title: Development of a fingerprinting approach to determine the geographical origin of vegetable oils: A case study for rapeseed oil from Hesse (Germany)
Creators: name: Xia, Lili
Publisher: name: UNSPECIFIED
Year: 2024

description: Vegetable oils play crucial roles as both a food source and a renewable energy resource. Determining their geographical origin is essential for ensuring food safety, health, and energy sustainability. While stable isotopic analysis of light elements combined with chemometric techniques has been effective in tracing the geographical origin of vegetable oils, the potential of stable hydrogen isotopic composition (δ2H) of fatty acids (FAs) as analytical markers and the associated fingerprinting approach remains underexplored, particularly for rapeseed oil, which is the third-largest vegetable oil globally. 
This dissertation aimed to develop a fingerprinting approach for determining the geographical origin of vegetable oils, using rapeseed oil as a case study. The research objectives are threefold: (1) to optimize the sample preparation method for efficient and high-throughput measurement of δ2H of FAs in rapeseed; (2) to analyze the spatial distribution of δ2H of FAs in rapeseeds from different regions and assess its correlation with climatic and soil factors; (3) to establish classification models using δ2H of FAs and elemental composition of rapeseed to differentiate geographical origins, including distinguishing between Hesse and other regions, as well as various regions within Hesse.

A rapid and straightforward sample preparation method by Garcés &amp; Mancha (1993) enables the direct conversion of rapeseed into fatty acid methyl esters (FAMEs). The addition of 2,2-dimethoxypropane (DMP) for effective conversion was evaluated through control experiments to assess its impact on the isotopic composition of individual FAMEs using gas chromatography-pyrolysis-isotope ratio mass spectrometry (GC-Py-IRMS).
For the second and third objectives, a total of 121 rapeseed and soil samples were collected from Hesse, Germany, during 2017-2020, and 28 rapeseed samples from Jianhu County, Jiangsu Province, China, in 2019. The δ2H of major FAs (C18:1, C18:2, C18:3, C16:0) in rapeseed were determined by GC-Py-IRMS, while the elemental composition of rapeseed was analyzed using inductively coupled plasma optical emission spectrometry (ICP-OES) and inductively coupled plasma mass spectrometry (ICP-MS). Climate data and soil parameters were sourced from publicly available databases or measured using standardized laboratory methods. Chemometric techniques were employed for data analysis, including stepwise linear regression analysis, principal component analysis (PCA), and orthogonal partial least squares discriminant analysis (OPLS-DA). 

Control experiments confirmed that DMP had no significant influence on the accuracy of δ2H values of FAs. The precision of hydrogen compound-specific stable isotope analysis (H-CSIA) ranged from ± 0.3 mUr to ± 3 mUr, resulting in satisfactory results. This method facilitated the analysis of approximately 150 rapeseed samples, enhancing experimental efficiency.
The spatial distribution of δ2H values of FAs in Hesse exceeded the instrumental precision and exhibited a spatial pattern similar to the δ2H values of precipitation on a regional scale. Correlation analysis revealed significant associations between δ2H of FAs and location-specific factors such as air temperatures in February and May, precipitation amounts in April, and silt content. Climatic conditions exerted a more pronounced influence on δ2H values of FAs compared to soil properties, indicating the potential of δ2H of FAs as markers for geographical traceability.
Classification models using OPLS-DA were developed to differentiate rapeseed from Hesse and Jianhu. The models achieved notable accuracy, with 82.8% of Hesse samples correctly identified and 93.1% of Jianhu samples accurately classified. δ²H of FAs and elemental data significantly contributed to the classification.
For differentiating rapeseed within Hesse, the state was divided into eight climatic zones based on three vital climatic conditions—monthly average temperature in February and May, and monthly average precipitation in April—that most influence the δ2H of FAs, as identified through correlation analysis. Effective discrimination was achieved between two zones by combining δ2H values of FAs and elemental data using the OPLS-DA method: one zone exhibited low May temperatures and low April precipitation, while the other had high May temperatures and high April precipitation. The classification model was validated, with a Q2 value of 0.8, indicating good predictive ability. Both δ2H of FAs and elemental data contributed significantly to the classification. Due to the limited sample size in these zones (n=8 and n=7, respectively), further verification with external datasets is recommended.

In conclusion, integrating stable hydrogen isotopic composition, elemental data, and OPLS-DA provides a robust approach for determining the origin of rapeseed, both over large distances (e.g., between Germany and China) and within closely situated regions (e.g., within Hesse, Germany), particularly where distinct climatic conditions exist. This approach is more accurate and predictive than using either isotopic or elemental data alone. By combining established soil-related markers with the new analytical markers, such as δ2H of FAs, this fingerprinting approach could be adapted for other vegetable oils, such as palm oil. This fingerprinting approach has the potential to be a practical tool for monitoring the origin of agricultural commodities, in line with EU sustainability directives and regulations, such as the Regulation on Deforestation-Free Products.