitoring wine distillation processes, and yeast strain classification.     

Rapid determination of sugar level in snack products using infrared spectroscopy

Real-time spectroscopic methods can provide a valuable window into food manufacturing to permit optimization of production rate, quality and safety. There is a need for cutting edge sensor technology directed at improving efficiency, throughput and reliability of critical processes. The aim of the research was to evaluate the feasibility of infrared systems combined with chemometric analysis to develop rapid methods for determination of sugars in cereal products. Samples were ground and spectra were collected using a mid-infrared (MIR) spectrometer equipped with a triple-bounce ZnSe MIRacle attenuated total reflectance accessory or Fourier transform near infrared (NIR) system equipped with a diffuse reflection-integrating sphere. Sugar contents were determined using a reference HPLC method. Partial least squares regression (PLSR) was used to create cross-validated calibration models. The predictability of the models was evaluated on an independent set of samples and compared with reference techniques. MIR and NIR spectra showed characteristic absorption bands for sugars, and generated excellent PLSR models (sucrose: SEP < 1.7% and r > 0.96). Multivariate models accurately and precisely predicted sugar level in snacks allowing for rapid analysis. This simple technique allows for reliable prediction of quality parameters, and automation enabling food manufacturers for early corrective actions that will ultimately save time and money while establishing a uniform quality. Practical Application: The U.S. snack food industry generates billions of dollars in revenue each year and vibrational spectroscopic methods combined with pattern recognition analysis could permit optimization of production rate, quality, and safety of many food products. This research showed that infrared spectroscopy is a powerful technique for near real-time (approximately 1 min) assessment of sugar content in various cereal products.     

A comparison and joint use of NIR and MIR spectroscopic methods for the determination of some parameters in European Emmental cheese

The determination of winter cheese chemical properties, namely, fat, sodium chloride (NaCl), pH, non protein nitrogen (NPN), total nitrogen (TN) and water soluble nitrogen (WSN) was done using spectroscopic technologies with different wavelength zones. The Emmental cheeses provided from different European countries were studied. A total of 91 cheeses produced during the winter time in Austria (n=4), Finland (n=6), Germany (n=13), France (n=30) and Switzerland (n=38) were analysed by near infrared (NIR) and mid infrared (MIR) spectroscopies. The combination of these two spectral regions (sum of their spectra) was also studied. The partial least square (PLS) regression with the leave one-out cross validation technique was used to build up calibration models using data set designated as calibration set. These models were validated with another data set designated as validation set. The obtained results suggest the use of the NIR for the determination of fat and TN contents, and the MIR for NaCl and NPN contents as well as for the pH. Similar results were obtained for WSN using the two techniques together. The combined spectra of both NIR and MIR did improve the results, while providing comparable results to those obtained from either the NIR or MIR spectroscopy.     

现代技术在食品真伪和产地鉴别中的应用

综述了近年来光谱技术（近红外、中红外、拉曼光谱、核磁共振光谱、稳定同位素和荧光光谱）、色谱技术（气相和高效液相）、电子鼻、生物技术（DNA技术和酶联免疫）等现代技术在食品真伪和产地鉴别中的应用。     

Differentiation of apple juice samples on the basis of heat treatment and variety using chemometric analysis of MIR and NIR data

The potential of mid-infrared (MIR) and near-infrared (NIR) spectroscopy for their ability to differentiate between apple juice samples on the basis of apple variety and applied heat-treatment was evaluated. The heat-treatment involved exposure of juice samples (15 ml) for 30 s in a 900 W microwave oven and the apple varieties used to produce the juice samples were Bramley, Elstar, Golden Delicious and Jonagold. The chemometric procedures applied to the MIR and NIR data were partial least squares regression (PLS1 for differentiation on the basis of heat-treatment, PLS2 for varietal differentiation) and linear discriminant analysis (LDA) applied to principal component (PC) scores. PLS1 and PLS2 gave the highest level of correct classification of the apple juice samples according to heat-treatment (77.2% for both MIR and NIR data) and variety (78.3–100% for MIR data; 82.4–100% for NIR data), respectively.     

