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<p>As the world’s second-largest producer of palm oil, Malaysia is committed to sustainable practices and a transparent palm oil supply chain. Geographical differentiation of crude palm oil (CPO) is a key factor in ensuring the traceability and sustainability throughout the palm oil logistics network. For industry implementation, simple, rapid, and economic techniques are inevitable. The potential of headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) and Fourier transform near-infrared (FT-NIR) spectroscopy, combined with chemometrics and data fusion, is investigated to differentiate Malaysian CPO from four mills located across the country in Peninsular and East Malaysia. The CPO from all four individual mills were successfully differentiated with accuracies of 88.98% and 92.37% from HS-GC-IMS and FT-NIR spectroscopy data respectively. Excellent distinction was also established for the Peninsula sources and also between the Peninsular and East Malaysian CPO samples. Low-level fusion of the HS-GC-IMS and FT-NIR data enhanced the performance of the models, and the highest classification accuracy was achieved for the Peninsular versus East Malaysia model at 98.31%. Key spectral regions and volatile organic compounds, mainly related to the degree of unsaturation, were linked to the geographical origin of the CPO and contributed to their correct classification rates. Overall, the results suggested that FT-NIR spectroscopy is more robust than HS-GC-IMS for discriminating CPO based on geographical origin, especially in the presence of environmental and seasonal variations, highlighting its prospect for empowering the geographical traceability of palm oil.</p>

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Geographical Traceability of Malaysian Crude Palm Oil by Headspace-Gas Chromatography-Ion Mobility Spectrometry and Fourier Transform Near-Infrared Spectroscopy Combined with Chemometrics and Data Fusion

  • 期刊论文

  • 发表日期：

    2026年3月23日

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  • Noor Idayu Tahir,
  • Alina Mihailova,
  • Syahidah Akmal Muhammad,
  • Evans R. Tawiah,
  • Marivil D. Islam,
  • Simon D. Kelly,
  • Christina Vlachou,
  • Nurul Liyana Rozali,
  • Nor Hayati Muhammad,
  • Ravigadevi Sambanthamurthi,
  • Umi Salamah Ramli,
  • Rajinder Singh,
  • Abrizah Othman

摘要

As the world’s second-largest producer of palm oil, Malaysia is committed to sustainable practices and a transparent palm oil supply chain. Geographical differentiation of crude palm oil (CPO) is a key factor in ensuring the traceability and sustainability throughout the palm oil logistics network. For industry implementation, simple, rapid, and economic techniques are inevitable. The potential of headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) and Fourier transform near-infrared (FT-NIR) spectroscopy, combined with chemometrics and data fusion, is investigated to differentiate Malaysian CPO from four mills located across the country in Peninsular and East Malaysia. The CPO from all four individual mills were successfully differentiated with accuracies of 88.98% and 92.37% from HS-GC-IMS and FT-NIR spectroscopy data respectively. Excellent distinction was also established for the Peninsula sources and also between the Peninsular and East Malaysian CPO samples. Low-level fusion of the HS-GC-IMS and FT-NIR data enhanced the performance of the models, and the highest classification accuracy was achieved for the Peninsular versus East Malaysia model at 98.31%. Key spectral regions and volatile organic compounds, mainly related to the degree of unsaturation, were linked to the geographical origin of the CPO and contributed to their correct classification rates. Overall, the results suggested that FT-NIR spectroscopy is more robust than HS-GC-IMS for discriminating CPO based on geographical origin, especially in the presence of environmental and seasonal variations, highlighting its prospect for empowering the geographical traceability of palm oil.