Instrumental intelligent test of food sensory quality as mimic of human panel test combining multiple cross-perception sensors and data fusion

Instrumental test of food quality using perception sensors instead of human panel test is attracting massive attention recently. A novel cross-perception multi-sensors data fusion imitating multiple mammal perception was proposed for the instrumental test in this work. First, three mimic sensors of electronic eye, electronic nose and electronic tongue were used in sequence for data acquisition of rice wine samples. Then all data from the three different sensors were preprocessed and merged. Next, three cross-perception variables i.e., color, aroma and taste, were constructed using principal components analysis (PCA) and multiple linear regression (MLR) which were used as the input of models. MLR, back-propagation artificial neural network (BPANN) and support vector machine (SVM) were comparatively used for modeling, and the instrumental test was achieved for the comprehensive quality of samples. Results showed the proposed cross-perception multi-sensors data fusion presented obvious superiority to the traditional data fusion methodologies, also achieved a high correlation coefficient (>90%) with the human panel test results. This work demonstrated that the instrumental test based on the cross-perception multi-sensors data fusion can actually mimic the human test behavior, therefore is of great significance to ensure the quality of products and decrease the loss of the manufacturers.     

Evaluation of Italian wine by the electronic tongue: recognition, quantitative analysis and correlation with human sensory perception

The electronic tongue based on a sensor array comprising 23 potentiometric cross-sensitive chemical sensors and pattern recognition and multivariate calibration data processing tools was applied to the analysis of Italian red wines. The measurements were made in 20 samples of Barbera d’Asti and in 36 samples of Gutturnio wine. The electronic tongue distinguished all wine samples of the same denomination and vintage, but from different vineyards. Simultaneously the following quantitative parameters of the wines were measured by the electronic tongue with precision within 12%: total and volatile acidity, pH, ethanol content, contents of tartaric acid, sulphur dioxide, total polyphenols, glycerol, etc. The electronic tongue is sensitive to multiple substances that determine taste and flavour of wine and, hence, the system was capable of predicting human sensory scores with average precision of 13% for Barbera d’Asti wines and 8% for Gutturnio wines.     

Near infrared spectroscopy as a rapid tool to measure volatile aroma compounds in Riesling wine: possibilities and limits

Volatile chemical compounds responsible for the aroma of wine are derived from a number of different biochemical and chemical pathways. These chemical compounds are formed during grape berry metabolism, crushing of the berries, fermentation processes (i.e. yeast and malolactic bacteria) and also from the ageing and storage of wine. Not surprisingly, there are a large number of chemical classes of compounds found in wine which are present at varying concentrations (ng L⁻¹ to mg L⁻¹), exhibit differing potencies, and have a broad range of volatilities and boiling points. The aim of this work was to investigate the potential use of near infrared (NIR) spectroscopy combined with chemometrics as a rapid and low-cost technique to measure volatile compounds in Riesling wines. Samples of commercial Riesling wine were analyzed using an NIR instrument and volatile compounds by gas chromatography (GC) coupled with selected ion monitoring mass spectrometry. Correlation between the NIR and GC data were developed using partial least-squares (PLS) regression with full cross validation (leave one out). Coefficients of determination in cross validation (R ²) and the standard error in cross validation (SECV) were 0.74 (SECV: 313.6 μg L⁻¹) for esters, 0.90 (SECV: 20.9 μg L⁻¹) for monoterpenes and 0.80 (SECV: 1658 μg L⁻¹) for short-chain fatty acids. This study has shown that volatile chemical compounds present in wine can be measured by NIR spectroscopy. Further development with larger data sets will be required to test the predictive ability of the NIR calibration models developed.     

Visualized attribute analysis approach for characterization and quantification of rice taste flavor using electronic tongue

This paper deals with a novel visualized attributive analysis approach for characterization and quantification of rice taste flavor attributes (softness, stickiness, sweetness and aroma) employing a multifrequency large-amplitude pulse voltammetric electronic tongue. Data preprocessing methods including Principal Component Analysis (PCA) and Fast Fourier Transform (FFT) were provided. An attribute characterization graph was represented for visualization of the interactive response in which each attribute responded by specific electrodes and frequencies. The model was trained using signal data from electronic tongue and attribute scores from artificial evaluation. The correlation coefficients for all attributes were over 0.9, resulting in good predictive ability of attributive analysis model preprocessed by FFT. This approach extracted more effective information about linear relationship between electronic tongue and taste flavor attribute. Results indicated that this approach can accurately quantify taste flavor attributes, and can be an efficient tool for data processing in a voltammetric electronic tongue system.     

