Comparison of a trained sensory panel and an electronic tongue in the assessment of bitter dairy protein hydrolysates

A Comparative Analysis of Plant-Based Milk Alternatives Part 1: Composition, Sensory, and Nutritional Value

Consumers are becoming increasingly interested in reducing the consumption of animal-based foods for health, sustainability, and ethical reasons. The food industry is developing products from plant-based ingredients that mimic animal-based foods’ nutritional and sensory characteristics. In this study, the focus is on plant-based milk alternatives (PBMAs). A potential problem with plant-based diets is the deficiency of important micronutrients, such as vitamin B12, B2, and calcium. Therefore, an analysis of micronutrients in PBMAs was conducted to assess their nutritional value. The second main focus was on the sensory description of the PBMAs, done by a trained panel, and instrumental assessment to characterize the sensory attributes. Almond drinks met the daily micronutrient requirements the least, while soy drinks came closest to cow’s milk in macro- and micronutrients. The experimentally determined electronic tongue and volatile compound results confirmed the sensory panel’s evaluations and could therefore be used as a method for easy and effective assessments of PBMAs. The PBMAs evaluated in this study could not completely replace cow’s milk’s nutritional and sensory properties. They are products in their own product group and must be evaluated accordingly. Given the variety of products, consumers should experiment and make their decisions regarding the substitution of cow’s milk.

Encapsulation of bitter peptides in water-in-oil high internal phase emulsions reduces their bitterness and improves gastrointestinal stability

Many peptides exhibit beneficial physiological functions, but their application in foods is limited because of their undesirable taste and their tendency to degrade when exposed to gastrointestinal conditions. In this study, water-in-oil high internal phase emulsions (W/O HIPEs) were used to encapsulate bitter peptides. A combination of confocal fluorescence and electron microscopy was used to confirm the formation of W/O HIPEs. The presence of high concentrations of bitter peptides increased the apparent shear viscosity, shear modulus and sedimentation stability. They also improved the oxidative stability of the HIPEs. Electronic-tongue and sensory analysis showed that encapsulated peptides within the HIPEs substantially reduced their bitterness. Moreover, a simulated gastrointestinal study showed that W/O HIPEs protected peptides from being released in the stomach. Our results show that W/O HIPEs can be used to mask the bitterness and improve the gastrointestinal stability of peptides, which may increase their utilization as bioactive ingredients in foods.

Structure determination, bitterness evaluation and hepatic gluconeogenesis inhibitory activity of triterpenoids from the Momordica charantia fruit

Triterpenoids are hypoglycemic substances and flavor components of Momordica charantia L., whether their bitterness correlated with hypoglycemic potential remain unknown. Thus, triterpenoids in M. charantia were isolated by phytochemical methods and identified by spectroscopic analysis. The bitterness levels and hypoglycaemic activity of isolated triterpenoids were evaluated by electronic tongue and hepatic gluconeogenesis assay. Eighteen triterpenoids including two new ones, Momordicoside Y and Z, were identified. Among the six identified bitter triterpenoids, karaviloside III, goyaglycoside C, and momordicoside F2 were bitterer than caffeine (P < 0.05), with caffeine equivalent (CE) values of 289.19, 4.32, and 41.24 mg CE/mg, respectively. Momordicoside Y, charantoside C, momordicoside F1, and momordicoside G could inhibit hepatic gluconeogenesis by 23.9%, 36.2%, 33.4%, 34.4% at 40 μM, respectively. These four compounds could interact with active site of phosphoenolpyruvate carboxykinase in molecular docking simulation. No correlation was observed between hepatic gluconeogenesis inhibitory activity and bitterness of triterpenoids.

