A Study Of Knowledge Structure And Knowledge Evolution In Biological Breeding Field

Breeding based on genetic information has been rapidly developed for more than half a century. As therapid increase of scientific literature and the development of technology information to digital, networkdirections, the number of electronic journals and books has been rapidly growing. Under thesecircumstances, scientific method can be used for information filtering and processing to explore thepotential value of overwhelming information. The analysis of the development in the science fieldprovide the most up-to-date progress of each individual area, identify current popular research topics,and discover the internal connection and the integration of the knowledge from different researchterritories. This information will provide the more accurate prediction of the future directions of scienceresearches.Firstly, this thesis has analyzed and summarized some basic theories and research methods related toknowledge structure and knowledge evolution. The existing theories and basic methods frombibliometrics, content analysis, scientific knowledge mapping and model theories are summarized in theintroduction part. This summary provides a theoretical basis for domain knowledge structure andknowledge evolution studies in the near future. Then, described the elements, distributions andrelationships of the knowledge structure. The phenomenon of knowledge diffusion, knowledge fusion,knowledge burst, knowledge proliferation and knowledge disappearance which are generated byevolution process has been explored. The causes and features of phenomena have been analyzed as well.The overall strategy of knowledge structure drawing in biological breeding field has been described inthis thesis. Different methods have been selected based on comparing and analyzing various techniqueswhich are involved in data processing, network generation and knowledge structure drawing. Theanalytical indexes have been chosen from the global and the individual angles to study the nation, theauthor, and the keyword datasets. And then, has finished building a knowledge structure for biologicalbreeding field. A method model of evolution for the knowledge of biological breeding has been drawn.This model elaborated the key techniques of time splice partitioning, threshold setting, calculation oftopic similarity, and recognition of knowledge evolution phenomenon in the model building process.Selected articles between1995and2012to test the model, analyzed the changes of knowledge structurebased on topic networks, co-author networks and country cooperation networks in biological breedingfield. Analyzed the evolution phenomenons of eighteen-year knowledge in biological breeding field, allthe results were evaluated based on the model.This research has drawn the following conclusions based on above studies: Molecular marker-assistedbreeding, genomics, germplasm selection research is the main research area of biological breeding field.The United States cooperates with most countries in the world, which occupied the first place inbiological breeding field. China’s position raised in recent years as the cooperations increased. Biological breeding field will be more prosperous as the academic exchanges increase among differentcountries in the future.The constructed model has revealed compositions and changes of the knowledge structure, fulfilled thephenomenon identifications of the knowledge evolution, recognised research focus and potential topicsin biological breeding field.