SONG Han,FANG Fang,WEI Zhe-wen,et al.Saffron Quality Analysis Based on High Resolution Mass Spectrometry and Deep Learning Visual Threshold[J].Journal of Instrumental Analysis,2023,42(10):1388-1394.
SONG Han,FANG Fang,WEI Zhe-wen,et al.Saffron Quality Analysis Based on High Resolution Mass Spectrometry and Deep Learning Visual Threshold[J].Journal of Instrumental Analysis,2023,42(10):1388-1394. DOI: 10.19969/j.fxcsxb.23062909.
Saffron Quality Analysis Based on High Resolution Mass Spectrometry and Deep Learning Visual Threshold
High resolution mass spectrometry combined with traditional data analysis methods is often used to identify the quality of saffron. However,the traditional data analysis algorithm sometimes has low accuracy and poor model fitting effect,resulting in high false positive rate and false negative rate of discrimination results,and it is difficult to accurately identify the quality of saffron. Deep learning algorithm can automatically extract the hidden feature information in the data,and combine with high resolution mass spectrometry technology to accurately identify the quality of saffron. This paper briefly summarizes research progresses of deep learning algorithms in processing high resolution mass spectrometry metabolomics data. On this basis,applications of deep learning algorithm in saffron quality identification were summarized,and the feasibility of combining high resolution mass spectrometry with deep learning algorithm was further discussed.
关键词
深度学习藏红花高分辨质谱特征提取品质鉴别
Keywords
deep learningsaffronhigh resolution mass spectrometryfeature extractionquality identification
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