Hybrid Electronic Tongue as a Tool for the Monitoring of Wine Fermentation and Storage Process

Hybrid electronic tongue based on potentiometric and voltammetric sensors was applied for the monitoring of wine production process. The sensor array formed by miniaturized ion‐selective electrodes and glassy carbon electrodes provided the analysis of the progress and correctness of wine fermentation and storage process, detection of the presence of disturbing factors and evaluation of the quality of final product. The efficiency of the proposed approach was compared with the monitoring of wine production carried out using standard reference methods. The results indicated that hybrid electronic tongue could be used as simple and reliable analytical tool dedicated to qualitative and quantitative assessment of wine production.     

A Novel Method for Quality Evaluation of Gardeniae fructus Praeparatus during Heat Processing Based on Sensory Characteristics and Chemical Compositions

The intrinsic chemical components and sensory characteristics of Gardeniae fructus Praeparatus (GFP) directly reflect its quality and subsequently, affect its clinical curative effect. However, there is little research on the correlation between the appearance traits and chemical compositions of GFP during heat processing. In this study, the major components of five typical processed decoction pieces of GFP were determined. With the deepening of processing, the contents of geniposidic acid and 5-HMF gradually increased, while the contents of deacetyl-asperulosidic acid methyl ester, gardenoside, and two pigments declined. Moreover, the electronic eye, electronic tongue, and electronic nose were applied to quantify GFP’s sensory properties. It was found that the chroma values showed a downward trend during the processing of GFP. The results of odor showed that ammonia, alkenes, hydrogen, and aromatic compounds were the material base for aroma characteristics. Complex bitterness in GF was more obvious than that in other GFP processed products. Furthermore, one mathematical model was established to evaluate the correlation between the sensory characteristics and chemical composition of GFP during five different stages. A cluster analysis and neural network analysis contributed to recognizing the processing stage of GFP. This study provided an alternative method for the exterior and interior correlation-based quality evaluation of herbs.     

Near infrared spectroscopic imaging assessment of cartilage composition: Validation with mid infrared imaging spectroscopy

Disease or injury to articular cartilage results in loss of extracellular matrix components which can lead to the development of osteoarthritis (OA). To better understand the process of disease development, there is a need for evaluation of changes in cartilage composition without the requirement of extensive sample preparation. Near infrared (NIR) spectroscopy is a chemical investigative technique based on molecular vibrations that is increasingly used as an assessment tool for studying cartilage composition. However, the assignment of specific molecular vibrations to absorbance bands in the NIR spectrum of cartilage, which arise from overtones and combinations of primary absorbances in the mid infrared (MIR) spectral region, has been challenging. In contrast, MIR spectroscopic assessment of cartilage is well-established, with many studies validating the assignment of specific bands present in MIR spectra to specific molecular vibrations. In the current study, NIR imaging spectroscopic data were obtained for compositional analysis of tissues that served as an in vitro model of OA. MIR spectroscopic data obtained from the identical tissue regions were used as the gold-standard for collagen and proteoglycan (PG) content. MIR spectroscopy in transmittance mode typically requires a much shorter pathlength through the sample (≤10 microns thick) compared to NIR spectroscopy (millimeters). Thus, this study first addressed the linearity of small absorbance bands in the MIR region with increasing tissue thickness, suitable for obtaining a signal in both the MIR and NIR regions. It was found that the linearity of specific, small MIR absorbance bands attributable to the collagen and PG components of cartilage (at 1336 and 856 cm⁻¹, respectively) are maintained through a thickness of 60 μm, which was also suitable for NIR data collection. MIR and NIR spectral data were then collected from 60 μm thick samples of cartilage degraded with chondroitinase ABC as a model of OA. Partial least squares (PLS) regression using NIR spectra as input predicted the MIR-determined compositional parameters of PG/collagen within 6% of actual values. These results indicate that NIR spectral data can be used to assess molecular changes that occur with cartilage degradation, and further, the data provide a foundation for future clinical studies where NIR fiber optic probes can be used to assess the progression of cartilage degradation.     

