基于光学特性的初榨橄榄油掺假度便携式分析仪设计与试验
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TN216

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国家自然科学基金项目(32202147);中国博士后基金项目(2021M690573);中央高校基本科研业务费专项资金项目(2572020BF05)


A portable analyzer for the adulteration degree of extra virgin olive oil using optical properties
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    摘要:

    针对我国愈来愈严重的橄榄油掺假问题,该研究研发了一种基于光学特性检测技术的特级初榨橄榄油掺假度无损检测仪。以8个产地的玉米油、花生油、菜籽油和大豆油为掺假油制备了339份掺假质量分数分别为0、1%、3%、6%、10%、15%、20%、25%、30%、35%、40%、45%、50%、55%和60%的掺假特级初榨橄榄油样本,采用连续投影算法分析了橄榄油掺假检测特征波长的分布情况,最终选取包含18个波段的多通道光谱传感器,根据特级初榨橄榄油的物理特性,设计了一种便携、低成本的橄榄油掺假检测仪器。利用研发装置采集的掺假油光谱数据分别建立了反向传播(back propagation,BP)神经网络、支持向量回归(support vector regression,SVR)和基于偏最小二乘回归(partial least squares regression,PLSR)的橄榄油掺假率定量分析模型。结果表明,建立的SVR模型结果最优,其校正集和验证集决定系数分别为0.989和0.965,均方根误差分别为0.020和0.037。为进一步评估检测装置的稳定性和准确性,使用平均变异系数分析了特级初榨橄榄油掺假样本的测定结果,并通过预测结果与实际掺假浓度值进行残差分析,结果表明所研制的橄榄油掺假度分析装置对橄榄油掺假分析检测的稳定性与精度均满足现场实时检测需求。

    Abstract:

    Olive oil adulteration is has ever been increasing in China in recent years. In this study, a portable non-destructive testing instrument was developed to detect the extra virgin olive oil adulteration using the visible/near-infrared spectroscopy. The instrument was consisted mainly of a multi-spectral acquisition module, a control and display module, a power supply module, and peripheral circuits. And then, the transmission spectrum of the adulterated sample was collected, according to the characteristics of extra virgin olive oil. Firstly, corn oil, peanut oil, rapeseed oil, and soybean oil from eight origins were used as the adulterated oils, and then mixed with the extra virgin olive oil from three origins in Spain, Italy, and Greece. 339 adulterated extra virgin olive oil samples were prepared with the mass fractions of 0, 1%, 3%, 6%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, and 60%, respectively. Secondly, a self-built spectral acquisition system was used to collect transmission spectra of the samples. Finally, partial least squares regression, support vector regression, and error back-propagation neural network models were used to analyze the feasibility of adulteration detection. The results show that the correlation coefficients of the calibration set were between 0.947 and 0.987 after spectral preprocessing. RMSEC values were between 0.031 and 0.063. The correlation coefficients of the validation set were between 0.956 and 0.990, and RMSEP values were between 0.026 and 0.063. The characteristic wavelengths for olive oil adulteration detection were extracted using the successive projection. A multi-channel spectral sensor was finally selected to contain 18 bands. A portable and low-cost olive oil adulteration detection instrument was designed, according to the physical characteristics of extra virgin olive oil. The spectral data of adulterated oil was collected by the R&D device. The quantitative analysis models were established for the olive oil adulteration rate using partial least squares regression, support vector regression, and error back propagation neural network. The prediction models were compared as well. The support vector regression model shared the best fit and optimal prediction, with the correction and validation set coefficients of determination of 0.989 and 0.965, and root mean square errors of 0.020 and 0.037, respectively. The prediction model with the support vector regression models was loaded into the detection device, in order to verify the accuracy and stability of the model and detection device. Within the range of 0-60% adulteration rate, three types of extra virgin olive oil adulterated samples were failed to coincide with the concentration of the model training set samples, which were randomly configured every 10%. The stability of the device was characterized by the coefficient of variation in the three predicted adulteration rates of the extra virgin olive oil. Within the range of adulteration rates, the average coefficient of variation was 0.019 in the adulterated samples, indicating the better adaptability and consistency of the model. The testing instrument showed the a highly stable performance with little fluctuation in the prediction over multiple tests. The accuracy of the device was verified to analyze the residuals between the predicted and the true values of the adulterated samples. The maximum absolute value was 4.43 for the residuals of the adulterated samples. The stability and accuracy of the portable device were achieved to analyze the adulteration rate of extra virgin olive oil, fully meeting the needs of on-site testing.

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赵庆典,马芸芸,杨冕清,汪国政,陈百超,刘大洋.基于光学特性的初榨橄榄油掺假度便携式分析仪设计与试验[J].农业工程学报,2024,40(18):321-328. DOI:10.11975/j. issn.1002-6819.202404116

ZHAO Qingdian, MA Yunyun, YANG Mianqing, WANG Guozheng, CHEN Baichao, LIU Dayang. A portable analyzer for the adulteration degree of extra virgin olive oil using optical properties[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE),2024,40(18):321-328. DOI:10.11975/j. issn.1002-6819.202404116

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  • 收稿日期:2024-04-17
  • 最后修改日期:2024-06-20
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  • 在线发布日期: 2024-09-11
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