
Routine Arsenic Quantification in Rice and Rice-Based Foods
Researchers at the University of Massachusetts Amherst demonstrated that X-ray fluorescence spectroscopy combined with chemometric modeling can provide a rapid, minimally destructive, and accurate alternative to traditional methods for routine arsenic quantification in rice and rice-based foods.
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In a recent study, researchers at the University of Massachusetts Amherst have reported a new approach for quantifying arsenic in rice that could simplify routine testing in food safety laboratories. This study, which was published in the journal Food Analytical Methods, outlined a new method using X-ray fluorescence (XRF) spectroscopy combined with chemometric modeling that was able to deliver accurate arsenic measurements without the time and cost associated with conventional methods.1
Arsenic contamination in rice remains a global food safety concern because of the crop’s tendency to accumulate the toxic element from soil and irrigation water.1,2 This is true for both brown and white rice, although arsenic concentration is often greater in brown rice.2
“Rice plants tend to be very porous,” registered dietician Beth Czerwony, RD, LD, said.3 “So, arsenic that’s in the soil or water where rice is being grown tends to be absorbed — and it eventually ends up in the grains of rice.”
Currently, the way that analysts detect for arsenic in rice products is typically based on wet digestion followed by atomic spectrometry.1 Although this method is reliable, there are several drawbacks to using it, including its destructive nature, its operation cost, and how labor-intensive it is.1 These limitations can restrict testing frequency, particularly in high-throughput or resource-limited settings.
To address this gap, the researchers developed a minimally destructive workflow using energy-dispersive X-ray fluorescence (XRF). In the study, milled rice samples were spiked with arsenic across a concentration range relevant to regulatory and monitoring needs, pelletized, and analyzed directly. The resulting XRF spectra were processed using partial least squares regression to build a predictive model for arsenic concentration.
According to the authors, the model demonstrated strong analytical performance, with a coefficient of determination of 0.99 and a root mean square error of calibration of 14.3 µg kg⁻¹.1 The method achieved a limit of detection of 27.76 µg kg⁻¹ and a limit of quantification of 92.52 µg kg⁻¹, indicating sensitivity suitable for routine screening.1 Validation using a certified reference material produced a prediction error of 8.96%.1
Importantly for practitioners, the team compared results from rice and rice-based food products analyzed by the XRF-chemometric approach with those obtained using traditional methods. The close agreement between techniques suggests the new method can provide reliable results while significantly reducing sample preparation time and analytical complexity.1
Not all rice is created equal when it comes to arsenic levels. For example, jasmine rice from Thailand and basmati rice from India tend to have lower arsenic levels.3 However, by enabling rapid, non-destructive analysis with minimal consumables, the approach could support more frequent testing and broader surveillance of arsenic in rice, ensuring all rice varieties are safe for consumption.
References
- Carroll, M.; Gao, Z.; He, L. Development of a Rapid, Minimally Destructive, and Accurate Method to Quantify Arsenic in Rice and Rice-Based Foods Utilizing X-ray Fluorescence Spectroscopy and Chemometrics. Food Anal. Methods 2026, 19, 72. DOI:
10.1007/s12161-025-02979-5 - Su, L. J.; Chiang, T.-C.; O’Connor, S. N. Arsenic in Brown Rice: Do the Benefits Outweigh the Risks? Front Nutr. 2023, 10, 1209574. DOI:
10.3389/fnut.2023.1209574 - Cleveland Clinic, Should You Be Worried About Arsenic in Rice? Cleveland Clinic. Available at:
https://health.clevelandclinic.org/arsenic-in-rice (accessed 2026-02-04).
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