Mid infrared spectroscopy and milk quality traits: A data analysis competition at the 'International Workshop on Spectroscopy and Chemometrics 2021'
| Autor: | Marco Stefanucci, Uche Mbaka, Antonio Bevilacqua, Katarina Domijan, Alessandro Casa, Thach Le Nguyen, Georgiana Ifrim, Giovanna Ranzato, Elena Hayes, Bhaskar Dhariyal, Maria Frizzarin, Federico Ferraccioli, Ashish K. Singh, Agnieszka Konkolewska |
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| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Computer science media_common.quotation_subject Fourier transform mid-infrared spectroscopy milk quality Quantitative Biology - Quantitative Methods Statistics - Applications Mid infrared spectroscopy Analytical Chemistry Competition (economics) Chemometrics Applications (stat.AP) Quality (business) Spectroscopy Quantitative Methods (q-bio.QM) media_common Process Chemistry and Technology chemometrics Data science Computer Science Applications machine learning Research centre FOS: Biological sciences Software |
| Zdroj: | Chemometrics and Intelligent Laboratory Systems |
| ISSN: | 0169-7439 |
| DOI: | 10.1016/j.chemolab.2021.104442 |
| Popis: | A chemometric data analysis challenge has been arranged during the first edition of the "International Workshop on Spectroscopy and Chemometrics", organized by the Vistamilk SFI Research Centre and held online in April 2021. The aim of the competition was to build a calibration model in order to predict milk quality traits exploiting the information contained in mid-infrared spectra only. Three different traits have been provided, presenting heterogeneous degrees of prediction complexity thus possibly requiring trait-specific modelling choices. In this paper the different approaches adopted by the participants are outlined and the insights obtained from the analyses are critically discussed. Comment: 17 pages, 6 figures, 6 tables |
| Databáze: | OpenAIRE |
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