Manufacturing of Plant-Based Bioactive Peptides Using Enzymatic Methods to Meet Health and Sustainability Targets of the Sustainable Development Goals

Due to the rapid growth in the global population, the consumption of animal-based food products/food compounds has been associated with negative implications for food sustainability/security. As a result, there is an increasing demand for the development of plant-based food and compounds as alternatives. Meanwhile, a growing number of studies report the health benefits of food protein-based peptides prepared via enzymatic hydrolysis and exhibiting biological properties such as antioxidant, antihypertensive, anti-thrombotic, and antidiabetic activities. However, the inherent bitterness of some peptides hinders their application in food products as ingredients. This article aims to provide the latest findings on plant-based bioactive peptides, particularly their health benefits, manufacturing methods, detection and qualification of their bitterness properties, as well as debittering methods to reduce or eliminate this negative sensory characteristic. However, there is still a paucity of research on the biological property of debittered peptides. Therefore, the role of plant protein-derived bioactive peptides to meet the health targets of the Sustainable Development Goals can only be realised if advances are made in the industrial-scale bioprocessing and debittering of these peptides.

Challenges in using electronic tongue to study rasa of plants: I. Finding the right tool for the right job

There is growing interest in understanding how ayurveda, the indigenous medical system of India, uses plants for therapeutic purpose. The aim of this two parts article is to explore how the analytical technique of Electronic tongue (E-tongue) can be used for studying rasa, one of the major ayurvedic parameter in the study of medicinal and nutritional plants. Although E-tongue is widely used in pharmaceutical, food and beverage industries for objective evaluation of taste, its use in plants from an ayurvedic perspective is novel. This first of the two parts article introduces the technique of E-tongue, positioning it in context for the following part. The latter discusses crucial control experiments required prior using E-tongue for studies on medicinal plants from an ayurvedic standpoint.

Filling the Gap: A Correlation between Objective and Subjective Measures of Injectability

Various injectable biomaterials are developed for the minimally invasive delivery of therapeutics. Typically, a mechanical tester is used to ascertain the force required to inject these biomaterials through a given syringe-needle system. However, currently there is no method to correlate the force measured in the laboratory to the perceived effort required to perform that injection by the end user. In this article, the injection force (F) for a variety of biomaterials, displaying a range of rheological properties, is compared with the effort scores from a 50 person panel study. The maximum injection force measured at crosshead speed 1 mm s^-1 is a good proxy for injection effort, with an R² of 0.89. This correlation leads to the following conclusions: participants can easily inject 5 mL of substance for F < 12 N; considerable effort is required to inject 5 mL for 12 N < F < 38 N; great effort is required and <5 mL can be injected for 38 N < F < 64 N; and materials are entirely non-injectable for F > 64 N. These values may be used by developers of injectable biomaterials to make decisions about formulations and needle sizes early in the translational process.

Glycated Beef Protein Hydrolysates as Sources of Bitter Taste Modifiers

Being averse to bitter taste is a common phenomenon for humans and other animals, which requires the pharmaceutical and food industries to source compounds that can block bitterness intensity and increase consumer acceptability. In this work, beef protein alcalase hydrolysates (BPAH) and chymotrypsin hydrolysates (BPCH) were reacted with glucose to initiate Maillard reactions that led to the formation of glycated or advanced glycation end products (AGEs), BPAH-AGEs and BPCH-AGEs, respectively. The degree of glycation was higher for the BPAH-AGEs (47-55%) than the BPCH-AGEs (30-38%). Analysis by an electronic tongue instrument showed that BPAH-AGEs and BPCH-AGEs had bitterness scores that were significantly (p < 0.05) less than quinine. The addition of BPAH-AGEs or BPCH-AGEs to quinine led to significant (p < 0.05) reductions (up to 38%) in bitterness intensity of quinine. The use of 3% hydrolysate to react with glucose yielded glycated peptides with a stronger ability to reduce quinine bitterness than when 1% was used. Calcium release from HEK293T cells stably expressing the T2R4 human bitter taste receptor was significantly (p < 0.05) attenuated by BPAH-AGEs (up to 96%) and BPCH-AGEs (up to 92%) when compared to the BPAH (62%) and BPCH (3%) or quinine (0%). We concluded that BPAH-AGEs and BPCH-AGEs may be used as bitter taste blockers to formulate better tasting foods.

