[{"page":"1-23","keyword":["ontinuous mashing","continuous stirred tank reactor","mean residence time","fermentable sugar"],"quality_controlled":"1","_id":"9697","language":[{"iso":"eng"}],"year":"2023","oa":"1","type":"scientific_journal_article","citation":{"ieee":"P. Wefing, M. Trilling, A. Gossen, P. Neubauer, and J. Schneider, “A continuous mashing plant controlled by mean residence time,” <i>Journal of The Institute of Brewing</i>, vol. 129, no. 1, pp. 1–23, 2023, doi: <a href=\"https://doi.org/10.58430/jib.v129i1.7\">10.58430/jib.v129i1.7</a>.","van":"Wefing P, Trilling M, Gossen A, Neubauer P, Schneider J. A continuous mashing plant controlled by mean residence time. Journal of The Institute of Brewing. 2023;129(1):1–23.","ama":"Wefing P, Trilling M, Gossen A, Neubauer P, Schneider J. A continuous mashing plant controlled by mean residence time. <i>Journal of The Institute of Brewing</i>. 2023;129(1):1-23. doi:<a href=\"https://doi.org/10.58430/jib.v129i1.7\">10.58430/jib.v129i1.7</a>","mla":"Wefing, Patrick, et al. “A Continuous Mashing Plant Controlled by Mean Residence Time.” <i>Journal of The Institute of Brewing</i>, vol. 129, no. 1, 2023, pp. 1–23, <a href=\"https://doi.org/10.58430/jib.v129i1.7\">https://doi.org/10.58430/jib.v129i1.7</a>.","chicago":"Wefing, Patrick, Marc Trilling, Arthur Gossen, Peter Neubauer, and Jan Schneider. “A Continuous Mashing Plant Controlled by Mean Residence Time.” <i>Journal of The Institute of Brewing</i> 129, no. 1 (2023): 1–23. <a href=\"https://doi.org/10.58430/jib.v129i1.7\">https://doi.org/10.58430/jib.v129i1.7</a>.","short":"P. Wefing, M. Trilling, A. Gossen, P. Neubauer, J. Schneider, Journal of The Institute of Brewing 129 (2023) 1–23.","din1505-2-1":"<span style=\"font-variant:small-caps;\">Wefing, Patrick</span> ; <span style=\"font-variant:small-caps;\">Trilling, Marc</span> ; <span style=\"font-variant:small-caps;\">Gossen, Arthur</span> ; <span style=\"font-variant:small-caps;\">Neubauer, Peter</span> ; <span style=\"font-variant:small-caps;\">Schneider, Jan</span>: A continuous mashing plant controlled by mean residence time. In: <i>Journal of The Institute of Brewing</i> Bd. 129, Wiley (2023), Nr. 1, S. 1–23","havard":"P. Wefing, M. Trilling, A. Gossen, P. Neubauer, J. Schneider, A continuous mashing plant controlled by mean residence time, Journal of The Institute of Brewing. 129 (2023) 1–23.","apa":"Wefing, P., Trilling, M., Gossen, A., Neubauer, P., &#38; Schneider, J. (2023). A continuous mashing plant controlled by mean residence time. <i>Journal of The Institute of Brewing</i>, <i>129</i>(1), 1–23. <a href=\"https://doi.org/10.58430/jib.v129i1.7\">https://doi.org/10.58430/jib.v129i1.7</a>","ufg":"<b>Wefing, Patrick u. a.</b>: A continuous mashing plant controlled by mean residence time, in: <i>Journal of The Institute of Brewing</i> 129 (2023), H. 1,  S. 1–23.","bjps":"<b>Wefing P <i>et al.</i></b> (2023) A Continuous Mashing Plant Controlled by Mean Residence Time. <i>Journal of The Institute of Brewing</i> <b>129</b>, 1–23.","chicago-de":"Wefing, Patrick, Marc Trilling, Arthur Gossen, Peter Neubauer und Jan Schneider. 2023. A continuous mashing plant controlled by mean residence time. <i>Journal of The Institute of Brewing</i> 129, Nr. 1: 1–23. doi:<a href=\"https://doi.org/10.58430/jib.v129i1.7\">10.58430/jib.v129i1.7</a>, ."