---
_id: '11495'
abstract:
- lang: eng
  text: 'To evaluate the suitability of an analytical instrument, essential figures
    of merit such as the limit of detection (LOD) and the limit of quantification
    (LOQ) can be employed. However, as the definitions k nown in the literature are
    mostly applicable to one signal per sample, estimating the LOD for substances
    with instruments yielding multidimensional results like electronic noses (eNoses)
    is still challenging. In this paper, we will compare and present different approaches
    to estimate the LOD for eNoses by employing commonly used multivariate data analysis
    and regression techniques, including principal component analysis (PCA), principal
    component regression (PCR), as well as partial least squares regression (PLSR).
    These methods could subsequently be used to assess the suitability of eNoses to
    help control and steer processes where volatiles are key process parameters. As
    a use case, we determined the LODs for key compounds involved in beer maturation,
    namely acetaldehyde, diacetyl, dimethyl sulfide, ethyl acetate, isobutanol, and
    2-phenylethanol, and discussed the suitability of our eNose for that dertermination
    process. The results of the methods performed demonstrated differences of up to
    a factor of eight. For diacetyl, the LOD and the LOQ were sufficiently low to
    suggest potential for monitoring via eNose. '
article_number: '3520'
article_type: original
author:
- first_name: Julia
  full_name: Kruse, Julia
  id: '82298'
  last_name: Kruse
- first_name: Julius
  full_name: Wörner, Julius
  id: '79011'
  last_name: Wörner
- first_name: Jan
  full_name: Schneider, Jan
  id: '13209'
  last_name: Schneider
  orcid: 0000-0001-6401-8873
- first_name: Helene
  full_name: Dörksen, Helene
  id: '46416'
  last_name: Dörksen
- first_name: Miriam
  full_name: Pein-Hackelbusch, Miriam
  id: '64952'
  last_name: Pein-Hackelbusch
  orcid: 0000-0002-7920-0595
citation:
  ama: Kruse J, Wörner J, Schneider J, Dörksen H, Pein-Hackelbusch M. Methods for
    Estimating the Detection and Quantification Limits of Key Substances in Beer Maturation
    with Electronic Noses . <i>Sensors</i>. 2024;24(11). doi:<a href="https://doi.org/10.3390/s24113520">10.3390/s24113520</a>
  apa: Kruse, J., Wörner, J., Schneider, J., Dörksen, H., &#38; Pein-Hackelbusch,
    M. (2024). Methods for Estimating the Detection and Quantification Limits of Key
    Substances in Beer Maturation with Electronic Noses . <i>Sensors</i>, <i>24</i>(11),
    Article 3520. <a href="https://doi.org/10.3390/s24113520">https://doi.org/10.3390/s24113520</a>
  bjps: <b>Kruse J <i>et al.</i></b> (2024) Methods for Estimating the Detection and
    Quantification Limits of Key Substances in Beer Maturation with Electronic Noses
    . <i>Sensors</i> <b>24</b>.
  chicago: Kruse, Julia, Julius Wörner, Jan Schneider, Helene Dörksen, and Miriam
    Pein-Hackelbusch. “Methods for Estimating the Detection and Quantification Limits
    of Key Substances in Beer Maturation with Electronic Noses .” <i>Sensors</i> 24,
    no. 11 (2024). <a href="https://doi.org/10.3390/s24113520">https://doi.org/10.3390/s24113520</a>.
  chicago-de: Kruse, Julia, Julius Wörner, Jan Schneider, Helene Dörksen und Miriam
    Pein-Hackelbusch. 2024. Methods for Estimating the Detection and Quantification
    Limits of Key Substances in Beer Maturation with Electronic Noses . <i>Sensors</i>
    24, Nr. 11. doi:<a href="https://doi.org/10.3390/s24113520">10.3390/s24113520</a>,
    .
