Use of Differential Scanning Calorimetry to Detect Canola Oil (Brassica napus L.) Adulterated with Lard Stearin

  • Nazrim Marikkar Jalaldeen Mohammed
    Halal Products Research Institute, Universiti Putra Malaysia Department of Biochemistry, Universiti Putra Malaysia
  • Rana Sohel
    Faculty of Science/Institute for Mathematical Research, Universiti Putra Malaysia

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  • Use of Differential Scanning Calorimetry to Detect Canola Oil (<i>Brassica napus</i> L.) Adulterated with Lard Stearin

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A study was conducted to detect and quantify lard stearin (LS) content in canola oil (CaO) using differential scanning calorimetry (DSC). Authentic samples of CaO were obtained from a reliable supplier and the adulterant LS were obtained through a fractional crystallization procedure as reported previously. Pure CaO samples spiked with LS in levels ranging from 5 to 15% (w/w) were analyzed using DSC to obtain their cooling and heating profiles. The results showed that samples contaminated with LS at 5% (w/w) level can be detected using characteristic contaminant peaks appearing in the higher temperature regions (0 to 70°C) of the cooling and heating curves. Pearson correlation analysis of LS content against individual DSC parameters of the adulterant peak namely peak temperature, peak area, peak onset temperature indicated that there were strong correlations between these with the LS content of the CaO admixtures. When these three parameters were engaged as variables in the execution of the stepwise regression procedure, predictive models for determination of LS content in CaO were obtained. The predictive models obtained with single DSC parameter had relatively lower coefficient of determination (R2 value) and higher standard error than the models obtained using two DSC parameters in combination. This study concluded that the predictive models obtained with peak area and peak onset temperature of the adulteration peak would be more accurate for prediction of LS content in CaO based on the highest coefficient of determination (R2 value) and smallest standard error.

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