Original document(12 pages)  中文版
    A method of using visual light and near infrared spectrum to identify variety of crop seed nondestructively includes fixing halogen lamp on A C frame, using power supply wire to provide 220V AC power to spectrograph and light source as well as computer, connecting spectrograph to computer through data line for transmitting collected data of sample spectrum to computer, carrying out process and analysis on collected data by spectrum special software ASD View Spec ProV 2.14 and Unscramble V9.2 then feeding analyzed data back to information platform for displaying variety of tested sample.
Application Number
申请号
200610050167 Application Date
申请日
2006.04.03
Title 名称 Method for nondistructive discriminating crop seed variety using visible light and near-infrared spectrum technology
Publication Number
公开号
1831515 Publication Date
公开日
2006.09.13
Approval Pub. Date Granted Pub. Date
International Classification 分类号 G01N21/31,C12Q1/68,A01C1/02
Applicant(s) Name
申请人
Zhejiang Univ.
Address 地址 310027
Inventor(s) Name 发明人 He Yong, Li Xiaoli
Attorney & Agent 代理人 lin fuyu

  
Biological gold extraction method of difficult separation concentrate and special equipment
Soil information satellite location measuring apparatus
Water-power siphon plant
Commodity network scanning anti-fake system and its electronic identification label
Method for controlling jet ink of micro body of fluid
Gene and application related to synthesizing xanthogen glue
New technique for producing N C formaldehyde C alkyl - benzoic acid, and N C formaldehyde C alkyl - benzoic ether
Method of producing chlorinated polypropylene
Intelligent no-mold drawing formation apparatus and process
Fruit quality damage-free detection method and system based on multiple spectral imaging technique
Google
Note:All patent data come from State Intellectual Property Office of the People's Republic of China. If there were discrepancies between here and the State Intellectual Property office, the later is more accurate. The patent data is only for public exchange and learning purposes. We are not responsible for the adverse consequences with unverified use of the data.