Katrien Beullens

Bio: Katrien Beullens is an academic researcher from Catholic University of Leuven. The author has contributed to research in topics: Taste & Electronic tongue. The author has an hindex of 10, co-authored 19 publications receiving 2076 citations. Previous affiliations of Katrien Beullens include Katholieke Universiteit Leuven.

The electronic tongue and ATR–FTIR for rapid detection of sugars and acids in tomatoes

Abstract: The electronic tongue and attenuated total reflectance–Fourier transform infrared spectroscopy (ATR–FTIR) have been evaluated as novel rapid techniques in taste research. The electronic tongue, consisting of 27 potentiometric sensors, and ATR–FTIR, a well-established spectroscopic technique, have been used to determine the sugar and acid profile of four tomato cultivars: Aranca, Climaks, Clotilde and DRW 73-29. The most abundant sugars (glucose, fructose and sucrose) and organic acids (citric acid, malic acid, tartaric acid, fumaric acid and succinic acid) in tomatoes were measured with HPLC as a traditional reference technique. The ability of the novel techniques to detect differences in sugar and acid profiles between these four tomato cultivars has been studied by means of unsupervised and supervised multivariate data analysis techniques such as principal components analysis (PCA) and canonical discriminant analysis (CDA). Canonical correlation analysis (CCA) was applied to compare the information content of the reference technique with that of the electronic tongue and ATR–FTIR. The potential of both the electronic tongue and ATR–FTIR to predict the chemical composition of a sample has been evaluated using partial least squares (PLS) models. Both the electronic tongue and ATR–FTIR have the potential to measure taste determining compounds. Tomato cultivars can be classified based on their sugar and acid profile. However, the prediction of individual components in tomato juice is still inaccurate and needs further optimization.

Analysis of tomato taste using two types of electronic tongues

Abstract: In this study the potential of two types of electronic tongues as rapid techniques to analyze taste is evaluated. The first electronic tongue was developed at the University of Saint-Petersburg and comprises of 18 potentiometric sensors. The second electronic tongue was the ASTREE electronic tongue developed by Alpha M.O.S. (Toulouse, France) which consists of a set of seven sensors which are commercially available. Six Belgian tomato cultivars were classified according to similarity in taste profile using both multisensor systems. The tomato cultivars were selected based on their difference in sweetness and sourness as perceived by trained sensory panels. The concentration of sugars (glucose and fructose), organic acids (citric acid, malic acid and glutamic acid) and minerals (Na and K) were also determined with reference techniques. Multivariate statistical data analysis techniques as principal components analysis (PCA), canonical discriminant analysis (CDA) and partial least squares regression (PLS) were used to classify tomato cultivars according to similarity in taste profile and to quantitatively relate the taste compounds to the sensory panel scores. Both electronic tongues were very well suited to classify tomato cultivars based on their taste profile. To quantify individual sugars, acids and minerals in a complex mixture the system which was developed at the University of Saint-Petersburg was highly appropriate, but this system could not predict general sweetness and umami taste as evaluated by the sensory panel. The ASTREE electronic tongue on the other hand was suitable to quantify glutamic acid and Na, but the sensor readings were poorly correlated to the sweetness, sourness, saltiness and umami in tomato as tasted by the sensory panel.

Analysis of apples varieties – comparison of electronic tongue with different analytical techniques

Abstract: The present study was aimed at application of rapid analytical techniques such as Electronic Tongue and FTIR spectroscopy to the recognition and quantitative analysis of different apple varieties. Five apple varieties were studied using three different analytical techniques: HPLC, electronic tongue multisensor system based on potentiometric chemical sensors and FTIR spectroscopy. Twenty samples (apples) of each variety were measured. Concentrations of organic acids such as malic, citric, galacturonic etc. and sugars were measured by HPLC, which is a conventional method for fruit analysis. HPLC data were used as reference for calibration of the electronic tongue and FTIR. Different aspects of data processing were addressed. Recognition and classification of the apples according to variety was performed by PCA and PLS DISCRIM using the data from three different analytical instruments. Quantitative calibration of the electronic tongue and FTIR with respect to organic acids content was performed using PLS regression. Different approaches to data merging from two different analytical instruments, ET and ATR-FTIRT, were considered. Low-level data fusion was found to be the most effective for ET and ATR-FTIR.

