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Researchers at Tianjin University of Technology develop a rapid, in situ technique for identifying adulteration in starch sausages using laser-induced breakdown spectroscopy.
Recently, a team of researchers from China’s Tianjin University of Technology created a new method that can rapidly and accurately detect the improper addition of chicken bone paste in starch sausages. This study is part of an ongoing push by researchers to develop new rapid, in situ tools that are capable of ensuring food safety and regulatory compliance. The study, led by Li Shen of Tianjin University of Technology and recently published in the journal Sensors (1), highlights how laser-induced breakdown spectroscopy (LIBS) can be used to identify trace elemental differences between authentic sausage products and those adulterated with bone material.
Chinese Sausage Saucisson in Hong Kong | Image Credit: © wingwing.foodfood - stock.adobe.com

Although chicken bone taste is routinely used in industries such as biomaterials and enzymatic hydrolysis, it is illegal to use it as an additive in food products (1). Therefore, there are serious legal concerns with the usage of chicken bone paste as a food additive. Additionally, despite its efficiency, using chicken bone paste as a food additive has raised significant safety and ethical concerns (1,2).
In starch sausages, a low-cost processed meat substitute, manufacturers may add chicken bone paste to enhance texture or calcium content. However, the presence of bone fragments can pose physical hazards, such as esophageal laceration, as well as trigger religious and cultural objections to consuming such adulterated products (2).
In their study, the research team sought to address concerns of chicken bone paste critics by developing a method that could differentiate between pure starch sausage and starch sausage adulterated with chicken bone paste. To do so, they used LIBS, a technique that uses high-energy laser pulses to ablate a sample’s surface and analyze the resulting plasma emission for its elemental composition (1). The team examined pure starch sausage, chicken bone paste, and mixtures of both at varying ratios. The spectral data revealed clear distinctions in the levels of key elements, including calcium (Ca), barium (Ba), and strontium (Sr), between legitimate sausage samples and those containing bone paste (1).
Apart from using LIBS, the research team made several data processing improvements. By normalizing the spectral data with reference lines, analyzing signals from the second laser pulse at the same position, and applying electron temperature corrections, they achieved significantly higher correlation coefficients (R² values) for key spectral lines (1). For instance, the R² for Ca I increased from 0.302 to 0.972, Ba II from 0.694 to 0.952, and Sr II from 0.691 to 0.982, which shows how their method improved the precision of elemental quantification (1).
Beyond quantitative analysis, the study used advanced multivariate statistical techniques to classify and visualize sample differences. Principal component analysis (PCA) successfully distinguished between starch sausage, chicken bone paste, and their mixtures (1). The t-distributed stochastic neighbor embedding (t-SNE) algorithm provided even clearer separation, highlighting the potential of combining LIBS with machine learning tools for robust food authentication (1).
According to the authors, there are several main key takeaways of this study. First, the results, according to the researchers, show how LIBS, as a fast, non-destructive, and highly sensitive technique, is capable of being used for in situ detection of adulteration in processed foods (1). Unlike traditional laboratory methods that require extensive sample preparation and chemical digestion, LIBS enables real-time elemental analysis, making it ideal for on-site food inspection in production facilities or at regulatory checkpoints (1).
As a result, this study demonstrates how this new LIBS-inspired method can be used to improve food safety during the production process. Food authenticity and regulatory monitoring remain important application areas, and this method offers an alternative solution to meet the challenges of ensuring consumer food products are safe for consumption (1).
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