基于二元逻辑回归分析的苹果汁鉴伪模型(英)

    Model for identifying apple juice authenticity based on binary logistic regression

    • 摘要: 为了研究苹果汁中有机酸与掺假苹果汁的关系,从而通过检测有机酸进行质量控制和食品安全监督。该文共收集了340个中国产苹果样本并制成苹果汁,涉及14个试点种植区域的19个品种。通过高效液相色谱测定样本中有机酸的种类和含量。该试验通过添加水、L-苹果酸和蔗糖模拟制作原果汁含量分别为57%,50%和25%的掺假苹果汁。在测得的包括原果汁和掺假果汁的有机酸种类和含量的基础上利用二元逻辑回归分析方法建立了判别模型,用以区别掺假苹果汁,模型的精确度和重现率分别为87.4%和94.51%。统计数据显示该模型判别效果良好,可用于苹果汁的质量控制。研究结果证实苹果汁中特征有机酸指纹图谱可以用来鉴别苹果汁掺假。

       

      Abstract: In order to explore the correlation between organic acids and adulterated apple juice and in turn to take control of apple juice quality to ensure food safety. A total of 340 apple samples from 14 different planting areas on 19 different varieties were collected throughout the main cultivation areas in China, high performance liquid chromatography (HPLC) was applied to detect organic acids profiles in apple juices. Adulterated juice samples at 75%, 50% and 25% (w/w) were prepared by adding water, L-malic acid and sucrose to adjust pH and total soluble solids (TSS) normal value. Binary logistic regression was adopted on the basis of organic acids in both authentic and adulterated apple juices to establish a predictive model to distinguish authentic and content-mislabeled apple juices. The accuracy and stability of the model were about 87.4% and 94.51% respectively. Statistic results indicate that the model works well and can be used as quality control guide. Therefore, apple juice has very distinct organic acids profiles that can be used as fingerprints for evaluating authenticity.

       

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