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岷县当归产量预报模型研究
引用本文:严辉,段金廒,王瑞琪,郭增祥,钱大玮,宋秉生,何子清,高鸿英.岷县当归产量预报模型研究[J].中药材,2012(4):511-514.
作者姓名:严辉  段金廒  王瑞琪  郭增祥  钱大玮  宋秉生  何子清  高鸿英
作者单位:南京中医药大学;甘肃省岷县中药材产业发展局;甘肃岷归中药材科技有限公司
基金项目:国家“十一五”科技支撑计划项目(2006BAI09B05-1;2007BA137B02);中医药行业科研专项(200807020;201107009);江苏高校优势学科建设工程资助项目
摘    要:目的:建立岷县当归药材产量预报模型,为相关部门和机构提供当归产量预报信息。方法:根据当归的生育期和生理特性,以1995~2009年岷县当归产量统计数据、成药期各旬气象资料作为研究基础,采用多项式预报法,建立岷县当归产量预报模型。结果:岷县当归产量预报模型的平均精度达97.2%,基本满足产量模拟预报的要求。结论:建立的当归药材气象预报模型有较高的准确度,可提供较为准确的当归产量预报信息,为我国药材生产过程中的产量预报提供方法学参考。

关 键 词:当归  药材产量  预报模型  产量预测

Study on Prediction Model of Angelicae sinensis Yield Per Unit in Min County
YAN Hui,DUAN Jin-ao,WANG Rui-qi,GUO Zeng-xiang,QIAN Da-wei,SONG Bing-sheng,HE Zi-qing,GAO Hong-ying.Study on Prediction Model of Angelicae sinensis Yield Per Unit in Min County[J].Jorunal of Chinese Medicinal Materials,2012(4):511-514.
Authors:YAN Hui  DUAN Jin-ao  WANG Rui-qi  GUO Zeng-xiang  QIAN Da-wei  SONG Bing-sheng  HE Zi-qing  GAO Hong-ying
Institution:1.College of Pharmacy,Nanjing University of Chinese Medicine,Nanjing 210046,China;2.Gansu Province Min County Industrial Development Bureau of Chinese Medicinal Materials,Min County 730010,China;3.Gansu Mingui Traditional Chinese Medicine Technology Co.,Ltd.,Lanzhou 730010,China)
Abstract:Objective: To establish a prediction model of Angelicae sinensis yield per unit in Min County,and the forecasting information can be provided to correlated department and organization.Methods: With the basis of the Angelicae sinensis yield statistics in Min County from 1995 to 2009 and weather data of development phase of each ten days,polynomial forecasting modeling was used and the stimulation forecasting of Angelicae sinensis yield in Min County was carried out.Results: The results showed that the average accuracy of prediction model was reached to 97.2%,which basically met the demand for yield prediction.Conclusion: The prediction model of Angelicae sinensis yield per unit in Min County has good accuracy and relatively correct forecasting information about Angelicae sinensis yield,which provides methodology and important references for dynamic forecasting in the progress of Chinese medicinal materials production.
Keywords:Angelicae sinensis(Oliv  ) Diels  Yield  Prediction model  Yield forecasting
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