---
_id: '7090'
abstract:
- lang: eng
  text: The conventional method for the determination of the lethal heat load during
    pasteurisation (expressed in so-called pasteurisation units (PU)) by measuring
    temperature and flow rate provides known inaccuracies and requires safety margins
    in terms of a planned over-pasteurisation to the detriment of the product quality.
    Based on the hypothesis that chemical conversions correlate with applied heat
    input, despite the differences in reaction kinetics between chemical conversion
    and microbiological inactivation, inline near infrared spectroscopy (NIRS) was
    investigated to identify and quantify applied PU. Acid hydrolytic sucrose degradation
    was confirmed a favourable marker reaction. In a first step by still using offline
    analytics (HPLC) and a calculation the feasibility and plausibility in principle
    could be proved. Compared with conventional PU deviation of only 0.3% were found
    when using the chemical marker reaction. However, the inline application using
    NIRS showed too high variations. The too low accuracy of the NIRS model for the
    sucrose measurement was identified of being the cause for failing the overall
    goal. Improvements in the inline determination seem to be promising.
author:
- first_name: Imke
  full_name: Weishaupt, Imke
  id: '58425'
  last_name: Weishaupt
- first_name: Peter
  full_name: Neubauer, Peter
  last_name: Neubauer
- first_name: Jan
  full_name: Schneider, Jan
  id: '13209'
  last_name: Schneider
  orcid: 0000-0001-6401-8873
citation:
  ama: Weishaupt I, Neubauer P, Schneider J. Approach to an inline monitoring of the
    heat impact in a high temperature short time treatment (HTST) of juice with the
    help of a chemical marker. <i>Brewing science</i>. 2022;75(1/2):1-8. doi:<a href="https://doi.org/10.23763/BrSc21-20weishaupt">10.23763/BrSc21-20weishaupt</a>
  apa: Weishaupt, I., Neubauer, P., &#38; Schneider, J. (2022). Approach to an inline
    monitoring of the heat impact in a high temperature short time treatment (HTST)
    of juice with the help of a chemical marker. <i>Brewing Science</i>, <i>75</i>(1/2),
    1–8. <a href="https://doi.org/10.23763/BrSc21-20weishaupt">https://doi.org/10.23763/BrSc21-20weishaupt</a>
  bjps: <b>Weishaupt I, Neubauer P and Schneider J</b> (2022) Approach to an Inline
    Monitoring of the Heat Impact in a High Temperature Short Time Treatment (HTST)
    of Juice with the Help of a Chemical Marker. <i>Brewing science</i> <b>75</b>,
    1–8.
  chicago: 'Weishaupt, Imke, Peter Neubauer, and Jan Schneider. “Approach to an Inline
    Monitoring of the Heat Impact in a High Temperature Short Time Treatment (HTST)
    of Juice with the Help of a Chemical Marker.” <i>Brewing Science</i> 75, no. 1/2
    (2022): 1–8. <a href="https://doi.org/10.23763/BrSc21-20weishaupt">https://doi.org/10.23763/BrSc21-20weishaupt</a>.'
  chicago-de: 'Weishaupt, Imke, Peter Neubauer und Jan Schneider. 2022. Approach to
    an inline monitoring of the heat impact in a high temperature short time treatment
    (HTST) of juice with the help of a chemical marker. <i>Brewing science</i> 75,
    Nr. 1/2: 1–8. doi:<a href="https://doi.org/10.23763/BrSc21-20weishaupt">10.23763/BrSc21-20weishaupt</a>,
    .'
  din1505-2-1: '<span style="font-variant:small-caps;">Weishaupt, Imke</span> ; <span
    style="font-variant:small-caps;">Neubauer, Peter</span> ; <span style="font-variant:small-caps;">Schneider,
    Jan</span>: Approach to an inline monitoring of the heat impact in a high temperature
    short time treatment (HTST) of juice with the help of a chemical marker. In: <i>Brewing
    science</i> Bd. 75, Carl (2022), Nr. 1/2, S. 1–8'
  havard: I. Weishaupt, P. Neubauer, J. Schneider, Approach to an inline monitoring
    of the heat impact in a high temperature short time treatment (HTST) of juice
    with the help of a chemical marker, Brewing Science. 75 (2022) 1–8.
  ieee: 'I. Weishaupt, P. Neubauer, and J. Schneider, “Approach to an inline monitoring
    of the heat impact in a high temperature short time treatment (HTST) of juice
    with the help of a chemical marker,” <i>Brewing science</i>, vol. 75, no. 1/2,
    pp. 1–8, 2022, doi: <a href="https://doi.org/10.23763/BrSc21-20weishaupt">10.23763/BrSc21-20weishaupt</a>.'