Determination of Calcium Content in Powdered Milk Using Near and Mid-Infrared Spectroscopy with Variable Selection and Chemometrics

Near infrared (NIR) and mid-infrared (MIR) spectroscopy techniques were evaluated to determine calcium content in powdered milk. A hybrid spectral variable selection algorithm combined with uninformation variable elimination (UVE) and successive projections algorithm (SPA) selected 11 NIR and 15 MIR variables from full 2,756 NIR and 3,727 MIR variables, respectively. Predicted results of least-squares support vector machine models for the samples in the prediction set show that the 15 MIR variables obtained much better results (0.930 for coefficient of determination (r ²), 3.703 for residual predictive deviation (RPD), 30.162 for root mean square error of prediction set (RMSEP) and 5.22% for relative errors of prediction (RSEP)) than 11 NIR variables did (0.636 for r ², 1.587 for RPD, 78.815 for RMSEP, and 13.40% for RSEP). The overall results indicate that MIR spectroscopy could be applied as a precision and rapid method to determine calcium content in powdered milk. The good performance shows a potential application using UVE-SPA to select NIR and MIR effective variables.     

Technical note: Feasibility of near infrared transmittance spectroscopy to predict cheese ripeness

The aim of the study was to evaluate the feasibility of near infrared (NIR) transmittance spectroscopy to predict cheese ripeness using the ratio of water-soluble nitrogen (WSN) to total nitrogen (TN) as an index of cheese maturity (WSN/TN). Fifty-two Protected Designation of Origin cow milk cheeses of 5 varieties (Asiago, Grana Padano, Montasio, Parmigiano Reggiano, and Piave) and different ripening times were available for laboratory and chemometric analyses. Reference measures of WSN and TN were matched with cheese spectral information obtained from ground samples by a NIR instrument that operated in transmittance mode for wavelengths from 850 to 1,050 nm. Prediction equations for WSN and TN were developed using (1) cross-validation on the whole data set and (2) external validation on a subset of the entire data. The WSN/TN was calculated as ratio of predicted WSN to predicted TN in cross-validation. The coefficients of determination for WSN and TN were >0.85 both in cross- and external validation. The high accuracy of the prediction equations for WSN and TN could facilitate implementation of NIR transmittance spectroscopy in the dairy industry to objectively, rapidly, and accurately monitor the ripeness of cheese through WSN/TN.     

Prediction of Inorganic Salt and Moisture Content of Process Cheese Using Dielectric Spectroscopy

The development of on-line sensors for compositional analysis during cheese manufacture is desirable for improved quality control. Dielectric properties of a food product are principally determined by its moisture and salt content. This indicates that dielectric spectroscopy may offer a rapid, on-line and non-destructive method for the determination of moisture and salt content of process cheese. However limited information is available in the literature on the dielectric properties of process cheese. Therefore the aims of this study are to investigate the dielectric properties of process cheese samples over a range of compositional parameters and to assess the potential of dielectric spectroscopy to improve process control during process cheese manufacture. Dielectric spectra of process cheese samples were measured using a coaxial line probe between 300 MHz and 3 GHz. A clear tend was observed between higher moisture content and increases in the dielectric constant. Inorganic salt content was found to have a major influence on the loss factor. The dielectric data obtained was used to develop chemometric models for the prediction of moisture and inorganic salt content of two experimental sets of process cheese samples (exp A and exp B). The root mean square error of prediction (RMSEP) for the models developed to predict moisture content were 0.524% (w/w) (exp A), and 0.423% (w/w) (exp B), while the RMSEP of the inorganic salt models were 0.220% (w/w) (exp A), and 0.263% (w/w) (exp B). It was concluded that dielectric spectroscopy has potential application for compositional analysis in process cheese manufacture.     

Nondestructive Spectroscopic and Imaging Techniques for Quality Evaluation and Assessment of Fish and Fish Products

Nowadays, people have increasingly realized the importance of acquiring high quality and nutritional values of fish and fish products in their daily diet. Quality evaluation and assessment are always expected and conducted by using rapid and nondestructive methods in order to satisfy both producers and consumers. During the past two decades, spectroscopic and imaging techniques have been developed to nondestructively estimate and measure quality attributes of fish and fish products. Among these noninvasive methods, visible/near-infrared (VIS/NIR) spectroscopy, computer/machine vision, and hyperspectral imaging have been regarded as powerful and effective analytical tools for fish quality analysis and control. VIS/NIR spectroscopy has been widely applied to determine intrinsic quality characteristics of fish samples, such as moisture, protein, fat, and salt. Computer/machine vision on the other hand mainly focuses on the estimation of external features like color, weight, size, and surface defects. Recently, by incorporating both spectroscopy and imaging techniques in one system, hyperspectral imaging cannot only measure the contents of different quality attributes simultaneously, but also obtain the spatial distribution of such attributes when the quality of fish samples are evaluated and measured. This paper systematically reviews the research advances of these three nondestructive optical techniques in the application of fish quality evaluation and determination and discuss future trends in the developments of nondestructive technologies for further quality characterization in fish and fish products.     

