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Monitoring PV in corn and soybean oils by NIR spectroscopy

Abstract

NIR spectroscopy was used successfully in our laboratory to monitor oxidation levels in vegetable oils. Calibration models were developed to measure PV in both soy and corn oils, using partial least squares (PLS) regression and forward stepwise multiple linear regression, from NIR transmission spectra. PV can be measured successfully in both corn and soy oils using a single calibration. The most successful calibration was based on PLS regression of first derivative spectra. When this calibration was applied to validation sample sets containing equal numbers of corn and soy oil samples, with PV ranging from 0 to 20 meq/kg, a correlation coefficient of 0.99 between titration and NIR values was obtained, with a standard error of prediction equal to 0.72 meq/kg. For both types of oil, changes occurred in the 2068 nm region of the NIR spectra as oxidation levels increased. These changes appear to be associated with the formation of hydroperoxides during oxidation of the oils.

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Correspondence to Randy L. Wehling.

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Yildiz, G., Wehling, R.L. & Cuppett, S.L. Monitoring PV in corn and soybean oils by NIR spectroscopy. J Amer Oil Chem Soc 79, 1085–1089 (2002). https://doi.org/10.1007/s11746-002-0608-1

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Key Words

  • Corn oil
  • edible oil
  • forward stepwise multiple linear (FSML) regression
  • lipid oxidation
  • multiple linear regression
  • near-infrared spectroscopy
  • partial least squares (PLS) regression
  • peroxide value
  • soy oil