---
res:
  bibo_abstract:
  - "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.@eng"
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Patrick
      foaf_name: Wefing, Patrick
      foaf_surname: Wefing
      foaf_workInfoHomepage: http://www.librecat.org/personId=68976
  - foaf_Person:
      foaf_givenName: Florian
      foaf_name: Conradi, Florian
      foaf_surname: Conradi
      foaf_workInfoHomepage: http://www.librecat.org/personId=68967
  - foaf_Person:
      foaf_givenName: Johannes
      foaf_name: Rämisch, Johannes
      foaf_surname: Rämisch
  - foaf_Person:
      foaf_givenName: Peter
      foaf_name: Neubauer, Peter
      foaf_surname: Neubauer
  - foaf_Person:
      foaf_givenName: Jan
      foaf_name: Schneider, Jan
      foaf_surname: Schneider
      foaf_workInfoHomepage: http://www.librecat.org/personId=13209
    orcid: 0000-0001-6401-8873
  bibo_doi: https://doi.org/10.23763/BrSc21-10wefing
  bibo_issue: 9/10
  bibo_volume: 74
  dct_date: 2021^xs_gYear
  dct_isPartOf:
  - http://id.crossref.org/issn/1866-5195
  - http://id.crossref.org/issn/0723-1520
  dct_language: eng
  dct_publisher: Carl@
  dct_subject:
  - mashing
  - NIR
  - machine learning
  - FAN
  dct_title: Determination of free amino nitrogen in beer mash with an inline NIR
    transflectance probe and data evaluation by machine learning algorithms@
...