},"main_file_link":[{"open_access":"1"}],"date_updated":"2025-01-30T15:33:02Z","date_created":"2023-04-12T07:26:12Z","department":[{"_id":"DEP4018"},{"_id":"DEP1308"},{"_id":"DEP4028"}],"user_id":"83781","doi":"10.58430/jib.v129i1.7","status":"public","issue":"1","publication":"Journal of The Institute of Brewing","author":[{"last_name":"Wefing","full_name":"Wefing, Patrick","first_name":"Patrick","id":"68976"},{"id":"81622","orcid":"0000-0002-3685-6383","last_name":"Trilling","full_name":"Trilling, Marc","first_name":"Marc"},{"first_name":"Arthur","full_name":"Gossen, Arthur","last_name":"Gossen","id":"76446"},{"first_name":"Peter","full_name":"Neubauer, Peter","last_name":"Neubauer"},{"id":"13209","first_name":"Jan","full_name":"Schneider, Jan","orcid":"0000-0001-6401-8873","last_name":"Schneider"}],"publisher":"Wiley","abstract":[{"lang":"eng","text":"Continuous processes offer more environmentally friendlier beer production compared to the batch production. However, the continuous production of mashing has not become state-of-the-art in the brewing industry. The controllability and flexibility of this process still has hurdles for practical implementation, but which are necessary to react to changing raw materials. Once overcome, a continuous mashing can be efficiently adapted to the raw materials. Both mean residence time and temperature were investigated as key parameters to influence the extract and fermentable sugar content of the wort. The continuous mashing process was implemented as continuous stirred tank reactor (CSTR) cascade consisting of mashing in (20°C), protein rest (50°C), β-amylase rest (62-64°C), saccharification rest (72°C) and mashing out (78°C). Two different temperature settings for the β-amylase rest were investigated with particular emphasis on fermentable sugars. Analysis of Variance (ANOVA) and a post-hoc analysis showed that the mean residence time and temperature settings were suitable control parameters for the fermentable sugars. In the experimental conditions, the most pronounced effect was with the β-amylase rest. These results broaden the understanding of heterogenous CSTR mashing systems about assembly and selection of process parameters"}],"publication_status":"published","has_accepted_license":"1","volume":129,"intvolume":"       129","ddc":["600"],"title":"A continuous mashing plant controlled by mean residence time"},{"status":"public","publication":"Brewing science ","issue":"9/10","publisher":"Carl","author":[{"id":"68976","last_name":"Wefing","first_name":"Patrick","full_name":"Wefing, Patrick"},{"id":"68967","last_name":"Conradi","first_name":"Florian","full_name":"Conradi, Florian"},{"first_name":"Johannes","full_name":"Rämisch, Johannes","last_name":"Rämisch"},{"full_name":"Neubauer, Peter","first_name":"Peter","last_name":"Neubauer"},{"id":"13209","first_name":"Jan","full_name":"Schneider, Jan","last_name":"Schneider","orcid":"0000-0001-6401-8873"}],"publication_status":"published","abstract":[{"lang":"eng","text":"Free amino nitrogen (FAN) concentrations in beer mash can be determined with machine learning algorithms\r\nfrom near-infrared (NIR) spectra. NIR spectroscopy is an alternative to a classical chemical analysis and\r\nallows for the application of inline process quality control. This study investigates the capabilities of\r\ndifferent machine learning techniques such as Ordinary Least Squares (OLS) regression, Decision Tree\r\nRegressor (DTR), Bayesian Ridge Regression (BRR), Ridge Regression (RR), K-nearest neighbours (KNN)\r\nregression as well as Support Vector Regression (SVR) to predict the FAN content in beer mash from NIR\r\nspectra. Various pre-processing strategies such as principal component analysis (PCA) and data\r\nstandardization were used to process NIR data that were used to train the machine learning algorithms.\r\nAlgorithm training was conducted with NIR data obtained from 16 beer mashes with varying FAN\r\nconcentrations. The trained models were then validated with 4 beer mashes that were not used for model\r\ntraining. Machine learning algorithms based on linear regression showed the highest prediction accuracy on\r\nunpre-processed data. BRR reached a root mean square error of calibration (RMSEC) of 2.58 mg/L (R2 = 0.96)\r\nand a prediction accuracy (RMSEP) of 2.81 mg/L (R2 = 0.96). The FAN concentration range of the investigated\r\nsamples was between approx. 