@misc{13820,
  abstract     = {{The goal of the dataset is to capture the long-term drift behavior of a commercial electronic nose based on 62 metal-oxide gas sensors. We measured three chemical analytes at different concentrations over 12 months: diacetyl (0.1 ppm and 1 ppm), 2-phenylethanol (200 ppm and 1000 ppm), and ethanol, resulting in 700 time series recordings for each sensor across 40 days. Each single measurement includes a three-stage cycle: 1) baseline air for 5 min, 2) sample air exposure for 5 min, and 3) recovery stage for 5 min. The cycle stage information is given in the dataset as well. The dataset includes the readings from all 62 gas sensors (‘R’), from a temperature sensor (‘T01’) and from one humidity sensor (‘H01’).}},
  author       = {{Wörner, Julius and Eimler, Jonas and Pein-Hackelbusch, Miriam}},
  keywords     = {{electronic nose, drift gas, sensors}},
  publisher    = {{Zenodo}},
  title        = {{{Long-Term Drift Behavior of Electronic Nose}}},
  doi          = {{10.5281/ZENODO.15681119}},
  year         = {{2025}},
}

@misc{10326,
  abstract     = {{In the food industry, and especially in wines as products thereof, ethanol and sulfur dioxide play an equally important role. Both substances are important wine quality characteristics as they influence the taste and odor. As both substances comprise volatile matter, electronic noses should be applicable to discriminate the different qualities of wines. Our study investigates the influence of alcohol and sulfur dioxide on the discrimination ability of wines (especially those of the same grape variety) using two different electronic nose systems. One system is equipped with metal oxide sensors and the other with quartz crystal microbalance sensors. Contrary to indications in literature, where the alcohol content is discussed to have a large influence on e-nose results, it was shown that a difference of 1 % ethanol was not sufficient to allow accurate discrimination using Linear Discriminant Analysis by any system. On the positive side, the analyzed concentrations of ethanol (about 12 %) did not superimpose other volatile information. So difference in sulfur dioxide content gave an accuracy for sample discrimination of up to 90.6 % with MOS nose. Thus, we are so far partially able to discriminate wines with electronic noses based on their volatile imprint.}},
  author       = {{Wörner, Julius and Dörksen, Helene and Pein-Hackelbusch, Miriam}},
  booktitle    = {{2023 IEEE 21st International Conference on Industrial Informatics (INDIN)}},
  keywords     = {{Ethanol, Pipelines, Metals, Nose, Electronic noses, Sensor systems, Sensors, Quartz crystals, Linear discriminant analysis, Sulfur}},
  location     = {{Lemgo}},
  title        = {{{Key Indicators for the Discrimination of Wines by Electronic Noses}}},
  doi          = {{https://doi.org/10.1109/INDIN51400.2023.10217912}},
  year         = {{2023}},
}