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Optimization of the selection of suitable harvesting periods for medicinal plants: taking Dendrobium officinale as an example

文献类型： 外文期刊

作者： Li, Peiyuan 1 ; Shen, Tao 3 ; Li, Li 1 ; Wang, Yuanzhong 2 ;

作者机构： 1.Jishou Univ, Coll Biol & Environm Sci Hunan Prov, Jishou 416000, Peoples R China

2.Yunnan Acad Agr Sci, Med Plants Res Inst, Kunming 650200, Peoples R China

3.Yuxi Normal Univ, Coll Chem Biol & Environm, Yuxi 653100, Yunnan, Peoples R China

关键词： Medicinal plant; Dendrobium officinale; ATR-FTIR; ResNet; Harvesting period; Anticipate

期刊名称：PLANT METHODS （ 影响因子：5.1； 五年影响因子：6.1 ）

ISSN：

年卷期： 2024 年 20 卷 1 期

页码：

收录情况： SCI

摘要： Background Dendrobium officinale is a medicinal plant with high commercial value. The Dendrobium officinale market in Yunnan is affected by the standardization of medicinal material quality control and the increase in market demand, mainly due to the inappropriate harvest time, which puts it under increasing resource pressure. In this study, considering the high polysaccharide content of Dendrobium leaves and its contribution to today's medical industry, (Fourier Transform Infrared Spectrometer) FTIR combined with chemometrics was used to combine the yields of both stem and leaf parts of Dendrobium officinale to identify the different harvesting periods and to predict the dry matter content for the selection of the optimal harvesting period. Results The Three-dimensional correlation spectroscopy (3DCOS) images of Dendrobium stems to build a (Split-Attention Networks) ResNet model can identify different harvesting periods 100%, which is 90% faster than (Support Vector Machine) SVM, and provides a scientific basis for modeling a large number of samples. The (Partial Least Squares Regression) PLSR model based on MSC preprocessing can predict the dry matter content of Dendrobium stems with Factor = 7, RMSE = 0.47, R-2 = 0.99, RPD = 8.79; the PLSR model based on SG preprocessing can predict the dry matter content of Dendrobium leaves with Factor = 9, RMSE = 0.2, R-2 = 0.99, RPD = 9.55. Conclusions These results show that the ResNet model possesses a fast and accurate recognition ability, and at the same time can provide a scientific basis for the processing of a large number of sample data; the PLSR model with MSC and SG preprocessing can predict the dry matter content of Dendrobium stems and leaves, respectively; The suitable harvesting period for D. officinale is from November to April of the following year, with the best harvesting period being December. During this period, it is necessary to ensure sufficient water supply between 7:00 and 10:00 every day and to provide a certain degree of light blocking between 14:00 and 17:00.

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