@misc{12021,
  author       = {{Segermann, Jan and Luttmann, Mario and Blome, André and Feldt, Sebastian and Sivanesan, Sujee and Holst, Christoph-Alexander and Lohweg, Volker and Frahm, Björn and Müller, Ulrich}},
  keywords     = {{sourdough, fermentation, near-infrared spectroscopy, support vector machine}},
  location     = {{Lemgo}},
  title        = {{{Die Rolle von ML-Modellen in der Lebensmitteltechnologie: Eine Fallstudie zur Sauerteigfermentation mit NIR-Spektroskopie}}},
  year         = {{2024}},
}

@phdthesis{13335,
  abstract     = {{The process of thermal preservation of liquid foods is a safety-relevant process step in the processing of products such as fruit juices and is associated with a high-energy expenditure and safety margin. There are already various approaches to improve this conventionally managed process step in terms of product and resource preservation. Compared to these novel technologies, the use of real-time process analytics offers great potential to improve already existing process plants by implementing inline capable process analytical tools. This allows direct control of the reactions taking place and changes during the running process. Instead of post process, random product control, quality control during the process can be made rendered. The chemical and pharmaceutical industry serves as a reference industry for the use of process analytical tools, although the reactions and product matrices are less complex. In the food industry, on the other hand, there is a greater variation in raw materials and intermediate products. In addition, a large number of reactions can take place in parallel within a process, and the physical states and properties of the individual components can vary. A uniform set of rules for the use of process analytical tools does not exist here. Each product, each process provides its own research potential, so that a large research gap opens up in the area of the food industry.
In order to contribute to closing this gap, this thesis presents a novel approach to improve the process of pasteurization of liquid food. For fruit juices as an application, near infrared spectroscopy in combination with chemometric methods was applied to make the process more product specific. Based on known weaknesses of the process, the relevant aspects for a product-specific treatment were identified. In the further course, the suitability of near infrared spectroscopy as a process analytical tool in the process of pasteurization was verified. Moreover, it was investigated whether a sufficiently accurate identification of the product type as well as the microbiologically relevant properties can be achieved by the application of chemometric methods. In the course of this, the suitability of the measurement methodology was confirmed and solutions were established for any process influences. The product classification and description of the microbiologically relevant parameters extract content and pH value were also implemented with sufficient accuracy. Knowing the destruction kinetics of relevant microorganisms, the product-specific determination of target values for the necessary lethal heat input could be realized. In addition, an analysis of the actual values was carried out on the basis of a chemometric regression method by inferring the microbiological pasteurization effect through the chemical reaction of acid hydrolytic sucrose degradation by means of the indirect approach. This required knowledge of the chemical reaction kinetics and mahematical modeling of the degradation behavior. The novel approach could be confirmed by calculations using results from off-line analysis, whereas the use of near infrared spectroscopy as an inline method still revealed potential for optimization with respect to measurement accuracies.
In summary, the results of this work provide a promising opportunity to make conventional processes for the preservation of liquid foods more product-specific by using near-infrared spectroscopy as an inline-capable and multimodal sensor technique, leading to an increase in process efficiency and product quality.}},
  author       = {{Weishaupt, Imke}},
  keywords     = {{fruit juice pasteurization, near infrared spectroscopy, process optimization, multivariate statistics, inline process analytics, Fruchtsaftpasteurisation, Prozessoptimierung, Nahinfrarotspektroskopie, multivariate Statistik, Inline-Prozessanalytik}},
  pages        = {{144}},
  publisher    = {{Technische Universität Berlin}},
  title        = {{{Near infrared spectroscopy as inline analytical tool to optimize the pasteurization process of liquid foods}}},
  doi          = {{https://doi.org/10.14279/depositonce-17804}},
  year         = {{2023}},
}