红外光谱技术在鱼产品质量检测与安全评估中的应用

近年来消费者对鱼产品的掺假问题愈发关注,从而针对鱼产品的质量评估的相关研究也逐渐增加。传统的鱼类成分分析和质量检测技术方法烦琐、费力、昂贵、费时,而光谱技术因其具有速度快、使用方便、样品制备最少或不需要样品制备,及避免样品破坏等优点而受到越来越多的关注。本文综述了以红外光谱技术为主的光谱技术,包括近红外光谱技术、中红外光谱技术等在鱼类及鱼产品的成分和其他质量特性监测中的应用,并对光谱技术的应用前景和发展方向进行了展望,以期为红外光谱技术在鱼类及鱼产品质量监测体系中推广应用提供指导,为解决鱼产品及相关行业的质量问题提供了一种新的途径。     

Characterization of Glycosylated Aroma Compounds in Tannat Grapes and Feasibility of the Near Infrared Spectroscopy Application for Their Prediction

The objective measure of grape quality is an important requirement to enhance wine quality. Particularly, the quantitation of glycosylated aroma compounds could be a useful index for winemakers. In the present work, we evaluated the bound compounds profile on Tannat grapes, and the potential of near infrared (NIR) spectroscopy coupled to chemometric techniques to determine the concentration of the different glycosylated aroma compounds present in this grape variety. The results showed phenols and norisoprenoids as the quantitative most important group of compounds, representing almost 80 % of the total glycosidic components present in Tannat grapes. The glycosidic form of ethyl-β-(4-hydroxy-3-methoxy-phenyl)-propionate was identified for the first time in grapes. The results suggested NIR technique as a screening tool for a fast analysis of the grape aroma potential. The application of such methodology would be ideal for fast grape screening purposes, contributing to the winemaking decisions, classification of the fruit, and perhaps maturity monitoring.     

Monitoring the ripening attributes of Turkish white cheese using miniaturized vibrational spectrometers

Monitoring the ripening process by prevalent analytic methods is laborious, expensive, and time consuming. Our objective was to develop a rapid and simple method based on vibrational spectroscopic techniques to understand the biochemical changes occurring during the ripening process of Turkish white cheese and to generate predictive algorithms for the determination of the content of key cheese quality and ripening indicator compounds. Turkish white cheese samples were produced in a pilot plant scale and ripened for 100 d, and samples were analyzed at 20 d intervals during storage. The collected spectra (Fourier-transform infrared, Raman, and near-infrared) correlated with major composition characteristics (fat, protein, and moisture) and primary products of the ripening process and analyzed by pattern recognition to generate prediction (partial least squares regression) and classification (soft independent analysis of class analogy) models. The soft independent analysis of class analogy models classified cheese samples based on the unique biochemical changes taking place during the ripening process. partial least squares regression models showed good correlation (R_Pre = 0.87 to 0.98) between the predicted values by vibrational spectroscopy and the reference values, giving low standard errors of prediction (0.01 to 0.57). Portable and handheld vibrational spectroscopy units can be used as a rapid, simple, and in situ technique for monitoring the quality of cheese during aging and provide real-time tools for addressing deviations in manufacturing.     

Analytical methods for the determination of the geographic origin of Emmental cheese: mid- and near-infrared spectroscopy

Four different Fourier transform infrared spectroscopic techniques (near infrared diffuse reflection (NIR/DR), mid-infrared attenuated total reflection (mIR/ATR) using two different instruments and mid-infrared transmission (mIR/Tr) spectroscopy) in combination with multivariate chemometrics were investigated for their potential for discriminating Emmental cheese of various geographic origins. A total of 20 Emmental cheese samples produced in winter from Switzerland (n=6), Allgäu (Germany) (n=3), Bretagne (France) (n=3), Savoie (France) (n=3), Vorarlberg (Austria) (n=3) and Finland (n=2) were analysed. The normalised spectra or their 2nd derivatives were analysed by principal component analysis (PCA) and linear discriminant analysis (LDA) of the PCA-scores. Despite the few samples in this preliminary investigation clear trends were observed. The mIR transmission spectra achieved 100% correct classification in LDA when differentiating the Swiss Emmental from the other samples pooled as one group. The NIR/DR spectroscopy allowed a classification by the six regions of cheese origin.     