180 and 220 mg/L. Machine learning based NIR spectra analysis is an alternative\r\nto classical chemical FAN level determination methods and can also be used as inline sensor system."}],"publication_identifier":{"eissn":["0723-1520"],"issn":["1866-5195"]},"intvolume":"        74","volume":74,"article_type":"original","title":"Determination of free amino nitrogen in beer mash with an inline NIR transflectance probe and data evaluation by machine learning algorithms","page":"107 - 121","keyword":["mashing","NIR","machine learning","FAN"],"quality_controlled":"1","language":[{"iso":"eng"}],"_id":"6689","year":"2021","type":"journal_article","citation":{"ama":"Wefing P, Conradi F, Rämisch J, Neubauer P, Schneider J. Determination of free amino nitrogen in beer mash with an inline NIR transflectance probe and data evaluation by machine learning algorithms. <i>Brewing science </i>. 2021;74(9/10):107-121. doi:<a href=\"https://doi.org/10.23763/BrSc21-10wefing\">https://doi.org/10.23763/BrSc21-10wefing</a>","short":"P. Wefing, F. Conradi, J. Rämisch, P. Neubauer, J. Schneider, Brewing Science  74 (2021) 107–121.","havard":"P. Wefing, F. Conradi, J. Rämisch, P. Neubauer, J. Schneider, Determination of free amino nitrogen in beer mash with an inline NIR transflectance probe and data evaluation by machine learning algorithms, Brewing Science . 74 (2021) 107–121.","chicago-de":"Wefing, Patrick, Florian Conradi, Johannes Rämisch, Peter Neubauer und Jan Schneider. 2021. Determination of free amino nitrogen in beer mash with an inline NIR transflectance probe and data evaluation by machine learning algorithms. <i>Brewing science </i> 74, Nr. 9/10: 107–121. doi:<a href=\"https://doi.org/10.23763/BrSc21-10wefing\">https://doi.org/10.23763/BrSc21-10wefing</a>, .","ufg":"<b>Wefing, Patrick u. a.</b>: Determination of free amino nitrogen in beer mash with an inline NIR transflectance probe and data evaluation by machine learning algorithms, in: <i>Brewing science </i> 74 (2021), H. 9/10,  S. 107–121.","bjps":"<b>Wefing P <i>et al.</i></b> (2021) Determination of Free Amino Nitrogen in Beer Mash with an Inline NIR Transflectance Probe and Data Evaluation by Machine Learning Algorithms. <i>Brewing science </i> <b>74</b>, 107–121.","mla":"Wefing, Patrick, et al. “Determination of Free Amino Nitrogen in Beer Mash with an Inline NIR Transflectance Probe and Data Evaluation by Machine Learning Algorithms.” <i>Brewing Science </i>, vol. 74, no. 9/10, 2021, pp. 107–21, <a href=\"https://doi.org/10.23763/BrSc21-10wefing\">https://doi.org/10.23763/BrSc21-10wefing</a>.","chicago":"Wefing, Patrick, Florian Conradi, Johannes Rämisch, Peter Neubauer, and Jan Schneider. “Determination of Free Amino Nitrogen in Beer Mash with an Inline NIR Transflectance Probe and Data Evaluation by Machine Learning Algorithms.” <i>Brewing Science </i> 74, no. 9/10 (2021): 107–21. <a href=\"https://doi.org/10.23763/BrSc21-10wefing\">https://doi.org/10.23763/BrSc21-10wefing</a>.","van":"Wefing P, Conradi F, Rämisch J, Neubauer P, Schneider J. Determination of free amino nitrogen in beer mash with an inline NIR transflectance probe and data evaluation by machine learning algorithms. Brewing science . 2021;74(9/10):107–21.","ieee":"P. Wefing, F. Conradi, J. Rämisch, P. Neubauer, and J. Schneider, “Determination of free amino nitrogen in beer mash with an inline NIR transflectance probe and data evaluation by machine learning algorithms,” <i>Brewing science </i>, vol. 74, no. 9/10, pp. 107–121, 2021, doi: <a href=\"https://doi.org/10.23763/BrSc21-10wefing\">https://doi.org/10.23763/BrSc21-10wefing</a>.","din1505-2-1":"<span style=\"font-variant:small-caps;\">Wefing, Patrick</span> ; <span style=\"font-variant:small-caps;\">Conradi, Florian</span> ; <span style=\"font-variant:small-caps;\">Rämisch, Johannes</span> ; <span style=\"font-variant:small-caps;\">Neubauer, Peter</span> ; <span