Journal of Food Science and Technology

, Volume 52, Issue 3, pp 1649–1655 | Cite as

Determination of fat, protein and moisture in ricotta cheese by near infrared spectroscopy and multivariate calibration

  • Elisângela Serenato Madalozzo
  • Elenise Sauer
  • Noemi Nagata
Original Article


Near-infrared reflectance spectroscopy (NIRS) with partial least squares regression (PLSR) was used to determine levels of fat, protein and moisture in ricotta cheese without complex sample preparation. Spectra of 19 conventional and low-fat ricotta samples from different manufacturers were collected in duplicate, with 33 of the 38 spectra used as a calibration set and the remaining 5 spectra used as an external validation set. The best results were obtained by processing the spectral region between 1,100 and 2,500 nm. Multivariate models with six latent variables (LVs) showed good prediction capability for fat and protein determinations, with average relative errors (Er) of 6.37 % and 5.95 %, respectively. For moisture, a more robust model was obtained with 4 LVs, showing better prevision capacity and Er of 1.91 %.


Ricotta cheese Fat Protein Moisture Near infrared PLSR 



This work was supported by the Fundação Araucária–Fundação de Amparo à Pesquisa do Paraná (232/2007-10788).


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Copyright information

© Association of Food Scientists & Technologists (India) 2013

Authors and Affiliations

  • Elisângela Serenato Madalozzo
    • 1
  • Elenise Sauer
    • 2
  • Noemi Nagata
    • 3
  1. 1.Departamento de Engenharia de AlimentosUniversidade Estadual de Ponta GrossaPonta GrossaBrazil
  2. 2.Universidade Tecnológica Federal do ParanáPonta GrossaBrazil
  3. 3.Departamento de QuímicaUniversidade Federal do ParanáCuritibaBrazil

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