The Practical Application of Agricultural Genetic Breeding Technology in Elm Cultivation Based on Big Data Analysis

Abstract

In order to explore the role of agricultural genetic breeding technology in elm cultivation, this paper improves the big data technology. According to the test data verification requirements, based on the Monte Carlo idea, a TDSTI statistical test method is proposed, and a set of judgment criteria for the significance of spatio-temporal autocorrelation is given. Moreover, in order to make the observed variables of the time lag series have a clearer geographical significance, the obtained spatio-temporal weight matrix is subjected to row standardization. In addition, this paper combines big data technology and agricultural genetic breeding technology to study the cultivation of elm trees. Finally, this paper conducts a correlation analysis between the distance matrix generated by cluster analysis of leaf shape traits and the distance matrix generated by cluster analysis of SSR molecular markers. The research results show that agricultural genetic breeding technology can play an important role in the cultivation of elm.