Prediction of Sensory Crispness of Potato Chips Using a Reference-Calibration Method

Reference calibration is a useful technique when sensory evaluation is not feasible or practical. This study was conducted to predict the crispness perception of potato chips evaluated by instrumental means through the reference-calibrated method. To investigate the relationship between sensory evaluation and instrumental measurement data, six different standard references for crispness were used. Instrumental crispness was predicted by measuring the total area of the chip with a texture analyzer. The samples were also evaluated by six trained panelists. Nine chips with various textures were tested by a mechanical test. The Fechner, Stevens, and Beidler models were applied to investigate the correlation across the reference scores with the total area then predicting the sensory crispness for the nine chips. The relationship between the instrumental total area and the sensory crispness of the standard references was found to be nonlinear over the standard crispness scale. The Fechner model seemed to be the best predictive model (R2 = 0.8; RMSEC = 1.3; robustness = 2.4; model discrimination index = 3.3) for predicting the sensory crispness of chips. This study suggests that standard references with a reference-calibration method can be used to calibrate the crispness of potato chips. It is the first study to demonstrate that sensory crispness of potato chips could be predicted using comprehensive references for crispness. Based on the results in this study, an equation established by the Fechner model could be utilized to estimate the various crispness of potato chips under circumstances in which sensory evaluation is not practical or available.

Comparison of Sensory and Electronic Tongue Analysis Combined with HS-SPME-GC-MS in the Evaluation of Skim Milk Processed with Different Preheating Treatments

It is well known that the flavor of skim milk is inferior to whole milk due to the lack of fat. With the popularity of low-fat dairy products, improving the flavor of skim milk is a main focus for food scientists. During the production of skim milk, preheating treatments have a significant effect for the flavor of skim milk. In this study, to explore the optimal processing conditions, milk was preheated at 30 °C, 40 °C, 50 °C, 60 °C for 30 min prior to defatting. When the optimal temperature was determined, milk was then preheated at the optimal temperature for 10 min, 20 min, 30 min, 40 min and 50 min, respectively, to obtain the best preheating time. Distinctions between skim milk samples with different processing conditions were studied by sensory evaluation, e-tongue and HS-SPME-GC-MS analysis. Principle components analysis (PCA) and cluster analysis (CA) were selected to associate with e-tongue results and compare the similarities and differences among the skim milks. Sensory and e-tongue results matched and both showed that a preheating temperature of 50 °C and 30 min time might be the optimal combination of processing conditions. Thirteen volatiles, including ketones, acids, aldehydes, alcohols, alkanes and sulfur compounds, were analyzed to evaluate flavor of the skim milks produced by different preheating treatments. Combined with previous studies, the results indicated that most volatile compounds were decreased by reducing the fat concentration and the typical compound 2-heptanone was not detected in our skim milk samples.

A predictive model for the evaluation of flavor attributes of raw and cooked beef based on sensor array analyses

There are currently no standardized objective measures to evaluate beef flavor attributes, especially the comparison between raw beef and cooked beef. Beef flavor attribute is one of the most significant parameters for consumers. This study described a predictive model using a 12-ion-sensor array and sensory properties to evaluate beef flavor attributes based on potential. Then the number of sensors was reduced to six via variance of analysis, and these six sensors were reserved with the saturated calomel reference electrode to constitute a new sensor array. Sensitive flavors of each sensor were selected through multiple comparative analysis. Results showed that the accuracy rate of classifying five basic flavors (acidity, sweetness, bitterness, saltiness, freshness) using the new sensor array was 100%. The processing methods used were based on multivariate statistical methods done with the cluster analysis (CA). Results were compared to sensory evaluation using genetic algorithm (GA). From GA, the accuracy rates of raw and cooked beef were 85.0% and 90.0%, which was consistent with the sensory analysis results. Moreover, reducing the number of sensors could decrease the data dimensionality and detection time. Also raw beef instead of cooked beef could be used in flavor attributes evaluation. This model could become an important method for evaluating beef flavor attributes repeatedly and objectively.

