Prediction of cyanidin 3-rutinoside content in Michelia crassipes based on near-infrared spectroscopic techniques

Yuguang Xiao; Xiaoshu Zhang; Jun Liu; He Li; Jingmin Jiang; Yanjie Li; Shu Diao

doi:10.3389/fpls.2024.1346192

Prediction of cyanidin 3-rutinoside content in Michelia crassipes based on near-infrared spectroscopic techniques

Front Plant Sci. 2024 May 3:15:1346192. doi: 10.3389/fpls.2024.1346192. eCollection 2024.

Authors

Yuguang Xiao¹, Xiaoshu Zhang², Jun Liu¹, He Li³, Jingmin Jiang¹, Yanjie Li¹, Shu Diao¹

Affiliations

¹ Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou, China.
² School of Civil Engineering and Architecture, Xinxiang University, Xinxiang, China.
³ Research Institute of Landscape Plants, Guizhou Academy of Forestry, Guiyang, China.

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.

Keywords: Michelia crassipes; NIR spectroscopy; cyanidin 3-rutinoside; model calibration; regression algorithm.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The research was supported by Zhejiang Science and Technology Major Program on Agricultural New Variety Breeding” (2021C02071-3).