On-line monitoring of food fermentation processes using electronic noses and electronic tongues: A review

Fermentation processes are often sensitive to even slight changes of conditions that may result in unacceptable end-product quality. Thus, close follow-up of this type of processes is critical for detecting unfavorable deviations as early as possible in order to save downtime, materials and resources. Nevertheless the use of traditional analytical techniques is often hindered by the need for expensive instrumentation and experienced operators and complex sample preparation. In this sense, one of the most promising ways of developing rapid and relatively inexpensive methods for quality control in fermentation processes is the use of chemical multisensor systems. In this work we present an overview of the most important contributions dealing with the monitoring of fermentation processes using electronic noses and electronic tongues. After a brief description of the fundamentals of both types of devices, the different approaches are critically commented, their strengths and weaknesses being highlighted. Finally, future trends in this field are also mentioned in the last section of the article. (C) 2013 Elsevier B.V. All rights reserved.Peris Tortajada, M.; Escuder Gilabert, L. (2013). On-line monitoring of food fermentation processes using electronic noses and electronic tongues: A review. Analytica Chimica Acta. 804:29-36. doi:10.1016/j.aca.2013.09.048S293680

Applications of ion mobility spectrometry, collision-induced dissociation and electron activated dissociation tandem mass spectrometry to structural analysis of proteins, glycoproteins and glycans

This dissertation mainly focuses on analytical method development for characterization of proteins, glycoproteins and glycans using the recently developed ion mobility spectrometry (IMS) techniques and various electron activated dissociation (ExD) tandem mass spectrometry methods. IMS and ExD have become important techniques in structure analysis of biomolecules. IMS is a gas-phase separation method orthogonal to liquid chromatography (LC) fractionation. ExD is capable of producing a large number of structurally informative fragment ions for elucidation of structural details, complementary to collision-induced dissociation (CID). We first applied the selected accumulation-trapped IMS (SA-TIMS)-electronic excitation dissociation (EED) method to analyze various mixtures of glycan isomers. Glycan linkage isomers with linear or branched structure were successfully separated and subsequently identified. Theoretical modeling was also performed to gain a better understanding of isomer separation. The calculated collisional cross section (CCS) values match well with the experimentally measured ones, and suggested that the choice of metal charge carrier and charge state is critical for successful IMS separation of isomeric glycans. In addition, a SA-TIMS-electron capture dissociation (ECD) approach was employed to study gas-phase protein conformation, as the ECD fragmentation pattern is influenced by both the charge distribution and the presence of various non-covalent interactions. We demonstrated that different conformations of protein ions in a single charge state could produce distinct fragmentation pattern, presumably because of their differences in tertiary structures and/or proton locations. The second part describes characterization of glycoproteins using LC-hot ECD. To improve the cleavage coverage of glycopeptides, hot ECD, a fragmentation method utilizing the irradiation of high-energy electrons, was optimized for both middle-down and bottom-up analyses of glycopeptides, including peptides with multiple glycosylation sites. Hot ECD was shown to be an effective fragmentation technique for sequencing of glycopeptides, even for ions in lower charge states. In addition, the online LC-hot ECD approach was applied to characterize extensively modified glycoproteins from biological sources in which all glycosylation sites could be unambiguously determined. This study expands the applications of IMS, CID and ExD to structural analysis of various biomolecules, and explores the analytical potential of combining them for investigation of complex biological systems, in particular, enzyme mechanisms

Active Wavelength Selection for Chemical Identification Using Tunable Spectroscopy