  mla: Weishaupt, Imke, et al. “Approach to an Inline Monitoring of the Heat Impact
    in a High Temperature Short Time Treatment (HTST) of Juice with the Help of a
    Chemical Marker.” <i>Brewing Science</i>, vol. 75, no. 1/2, 2022, pp. 1–8, <a
    href="https://doi.org/10.23763/BrSc21-20weishaupt">https://doi.org/10.23763/BrSc21-20weishaupt</a>.
  short: I. Weishaupt, P. Neubauer, J. Schneider, Brewing Science 75 (2022) 1–8.
  ufg: '<b>Weishaupt, Imke/Neubauer, Peter/Schneider, Jan</b>: Approach to an inline
    monitoring of the heat impact in a high temperature short time treatment (HTST)
    of juice with the help of a chemical marker, in: <i>Brewing science</i> 75 (2022),
    H. 1/2,  S. 1–8.'
  van: Weishaupt I, Neubauer P, Schneider J. Approach to an inline monitoring of the
    heat impact in a high temperature short time treatment (HTST) of juice with the
    help of a chemical marker. Brewing science. 2022;75(1/2):1–8.
date_created: 2022-02-28T10:50:48Z
date_updated: 2026-03-12T11:52:14Z
department:
- _id: DEP4018
- _id: DEP1308
- _id: DEP4028
doi: 10.23763/BrSc21-20weishaupt
external_id:
  isi:
  - '000858906600001'
intvolume: '        75'
isi: '1'
issue: 1/2
keyword:
- near infrared spectroscopy
- apple juice
- pasteurisation
- acid hydrolytic sucrose degradation
- inline measure-ment of heat input
- pasteurisation units
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.researchgate.net/publication/360806853_Approach_to_an_inline_monitoring_of_the_heat_impact_in_a_high_temperature_short_time_treatment_HTST_of_juice_with_the_help_of_a_chemical_marker
oa: '1'
page: 1-8
publication: Brewing science
publication_identifier:
  eissn:
  - 1613-2041
  issn:
  - '1866-5195 '
publication_status: published
publisher: Carl
status: public
title: Approach to an inline monitoring of the heat impact in a high temperature short
  time treatment (HTST) of juice with the help of a chemical marker
type: journal_article
user_id: '83778'
volume: 75
year: '2022'
...
---
_id: '2068'
abstract:
- lang: eng
  text: The production of printing goods is laborious. Furthermore, the print quality,
    especially in banknotes, must be assured. It is accepted, that print defects are
    generated because printing parameters, also machine parameters can change unnoticed.
    Therefore, a combined concept for a multi-sensory learning and classification
    model based on new adaptive fuzzy-pattern-classifiers for data inspection is proposed.
    This inspection concept, which combines optical, acoustical and other machine
    information, comes up with a large amount of data, which leads to multivariate
    methods for data analysis. Multivariate methods are useful for analysis of large
    and complex data sets that consist of many variables measured on large numbers
    of physical data.
author:
- first_name: Walter
  full_name: Dyck, Walter
  last_name: Dyck
- first_name: Thomas
  full_name: Türke, Thomas
  last_name: Türke
- first_name: Johannes
  full_name: Schaede, Johannes
  id: '2128'
  last_name: Schaede
- first_name: Volker
  full_name: Lohweg, Volker
  id: '1804'
  last_name: Lohweg
  orcid: 0000-0002-3325-7887
citation:
  ama: 'Dyck W, Türke T, Schaede J, Lohweg V. A Fuzzy-Pattern-Classifier-Based Adaptive
    Learning Model for Sensor Fusion. In: Thessaloniki, Greece: MLSP 2007 - International
    Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING; 2007:accepted for publication.
    doi:<a href="https://doi.org/10.1109/MLSP.2007.4414320">10.1109/MLSP.2007.4414320</a>'
  apa: 'Dyck, W., Türke, T., Schaede, J., &#38; Lohweg, V. (2007). A Fuzzy-Pattern-Classifier-Based
    Adaptive Learning Model for Sensor Fusion (p. accepted for publication). Thessaloniki,
    Greece: MLSP 2007 - International Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING.
