Analysis of Related Databases of Maize Test Breeding System

The test is an important step in the genetics and breeding of corn crops. There are a wide range of items and varieties involved in the test and a large number of data concerning corn traits are collected. These traits data need to be collected, organized, recorded, counted, analyzed, Storage, how to screen out the required species from a large number of test data is extremely important for improving the efficiency of corn breeding. In recent years, computer technology has developed rapidly, and various computer software has been presented to meet users' needs. However, due to the particularity of the agricultural industry, computer software design in the agricultural sector lags behind. At present, the scientific computer software design for the test is in its infancy. The related application software is very limited, and the system design is not mature. The background of the corn test system designed in this paper is to use Oracle large-scale database management system to save a large amount of seed resource data. The front desk applies Delphi to design application software and provide users with an operating environment. The corn test system is the main instrument for testing and plays an important role in modern test.

The corn test system consists of four modules: data entry, variety inquiry, character data analysis, and user management. The trait data analysis module is divided into three submenus: variance statistics, estimated production, and neural network training. The varietal data entry module can record the trait data recorded in each corn variety test, and can also modify and export the print history data. Variety search module can query trait data by species name, species code, and year. The system is developed based on the network environment and involves different users. The user management module is used to assign different rights to different users for different users to use. The trait data analysis module can obtain metrics, variance values, etc. from the trait data. It can also estimate the yield based on the estimated production formula. The trait data can also be used as sample data to be input to the neural network module, which can be repeatedly trained and screened out. Variety with reference value.

The corn test system background database uses Oracle9i. Oracle9i is a mainstream database today, powerful, you can use its triggers on the business stored procedures, packages, functions, etc. in the database server to achieve some corn traits data, mean value, variance, etc. automatically calculated for the front-end client to call. Oracle9i ArcSDE912 multi-source spatial database, data management through ArcSDE, data stored in the Oracle database SDE table space. The data in different regions is built in different SDE tablespaces. When the data volume increases and the tablespace size is insufficient, the data can be entirely transferred to a new tablespace, which is beneficial to the security of the database and to the distributed application of the database.

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