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Prediction of cyanidin 3-rutinoside content in Michelia crassipes based on near-infrared spectroscopic techniques.
Xiao, Yuguang; Zhang, Xiaoshu; Liu, Jun; Li, He; Jiang, Jingmin; Li, Yanjie; Diao, Shu.
Afiliación
  • Xiao Y; Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou, China.
  • Zhang X; School of Civil Engineering and Architecture, Xinxiang University, Xinxiang, China.
  • Liu J; Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou, China.
  • Li H; Research Institute of Landscape Plants, Guizhou Academy of Forestry, Guiyang, China.
  • Jiang J; Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou, China.
  • Li Y; Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou, China.
  • Diao S; Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou, China.
Front Plant Sci ; 15: 1346192, 2024.
Article en En | MEDLINE | ID: mdl-38766470
ABSTRACT
Currently the determination of cyanidin 3-rutinoside content in plant petals usually requires chemical assays or high performance liquid chromatography (HPLC), which are time-consuming and laborious. In this study, we aimed to develop a low-cost, high-throughput method to predict cyanidin 3-rutinoside content, and developed a cyanidin 3-rutinoside prediction model using near-infrared (NIR) spectroscopy combined with partial least squares regression (PLSR). We collected spectral data from Michelia crassipes (Magnoliaceae) tepals and used five different preprocessing methods and four variable selection algorithms to calibrate the PLSR model to determine the best prediction model. The results showed that (1) the PLSR model built by combining the blockScale (BS) preprocessing method and the Significance multivariate correlation (sMC) algorithm performed the best; (2) The model has a reliable prediction ability, with a coefficient of determination (R2) of 0.72, a root mean square error (RMSE) of 1.04%, and a residual prediction deviation (RPD) of 2.06. The model can be effectively used to predict the cyanidin 3-rutinoside content of the perianth slices of M. crassipes, providing an efficient method for the rapid determination of cyanidin 3-rutinoside content.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Plant Sci Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Plant Sci Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza