Design And Experiment Of Automatic Acquisition System For Maize Test Parameters Based On MCGS

Maize is one of the main food crops in the world. It has important significance to improve the yield of maize in alleviating the pressure of grain yield and ensuring the security of food supply. Breeding and planting of maize varieties is the key way to speed up the high quality and high yield of maize. Maize variety test is an important part of the process of genetic maize breeding. In the maize seed species process, it needs to measure, statistics and analysis a variety of test species traits data including the number of grains, grain length, grain width, ear weight, grain moisture content, etc. The traditional way of maize variety test requires a lot of manpower and resources, the efficiency of variety test has become one of the important challenges in the genetic maize breeding.In view of the present situation of low efficiency and poor precision of test, the design and research of automatic acquisition system is carried out according to the technical requirements of the corn test, in order to obtain the parameters of the characteristics of the corn test. A automatic acquisition system for maize test parameters based on MCGS was designed this paper. Constructing the whole hardware structure, the whole system uses the automatic control technology and image processing technology to obtain the maize test character parameters. It can be achieved from corn ear to corn grain processing and test species traits acquired fast, efficient, stable and accurate automated process corn test species.In this paper, the main contents are as follows:According to the system design requirements, the overall program and the components of the assembly line system are designed. In the pipeline system, the technology of parameter acquisition and host computer control system based on MCGS embedded configuration software are studied deeply.By comparing the image analysis algorithm, using gray-scale processing, Gauss filtering, threshold segmentation algorithm and Otsu segmentation algorithm and open operation morphological processing method for image processing analysis on grain, a method for obtaining the parameters of maize kernel phenotypic characters was obtained by using the minimum circumscribed circle and the minimum enclosing rectangle model. The configuration of the system design using MCGS embedded configuration software, through the analysis and comparison of the open loop, closed loop and PID algorithm on the system as a whole and each part of the control process of the control strategy design.The whole test system is debugged and tested. The results show that the system enables fast, efficient, stable, accurate, high-throughput corn test species procedure. The average test time of single ear corn uses 21s. Test efficiency can reach 250 spike/h. Grain counting accuracy can reach 98%,the grain length, width measurement error were within±3%, the measurement error of ear weight data does not exceed 0.9%, grain moisture content measuring relative error within ±5%.