  din1505-2-1: '<span style="font-variant:small-caps;">Kruse, Julia</span> ; <span
    style="font-variant:small-caps;">Wörner, Julius</span> ; <span style="font-variant:small-caps;">Schneider,
    Jan</span> ; <span style="font-variant:small-caps;">Dörksen, Helene</span> ; <span
    style="font-variant:small-caps;">Pein-Hackelbusch, Miriam</span>: Methods for
    Estimating the Detection and Quantification Limits of Key Substances in Beer Maturation
    with Electronic Noses . In: <i>Sensors</i> Bd. 24, MDPI (2024), Nr. 11'
  havard: J. Kruse, J. Wörner, J. Schneider, H. Dörksen, M. Pein-Hackelbusch, Methods
    for Estimating the Detection and Quantification Limits of Key Substances in Beer
    Maturation with Electronic Noses , Sensors. 24 (2024).
  ieee: 'J. Kruse, J. Wörner, J. Schneider, H. Dörksen, and M. Pein-Hackelbusch, “Methods
    for Estimating the Detection and Quantification Limits of Key Substances in Beer
    Maturation with Electronic Noses ,” <i>Sensors</i>, vol. 24, no. 11, Art. no.
    3520, 2024, doi: <a href="https://doi.org/10.3390/s24113520">10.3390/s24113520</a>.'
  mla: Kruse, Julia, et al. “Methods for Estimating the Detection and Quantification
    Limits of Key Substances in Beer Maturation with Electronic Noses .” <i>Sensors</i>,
    vol. 24, no. 11, 3520, 2024, <a href="https://doi.org/10.3390/s24113520">https://doi.org/10.3390/s24113520</a>.
  short: J. Kruse, J. Wörner, J. Schneider, H. Dörksen, M. Pein-Hackelbusch, Sensors
    24 (2024).
  ufg: '<b>Kruse, Julia u. a.</b>: Methods for Estimating the Detection and Quantification
    Limits of Key Substances in Beer Maturation with Electronic Noses , in: <i>Sensors</i>
    24 (2024), H. 11.'
  van: Kruse J, Wörner J, Schneider J, Dörksen H, Pein-Hackelbusch M. Methods for
    Estimating the Detection and Quantification Limits of Key Substances in Beer Maturation
    with Electronic Noses . Sensors. 2024;24(11).
date_created: 2024-06-03T07:43:48Z
date_updated: 2025-06-25T13:00:14Z
department:
- _id: DEP4028
doi: 10.3390/s24113520
external_id:
  isi:
  - '001245424000001'
  pmid:
  - '38894312'
intvolume: '        24'
isi: '1'
issue: '11'
keyword:
- multidimensional sensor arrays
- MOS sensors
- beer fermentation
- process control
- gas analysis
- metal oxide semiconductors
- intentional data analysis
- chemometrics
- PLSR
- PCA
- first-order calibration
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.mdpi.com/1424-8220/24/11/3520
oa: '1'
pmid: '1'
publication: Sensors
publication_identifier:
  issn:
  - '1424-8220 '
publication_status: published
publisher: MDPI
quality_controlled: '1'
status: public
title: 'Methods for Estimating the Detection and Quantification Limits of Key Substances
  in Beer Maturation with Electronic Noses '
type: scientific_journal_article
user_id: '83781'
volume: 24
year: '2024'
...
---
_id: '12230'
abstract:
- lang: eng
  text: Model ensembles have several benefits compared to single-model applications
    but are not frequently used within the lake modelling community. Setting up and
    running multiple lake models can be challenging and time consuming, despite the
    many similarities between the existing models (forcing data, hypsograph, etc.).
