Triyasmono Liling, Schollmayer Curd, Holzgrabe Ulrike
Institute for Pharmacy and Food Chemistry, University of Würzburg, Würzburg, Germany.
Department of Pharmacy, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat University, Banjar Baru, Indonesia.
Phytochem Anal. 2023 Oct;34(7):788-799. doi: 10.1002/pca.3196. Epub 2022 Dec 12.
Red fruit oil (RFO) is a natural product extracted from Pandanus conoideus Lam. fruit, a native plant from Papua, Indonesia. Recent studies indicate that RFO is popularly consumed as herbal medicine. Therefore, the quality of RFO must be assured.
This study aimed to develop a chemometric analysis applied to H nuclear magnetic resonance (NMR) and Fourier transform infrared (FTIR) data for important quality parameter distinction of red fruit oil (RFO), especially regarding the degree of unsaturation and the amount of free fatty acids (FFA).
Forty samples consisting of one crude RFO, thirty-three commercial RFOs, and three oils as blends, including olive oil, virgin coconut oil, and black seed oil, were analysed by H NMR and FTIR spectroscopy. After appropriate preprocessing of the spectra, principal component analysis (PCA) and partial least squares regression (PLSR) were used for model development.
The essential signals for modelling the degree of unsaturation are the signal at δ = 5.37-5.27 ppm ( H NMR) and the band at 3000-3020 cm (FTIR). The FFA profile represents the signal at δ = 2.37-2.20 ppm ( H NMR) and the band at 1680-1780 cm (FTIR). PCA allows the visualisation grouping on both methods with > 98% total principal component (PC) for the degree of unsaturation and > 88% total PC for FFA values. In addition, the PLSR model provides an acceptable coefficient of determination (R ) and errors in calibration, prediction, and cross-validation.
Chemometric analysis applied to H NMR and FTIR spectra of RFO successfully grouped and predicted product quality based on the degree of unsaturation and FFA value categories.
红果油（RFO）是从露兜树属圆锥叶露兜树的果实中提取的天然产物，该植物原产于印度尼西亚巴布亚。最近的研究表明，红果油作为草药被广泛食用。因此，必须确保红果油的质量。
本研究旨在开发一种化学计量学分析方法，应用于氢核磁共振（NMR）和傅里叶变换红外（FTIR）数据，以区分红果油（RFO）的重要质量参数，特别是不饱和程度和游离脂肪酸（FFA）的含量。
通过氢核磁共振和傅里叶变换红外光谱对40个样品进行分析，其中包括1个粗制红果油、33个市售红果油以及3种混合油，包括橄榄油、初榨椰子油和黑种草籽油。在对光谱进行适当预处理后，使用主成分分析（PCA）和偏最小二乘回归（PLSR）进行模型开发。
用于模拟不饱和程度的关键信号是δ = 5.37 - 5.27 ppm处的信号（氢核磁共振）和3000 - 3020 cm处的谱带（傅里叶变换红外）。游离脂肪酸谱代表δ = 2.37 - 2.20 ppm处的信号（氢核磁共振）和1680 - 1780 cm处的谱带（傅里叶变换红外）。主成分分析允许在两种方法上进行可视化分组，不饱和程度的总主成分（PC）> 98%，游离脂肪酸值的总主成分> 88%。此外，偏最小二乘回归模型提供了可接受的决定系数（R）以及校准、预测和交叉验证中的误差。
应用于红果油氢核磁共振和傅里叶变换红外光谱的化学计量学分析成功地根据不饱和程度和游离脂肪酸值类别对产品质量进行了分组和预测。
