Resolution of galactose, glucose, xylose and mannose in sugarcane bagasse employing a voltammetric electronic tongue formed by metals oxy-hydroxide/MWCNT modified electrodes

1IntroductionThea nalysis of amino acids (AAs) is usually performed using techniques such as gas [1,2] and liquid [3,4] chromatography or capillary electrophoresis [5][6][7].T hough, the great demand of AA determinations in many important fields,s uch as clinicala nalysiso rf ood and pharmaceuticali ndustry [ 8,9],l eads to then eed of simpler and faster procedures,s uch as sensor-based methods.T hese electroanalyticala pproaches are reported as good methods for the analysis of specific AAs thankst ot he electroactivityp resented by aromaticand thiolg roups [8].Materials traditionally usedi nt he constructiono fs ensors for this kind of applications are carbon,p latinum and gold. But these materials are usually modified in order to increase the sensitivity and introducen ew features due to electrocatalytic activity, which leads to an increase in the range of detectable AAs [10].Theu se of metal oxide-modified sensors (MOS) has increasedd uring the last years duet oi ts great potential in the analysis of manye lectroactive substances [11,12] or even the detection of the presence of some bacteria in complex systems [13].M oreover, the recent availability of these materials in the form of nanopowder has facilitated enormously the possibility of using them as electrode modifiers.P otential of usingM OS materials has widened its scope especially by the use of semiconducting MOS arrays as gas sensors forming electronic noses (ENs). ENs have gained recognition in many fields like food, aromao rm edical diagnosis [ 14].T he large amount of data provided by ENs increases the sensitivity and selectivity of the method just by multivariate data processing, which avoids tedious derivatizationo ro ptimisation of the sensors for eacha nalyte [15,16].H owever,t he use of MOS is only ap ossible option to develop electronic noses and/or electronic tongues (ETs) [17].ETs have been used for more than ad ecade,a nd its use has grown considerably as they present al arge scope of applications,i ncluding environmental analysis, food industry and agriculture [18][19][20].D ue to the good performance of voltammetric techniques to analyze certain AAs, voltammetric ETs have already been presenteda s ag ood approach for their analysis,i nt his case for the ones with oxidizable properties,s uch as cysteine( CYS), tyrosine (TYR) and tryptophan (TRP) [21][22][23].An important weakness of voltammetric ETs residesi n the complexity of the response obtained, as there is an eed to process each voltammogram from eachs ensor. However, huge amounts of data derived from voltammetric analysis have usually been modelleds uccessfully by usingp rior compression which interprets and extracts meaningful data, offsets any matrix effecta nd may allow the resolution of interfering agents and drifts.T he most widely used multivariate data analysis techniques for voltammetric ETs are principal componenta nalysis,p artial least squares regression (PLS) and artificial neural networks (ANNs) [24][25][26].PLS represents the data in new coordinate axes, but in this ca...

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“…You may get deeper into the chemometric routines of our research group by checking some of our related works .…”

Section: Methodsmentioning

confidence: 99%

Analysis of Amino Acid Mixtures by Voltammetric Electronic Tongues and Artificial Neural Networks

2016

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“…Carbohydrates are detected by measuring the current generated in their oxidation on the surface of NiOOH nanoparticles . The products of their oxidations can, nonetheless, poison the electrode surface when chronoamperometry technique is applied.…”

Section: Resultsmentioning

confidence: 99%

New Method for Carbohydrates Determination in Sugarcane Bagasse by HPAEC‐RPAD Using Glassy Carbon Electrode Modified with Carbon Nanotubes and Nickel Nanoparticles

et al. 2017

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Second generation ethanol can be produced from carbohydrates released from both sugarcane bagasse cell wall and sugarcane straw. The development of new method for the analysis of carbohydrates is, in this sense, seen as extremely relevant in the area of bioenergy. Based on the above considerations, the scope of this work encompasses the identification and quantification of carbohydrates composition in sugarcane bagasse without the need of sample derivatization, developing a novel analytical method using a glassy carbon electrode modified with multi-walled carbon nanotubes containing nickel oxyhydroxide nanoparticles (GCE/MWCNT/NiOOH) and applying the modified electrode as a detector in HPAEC (High Performance Anion-Exchange Chromatography) with reverse pulsed amperometric detection (RPAD) towards the determination of arabinose, galactose, glucose and xylose in hydrolyzed sugarcane bagasse. The carbohydrates concentrations determined in the hydrolyzed sugarcane bagasse were 6.1 3 10 À4 mol L À1 , 1.0 3 10 À2 mol L À1 and 2.8 3 10 À3 mol L À1 for arabinose, glucose, and xylose respectively. Our results showed that the present method is, in essence, attractive for analysis in the course of the production process of second generation ethanol production in that it does not require sample derivatization, has rapid run time, satisfactory separation, and can be used for the detection of carbohydrates without the interference of other electroactive species.

