基于近红外光谱和随机森林方法鉴别蜂蜜真伪

Detection of honey adulteration by near infrared spectroscopy coupled with random forest method

中文关键词:  近红外光谱法  随机森林法  蜂蜜  掺伪鉴别

英文关键词:near infrared spectroscopy(NIR)  Random Forest method  honey  adulteration detection

中文摘要:

      目的 建立蜂蜜样品真伪鉴别的近红外光谱快速检测方法, 为今后蜂蜜检验工作提供可靠参考依据。方法 采用积分球透反射模式采集样品近红外光谱数据, 以Savitzky-Golay 1阶微分方法对原始光谱进行预处理, 以随机森林方法建立光谱数据与蜂蜜真伪的定性判别模型。结果 所建立的判别模型中训练样本判别正确率为100%, 测试样本判别正确率为95%。结论 近红外透反射光谱技术应用于蜂蜜真伪鉴别的可行性, 同其他分析方法相比具有操作简单、速度快、效率高、无污染、费用低、无需复杂前处理等优点。

英文摘要:

      Objective To study honey adulteration by near infrared spectroscopy-chemometrics method. Methods Transflectance mode with integrating sphere was used to collect NIR spectra. Savitzky-Golay first derivative method was employed to preprocess the raw NIR spectra. A Random Forest model was established based on the correlation between the NIR spectra and reference value. Results The prediction accuracy of the proposed method was 100% for training samples and 95% for test samples. Conclusion The proposed method is fast and non-destructive, and it provides a novel efficient and environmental friendly approach for the rapid qualitative detection of honey adulteration.