    Here we present an R package, LakeEnsemblR, that facilitates running ensembles
    of five different vertical one-dimensional hydrodynamic lake models (FLake, GLM,
    GOTM, Simstrat, MyLake). The package requires input in a standardised format and
    a single configuration file. LakeEnsemblR formats these files to the input required
    by each model, and provides functions to run and calibrate the models. The outputs
    of the different models are compiled into a single file, and several post-processing
    operations are supported. LakeEnsemblR's workflow standardisation can simplify
    model benchmarking and uncertainty quantification, and improve collaborations
    between scientists. We showcase the successful application of LakeEnsemblR for
    two different lakes.
article_number: '105101'
author:
- first_name: Tadhg N.
  full_name: Moore, Tadhg N.
  last_name: Moore
- first_name: Jorrit P.
  full_name: Mesman, Jorrit P.
  last_name: Mesman
- first_name: Robert
  full_name: Ladwig, Robert
  last_name: Ladwig
- first_name: Johannes
  full_name: Feldbauer, Johannes
  last_name: Feldbauer
- first_name: Freya
  full_name: Olsson, Freya
  last_name: Olsson
- first_name: Rachel M.
  full_name: Pilla, Rachel M.
  last_name: Pilla
- first_name: Tom
  full_name: Shatwell, Tom
  id: '86424'
  last_name: Shatwell
  orcid: 0000-0002-4520-7916
- first_name: Jason J.
  full_name: Venkiteswaran, Jason J.
  last_name: Venkiteswaran
- first_name: Austin D.
  full_name: Delany, Austin D.
  last_name: Delany
- first_name: Hilary
  full_name: Dugan, Hilary
  last_name: Dugan
- first_name: Kevin C.
  full_name: Rose, Kevin C.
  last_name: Rose
- first_name: Jordan S.
  full_name: Read, Jordan S.
  last_name: Read
citation:
  ama: 'Moore TN, Mesman JP, Ladwig R, et al. LakeEnsemblR: An R package that facilitates
    ensemble modelling of lakes. <i>Environmental modelling &#38; software with environment
    data news</i>. 2021;143. doi:<a href="https://doi.org/10.1016/j.envsoft.2021.105101">10.1016/j.envsoft.2021.105101</a>'
  apa: 'Moore, T. N., Mesman, J. P., Ladwig, R., Feldbauer, J., Olsson, F., Pilla,
    R. M., Shatwell, T., Venkiteswaran, J. J., Delany, A. D., Dugan, H., Rose, K.
    C., &#38; Read, J. S. (2021). LakeEnsemblR: An R package that facilitates ensemble
    modelling of lakes. <i>Environmental Modelling &#38; Software with Environment
    Data News</i>, <i>143</i>, Article 105101. <a href="https://doi.org/10.1016/j.envsoft.2021.105101">https://doi.org/10.1016/j.envsoft.2021.105101</a>'
  bjps: '<b>Moore TN <i>et al.</i></b> (2021) LakeEnsemblR: An R Package That Facilitates
    Ensemble Modelling of Lakes. <i>Environmental modelling &#38; software with environment
    data news</i> <b>143</b>.'
  chicago: 'Moore, Tadhg N., Jorrit P. Mesman, Robert Ladwig, Johannes Feldbauer,
    Freya Olsson, Rachel M. Pilla, Tom Shatwell, et al. “LakeEnsemblR: An R Package
    That Facilitates Ensemble Modelling of Lakes.” <i>Environmental Modelling &#38;
    Software with Environment Data News</i> 143 (2021). <a href="https://doi.org/10.1016/j.envsoft.2021.105101">https://doi.org/10.1016/j.envsoft.2021.105101</a>.'
  chicago-de: 'Moore, Tadhg N., Jorrit P. Mesman, Robert Ladwig, Johannes Feldbauer,
    Freya Olsson, Rachel M. Pilla, Tom Shatwell, u. a. 2021. LakeEnsemblR: An R package
    that facilitates ensemble modelling of lakes. <i>Environmental modelling &#38;
    software with environment data news</i> 143. doi:<a href="https://doi.org/10.1016/j.envsoft.2021.105101">10.1016/j.envsoft.2021.105101</a>,
    .'