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“…Since the standard solution preparation followed an orthogonal experimental design, variability in sugars' concentrations was guaranteed, and together with the complexity of conditions of the present study, contributed to a greater degree of confidence in the results. It may have contributed to the achievement of good results, when compared to results presented in other studies that used real samples in the calibration, and other types of E-tongues [18][19][20][21][22]. These issues show the importance of ensuring, in direct studies on synthetic or real samples, a high number of samples with variability of concentrations and matrix composition, and a reference analytical method with low analytical errors, to guarantee a small source of error.…”

Section: Multiple Linear Regression Performance Using External Validamentioning

confidence: 93%

“…Voltammetric E-tongues have also been used in the analysis of sugars. Cardoso de Sa et al [21] evaluated the concentrations of glucose, xylose, galactose and mannose in sugarcane using a voltammetric E-tongue with five carbon electrodes, modified with multi-walled carbon nanotubes, containing metal oxy-hydroxide nanoparticles. For that, an artificial neural network (ANN) calibration model was established and its prediction performance tested using a test data group.…”

Section: Introductionmentioning

confidence: 99%

Sugars’ Quantifications Using a Potentiometric Electronic Tongue with Cross-Selective Sensors: Influence of an Ionic Background

et al. 2019

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Glucose, fructose and sucrose are sugars with known physiological effects, and their consumption has impact on the human health, also having an important effect on food sensory attributes. The analytical methods routinely used for identification and quantification of sugars in foods, like liquid chromatography and visible spectrophotometry have several disadvantages, like longer analysis times, high consumption of chemicals and the need for pretreatments of samples. To overcome these drawbacks, in this work, a potentiometric electronic tongue built with two identical multi-sensor systems of 20 cross-selectivity polymeric sensors, coupled with multivariate calibration with feature selection (a simulated annealing algorithm) was applied to quantify glucose, fructose and sucrose, and the total content of sugars as well. Standard solutions of ternary mixtures of the three sugars were used for multivariate calibration purposes, according to an orthogonal experimental design (multilevel fractional factorial design) with or without ionic background (KCl solution). The quantitative models’ predictive performance was evaluated by cross-validation with K-folds (internal validation) using selected data for training (selected with the K-means algorithm) and by external validation using test data. Overall, satisfactory predictive quantifications were achieved for all sugars and total sugar content based on subsets comprising 16 or 17 sensors. The test data allowed us to compare models’ predictions values and the respective sugar experimental values, showing slopes varying between 0.95 and 1.03, intercept values statistically equal to zero (p-value ≥ 0.05) and determination coefficients equal to or greater than 0.986. No significant differences were found between the predictive performances for the quantification of sugars using synthetic solutions with or without KCl (1 mol L−1), although the adjustment of the ionic background allowed a better homogenization of the solution’s matrix and probably contributed to an enhanced confidence in the analytical work across all of the calibration working range.

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Resolution of galactose, glucose, xylose and mannose in sugarcane bagasse employing a voltammetric electronic tongue formed by metals oxy-hydroxide/MWCNT modified electrodes

Abstract: Second generation ethanol is produced from the carbohydrates released from the cell wall of bagasse and straw of sugarcane. The objective of this work is the characterization and application of a voltammetric electronic tongue using an array of

Cited by 36 publications

References 55 publications

Analysis of Amino Acid Mixtures by Voltammetric Electronic Tongues and Artificial Neural Networks

Analysis of Amino Acid Mixtures by Voltammetric Electronic Tongues and Artificial Neural Networks

New Method for Carbohydrates Determination in Sugarcane Bagasse by HPAEC‐RPAD Using Glassy Carbon Electrode Modified with Carbon Nanotubes and Nickel Nanoparticles

Sugars’ Quantifications Using a Potentiometric Electronic Tongue with Cross-Selective Sensors: Influence of an Ionic Background

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