Discriminating aging and protein-to-fat ratio in Cheddar cheese using sensory analysis and a potentiometric electronic tongue

The objectives of this study were to evaluate the flavor and taste attributes of full-fat Cheddar cheeses with different protein-to-fat ratios (PFR) over aging time using a descriptive sensory analysis panel and a consumer panel, and to correlate these attributes with instrumental parameters obtained by the potentiometric electronic tongue. Three Cheddar cheese formulations (PFR of 0.74, 0.85, and 1.01) were produced in triplicate and composition was verified. Cheese was aged at 7.2°C and evaluated at 2, 5, 8, 10, 11, and 12 mo by a trained panel (n = 10) for 8 flavor and 5 taste attributes and using an electronic tongue for 7 nonvolatile taste attributes. Cheese aged for 12 mo was also evaluated by a consumer sensory panel for liking and intensity attributes. Principal component analysis was performed to discriminate cheese based on aging time and PFR, whereas correlation between sensory and instrumental attributes was assessed using partial least squares regression. Descriptive sensory analysis of flavor and taste attributes differentiated Cheddar cheeses over aging time, but not among PFR formulations. The electronic tongue distinguished changes among cheese samples due to PFR formulation and aging time. The electronic tongue proved successful in characterizing the nonvolatile flavor components in Cheddar cheese and correlated with taste perceptions measured by descriptive sensory analysis. Consumer evaluations showed distinctive attribute profiles for the 3 PFR Cheddar cheese formulations. Overall, higher fat content was associated with increased flavor intensities in Cheddar cheese and drove consumer acceptability and purchase intent ratings. The electronic tongue detected smaller changes in tastes (bitter, metallic, salty, sour, spicy, sweet, and umami) of the 3 PFR formulations over time when compared with the trained panelists, who detected no differences, suggesting that the electronic tongue may be more sensitive to tastants than humans and may have the capability for early detection or identification of problems in a batch of cheese during aging. Results suggest taste quality of cheese may be monitored using the electronic tongue with greater sensitivity than a trained panel, and may be more objective, rapid, and cost effective than human panelists.

Bitterness in sodium caseinate hydrolysates: role of enzyme preparation and degree of hydrolysis

BACKGROUND

Enzymatic hydrolysis of sodium caseinate (NaCas) may lead to the development of bitterness. Careful selection of hydrolysis conditions (i.e. enzyme preparation and duration) yielding different degrees of hydrolysis (DH) may aid in the development of low bitterness.

RESULTS

Eighteen NaCas hydrolysates were generated with four enzyme preparations (Alcalase 2.4L, Prolyve 1000, FlavorPro Whey and pepsin) to different DH values. Hydrolysate bitterness score, assessed using a trained panel (ten assessors), generally increased at higher DH values for Alcalase, Prolyve and pepsin hydrolysates. However, all FlavorPro Whey hydrolysates (DH 0.38-10.62%) displayed low bitterness score values (<26.0%) comparable to that of intact NaCas (13.8 ± 2.0%, P > 0.05).

CONCLUSION

Enzyme preparation and DH affect the bitterness of NaCas hydrolysates. The results are relevant for the generation of NaCas hydrolysates with reduced bitterness. © 2017 Society of Chemical Industry.

Application of Sensory Evaluation, HS-SPME GC-MS, E-Nose, and E-Tongue for Quality Detection in Citrus Fruits

