Key Points
- A study published in Food Control introduced a faster, environmentally friendly method for accurately measuring protein content in river snail rice noodles by combining NIR and FT-IR spectroscopy with partial least squares regression (PLSR).
- The NIR-based model achieved exceptionally high predictive accuracy (r² = 0.99 for training, 0.986 for validation), outperforming FT-IR, and identified key spectral regions linked to protein content.
- Compared to the traditional Kjeldahl method, this approach requires no chemicals, less time, and minimal sample prep, offering practical benefits for real-time, on-site protein analysis in food production.
A recent study explored a new method that can measure protein content in rice noodles more accurately and efficiently. This study, published in the journal Food Control, tested out a novel method using near-infrared (NIR) and Fourier transform infrared (FT-IR) spectroscopy (1). When combined with partial least squares regression (PLSR), the method proved to be an effective evaluator of river snail rice noodles, important information for food manufacturers as they look to refine quality control processes.
What are river snail rice noodles?
River snail rice noodles, also known as luosifen, are a popular delicacy in the Guangxi Zhang Autonomous Region in China (2). The river snail meat present in these noodles gives it an umami taste that is desirable to consumers (2). Integral to river snail rice noodles is its protein content. As a result, it is important that quality control methods for food manufacturers are able to accurately assess protein content and ensure the best quality river snail rice noodles are sent to market.
What are traditional methods used to analyze protein content and why are they insufficient?
For protein quantification in food products, a popular method food manufacturers use is the Kjeldahl method, an analytical chemistry technique used to determine the nitrogen content in a food product (3). However, the problem with this method is that, while it is accurate, it requires a lot of time and resources. As a result, researchers have been exploring more effective methods to analyze protein content.
In this study, the research team combined NIR and FT-IR spectroscopy with PLSR to determine protein levels in rice noodles. The research team analyzed a wide range of commercial rice noodle samples used in luosifen products. The protein content among the samples varied significantly, ranging from 1.84 to 7.85 grams per 100 grams (1). These differences were largely attributed to varying rice-to-starch ratios in the manufacturing process, which is an issue that can greatly influence both the sensory and nutritional properties of the final product (1).
What did the spectral analysis show?
Using spectral analysis, the team identified specific regions in the NIR spectrum, particularly around 1500 nm and 2500 nm, as being highly responsive to changes in protein levels (1). In the FT-IR spectrum, the amide I band (1681–1695 cm⁻¹) emerged as a critical area for model accuracy (1). These findings provided the foundation for constructing robust calibration and validation models using PLS regression.
The results demonstrated how a combined NIR–FT-IR approach, with assistance from artificial intelligence (AI), can accurately analyze protein content in rice noodles. The researchers found that the NIR-based PLS model achieved a coefficient of determination (r²) of 0.99 for the training set and 0.986 for the validation set, which indicates great predictive accuracy (1). The FT-IR-based model also performed well, with r² values of 0.94 (training) and 0.897 (validation) (1). However, the researchers concluded based on the results that the NIR approach was better.
What are several advantages of the proposed method?
There were several advantages to this proposed method. For one, using spectroscopy was more environmentally friendly and quicker than the traditional Kjeldahl technique (1). Second, the dual spectroscopy method did not require extensive sample preparation or chemical reagents (1). Additionally, because NIR and FT-IR instruments are becoming more portable, it makes them suitable for use on factory floors or even in retail environments (1).
There are several key practical implications from the results of this study. For one, the ability to rapidly assess protein content during or after the production process allows manufacturers to fine-tune their formulations and meet quality benchmarks with minimal delays (1). This is important because it allows manufacturers to ensure regulatory compliance more quickly, which in turn increases consumer confidence (1).
By leveraging NIR and FT-IR spectroscopy alongside advanced chemometric analysis, the team has presented a powerful new tool to support the ongoing growth and standardization of one of China’s most popular food products.
References
- Zhang, J.; Cheng, Y.; Tang, N. Rapid Analysis of Protein Content in Rice Noodles Using NIR and FT-IR Spectroscopy for Quality Control of River Snail Rice Noodle Products. Food Cont. 2025, 168, 110906. DOI: 10.1016/j.foodcont.2024.110906
- Gao, X.; Yu, M.; Han, X.; et al. Characterization of Odor-active Compounds in Liuzhou River Snail Rice Noodles Soup by Sensory-directed Flavor Analysis. J. Food Comp. Anal. 2024, 131, 106276. DOI: 10.1016/j.jfca.2024.106276
- MSE Supplies, Nitrogen Analysis: Kjeldahl Method. MSE Supplies. Available at: https://www.msesupplies.com/blogs/news/nitrogen-analysis-kjeldahl-method#:~:text=The%20method%20of%20analysis%20involves,to%20prevail%20in%20the%20method. (accessed 2025-07-21).