Classification of white wine aromas with an electronic nose

This paper reports the use of a tin dioxide multisensor array based electronic nose for recognition of 29 typical aromas in white wine. Headspace technique has been used to extract aroma of the wine. Multivariate analysis, including principal component analysis (PCA) as well as probabilistic neural networks (PNNs), has been used to identify the main aroma added to the wine. The results showed that in spite of the strong influence of ethanol and other majority compounds of wine, the system could discriminate correctly the aromatic compounds added to the wine with a minimum accuracy of 97.2%.     

Changes in Phenols,Polysaccharides and Volatile Profiles of Noni (Morinda citrifolia L.) Juice during Fermentation

The change in phenols, polysaccharides and volatile profiles of noni juice from laboratory- and factory-scale fermentation was analyzed during a 63-day fermentation process. The phenol and polysaccharide contents and aroma characteristics clearly changed according to fermentation scale and time conditions. The flavonoid content in noni juice gradually increased with fermentation. Seventy-three volatile compounds were identified by solid-phase microextraction coupled with gas chromatography–mass spectrometry (SPME-GC-MS). Methyl hexanoate, 3-methyl-3-buten-1-ol, octanoic acid, hexanoic acid and 2-heptanone were found to be the main aroma components of fresh and fermented noni juice. A decrease in octanoic acid and hexanoic acid contents resulted in the less pungent aroma in noni juice from factory-scale fermentation. The results of principal component analysis of the electronic nose suggested that the difference in nitrogen oxide, alkanes, alcohols, and aromatic and sulfur compounds, contributed to the discrimination of noni juice from different fermentation times and scales.     

Anharmonicity and Spectra–Structure Correlations in MIR and NIR Spectra of Crystalline Menadione (Vitamin K3)

Mid-infrared (MIR) and near-infrared (NIR) spectra of crystalline menadione (vitamin K₃) were measured and analyzed with aid of quantum chemical calculations. The calculations were carried out using the harmonic approach for the periodic model of crystal lattice and the anharmonic DVPT2 calculations applied for the single molecule model. The theoretical spectra accurately reconstructed the experimental ones permitting for reliable assignment of the MIR and NIR bands. For the first time, a detailed analysis of the NIR spectrum of a molecular system based on a naphthoquinone moiety was performed to elucidate the relationship between the chemical structure of menadione and the origin of the overtones and combination bands. In addition, the importance of these bands during interpretation of the MIR spectrum was demonstrated. The overtones and combination bands contribute to 46.4% of the total intensity of menadione in the range of 3600–2600 cm⁻¹. Evidently, these bands play a key role in shaping of the C-H stretching region of MIR spectrum. We have shown also that the spectral regions without fundamentals may provide valuable structural information. For example, the theoretical calculations reliably reconstructed numerous overtones and combination bands in the 4000–3600 and 2800–1800 cm⁻¹ ranges. These results, provide a comprehensive origin of the fundamentals, overtones and combination bands in the NIR and MIR spectra of menadione, and the relationship of these spectral features with the molecular structure.     

Relationship between wine scores and visible–near-infrared spectra of Australian red wines

Sensory analysis of wine involves the measurement, interpretation and understanding of human responses to the properties perceived by the senses such as sight, smell and taste. The sensory evaluation of wine is often carried out by wine judges, winemakers and technical staff, and allows characterization of the quality of the wine. However, this method is lengthy, expensive, and its results depend on panel training and the specific vocabulary used by the panel. A robust, rapid, unbiased and inexpensive method to assist in quality assessment purposes will therefore be beneficial for the modern wine industry. This study aims to investigate the relationship between sensory analysis, visible (VIS) and near-infrared (NIR) spectroscopy to assess sensory properties of commercial Australian wine varieties. For the purposes of this study 118 red wine samples (Cabernet Sauvignon, Shiraz, Pinot Noir, Tempranillo, Nebbiolo and blends) graded by a panel of experienced tasters and scored according to the Australian wine show system were scanned in transmission in the VIS and NIR range (400–2,500nm). Partial least squares regression models were developed between the overall score given by the judges and the combined VIS–NIR spectra, using full cross validation (leave-one-out method). The results showed that NIR spectroscopy was able to predict wine quality scores in red wine samples (R = 0.61 and standard error of prediction of 0.81). The practical implication of this study is that instrumental methods such as VIS–NIR spectroscopy can be used to complement sensory analysis and can facilitate the task at early stages of product development, making high-throughput screening of novel products feasible or maintaining the consistency of the product.     