Spectrometers are the cornerstone of analytical chemistry. Recent advances in microoptics manufacturing provide lightweight and portable alternatives to traditional spectrometers. In this dissertation, we developed a spectrometer based on Fabry-Perot interferometers (FPIs). A FPI is a tunable (it can only scan one wavelength at a time) optical filter. However, compared to its traditional counterparts such as FTIR (Fourier transform infrared spectroscopy), FPIs provide lower resolution and lower signal-noiseratio (SNR). Wavelength selection can help alleviate these drawbacks. Eliminating uninformative wavelengths not only speeds up the sensing process but also helps improve accuracy by avoiding nonlinearity and noise. Traditional wavelength selection algorithms follow a training-validation process, and thus they are only optimal for the target analyte. However, for chemical identification, the identities are unknown. To address the above issue, this dissertation proposes active sensing algorithms that select wavelengths online while sensing. These algorithms are able to generate analytedependent wavelengths. We envision this algorithm deployed on a portable chemical gas platform that has low-cost sensors and limited computation resources. We develop three algorithms focusing on three different aspects of the chemical identification problems. First, we consider the problem of single chemical identification. We formulate the problem as a typical classification problem where each chemical is considered as a distinct class. We use Bayesian risk as the utility function for wavelength selection, which calculates the misclassification cost between classes (chemicals), and we select the wavelength with the maximum reduction in the risk. We evaluate this approach on both synthesized and experimental data. The results suggest that active sensing outperforms the passive method, especially in a noisy environment. Second, we consider the problem of chemical mixture identification. Since the number of potential chemical mixtures grows exponentially as the number of components increases, it is intractable to formulate all potential mixtures as classes. To circumvent combinatorial explosion, we developed a multi-modal non-negative least squares (MMNNLS) method that searches multiple near-optimal solutions as an approximation of all the solutions. We project the solutions onto spectral space, calculate the variance of the projected spectra at each wavelength, and select the next wavelength using the variance as the guidance. We validate this approach on synthesized and experimental data. The results suggest that active approaches are superior to their passive counterparts especially when the condition number of the mixture grows larger (the analytes consist of more components, or the constituent spectra are very similar to each other). Third, we consider improving the computational speed for chemical mixture identification. MM-NNLS scales poorly as the chemical mixture becomes more complex. Therefore, we develop a wavelength selection method based on Gaussian process regression (GPR). GPR aims to reconstruct the spectrum rather than solving the mixture problem, thus, its computational cost is a function of the number of wavelengths. We evaluate the approach on both synthesized and experimental data. The results again demonstrate more accurate and robust performance in contrast to passive algorithms

Signal and data processing for machine olfaction and chemical sensing: A review

Signal and data processing are essential elements in electronic noses as well as in most chemical sensing instruments. The multivariate responses obtained by chemical sensor arrays require signal and data processing to carry out the fundamental tasks of odor identification (classification), concentration estimation (regression), and grouping of similar odors (clustering). In the last decade, important advances have shown that proper processing can improve the robustness of the instruments against diverse perturbations, namely, environmental variables, background changes, drift, etc. This article reviews the advances made in recent years in signal and data processing for machine olfaction and chemical sensing

Electronic noses and tongues to assess food authenticity and adulteration

[EN] Background: There is a growing concern for the problem of food authenticity assessment (and hence the detection of food adulteration), since it cheats the consumer and can pose serious risk to health in some instances. Unfortunately, food safety/integrity incidents occur with worrying regularity, and therefore there is clearly a need for the development of new analytical techniques. Scope and approach: In this review, after briefly commenting the principles behind the design of electronic noses and electronic tongues, the most relevant contributions of these sensor systems in food adulteration control and authenticity assessment over the past ten years are discussed. It is also remarked that future developments in the utilization of advanced sensors arrays will lead to superior electronic senses with more capabilities, thus making the authenticity and falsification assessment of food products a faster and more reliable process. Key findings and conclusions: The use of both types of e-devices in this field has been steadily increasing along the present century, mainly due to the fact that their efficiency has been significantly improved as important developments are taking place in the area of data handling and multivariate data analysis methods. (C) 2016 Elsevier Ltd. All rights reserved.Peris Tortajada, M.; Escuder Gilabert, L. (2016). Electronic noses and tongues to assess food authenticity and adulteration. Trends in Food Science and Technology. 58:40-54. doi:10.106/j.tifs.2016.10.014S40545

A review of current techniques for the evaluation of powder mixing

Blending a mixture of powders to a homogeneous system is a crucial step in many manufacturing processes. To achieve a high quality of the end product, powder mixtures should be made with high content uniformity. For instance, producing uniform tablets depends on the homogeneous dispersion of active pharmaceutical ingredient (API), often in low level quantities, into excipients. To control the uniformity of a powder mixture, the first required step is to estimate the powder content information during blending. There are several powder homogeneity evaluation techniques which differ in accuracy, fundamental basis, cost and operating conditions. In this article, emerging techniques for the analysis of powder content and powder blend uniformity, are explained and compared. The advantages and drawbacks of all the techniques are reviewed to help the readers to select the appropriate equipment for the powder mixing evaluation. In addition, the paper highlights the recent innovative on-line measurement techniques used for the non-invasive evaluation of the mixing performance