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    OPTOSKY /NEWS /Raman Blog /Application Case | Online Raman PAT for Rapid Detection of Camellia Oil Adulteration /

    Application Case | Online Raman PAT for Rapid Detection of Camellia Oil Adulteration

    2025-09-03
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    01  Application Background
    Application Focus: Detection of Adulteration in Camellia Oil
    Traditional methods for detecting adulteration in edible oils primarily rely on physicochemical assays, chromatography, GC-MS, infrared spectroscopy, and other techniques. These methods often require cumbersome pre-treatment processes, are time-consuming, labor-intensive, costly, and unable to trace the origin of the oil. This leads to inefficiencies and delays in data acquisition for researchers in both experimental and applier settings.
    02  Case Study
    In an edible oil R&D project at a Provincial Academy of Forestry, camellia oil is widely promoted due to its unique nutritional value and health benefits. However, incidents of adulteration and counterfeiting in the market not only compromise the quality and brand reputation of camellia oil but also interfere with experimental results. Therefore, the R&D team required an efficient and reliable detection method for measuring adulteration during camellia oil development and quality control.
    To address these challenges, the customer chose the ATR7010 Online Raman PAT of Optosky. This instrument utilizes Raman spectroscopy for non-destructive testing of edible oils. Through proprietary algorithms for modeling and analysis, it achieves accurate detection of adulteration in high-value oils like camellia oil. The absolute measurement error is controlled within 2%, and the results have been highly commended by users.
    On-Site Experiment
    Software Analysis
    The ATR7010 Raman spectrometer was used to test camellia oil, soybean oil, and camellia oils from different regions. The resulting spectral information is shown in the figures below:
     
    Raman characteristic spectra of edible oils
    Raman characteristic spectra of camellia oils from different origins
    As shown above: camellia oil and soybean oil exhibit characteristic Raman peaks at wavenumbers 1262 cm⁻¹, 1298 cm⁻¹, 1437 cm⁻¹, and 1653 cm⁻¹. The peaks at 1263 cm⁻¹ and 1653 cm⁻¹ are characteristic of unsaturated fatty acids, while those at 1298 cm⁻¹ and 1437 cm⁻¹ are characteristic of saturated fatty acids. Different adulteration ratios result in variations in the intensity of these characteristic peaks.
    Furthermore, camellia oils from different origins also show differences in Raman peak intensities, enabling users and relevant institutions to identify the geographic origin of the edible oil. By analyzing the Raman spectral intensities of characteristic peaks from different camellia oils at various concentrations, origin prediction and adulteration concentration analysis can be performed. The analysis results are as follows:
    Origin identification using Raman quantification software
    Relationship between adulteration concentration and Raman characteristic peak intensity in camellia oil
    ATR7010 can distinguish and identify the origin of camellia oil. Raman spectral analysis of the characteristic peaks of edible oils shows a strong linear relationship between spectral intensity and the level of adulteration.
    Single-feature linear models can exhibit significant random deviations in analysis, potentially leading to inaccuracies. Using 20 training samples of camellia-soybean oil mixtures with 5% concentration intervals, multiple linear regression was performed based on the characteristic peak intensities of camellia oil. The cross-validated R² value reached 0.99. Utilizing multiple features significantly enhances model robustness compared to using a single feature. The established model is shown below:
     
    Soybean oil was adulterated into camellia oil at concentrations of 9.99%, 19.47%, 30.03%, 39.39%, 50.01%, 59.93%, 69.98%, 79.75%, and 88.68%. Raman intensities of these samples were measured using the Raman spectrometer and validated against the model established by our instrument.
    A comparison between the model predictions and actual results is shown below:
    Multiple linear regression model
    03  Product Introduction
    ATR7010 Online Raman PAT
    //www.optosky.net/ATR7010.html
    Pharmaceutical Efficacy Testing
    Benzoic acid testing in white oil
    Benzoic acid testing in white oil
    Biochemical indicator detection
    Product Features
    • Quantitative Detection: Eliminates complex sampling, avoids operator exposure to hazardous chemicals—safe and efficient.
    • Real-Time Monitoring: Supports reaction endpoint alarms, saves production time, and reduces losses from anomalies.
    • High Sensitivity: Cooled CCD enables low-concentration detection, down to 0.1%.
    • Strong Applicability: High-temperature resistant, acid-alkali resistant long probe meets demands of complex environments.
    • One-Click Analysis: User-friendly software interface and one-click operation design for ease of use and fast results.
    Application Fields:
    Crystallization processes, biocatalysis and enzymatic catalysis, flow chemistry, polymorph identification, bioprocess monitoring, chemical synthesis, and more.
    ATR7010 Online Raman PAT, independently developed by Optosky, leverages its high sensitivity and real-time monitoring capabilities. It has not been successfully applied to the detection of adulteration in camellia oil within edible oil R&D but also demonstrates excellent performance in applications such as pharmaceutical efficacy testing, benzoic acid detection in white oil, and biochemical indicator analysis. Its rapid and accurate detection capabilities effectively meet diverse client needs in quality control and R&D.
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