Prediction of coffee traits by artificial neural networks and laser-assisted rapid evaporative ionization mass spectrometry.

Journal: Food research international (Ottawa, Ont.)
PMID: 40022319

Abstract

BACKGROUND: Coffee is an important commodity in the worldwide economy and smart technologies are important for accurate quality control and consumer-oriented product development. Sensory perception is probably the most important information since it is directly related to product acceptance. However, sensory analysis is imprecise and present large deviation related to subjectivity and relying exclusively on the sensory panel. Thus, practical technologies may be developed to assist in making accurate decisions.

Authors

  • Victor Gustavo Kelis Cardoso
    Institute of Chemistry, University of Campinas, Campinas, Brazil; National Institute of Science and Technology in Bioanalytics (INCTBio), Campinas, Brazil.
  • Julia Balog
    Waters Research Center, Budapest, Hungary.
  • Viktor Zsellér
    Waters Research Center, Budapest, Hungary.
  • Tamas Karancsi
    Waters Research Center, Budapest, Hungary.
  • Guilherme Post Sabin
    Institute of Chemistry, University of Campinas, Campinas, Brazil; OpenScience, Campinas, Brazil.
  • Leandro Wang Hantao
    Institute of Chemistry, University of Campinas, Campinas, Brazil; National Institute of Science and Technology in Bioanalytics (INCTBio), Campinas, Brazil. Electronic address: wang@unicamp.br.

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