    <a href="https://doi.org/10.1109/MLSP.2007.4414320">https://doi.org/10.1109/MLSP.2007.4414320</a>'
  bjps: '<b>Dyck W <i>et al.</i></b> (2007) A Fuzzy-Pattern-Classifier-Based Adaptive
    Learning Model for Sensor Fusion. Thessaloniki, Greece: MLSP 2007 - International
    Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING, p. accepted for publication.'
  chicago: 'Dyck, Walter, Thomas Türke, Johannes Schaede, and Volker Lohweg. “A Fuzzy-Pattern-Classifier-Based
    Adaptive Learning Model for Sensor Fusion,” accepted for publication. Thessaloniki,
    Greece: MLSP 2007 - International Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING,
    2007. <a href="https://doi.org/10.1109/MLSP.2007.4414320">https://doi.org/10.1109/MLSP.2007.4414320</a>.'
  chicago-de: 'Dyck, Walter, Thomas Türke, Johannes Schaede und Volker Lohweg. 2007.
    A Fuzzy-Pattern-Classifier-Based Adaptive Learning Model for Sensor Fusion. In:
    , accepted for publication. Thessaloniki, Greece: MLSP 2007 - International Workshop
    on MACHINE LEARNING FOR SIGNAL PROCESSING. doi:<a href="https://doi.org/10.1109/MLSP.2007.4414320,">10.1109/MLSP.2007.4414320,</a>
    .'
  din1505-2-1: '<span style="font-variant:small-caps;">Dyck, Walter</span> ; <span
    style="font-variant:small-caps;">Türke, Thomas</span> ; <span style="font-variant:small-caps;">Schaede,
    Johannes</span> ; <span style="font-variant:small-caps;">Lohweg, Volker</span>:
    A Fuzzy-Pattern-Classifier-Based Adaptive Learning Model for Sensor Fusion. In:
    . Thessaloniki, Greece : MLSP 2007 - International Workshop on MACHINE LEARNING
    FOR SIGNAL PROCESSING, 2007, S. accepted for publication'
  havard: 'W. Dyck, T. Türke, J. Schaede, V. Lohweg, A Fuzzy-Pattern-Classifier-Based
    Adaptive Learning Model for Sensor Fusion, in: MLSP 2007 - International Workshop
    on MACHINE LEARNING FOR SIGNAL PROCESSING, Thessaloniki, Greece, 2007: p. accepted
    for publication.'
  ieee: W. Dyck, T. Türke, J. Schaede, and V. Lohweg, “A Fuzzy-Pattern-Classifier-Based
    Adaptive Learning Model for Sensor Fusion,” 2007, p. accepted for publication.
  mla: Dyck, Walter, et al. <i>A Fuzzy-Pattern-Classifier-Based Adaptive Learning
    Model for Sensor Fusion</i>. MLSP 2007 - International Workshop on MACHINE LEARNING
    FOR SIGNAL PROCESSING, 2007, p. accepted for publication, doi:<a href="https://doi.org/10.1109/MLSP.2007.4414320">10.1109/MLSP.2007.4414320</a>.
  short: 'W. Dyck, T. Türke, J. Schaede, V. Lohweg, in: MLSP 2007 - International
    Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING, Thessaloniki, Greece, 2007,
    p. accepted for publication.'
  ufg: '<b>Dyck, Walter et. al. (2007)</b>: A Fuzzy-Pattern-Classifier-Based Adaptive
    Learning Model for Sensor Fusion, in: , Thessaloniki, Greece, S. accepted for
    publication.'
  van: 'Dyck W, Türke T, Schaede J, Lohweg V. A Fuzzy-Pattern-Classifier-Based Adaptive
    Learning Model for Sensor Fusion. In Thessaloniki, Greece: MLSP 2007 - International
    Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING; 2007. p. accepted for publication.'
date_created: 2019-11-29T13:50:28Z
date_updated: 2023-03-15T13:49:38Z
department:
- _id: DEP5023
doi: 10.1109/MLSP.2007.4414320
keyword:
- Sensor fusion
- Inspection
- Optical sensors
- Printing machinery
- Data security
- Data analysis
- Production
- Degradation
- Principal component analysis
- Karhunen-Loeve transforms
language:
- iso: eng
main_file_link:
- url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4414320&tag=1
page: accepted for publication
place: Thessaloniki, Greece
publication_identifier:
  eisbn:
  - 978-1-4244-1566-3
  isbn:
  - 978-1-4244-1565-6
  issn:
  - '1551-2541 '
  unknown:
  - '2378-928X '
publication_status: published
publisher: MLSP 2007 - International Workshop on MACHINE LEARNING FOR SIGNAL PROCESSING
status: public
title: A Fuzzy-Pattern-Classifier-Based Adaptive Learning Model for Sensor Fusion
type: conference
user_id: '45673'
year: 2007
...