Improvement of NIR models for quality parameters of leech and earthworm medicines using outlier multiple diagnoses

• Main Authors: Chunyan Wu, Jiashan Chen, Mengru Li, Yongjiang Wu, Xuesong Liu
• Format: Article
• Language: English
• Published: World Scientific Publishing 2018-01-01
• Series: Journal of Innovative Optical Health Sciences
• Subjects: Leech; earthworm; near-infrared spectroscopy; outlier multiple diagnoses
• Online Access: http://www.worldscientific.com/doi/pdf/10.1142/S1793545817500092

Leeches and earthworms are the main ingredients of Shuxuetong injection compositions, which are natural biomedicines. Near infrared (NIR) diffuse reflection spectroscopy has been used for quality assurance of Chinese medicines. In the present work, NIR spectroscopy was proposed as a rapid and nondestructive technique to assess the moisture content (MC), soluble solid content (SSC) and hypoxanthine content (HXC) of leeches and earthworms. This study goal was to improve NIR models for accurate quality control of leech and earthworm using outlier multiple diagnoses (OMD). OMD was composed of four outlier detection methods: spectrum outlier diagnostic (MD), leverage diagnostic (LD), principal component scores diagnostic (PCSD) and factor loading diagnostic (FLD). Conventional outlier diagnoses (MD, LD) and OMD were compared, and the best NIR models were those based on OMD. The correlation coefficients (R) for leech were 0.9779, 0.9616 and 0.9406 for MC, SSC and HXC, respectively. The values of relative standard error of prediction (RSEP) for leech were 2.3%, 5.1% and 9.0% for MC, SSC and HXC, respectively. The values of R for earthworm were 0.9478, 0.9991 and 0.9605 for MC, SSC and HXC, respectively. The values of RSEP for earthworm were 8.8%, 2.4% and 12% for MC, SSC and HXC, respectively. The performance of the NIR models was certainly improved by OMD.