Reserch And Design Of The Greenhouse Vegetable Technology For The Intelligent Decision Making System By Balancing The Warter And Fertilizer Ratio

With the continuous growth of China’s population and urbanization,the increasing demand of the quality and amounts of vegetable is more and more fierce.Therefore,the facility vegetable industry has been noticed by government and attracted more and more eyes in recent years.As the NPK is the key factor affecting the growth of greenhouse vegetable,this paper used butter lettuce as an example,designed the three-factor five-level quadratic regression universal rotation combination experiment with different NPK ratios,and designed different ratio of NPK to understand the relationship between vegetable yields and the NPK ratio.Moreover,using expert system theory,ASP.NET framework.,database technology,B/S architecture,network technology,vegetable planting technology and other technologies,to research and design the intelligent of Greenhouse Vegetable Technology(GVT),which is about the water and fertilizer intelligent decision-making system.GVT Water and Fertilizer Intelligent Decision-Making System provides professional water and fertilizer ratio suggestions,improves annual yield,reduce limited earth resources,and brings higher economic benefits.Moreover,it is a valuable test to combine the information tech to the agriculture producing.This paper has achieved the following results:(1)Designed the three-factor and five-level quadratic regression universal rotation,and combined water and fertilizer ratio experiment.Researched the relationship between the yield of butter lettuce and the nitrogen,phosphorus and potassium(NPP)in nutrient solution.The content of NPP and butter lettuce were found.Studied a significant relationship,when the content of P and K concentrations is 3.22 mmol / L,0.6 mmol / L and 2 mmol / L,the butter lettuce maximum yield 76.42 g / strain.Moreover,the nitrogen has the greatest impact on yield.The order of impact on yield is N>P>K,which provides a theory basis for intelligent management of GVT.(2)Using the relationship model between NPP and yield to provides the knowledge for expert decision-making system.On the other hand,established corresponding knowledge rules,the knowledge base,formula library,decision rule base,expert database and other knowledge.Also,using a mixed way,that is direct and forward reasoning,to provide support for the intelligent decision-making for GVT.(3)Established background development by C# language.On the other hand,write front-end code by the ASP.NET MVC framework,SqlServer database,and combined with the theory of expert system and HTML+CSS+JavaScript language.Using front-end EasyUI framework to design and implement crop yield-based GVT Water and Fertilizer Intelligent Decision System.Also it provides a platform for the management of GVT.