  din1505-2-1: '<span style="font-variant:small-caps;"><span style="font-variant:small-caps;">Moore,
    Tadhg N.</span> ; <span style="font-variant:small-caps;">Mesman, Jorrit P.</span>
    ; <span style="font-variant:small-caps;">Ladwig, Robert</span> ; <span style="font-variant:small-caps;">Feldbauer,
    Johannes</span> ; <span style="font-variant:small-caps;">Olsson, Freya</span>
    ; <span style="font-variant:small-caps;">Pilla, Rachel M.</span> ; <span style="font-variant:small-caps;">Shatwell,
    Tom</span> ; <span style="font-variant:small-caps;">Venkiteswaran, Jason J.</span>
    ; u. a.</span>: LakeEnsemblR: An R package that facilitates ensemble modelling
    of lakes. In: <i>Environmental modelling &#38; software with environment data
    news</i> Bd. 143, Elsevier BV (2021)'
  havard: 'T.N. Moore, J.P. Mesman, R. Ladwig, J. Feldbauer, F. Olsson, R.M. Pilla,
    T. Shatwell, J.J. Venkiteswaran, A.D. Delany, H. Dugan, K.C. Rose, J.S. Read,
    LakeEnsemblR: An R package that facilitates ensemble modelling of lakes, Environmental
    Modelling &#38; Software with Environment Data News. 143 (2021).'
  ieee: 'T. N. Moore <i>et al.</i>, “LakeEnsemblR: An R package that facilitates ensemble
    modelling of lakes,” <i>Environmental modelling &#38; software with environment
    data news</i>, vol. 143, Art. no. 105101, 2021, doi: <a href="https://doi.org/10.1016/j.envsoft.2021.105101">10.1016/j.envsoft.2021.105101</a>.'
  mla: 'Moore, Tadhg N., et al. “LakeEnsemblR: An R Package That Facilitates Ensemble
    Modelling of Lakes.” <i>Environmental Modelling &#38; Software with Environment
    Data News</i>, vol. 143, 105101, 2021, <a href="https://doi.org/10.1016/j.envsoft.2021.105101">https://doi.org/10.1016/j.envsoft.2021.105101</a>.'
  short: T.N. Moore, J.P. Mesman, R. Ladwig, J. Feldbauer, F. Olsson, R.M. Pilla,
    T. Shatwell, J.J. Venkiteswaran, A.D. Delany, H. Dugan, K.C. Rose, J.S. Read,
    Environmental Modelling &#38; Software with Environment Data News 143 (2021).
  ufg: '<b>Moore, Tadhg N. u. a.</b>: LakeEnsemblR: An R package that facilitates
    ensemble modelling of lakes, in: <i>Environmental modelling &#38; software with
    environment data news</i> 143 (2021).'
  van: 'Moore TN, Mesman JP, Ladwig R, Feldbauer J, Olsson F, Pilla RM, et al. LakeEnsemblR:
    An R package that facilitates ensemble modelling of lakes. Environmental modelling
    &#38; software with environment data news. 2021;143.'
date_created: 2024-12-08T20:18:32Z
date_updated: 2024-12-09T11:27:54Z
department:
- _id: DEP8022
doi: 10.1016/j.envsoft.2021.105101
extern: '1'
intvolume: '       143'
keyword:
- Ensemble modeling
- Vertical one-dimensional lake model
- R package
- Calibration
- Thermal structure
- Hydrodynamics
language:
- iso: eng
main_file_link:
- url: https://doi.org/10.1016/j.envsoft.2021.105101
publication: Environmental modelling & software with environment data news
publication_identifier:
  eissn:
  - 1873-6726
  issn:
  - 1364-8152
publication_status: published
publisher: Elsevier BV
quality_controlled: '1'
status: public
title: 'LakeEnsemblR: An R package that facilitates ensemble modelling of lakes'
type: scientific_journal_article
user_id: '83781'
volume: 143
year: '2021'
...