Multi-component quantitative and feed-forward neural network for pattern classification of raw and wine-processed Corni Fructus

Background:To promote the quality evaluation,clarify the processing mechanism and distinguish origins of Corni Fructus(cornus)from different regions.Methods:This study developed a high performance liquid chromatography method for simultaneous determination of 5-hydroxymethylfurfural,2 phenolic acids and 4 iridoid glycosides and the reference fingerprint of cornus from different regions.In addition,the feedforward neural network model provided a pattern classification of sample regions.Results:The content of morroniside and loganin were the highest in all raw cornus samples ranging from 9.45μg/mg to 16.3μg/mg and 6.64μg/mg to 13.7μg/mg,respectively.The level of sweroside in raw cornus from Henan(0.83μg/mg^(-1).39μg/mg)and Zhejiang(0.64μg/mg^(-1).17μg/mg)were greater than other origins.After wine-processing,the glucose or fructose were dehydrated to increase the levels of 5-hydroxymethylfurfural.The C-4 position of-COOCH3 of hot-sensitive iridoid glycosides was hydrolyzed to generate-COOH as stable components.Polyphenol derivatives may be degraded to increase the content of phenolic acid.Subsequently,an excellent feedforward neural network model for identification of raw cornus and wine-prepared cornus was established which could distinguish the sample origins.Conclusion:This work provided a trustworthy method to evaluate the quality and distinguish the sources of cornus.Meanwhile,the clear processing mechanism provided a scientific foundation for controlling the cornus quality during wine-processing.

优质药材山茱萸生产技术

中药材山茱萸具有10余种生理活性,应用范围不断扩大,市场供给矛盾日益突出,梳理其原植物栽培要点,总结优质药材山茱萸生产技术具有重要意义。首先,结合山茱萸资源自然分布特点,发现陕西秦岭和河南伏牛山、浙江天目山“一岭二山地区”是药材山茱萸道地产区,这些地区的山茱萸(Cornus officinalis Sieb et.Zucc.)生长综合生产能力强,品质优良。其次,以山茱萸为药材山茱萸唯一基原植物栽培,应选择适宜当地种植的综合抗性强、丰产稳产、品质优良的主导品种。最后,采取规范化栽培措施是优质山茱萸生产的重要环节,栽培选地、育苗管理、幼林抚育、成林管护、病虫害防治以及产地加工等过程对药材山茱萸品质均有影响。