Effect of Yellowing Duration on the Chemical Profile of Yellow Tea and the Associations with Sensory Traits

The yellowing process is the crucial step to form the characteristic sensory and chemical properties of yellow tea. To investigate the chemical changes and the associations with sensory traits during yellowing, yellow teas with different yellowing times (0–13 h) were prepared for sensory evaluation and chemical analysis. The intensities of umami and green-tea aroma were reduced whereas sweet taste, mellow taste and sweet aroma were increased under long-term yellowing treatment. A total of 230 chemical constituents were determined, among which 25 non-volatiles and 42 volatiles were the key chemical contributors to sensory traits based on orthogonal partial least squares discrimination analysis (OPLS-DA), multiple factor analysis (MFA) and multidimensional alignment (MDA) analysis. The decrease in catechins, flavonol glycosides and caffeine and the increase in certain amino acids contributed to the elevated sweet taste and mellow taste. The sweet, woody and herbal odorants and the fermented and fatty odorants were the key contributors to the characteristic sensory feature of yellow tea with sweet aroma and over-oxidation aroma, including 7 ketones, 5 alcohols, 1 aldehyde, 5 acids, 4 esters, 5 hydrocarbons, 1 phenolic compound and 1 sulfocompound. This study reveals the sensory trait-related chemical changes in the yellowing process of tea, which provides a theoretical basis for the optimization of the yellowing process and quality control of yellow tea.     

Instrumental measurement of bitter taste in red wine using an electronic tongue

An electronic tongue (ET) based on potentiometric chemical sensors was assessed as a rapid tool for the quantification of bitterness in red wines. A set of 39 single cultivar Pinotage wines comprising 13 samples with medium to high bitterness was obtained from the producers in West Cape, South Africa. Samples were analysed with respect to a set of routine wine parameters and major phenolic compounds using Fourier transform infrared-multiple internal reflection spectroscopy (WineScan) and high-performance liquid chromatography, respectively. A trained sensory panel assessed the bitterness intensity of 15 wines, 13 of which had a bitter taste of medium to high intensity. Thirty-one wine samples including seven bitter-tasting ones were measured by the ET. Influence of the chemical composition of wine on the occurrence of the bitter taste was evaluated using one-way analysis of variance. It was found that bitter-tasting wines had higher concentrations of phenolic compounds (catechin, epicatechin, gallic and caffeic acids and quercetin) than non-bitter wines. Sensitivity of the sensors of the array to the phenolic compounds related to the bitterness was studied at different pH levels. Sensors displayed sensitivity to all studied compounds at pH 7, but only to quercetin at pH 3.5. Based on these findings, the pH of wine was adjusted to 7 prior to measurements. Calibration models for classification of wine samples according to the presence of the bitter taste and quantification of the bitterness intensity were calculated by partial least squares-discriminant analysis (PLS-DA) regression. Statistical significance of the classification results was confirmed by the permutation test. Both ET and chemical analysis data could discriminate between bitter and control wines with the correct classification rates of 94% and 91%, respectively. Prediction of the bitterness intensity with good accuracy (root mean square error of 2 and mean relative error of 6% in validation) was possible only using ET data.     

Pervaporation membrane separation process for enhancing the selectivity of an artificial olfactory system (“electronic nose”)

This study investigates the potential of pervaporation (a selective membrane separation technique) combined with an electronic nose based on metal oxide sensors for analyzing wine model solutions. Choosing a suitable membrane polymer, it is shown that subtle variations in aroma composition can be detected by the metal oxide sensors, even when 12% (v/v) ethanol is present in the original sample. Simulations of the composition of the permeate demonstrate that, despite the low molecular density of the permeate, the respective solute concentrations are sufficiently high to generate a reproducible and significant response from the metal oxide sensors.     

