Recently, the Cereal Processing and Quality Control Innovation Team at the Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences (CAAS), has uncovered how the stable hydrogen and oxygen isotopic composition of cooking water can significantly affect the isotopic fingerprints of wheat noodles with varying gluten-to-starch formulations after boiling. The findings were published in Current Research in Food Science (JCR Q1, IF=6.2). The paper’s first author is Jingjie Yang, a joint PhD student (class of 2020) between CAAS and Wageningen University & Research, with Professor Boli Guo and Professor Saskia M. Van Ruth serving as co-corresponding authors. This study was funded by the National Natural Science Foundation of China (Grant No. 31972159) and the China Scholarship Council.

With the increasing globalization of the wheat trade, tracing the geographical origin of wheat and its processed products has become a growing concern for regulators and consumers. Stable isotope fingerprinting, especially analysis of hydrogen (δ²H) and oxygen (δ¹O) isotopes, has emerged as a powerful tool for determining the origin of wheat raw materials. However, high-temperature boiling, a common processing step in wheat-based food production, introduces complex variables that can alter isotopic signatures, particularly for hydrogen and oxygen, thus challenging the application of stable isotope techniques in traceability.

In this study, the researchers applied isotope ratio mass spectrometry (IRMS) to analyse eight formulations of wheat noodles with varying gluten-to-starch ratios. The noodles were boiled in six types of water with significantly different hydrogen and oxygen isotopic abundances. They systematically evaluated the shifts in δ²H and δ¹O values in the noodles after boiling and developed a hydrogen isotope exchange factor model (f(H)ₑₓ). The results demonstrated that the δ²H values in the noodles were strongly influenced by the isotopic composition of the cooking water, while δ¹O values remained relatively stable during boiling. Moreover, noodles with higher starch content exhibited greater δ²H shifts compared to those with higher gluten content. The established linear regression models successfully predicted δ²H variations across formulations and cooking water conditions, with R² values reaching up to 0.94.

This research provides the first quantification of hydrogen isotope exchange behavior during the processing of cereal-based products and confirms the systematic impact of cooking water as an “exogenous water source” on food isotope fingerprints. These findings offer crucial theoretical support for advancing stable isotope techniques in the authenticity verification and geographical traceability of highly processed food products.

Link to the full study: https://doi.org/10.1016/j.crfs.2025.101024

Experimental Design and Workflow Diagram