style=\"font-variant:small-caps;\">Schneider, Jan</span>: Determination of free amino nitrogen in beer mash with an inline NIR transflectance probe and data evaluation by machine learning algorithms. In: <i>Brewing science </i> Bd. 74, Carl (2021), Nr. 9/10, S. 107–121","apa":"Wefing, P., Conradi, F., Rämisch, J., Neubauer, P., &#38; Schneider, J. (2021). Determination of free amino nitrogen in beer mash with an inline NIR transflectance probe and data evaluation by machine learning algorithms. <i>Brewing Science </i>, <i>74</i>(9/10), 107–121. <a href=\"https://doi.org/10.23763/BrSc21-10wefing\">https://doi.org/10.23763/BrSc21-10wefing</a>"},"oa":"1","user_id":"83781","date_created":"2021-11-02T10:06:04Z","department":[{"_id":"DEP1308"},{"_id":"DEP4028"}],"main_file_link":[{"open_access":"1","url":"https://www.researchgate.net/publication/355735532_Determination_of_free_amino_nitrogen_in_beer_mash_with_an_inline_NIR_transflectance_probe_and_data_evaluation_by_machine_learning_algorithms"}],"date_updated":"2025-01-30T15:43:53Z","doi":"https://doi.org/10.23763/BrSc21-10wefing"},{"author":[{"first_name":"Patrick","full_name":"Wefing, Patrick","last_name":"Wefing","id":"68976"},{"full_name":"Conradi, Florian","first_name":"Florian","last_name":"Conradi","id":"68967"},{"id":"81622","last_name":"Trilling-Haasler","orcid":"0000-0002-3685-6383","full_name":"Trilling-Haasler, Marc","first_name":"Marc"},{"last_name":"Neubauer","first_name":"Peter","full_name":"Neubauer, Peter"},{"id":"13209","last_name":"Schneider","orcid":"0000-0001-6401-8873","first_name":"Jan","full_name":"Schneider, Jan"}],"abstract":[{"text":"Continuous mashing provides advantages compared to conventional batch-wise mashing in terms of space time yield. The majority of fermentable sugars are generated during the so-called “β-amylase rest” (62–64 ◦C). These low molecular sugars are fermented later in the brewing process by yeasts and therefore determine the beer attenuation degree. Biological malt variations complicate the application of a continuous system in industrial scale particularly concerning targeted quality parameters. The aim is the prediction of sugar formation from process parameters for a real time control system. Therefore, a semi-empirical model for sugar formation in a continuous stirred tank reactor (CSTR) system was developed under incorporation of the residence time distri- bution (RTD). The here presented model, which focuses on the “β-amylase rest”, is able to predict fermentable sugar concentrations in the continuous “β-amylase rest” with sufficient accuracy, in contrast to models that only use the flow rate and the reactor volume to determine the reaction time. However, the precision and trueness depend on the quality of the empirical data acquired previously in laboratory experiments for the selected temperature and raw material quality.","lang":"eng"}],"publication_status":"published","status":"public","publication":"Biochemical Engineering Journal ","title":"Approach for modelling the extract formation in continuous conducted \"beta-amylase rest\" as part of the production of beer mash with targeted sugar content","article_type":"original","volume":164,"intvolume":"       164","quality_controlled":"1","_id":"5419","language":[{"iso":"eng"}],"article_number":"107765","keyword":["Continuous mashing","Residence time distribution","Beer","Enzyme bioreactor","Maltose rest"],"date_updated":"2024-07-03T07:08:55Z","date_created":"2021-04-08T05:59:08Z","department":[{"_id":"DEP4023"},{"_id":"DEP1308"},{"_id":"DEP4018"}],"user_id":"83780","doi":"10.1016/j.bej.2020.107765","year":"2020","citation":{"apa":"Wefing, P., Conradi, F., Trilling-Haasler, M., Neubauer, P., &#38; Schneider, J. (2020). Approach for modelling the extract formation in continuous conducted “beta-amylase rest” as part of the production of beer mash with targeted sugar content. <i>Biochemical