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Key Research On Digital Extraction Technology For Corn Kernel Phenotypic Traits

Posted on:2016-01-26Degree:MasterType:Thesis
Country:ChinaCandidate:K WangFull Text:PDF
GTID:2283330461490358Subject:Agricultural mechanization project
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Maize is a very important part of crops, which has a very wide range of applications in food consumption, feed consumption and commercial consumption, etc. By the influence of environment degradation and saturation of arable land, it becomes more and more obvious to increase the maize yield because of the population growth. Breeding and cultivation of new varieties is a key way to speed up the maize yield and quality. With the rapid development of maize functional genomics and breeding technology, the phenotypic traits of large quantities corn kernels should be measured in the shortest possible time. To achieve the high-throughput measurement of corn kernel phenotypic traits, this paper designs and implements a on- line system for corn kernels to accomplish the high-throughput measurement of corn kernel phenotypic traits. The main contents and results are as follows:(1) Accomplished the design of the measurement system overall program based on the physical characteristics of corn kernel. By researching the image acquisition module, fulfilled the selection of the key components and the key parameters. The undistorted images of corn kernel were acquired to debug and regulate the camera, match the conveyor speed and line-scan speed, set 1305 HZ for the acquisition frequency of line CCD, 14862 for the pulse frequency of PLC. With PLC as the core controller, completed PLC control program and electrical wiring to achieve the collaborative work of PC, PLC and execution units. In the PLC serial communication program, added self- monitoring and self- restart function to realize the normal communication and fault detection of PC and PLC.(2) Determined the methods of the kernel image processing and the parameter measurements. Through image segmentation, stitching and removing noise to acquire the kernel complete profile. Used area threshold determination to distinguish the touching kernels and no-touching kernels, the touching kernels were only used to calculate the total kernel numbers and the no-touching kernels were used to calculate the grain shape parameters. Counted the angle of the kernel and horizontal axis, what angle as the basis to rotate the kernel, the circumscribed rectangle length and width of the rotated kernel was as the kernel length and width measurements. In the procedure of image processing, the kernel profile needed to be retained as much as possible to insure the accuracy of the other parameter measurements such as the average projected area, the average projected perimeter and roundness. 20 kernel samples and 58 kernel samples were measured to analysis the error of kernel adhesion measurement and the phenotypic parameter measurements, respectively. The results showed that the average absolute error of touching kernels measurement was o.7, the measurement accuracy(mean absolute percentage error, MAPE) of total number, length, width and length-width ratio were 0.5%, 1.22%, 3.34% and 4.22%, respectively.(3) Completed the design of system software to achieve the information exchange of PC and PLC. The software could fulfill the image dynamic acquisition and preservation, the image online processing and data retention, the automatically saved of bar code data and weighing scales. To make the whole union level debugging for the measurement system, 673 samples were measured to test the overall performance and the results showed that, the measurement accuracy of total numbers, length, width and length-width ratio were 99.34%, 98.76%, 97.67% and 97.28%, respectively; The standard error were 2.23, 0.16 mm, 0.24 mm and 0.04, respectively; the measuring efficiency of system was 12 s per ear, the theoretically measuring efficiency could reach 7200 ears per day if the system worked all day; In repetitive measurements, the average CV of the total numbers and the average projected area were less than 1%, the maximum coefficient of variation of length, width, length-width ratio, the average projected area and perimeter were 2.24%, 2.28%, 2.48%, 1.80% and 0.83%, respectively.Through combined with line-scan technology and automatic control technology, a corn kernel measurement system was designed to achieve high-precision, high-throughput, high-stability measurements of corn kernel phenotypic traits. Key words: Corn kernel; Line-scan; PLC control; Traits measurement; High-throughput...
Keywords/Search Tags:Corn kernel, Line-scan, PLC control, Traits measurement, High-throughput
PDF Full Text Request
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