Design And Development Of Pesticide Preparation Database

Chemical database is of great value to chemical researchers and has become the basic platform of research. With the rapid development of computer technologies and molecular graphics, computer-aided technology can be used in the developing of new pesticide adjuvants. The building of pesticide formulations database instead of single data has great significance to work efficiency and gradually realize digital. This paper mainly studied on the following aspects:(1) Thousands of common surfactants information was established and perfected including surfactants trade name, chemical structure, NMR, IR and MS as well as physical and chemical parameters of surfactants, HLB value, CMC value, security level, national standard, MSDS report and application examples. The established pesticide formulations database includes three aspects, one is the chemical structure of the pesticide, the spectral data, physico-chemical parameters, MSDS report. Second, pesticide formulations recipe information, pesticide formulations complex formulations and application information. Third, pesticide formulations filler information, such as specific surface area silica, TEM chart and SEM chart.(2) Based on the above database, Pesticide Adjuvant Compound Information Management Systems and Surfactants and Formulations Application Service System was designed and developed based on.Net technology platform and Web technology platform. Through rigorous system testing, the results showed that both the structure of the system is stable, fully meet the demand of project development and can be applied in practice.(3) In structure retrieval module, compared with some of the current major algorithm, the GMA algorithm optimized by Sunwanyi was used and achieved the algorithm by Language C# to realize structure matching retrieval functions.(4) In prediction module, Davis additivity principle and QSPR models(QSPR) was used to prediction hydrophile-lipophile balance(HLB) values and critical micelle concentration(CMC) values. QSPR model can predict the HLB value of sulfate, sulphate, carboxylate and polyethenoxy ether as well as Log CMC value of surfactant.