Near-infrared spectroscopy and hyperspectral imaging: non-destructive analysis of biological materials

Abstract: Near-infrared (NIR) spectroscopy has come of age and is now prominent among major analytical technologies after the NIR region was discovered in 1800, revived and developed in the early 1950s and put into practice in the 1970s. Since its first use in the cereal industry, it has become the quality control method of choice for many more applications due to the advancement in instrumentation, computing power and multivariate data analysis. NIR spectroscopy is also increasingly used during basic research performed to better understand complex biological systems, e.g. by means of studying characteristic water absorption bands. The shorter NIR wavelengths (800–2500 nm), compared to those in the mid-infrared (MIR) range (2500–15 000 nm) enable increased penetration depth and subsequent non-destructive, non-invasive, chemical-free, rapid analysis possibilities for a wide range of biological materials. A disadvantage of NIR spectroscopy is its reliance on reference methods and model development using chemometrics. NIR measurements and predictions are, however, considered more reproducible than the usually more accurate and precise reference methods. The advantages of NIR spectroscopy contribute to it now often being favoured over other spectroscopic (colourimetry and MIR) and analytical methods, using chemicals and producing chemical waste, such as gas chromatography (GC) and high performance liquid chromatography (HPLC). This tutorial review intends to provide a brief overview of the basic theoretical principles and most investigated applications of NIR spectroscopy. In addition, it considers the recent development, principles and applications of NIR hyperspectral imaging. NIR hyperspectral imaging provides NIR spectral data as a set of images, each representing a narrow wavelength range or spectral band. The advantage compared to NIR spectroscopy is that, due to the additional spatial dimension provided by this technology, the images can be analysed and visualised as chemical images providing identification as well as localisation of chemical compounds in non-homogenous samples.

Advanced applications of hyperspectral imaging technology for food quality and safety analysis and assessment: A review — Part II: Applications

Abstract: In recent years, hyperspectral imaging has gained a wide recognition as a non-destructive and fast quality and safety analysis and assessment method for a wide range of food products. As the second part of this review, applications in quality and safety determination for food products are presented to illustrate the capability of this technique in the food industry for classification and grading, defect and disease detection, distribution visualization of chemical attributes, and evaluations of overall quality of meat, fish, fruits, vegetables, and other food products. The state of the art of hyperspectral imaging for each of the categories was summarized in the aspects of the investigated quality and safety attributes, the used systems (wavelength range, acquisition mode), the data analysis methods (feature extraction, multivariate calibration, variables selection), and the performance (correlation, error, visualization). With its success in different applications of food quality and safety analysis and assessment, it is evident that hyperspectral imaging can automate a variety of routine inspection tasks. Industrial relevance It is anticipated that real-time food monitoring systems with this technique can be expected to meet the requirements of the modern industrial control and sorting systems in the near future.

Recent Advances and Applications of Hyperspectral Imaging for Fruit and Vegetable Quality Assessment

Abstract: Hyperspectral imaging systems are starting to be used as a scientific tool for food quality assessment. A typical hyperspectral image is composed of a set of a relatively wide range of monochromatic images corresponding to continuous wavelengths that normally contain redundant information or may exhibit a high degree of correlation. In addition, computation of the classifiers used to deal with the data obtained from the images can become excessively complex and time-consuming for such high-dimensional datasets, and this makes it difficult to incorporate such systems into an industry that demands standard protocols or high-speed processes. Therefore, recent works have focused on the development of new systems based on this technology that are capable of analysing quality features that cannot be inspected using visible imaging. Many of those studies have also centred on finding new statistical techniques to reduce the hyperspectral images to multispectral ones, which are easier to implement in automatic, non-destructive systems. This article reviews recent works that use hyperspectral imaging for the inspection of fruit and vegetables. It explains the different technologies available to acquire the images and their use for the non-destructive inspection of the internal and external features of these products. Particular attention is paid to the works aimed at reducing the dimensionality of the images, with details of the statistical techniques most commonly used for this task.