Prediction of total protein and intact casein in cheddar cheese using a low-cost handheld short-wave near-infrared spectrometer

Yizhou B. Ma, Karthik S. Babu, Jayendra K. Amamcharla

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

This study aims to develop and validate rapid quantification technique for intact casein (IC) and total protein in cheddar cheese using SCiO™, a low-cost short-wave near-infrared spectrometer. SCiO™ was used to collect the spectral scans (from 740 nm to 1070 nm) of cheddar cheese (N = 49). Reference values of IC and total protein were quantified by the Kjeldahl method. The spectra acquired from the SCiO™ were preprocessed using standard normal variate and second derivation, and subsequently partial least squares regression (PLSR) based models were developed (ncal = 35). In addition, wavelength selection methods (backward elimination, multiple linear regression-forward selection, and inteval PLSR) were applied to further improve the model performances. Based on external validation (nval = 14), IC prediction resulted in a range of root mean square error of prediction (RMSEP) between 0.91 and 1.58 g/100 g cheese, and residual prediction deviation (RPD) between 1.2 and 2.1. For total protein prediction, the RMSEP ranged from 0.62 to 0.88 g/100 g cheese, while the RPD was found between 1.4 and 2.0. The prediction results indicated that SCiO™ can provide useful quantification tool for a rapid prediction of IC and total protein in cheddar cheese.

Original languageEnglish (US)
Pages (from-to)319-326
Number of pages8
JournalLWT
Volume109
DOIs
StatePublished - Jul 2019
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2019 Elsevier Ltd

Keywords

  • Chemometrics
  • Feature selection
  • Rapid method

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