Stradling Joe, Lima Cassio, Grosman Rudi, Barsukov Igor, Xu Yun, Teye Ernest, Elliott Chris, Muhamadali Howbeer, Goodacre Royston
Centre for Metabolomics Research, Department of Biochemistry, Cell and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.
NMR Facility, Department of Biochemistry, Cell and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.
NPJ Sci Food. 2025 Jun 5;9(1):95. doi: 10.1038/s41538-025-00462-3.
Determining the geographic origin of palm oil in West Africa is vital for economic, environmental, and health reasons. It enhances traceability, protects local farmers, supports conservation by monitoring deforestation, and reduces food fraud, ensuring quality and regulatory compliance. Portable Raman spectroscopy offers a rapid method to identify the origin of palm oils from West Africa. Using principal component analysis (PCA), distinct clusters in scores plots were observed which reflected the geographic origin of the palm oils, with loadings from the first principal component (PC-1) highlighting β-carotene as a major source of variation among the samples. To quantify β-carotene content, a partial least squares regression (PLS-R) model was developed in coconut oil as the base oil as it is known to be β-carotene free. Once calibrated, PLS-R was used to rank the palm oil from West Africa based on their β-carotene levels. The resulting models in coconut oil demonstrated strong linearity and predictive performance, with R² and Q² values of 0.9848 and 0.9552, respectively, alongside low root mean square errors of cross-validation (0.1282 mM) and prediction (0.0747 mM); moreover, this model allows the palm oils to be ranked based on β-carotene content which was entirely reflective of the oils position in PC-1 from PCA. These findings underscore the potential of Raman spectroscopy as an effective tool for authenticating the geographic origin of palm oil from West Africa.
确定西非棕榈油的地理来源对于经济、环境和健康方面都至关重要。它提高了可追溯性，保护了当地农民，通过监测森林砍伐来支持环境保护，并减少了食品欺诈行为，确保了质量和法规合规性。便携式拉曼光谱法提供了一种快速识别西非棕榈油来源的方法。使用主成分分析（PCA），在得分图中观察到了不同的聚类，这些聚类反映了棕榈油的地理来源，第一主成分（PC-1）的载荷突出了β-胡萝卜素是样品间变异的主要来源。为了量化β-胡萝卜素含量，以已知不含β-胡萝卜素的椰子油为基础油建立了偏最小二乘回归（PLS-R）模型。校准后，PLS-R用于根据β-胡萝卜素水平对西非棕榈油进行排名。在椰子油中得到的模型显示出很强的线性和预测性能，R²和Q²值分别为0.9848和0.9552，同时交叉验证（0.1282 mM）和预测（0.0747 mM）的均方根误差较低；此外，该模型允许根据β-胡萝卜素含量对棕榈油进行排名，这完全反映了油在PCA中PC-1的位置。这些发现强调了拉曼光谱作为鉴定西非棕榈油地理来源的有效工具的潜力。
