Identification and quantification of anthocyanins,flavonoids, and phenolic acids in flowers of Rhododendron arboreum and evaluation of their antioxidant potential

The current study aimed to investigate the anthocyanins, non-anthocyanins (flavonoids and phenolic acids), and free radicals scavenging potential in the flowers of Rhododendron arboreum using ultra high performance liquid chromatography with ion mobility quadrupole time of flight tandem mass spectrometry. A total of 25 constituents including nine anthocyanins, six phenolic acids, and ten flavonoids were identified in the flower extract. The major anthocyanins identified were cyanidin-3-O-β-galactoside ( 1 ), cyanidin-3-O-α-arabinoside ( 4 ), and cyanidin-3-O-rhamnoside ( 8 ), while quercetin glycosides were the main identified flavonoids in R. arboreum flowers. Additionally, ultra high performance liquid chromatography methods were developed and validated for the quantification of nine compounds (anthocyanins, flavonoid glycosides, and phenolic acids); five of them were quantified using internal standards. The extracts were analyzed for total phenolics (123.6 mg GAE/g), anthocyanin content (1.76% w/w), and evaluated for antioxidant properties against 2,2-diphenyl-1-picrylhydrazyl radical (IC₅₀: 102.06 and 96.92 μg/mL) and 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) radical cation (112.25 and 45.59 μM TE/g) assays. The profiling of R. arboreum for anthocyanins is reported for the first time. The findings suggest that the flowers are a promising source of bioactive constituents and could be used as functional food, antioxidants, and nutraceuticals.     

浙江杜鹃花属植物的研究

本文报道了浙江产杜鹃花属植物16 种及 1 变型其中白花满山红为新变型,丁香杜 鹃和江西杜码为浙江分布新记录.根据最新分类系统,本属分为 5 个亚属,在浙江都有 它们的代表,说明浙江的杜鹃花属植物在该属系统研究中的地位,此外,文中还附有分种 检 索表和种类列举 ( 分布、用途 )     

Spectral characteristics and species identification of rhododendrons using a discriminative restricted Boltzmann machine

Rhododendrons are an important genus of alpine flowering plant used ornamentally worldwide. The purpose of this study is to improve the application of remote-sensing technology for investigating and monitoring mountain rhododendron germplasm. Research area is the Baili Rhododendron National Forest Park located in the karst region of Guizhou Province, China. Field spectrometry was used to acquire spectral data for 20 samples extracted from eight rhododendron species. A deep-learning algorithm from a discriminative restricted Boltzmann machine was used with the original spectral data from the different rhododendron species to obtain the optimal parameters for the model. Simultaneously, the data processing methodology from the discriminative restricted Boltzmann machine was used to recognize the original spectra, the noise smoothed spectra, and the first- and second-order spectral derivatives with accuracies of 88.54%, 88.54%, 93.75%, and 90.62%, respectively. The results show that the discriminative restricted Boltzmann machine is effective in recognizing spectral information for different rhododendron species. Changes in the first-order derivative gave the most accurate classification, but changes in the second-order derivative significantly reduced the sample training time. Changes in both derivatives therefore proved useful in recognizing and extracting particular features of the plant species. This research may therefore further support the use of hyperspectral remote-sensing imagery for investigating and monitoring germplasm, species classification, and physiological parameter inversions for rhododendrons from various mountain regions of China.     

双波长分光光度法测定乳浊液中烈香杜鹃油含量

本文建立了双波长分光光度法测定乳浊液中烈香杜鹃油的分析方法,烈香杜鹃油含量在0.005~0.8 g.L-1的范围内线性关系良好(R=0.9999,n=9),平均回收率为99.92%,相对标准偏差为1.64%。该测定方法简便快速,结果准确,为性质相似的其它油性药物在乳浊液中含量的分析测定提供了参考。