Application of near (NIR) infrared and mid (MIR) infrared spectroscopy as a rapid tool to classify extra virgin olive oil on the basis of fruity attribute intensity

A sensory analysis of 112 virgin olive oils was performed by a fully trained taste panel. The samples were divided in “defective” and “not defective” on the basis of their olfactory attributes. Then, the “not defective” samples were classified into “low”, “medium” and “high” according to the fruity aroma intensity perceived by assessors. All samples were also analysed by FT-NIR and FT-IR spectroscopy and processed by classification methods (LDA and SIMCA). The results showed that NIR and MIR spectroscopy coupled with statistical methods are an interesting technique compared with traditional sensory assessment in classifying olive oil samples on the basis of the fruity attribute. The prediction rate varied between 71.6% and 100%, as average value. The spectroscopic methods, combined with chemometric strategies, could represent a reliable, cheap and fast classification tool, able to draw a complete fingerprint of a food product, describing its intrinsic quality attributes, that include its sensory attributes.     

Raman and mid-infrared spectroscopy to assess changes in Cheddar cheese with maturation

Infrared spectroscopy and Raman spectroscopy, when applied to food samples, have the unique ability to interrogate their chemical structure. In this research, Raman and mid-infrared (MIR) spectroscopy in conjunction with selected chemometrics approaches were used to investigate the effects of ageing on the protein structure in Cheddar cheese. The results illustrate the potential of Raman confocal imaging and MIR spectroscopy for an understanding of chemical changes in complex dairy matrices.     

Sensing of Mycotoxin Producing Fungi in the Processing of Grains

Due to the growing demand for rapid, sensitive and inexpensive detection of contaminations in food and feed, both in the field and after harvest, non-invasive and non-destructive spectroscopic methods are reviewed for the direct identification of fungi and mycotoxins on grain and in grain products. Different model samples containing defined contaminations of fungi and/or mycotoxins as well as real-world samples were investigated using spectroscopic methods (steady-state and time-resolved fluorescence spectroscopy, ultraviolet/visible/near infrared (NIR) spectroscopy, two-photon-induced fluorescence (TPIF)). To evaluate the capability of TPIF for on-line and in-line mycotoxin analysis in real-world samples, fundamental parameters of different mycotoxins, such as two-photon cross-sections, were determined in beer and wine. A comparison showed that the disturbance due to background emission originating from matrix constituents is significantly reduced under two-photon excitation conditions, and TPIF can be applied for a qualitative and quantitative analysis of mycotoxins in wine and beer. The combination of data obtained from different spectroscopic methods (such as optimised excitation and emission wavelengths, fluorescence decay times and fluorescence quantum efficiency on the one hand side and NIR spectroscopy on the other side) is promising for the qualitative as well as quantitative identification of fungi and mycotoxins. Moreover, NIR reflection spectra yield additional information on ingredients, moisture content and the presence (or absence) of fungi in the sample. The spectroscopic techniques are complemented by chemometric tools to extract the desired chemical information, e.g. with respect to the presence of contaminations.     

NIR Spectroscopy Applications for Internal and External Quality Analysis of Citrus Fruit—A Review

The global citrus industry is continually confronted by new technological challenges to meet the ever-increasing consumer awareness and demand for quality-assured fruit. To face these challenges, recent trend in agribusiness is declining reliance on subjective assessment of quality and increasing adoption of objective, quantitative and non-destructive techniques of quality assessment. Non-destructive instrument-based methods are preferred to destructive techniques because they allow the measurement and analysis of individual fruit, reduce waste and permit repeated measures on the same item over time. A wide range of objective instruments for sensing and measuring the quality attributes of fresh produce have been reported. Among non-destructive quality assessment techniques, near-infrared (NIR) spectroscopy (NIRS) is arguably the most advanced with regard to instrumentation, applications, accessories and chemometric software packages. This paper reviews research progress on NIRS applications in internal and external quality measurement of citrus fruit, including the selection of NIR characteristics for spectra capture, analysis and interpretation. A brief overview on the fundamental theory, history, chemometrics of NIRS including spectral pre-processing methods, model calibration, validation and robustness is included. Finally, future prospects for NIRS-based imaging systems such as multispectral and hyperspectral imaging as well as optical coherence tomography as potential non-destructive techniques for citrus quality assessment are explored.     

Implementation of chemometrics in quality evaluation of food and beverages

Conventional methods for food quality evaluation based on chemical or microbiological analysis followed by traditional univariate statistics such as ANOVA are considered insufficient for some purposes. More sophisticated instrumental methods including spectroscopy and chromatography, in combination with multivariate analysis—chemometrics, can be used to determine food authenticity, identify adulterations or mislabeling and determine food safety. The purpose of this review is to present the current state of knowledge on the use of chemometric tools for evaluating quality of food products of animal and plant origin and beverages. The article describes applications of several multivariate techniques in food and beverages research, showing their role in adulteration detection, authentication, quality control, differentiation of samples and comparing their classification and prediction ability.