TY - JOUR A1 - Wojcik, Michal A1 - Brinkmann, Pia A1 - Zdunek, Rafał A1 - Riebe, Daniel A1 - Beitz, Toralf A1 - Merk, Sven A1 - Cieslik, Katarzyna A1 - Mory, David A1 - Antonczak, Arkadiusz T1 - Classification of copper minerals by handheld laser-induced breakdown spectroscopy and nonnegative tensor factorisation JF - Sensors N2 - Laser-induced breakdown spectroscopy (LIBS) analysers are becoming increasingly common for material classification purposes. However, to achieve good classification accuracy, mostly noncompact units are used based on their stability and reproducibility. In addition, computational algorithms that require significant hardware resources are commonly applied. For performing measurement campaigns in hard-to-access environments, such as mining sites, there is a need for compact, portable, or even handheld devices capable of reaching high measurement accuracy. The optics and hardware of small (i.e., handheld) devices are limited by space and power consumption and require a compromise of the achievable spectral quality. As long as the size of such a device is a major constraint, the software is the primary field for improvement. In this study, we propose a novel combination of handheld LIBS with non-negative tensor factorisation to investigate its classification capabilities of copper minerals. The proposed approach is based on the extraction of source spectra for each mineral (with the use of tensor methods) and their labelling based on the percentage contribution within the dataset. These latent spectra are then used in a regression model for validation purposes. The application of such an approach leads to an increase in the classification score by approximately 5% compared to that obtained using commonly used classifiers such as support vector machines, linear discriminant analysis, and the k-nearest neighbours algorithm. KW - LIBS KW - NTF KW - HALS KW - classification KW - copper minerals Y1 - 2020 U6 - https://doi.org/10.3390/s20185152 SN - 1424-8220 VL - 20 IS - 18 PB - MDPI CY - Basel ER - TY - JOUR A1 - Erler, Alexander A1 - Riebe, Daniel A1 - Beitz, Toralf A1 - Löhmannsröben, Hans-Gerd A1 - Grothusheitkamp, Daniela A1 - Kunz, Thomas A1 - Methner, Frank-Jürgen T1 - Characterization of volatile metabolites formed by molds on barley by mass and ion mobility spectrometry JF - Journal of mass spectrometr N2 - The contamination of barley by molds on the field or in storage leads to the spoilage of grain and the production of mycotoxins, which causes major economic losses in malting facilities and breweries. Therefore, on-site detection of hidden fungus contaminations in grain storages based on the detection of volatile marker compounds is of high interest. In this work, the volatile metabolites of 10 different fungus species are identified by gas chromatography (GC) combined with two complementary mass spectrometric methods, namely, electron impact (EI) and chemical ionization at atmospheric pressure (APCI)-mass spectrometry (MS). The APCI source utilizes soft X-radiation, which enables the selective protonation of the volatile metabolites largely without side reactions. Nearly 80 volatile or semivolatile compounds from different substance classes, namely, alcohols, aldehydes, ketones, carboxylic acids, esters, substituted aromatic compounds, alkenes, terpenes, oxidized terpenes, sesquiterpenes, and oxidized sesquiterpenes, could be identified. The profiles of volatile and semivolatile metabolites of the different fungus species are characteristic of them and allow their safe differentiation. The application of the same GC parameters and APCI source allows a simple method transfer from MS to ion mobility spectrometry (IMS), which permits on-site analyses of grain stores. Characterization of IMS yields limits of detection very similar to those of APCI-MS. Accordingly, more than 90% of the volatile metabolites found by APCI-MS were also detected in IMS. In addition to different fungus genera, different species of one fungus genus could also be differentiated by GC-IMS. KW - APCI KW - fungus KW - gas chromatography KW - ion mobility spectrometry KW - mass KW - spectrometry KW - mold KW - soft X-ray Y1 - 2020 U6 - https://doi.org/10.1002/jms.4501 SN - 1076-5174 SN - 1096-9888 VL - 55 IS - 5 SP - 1 EP - 10 PB - Wiley CY - Hoboken ER -