In this study, electronic tongue (E-tongue), headspace solid-phase microextraction gas chromatography-mass spectrometer (GC-MS), electronic nose (E-nose), and quantitative describe analysis (QDA) were applied to describe the 2 types of citrus fruits (Satsuma mandarins [Citrus unshiu Marc.] and sweet oranges [Citrus sinensis {L.} Osbeck]) and their mixing juices systematically and comprehensively. As some aroma components or some flavor molecules interacted with the whole juice matrix, the changes of most components in the fruit juice were not in proportion to the mixing ratio of the 2 citrus fruits. The potential correlations among the signals of E-tongue and E-nose, volatile components, and sensory attributes were analyzed by using analysis of variance partial least squares regression. The result showed that the variables from the sensor signals (E-tongue system and E-nose system) had significant and positive (or negative) correlations to the most variables of volatile components (GC-MS) and sensory attributes (QDA). The simultaneous utilization of E-tongue and E-nose obtained a perfect classification result with 100% accuracy rate based on linear discriminant analysis and also attained a satisfying prediction with high coefficient association for the sensory attributes (R(2) > 0.994 for training sets and R(2) > 0.983 for testing sets) and for the volatile components (R(2) > 0.992 for training sets and R(2) > 0.990 for testing sets) based on random forest. Being easy-to-use, cost-effective, robust, and capable of providing a fast analysis procedure, E-nose and E-tongue could be used as an alternative detection system to traditional analysis methods, such as GC-MS and sensory evaluation by human panel in the fruit industry.

PRACTICAL APPLICATION

Being easy-to-use, cost-effective, robust, and capable of providing a fast analysis procedure, E-nose and E-tongue could be used as an alternative detection system to traditional analysis methods for characterizing food flavors. Based on those results, one can draw a conclusion that the fusion system composed of E-tongue and E-nose could guarantee a satisfying result in the prediction of sensory attributes and volatile components for fruit quality profile.

Discrimination of Rice with Different Pretreatment Methods by Using a Voltammetric Electronic Tongue

In this study, an application of a voltammetric electronic tongue for discrimination and prediction of different varieties of rice was investigated. Different pretreatment methods were selected, which were subsequently used for the discrimination of different varieties of rice and prediction of unknown rice samples. To this aim, a voltammetric array of sensors based on metallic electrodes was used as the sensing part. The different samples were analyzed by cyclic voltammetry with two sample-pretreatment methods. Discriminant Factorial Analysis was used to visualize the different categories of rice samples; however, radial basis function (RBF) artificial neural network with leave-one-out cross-validation method was employed for prediction modeling. The collected signal data were first compressed employing fast Fourier transform (FFT) and then significant features were extracted from the voltammetric signals. The experimental results indicated that the sample solutions obtained by the non-crushed pretreatment method could efficiently meet the effect of discrimination and recognition. The satisfactory prediction results of voltammetric electronic tongue based on RBF artificial neural network were obtained with less than five-fold dilution of the sample solution. The main objective of this study was to develop primary research on the application of an electronic tongue system for the discrimination and prediction of solid foods and provide an objective assessment tool for the food industry.

Assessment of taste attributes of peanut meal enzymatic-hydrolysis hydrolysates using an electronic tongue

Peanut meal is the byproduct of high-temperature peanut oil extraction; it is mainly composed of proteins, which have complex tastes after enzymatic hydrolysis to free amino acids and small peptides. The enzymatic hydrolysis method was adopted by using two compound proteases of trypsin and flavorzyme to hydrolyze peanut meal aiming to provide a flavor base. Hence, it is necessary to assess the taste attributes and assign definite taste scores of peanut meal double enzymatic hydrolysis hydrolysates (DEH). Conventionally, sensory analysis is used to assess taste intensity in DEH. However, it has disadvantages because it is expensive and laborious. Hence, in this study, both taste attributes and taste scores of peanut meal DEH were evaluated using an electronic tongue. In this regard, the response characteristics of the electronic tongue to the DEH samples and standard five taste samples were researched to qualitatively assess the taste attributes using PCA and DFA. PLS and RBF neural network (RBFNN) quantitative prediction models were employed to compare predictive abilities and to correlate results obtained from the electronic tongue and sensory analysis, respectively. The results showed that all prediction models had good correlations between the predicted scores from electronic tongue and those obtained from sensory analysis. The PLS and RBFNN prediction models constructed using the voltage response values from the sensors exhibited higher correlation and prediction ability than that of principal components. As compared with the taste performance by PLS model, that of RBFNN models was better. This study exhibits potential advantages and a concise objective taste assessment tool using the electronic tongue in the assessment of DEH taste attributes in the food industry.