@article{7090,
  abstract     = {{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       = {{Weishaupt, Imke and Neubauer, Peter and Schneider, Jan}},
  issn         = {{1613-2041}},
  journal      = {{Brewing science}},
  keywords     = {{near infrared spectroscopy, apple juice, pasteurisation, acid hydrolytic sucrose degradation, inline measure-ment of heat input, pasteurisation units}},
  number       = {{1/2}},
  pages        = {{1--8}},
  publisher    = {{Carl}},
  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}}},
  doi          = {{10.23763/BrSc21-20weishaupt}},
  volume       = {{75}},
  year         = {{2022}},
}

@article{5425,
  abstract     = {{The feasibility of inline classification and characterization of seven fruit juice varieties was investigated by the application of near-infrared spectroscopy (NIRS) combined with chemometrics. The findings are intended to be used to optimize the flash pasteurization of liquid foods. More precise information of the kind of product in real time had to be achieved to enable a more product-specific process. Using the method of partial least squares discriminant analysis, the fruit juice varieties were classified, showing a classification rate of 100% regarding an internal and 69% regarding an external test sets. A characterization by the extract content, pH value, turbidity, and viscosity was made by fitting a partial least squares regression model. The percentage prediction error of the pH value was <3% for internal and external test sets, and for the Brix value prediction errors were about 4% (internal) and 20% (external). The parameters viscosity and turbidity were found to be unsuitable. Despite this, the strategy applied to gain more product-specific information in real time showed to be feasible. By linking the results to a database containing potentially harmful microorganisms for various types of fruit juices, a more product-specific calculation of the necessary heat input can be performed. To demonstrate the practical relevance, a comparison between conventional and product-adapted process control was performed using two fruit varieties as examples in case of Alicyclobacillus acidoterrestris. Thus, with more accurate product information, achieved through the use of NIRS with chemometrics, a more precise calculation of the heat input can be achieved.}},
  author       = {{Weishaupt, Imke and Neubauer, Peter and Schneider, Jan}},
  issn         = {{2048-7177}},
  journal      = {{Food Science & Nutrition}},
  keywords     = {{flash pasteurization, fruit juice characterization and classification, inline near-infrared spectroscopy, multivariate data analysis}},
  number       = {{3}},
  pages        = {{800--812}},
  publisher    = {{Wiley}},
  title        = {{{Near-infrared spectroscopy for the inline classification and characterization of fruit juices for a product-customized flash pasteurization}}},
  doi          = {{ https://doi.org/10.1002/fsn3.2709}},
  volume       = {{10}},
  year         = {{2022}},
}

@article{5424,
  abstract     = {{Near infrared spectroscopy in combination with a transflection probe was investigated as inline measurement in a continuous flash pasteurizer system with a sugar-water model solution. Robustness and reproducibility of fluctuations of recorded spectra as well as trueness of the chemometric analysis were compared under different process parameter settings. Variable parameters were the flow rate (from laminar flow at 30 L/h to turbulent flow at 90 L/h), temperature (20 to 100 degrees C) and the path length of the transflection probe (2 and 4 mm) while the pressure was kept constant at 2.5 bar. Temperature and path length were identified as the most affecting parameters, in case of homogenous test medium. In case of particle containing systems, the flow rate could have an impact as well. However, the application of a PLS model, which includes a broad temperature range, and the correction of prediction results by applying a polynomial regression function for prediction errors, was able to compensate these effects. Also, a path length of 2 mm leads to a higher accuracy. The applied strategy shows that by the identification of relevant process parameters and settings as well as the establishment of a compensation strategy, near infrared spectroscopy is a powerful process analytical tool for continuous flash pasteurization systems.}},
  author       = {{Weishaupt, Imke and Zimmer, Manuel and Neubauer, Peter and Schneider, Jan}},
  isbn         = {{0022-1147}},
  issn         = {{1750-3841}},
  journal      = {{Journal of Food Science}},
  keywords     = {{flash pasteurization, inline near infrared spectroscopy, multivariate data analysis, process condition influences, sugar-water-solution model beverage}},
  number       = {{7}},
  pages        = {{2020 -- 2031}},
  title        = {{{Model based optimization of transflection near infrared spectroscopy as a process analytical tool in a continuous flash pasteurizer}}},
  doi          = {{10.1111/1750-3841.15307}},
  volume       = {{85}},
  year         = {{2020}},
}