A voltammetric electronic tongue made of modified epoxy-graphite electrodes for the qualitative analysis of wine

First results are presented of a new voltammetric electronic tongue which employs modified epoxy-graphite electrodes. This analytical tool has been applied to qualitative wine analysis, performing the classification of wine varieties, as well as recognition of the oxygenation effect. In the same way, studies related to the detection of some defects in wine production were also assessed, such as its vinegary taste in open-air contact or the use of excess sulphite preservative. The electronic tongue was formed by five voltammetric electrodes, four of them being bulk-modified with different substances: copper and platinum nanoparticles on one side, and polyaniline and polypyrrole powder on the other. The responses were preprocessed employing Principal Component Analysis (PCA) to visualize and identify distinct episodes. The resulting PCA scores were modelled with an artificial neural network that accomplishes final prediction with the qualitative classification of wines and/or detection of defects.     

Outer product analysis of electronic nose and visible spectra: application to the measurement of peach fruit characteristics

Visual aspect and aroma are among the most important features of fruit that determine consumer preferences. Electronic nose and spectroscopic techniques have shown positive results in evaluating some basic analytical parameters of fruit and global features such as the cultivar.In this paper, we illustrate and discuss a study aimed at evaluating the improvement derived by the fusion of visible spectra and electronic nose data. These experiments were performed on a population of yellow peaches belonging to two cultivars. Each sample was measured by visible optical spectroscopy and by electronic nose. In addition, a number of reference parameters were also measured by conventional destructive methodologies.Collected data were analysed individually and then fused together in order to classify the two cultivars and to estimate the reference parameters. Data fusion was performed building the outer product matrix for each measurement. The set of matrices was then successively unfolded and analysed by conventional chemometrics tools.Results were improved using outer products, for instance in classification average percentage errors of 25, 10, and 7 for electronic nose, spectra, and outer product, respectively was achieved. Regression analysis provides the evidence of a substantial orthogonal appearance of the datasets, which offer former hidden information on fruit classification.     

NIR and UV-vis spectroscopy, artificial nose and tongue: Comparison of four fingerprinting techniques for the characterisation of Italian red wines

Four rapid and low-cost vanguard analytical systems (NIR and UV-vis spectroscopy, a headspace-mass based artificial nose and a voltammetric artificial tongue), together with chemometric pattern recognition techniques, were applied and compared in addressing a food authentication problem: the distinction between wine samples from the same Italian oenological region, according to the grape variety.Specifically, 59 certified samples belonging to the Barbera d’Alba and Dolcetto d’Alba appellations and collected from the same vintage (2007) were analysed.The instrumental responses, after proper data pre-processing, were used as fingerprints of the characteristics of the samples: the results from principal component analysis and linear discriminant analysis were discussed, comparing the capability of the four analytical strategies in addressing the problem studied.     

Analytical methods for the quantification of volatile aromatic compounds

The investigation of odorants is not an easy task, which needs to be undertaken in the context of fit-for-purpose quality systems. To date, great attention has been paid to determination of the volatile fractions of odorants, since they are responsible for the attributes of global flavor [i.e. a combination of olfactory (aroma) and gustatory (taste) sensations produced by chemicals]. This kind of determination can be carried out by analytical techniques [e.g., gas chromatography (GC) combined with mass spectrometry and/or olfactometric GC]. Methods complementary to GC analysis are available, allowing assessment of the olfactory impact by an electronic nose (e-nose) or a panel of selected individuals. Also, we consider some innovative analytical techniques to study the effects of odorants in food during consumption.     

Influence of Triazole Pesticides on Wine Flavor and Quality Based on Multidimensional Analysis Technology

Triazole pesticides are widely used to control grapevine diseases. In this study, we investigated the impact of three triazole pesticides—triadimefon, tebuconazole, and paclobutrazol—on the concentrations of wine aroma compounds. All three triazole pesticides significantly affected the ester and acid aroma components. Among them, paclobutrazol exhibited the greatest negative influence on the wine aroma quality through its effect on the ester and acid aroma substances, followed by tebuconazole and triadimefon. Qualitative and quantitative analysis by solid-phase micro-extraction gas chromatography coupled with mass spectrometry revealed that the triazole pesticides also changed the flower and fruit flavor component contents of the wines. This was attributed to changes in the yeast fermentation activity caused by the pesticide residues. The study reveals that triazole pesticides negatively impact on the volatile composition of wines with a potential undesirable effect on wine quality, underlining the desirability of stricter control by the food industry over pesticide residues in winemaking.