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Discrimination and evaluation Gentiana rigescens-Camellia sinensis with different planting year using Fourier transform infrared spectroscopy
Agroforest Syst Agroforestry Systems : An International Journal incorporating Agroforestry Forum
Format: Journal Article
Publication Date: Nov 30, 2018
Pages: 1157 - 1166
Sources ID: 106251
Visibility: Public (group default)
Abstract: (Show)
Agroforestry system, as the most promising substitute plantation approach, has been widely regarded as a prominent strategy for mitigating the conflicts between rapid growing population and limited arable land resources. This paper aims to screen the optimal planting pattern for Gentiana rigescens base on the content of gentiopicroside, providing the scientific basis for sustainable supply and application of this plant. Generally, Fourier transform infrared (FTIR) spectroscopy is effective to integrally monitor and reflect the whole constituents of natural materials. FTIR combined with chemometrics was used for distinguishing the G. rigescens from different compound planting models in this research. The result of partial least square discriminant analysis implied that planting year of G. rigescens had a greater impact on the content of gentiopicroside than that of Camellia sinensis. The gentiopicroside content in 1.5- or 2-year-old G. rigescens was higher. Wavelet denoising was effective for the classification. Samples which had higher contents of gentiopicroside were clustered together relatively, while those with lower contents of gentiopicroside were classified into the other large category. Our investigation revealed that G. rigescens can be successfully cultivated with C. sinensis, which met the requirement of the gentiopicroside content recommended by Pharmacopoeia of the People’s Republic of China. That 2-year-old G. rigescens grown with 12-year-old C. sinensis was the optimal compound planting pattern, according this study. The present study provided the optimal compound planting pattern of G. rigescens, which is helpful for improving land-use efficiency and economic returns.