Engineering Journal </i>, <i>164</i>, Article 107765. <a href=\"https://doi.org/10.1016/j.bej.2020.107765\">https://doi.org/10.1016/j.bej.2020.107765</a>","din1505-2-1":"<span style=\"font-variant:small-caps;\">Wefing, Patrick</span> ; <span style=\"font-variant:small-caps;\">Conradi, Florian</span> ; <span style=\"font-variant:small-caps;\">Trilling-Haasler, Marc</span> ; <span style=\"font-variant:small-caps;\">Neubauer, Peter</span> ; <span style=\"font-variant:small-caps;\">Schneider, Jan</span>: Approach for modelling the extract formation in continuous conducted „beta-amylase rest“ as part of the production of beer mash with targeted sugar content. In: <i>Biochemical Engineering Journal </i> Bd. 164 (2020)","chicago":"Wefing, Patrick, Florian Conradi, Marc Trilling-Haasler, Peter Neubauer, and Jan Schneider. “Approach for Modelling the Extract Formation in Continuous Conducted ‘Beta-Amylase Rest’ as Part of the Production of Beer Mash with Targeted Sugar Content.” <i>Biochemical Engineering Journal </i> 164 (2020). <a href=\"https://doi.org/10.1016/j.bej.2020.107765\">https://doi.org/10.1016/j.bej.2020.107765</a>.","mla":"Wefing, Patrick, et al. “Approach for Modelling the Extract Formation in Continuous Conducted ‘Beta-Amylase Rest’ as Part of the Production of Beer Mash with Targeted Sugar Content.” <i>Biochemical Engineering Journal </i>, vol. 164, 107765, 2020, <a href=\"https://doi.org/10.1016/j.bej.2020.107765\">https://doi.org/10.1016/j.bej.2020.107765</a>.","van":"Wefing P, Conradi F, Trilling-Haasler M, Neubauer P, Schneider J. Approach for modelling the extract formation in continuous conducted “beta-amylase rest” as part of the production of beer mash with targeted sugar content. Biochemical Engineering Journal . 2020;164.","ieee":"P. Wefing, F. Conradi, M. Trilling-Haasler, P. Neubauer, and J. Schneider, “Approach for modelling the extract formation in continuous conducted ‘beta-amylase rest’ as part of the production of beer mash with targeted sugar content,” <i>Biochemical Engineering Journal </i>, vol. 164, Art. no. 107765, 2020, doi: <a href=\"https://doi.org/10.1016/j.bej.2020.107765\">10.1016/j.bej.2020.107765</a>.","chicago-de":"Wefing, Patrick, Florian Conradi, Marc Trilling-Haasler, Peter Neubauer und Jan Schneider. 2020. Approach for modelling the extract formation in continuous conducted „beta-amylase rest“ as part of the production of beer mash with targeted sugar content. <i>Biochemical Engineering Journal </i> 164. doi:<a href=\"https://doi.org/10.1016/j.bej.2020.107765\">10.1016/j.bej.2020.107765</a>, .","ufg":"<b>Wefing, Patrick u. a.</b>: Approach for modelling the extract formation in continuous conducted „beta-amylase rest“ as part of the production of beer mash with targeted sugar content, in: <i>Biochemical Engineering Journal </i> 164 (2020).","bjps":"<b>Wefing P <i>et al.</i></b> (2020) Approach for Modelling the Extract Formation in Continuous Conducted ‘Beta-Amylase Rest’ as Part of the Production of Beer Mash with Targeted Sugar Content. <i>Biochemical Engineering Journal </i> <b>164</b>.","havard":"P. Wefing, F. Conradi, M. Trilling-Haasler, P. Neubauer, J. Schneider, Approach for modelling the extract formation in continuous conducted “beta-amylase rest” as part of the production of beer mash with targeted sugar content, Biochemical Engineering Journal . 164 (2020).","short":"P. Wefing, F. Conradi, M. Trilling-Haasler, P. Neubauer, J. Schneider, Biochemical Engineering Journal  164 (2020).","ama":"Wefing P, Conradi F, Trilling-Haasler M, Neubauer P, Schneider J. Approach for modelling the extract formation in continuous conducted “beta-amylase rest” as part of the production of beer mash with targeted sugar content. <i>Biochemical Engineering Journal </i>. 2020;164. doi:<a href=\"https://doi.org/10.1016/j.bej.2020.107765\">10.1016/j.bej.2020.107765</a>"},"type":"journal_article"}]