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Authors and Affiliation

This study was conducted by Md Sanaul Huda, Preston Wilson, Niloy Chandra Sarker and Ewumbua Monono,
Department of Agricultural and Biosystems Engineering, North Dakota State University, Fargo, ND, USA.

Background: A Complex Oil Requiring Precise Quality Control

Distillers Corn Oil (DCO), a byproduct of bioethanol production, contains high levels of carotenoids and exhibits intense red–yellow coloration. Its refining requires careful control of pigment removal while preserving nutritionally valuable compounds such as β-carotene. Bleaching is a central stage in this process, yet the optimal combination of bleaching clay dosage, temperature and treatment time had not been previously established.

To address this knowledge gap, the research team conducted a systematic optimization study using Response Surface Methodology (RSM) and evaluated 15 different bleaching conditions.

Analytical Challenge: Monitoring Oxidation and Hydrolysis in Real Time

Two quality parameters were essential to assess the effect of bleaching:

Because numerous experimental runs had to be monitored quickly and consistently, the researchers required an analytical solution that ensured:

  • high reproducibility,
  • minimal sample preparation,
  • rapid throughput compatible with iterative experimental design.

Analytical Solution: Using CDR FoodLab® for PV and FFA Determination

The study employed CDR FoodLab® to quantify PV and FFA during all bleaching trials.

Key methodological advantages highlighted in the study include:

  • Prefilled disposable cuvettes, eliminating manual reagent handling.
  • Extremely small sample volumes (2.5–5 μL).
  • Direct addition of oil to the cuvette, without titration or solvent preparation.
  • Rapid enzymatic–photometric determination, ideal for repeated measurements.

PV and FFA values generated with the CDR FoodLab® system were crucial for evaluating oxidative stability and validating optimal processing parameters.

Results: Identifying the Optimal Bleaching Conditions

The RSM model identified an optimal bleaching condition that balances color reduction, β-carotene preservation and oxidative stability:

  • 1.2 % bleaching clay
  • 23.2 minutes
  • 99.1 °C

Under these conditions:

  • PV values remained within the typical range for refined edible oils (5–10 meq O₂/kg).
  • FFA levels remained stable after neutralization.
  • Red and yellow color components were significantly reduced while limiting β-carotene loss.

Across all optimized samples, PV values measured using CDR FoodLab® ranged between 1.7 and 9.4 meq O₂/kg, confirming acceptable oxidative stability.

Summary Table of Analytical Findings

ParameterAnalytical MethodObserved RangeInterpretation
Peroxide Value (PV)CDR FoodLab® photometric cuvettes1.7 – 9.4 meq O₂/kgConfirms effective control of primary oxidation throughout bleaching
Free Fatty Acids (FFA)CDR FoodLab® photometric cuvettes1.6 – 1.7 % (after neutralization)Indicates minimal hydrolytic impact during bleaching
β-Carotene ReductionSpectrophotometry0.2 – 36 %Optimization aimed at preserving nutritional value
Red Color ReductionLovibond colorimetry27 – 88 %Strong dependence on clay dosage and time
Yellow Color ReductionLovibond colorimetry0 – 83 %Complementary removal of yellow pigments

Conclusion: The Role of CDR FoodLab® in Supporting Refining Optimization

In this study conducted by Huda, Wilson, Sarker and Monono, the measurements obtained with CDR FoodLab® provided fast and consistent determinations of PV and FFA, contributing to the monitoring of oxidative and hydrolytic changes during the bleaching trials. These parameters were essential to:

  • validate bleaching efficiency,
  • assess oxidative effects,
  • monitor process variability across 15 experimental conditions.

This case illustrates how practical analytical tools can support data-driven optimization in edible oil refining and offer valuable insights for the characterization of non-traditional oils with high nutritional potential.

Reference

Optimizing Bleaching Process Parameters of Distillers Corn Oil for edible applications using a response surface methodology
Author links open overlay panel: Md Sanaul Huda, Preston Wilson, Niloy Chandra Sarker, Ewumbua Monono
Department of Agricultural and Biosystems Engineering, North Dakota State University, Fargo, ND, USA
Scince Direct - www.sciencedirect.com - Received 8 August 2024, Revised 31 October 2024, Accepted 2 November 2024, Available online 3 November 2024, Version of Record 9 November 2024.

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