The Design And Implementation Of Soybean Pod Phenotype Morphological Analysis System Based On Machine Vision

At present,the determination of soybean phenotypic traits is basically done manually,with high labor intensity,long cycle,low efficiency,cumbersome procedures,and low precision,which has severely restricted the development speed of soybean seed industry in my country[1].The plant characteristics and traits obtained by manual subjective measurement and simple measurement are very limited,and there is also a lack of standardized characterization,which cannot meet the actual needs of crop genome function research and crop breeding.There are many analytical monitoring techniques available for plant phenotype research,which can accurately obtain a variety of plant characteristics and traits ranging from molecules to populations.The rapid development of computer technology has made it possible to effectively manage the rapidly increasing biological data,and bioinformatics has become the main means of processing and mining high-throughput data information^[4].This study takes soybean as the research object,researches and processes the pods at the mature stage,uses digital image processing technology and machine vision technology to study and analyze the phenotype of pods,and develops phenotypic data of soybean pods efficiently,quickly and accurately Research on extraction methods,and on this basis,establish a detection model for the rapid measurement of soybean pod data,and develop a phenotype analysis system for soybean pods.The main research of this article is as follows:（1）By formulating a unified image collection standard for pods,in order to facilitate the processing of pod image for grains,we built a specific image acquisition platform,and used a standard background board,as well as a standard marked square block.（2）In this paper,through the analysis of the phenotype morphology of the grain pods,through the preprocessing of the collected images,the segmentation of the image background,and the extraction of the integrity of the pod areas,the Alex Net network was trained on this b atch of data to obtain three types The grains are referenced by the pod morphology classification coefficient,and are quickly segmented through standard marks,knowing the actual side length and area,and converting the pixel and actual size data to obtai n the geometric parameters and color component values of the pods,and breeding excellent varieties for soybean Provide basic data reference.（3）This article designs the soybean pod morphology analysis system through MATLAB’s GUI visualization function.The basic functions include:camera start to collect pictures,file selection,image processing,data measurement,data summary,morphological classification,etc.The morphological analysis method of grain pods is applied to the system implementation,and the initial setting function is achieved.