Therefore, it was concluded that HCMV CPI-613 infection in mouse cells was blocked at the IE stage. However, it has been reported that the laboratory strains of HCMV experience profound mutations during replication in human fibroblast cells. The mutations lead not only to the attenuation of HCMV but also to the narrowing of cell tropisms. The mutation of HCMV cell tropism occurred at gene UL128-131 since the repaired UL128-131 caused the recovery of cell tropisms. Therefore, this time using both the clinical HCMV strain and the repaired HCMV, we reentered the study of HCMV infection in mouse cells. At this point, we found that HCMV could produce IE proteins and some early proteins, but failed to replicate DNA. We now conclude that HCMV infection in mouse cells was blocked before DNA replication. Unlike what takes place in RNA viruses, the species-specific restriction of CMV occurs not at the entry to cells but at the post-DNA replication stage for MCMV infection in human cells and at the early stage before DNA replication for HCMV infection in mouse cells. Cellular proteins, including transcription repressors, have suppressive effects on viral gene expression and represent an intrinsic, host-cell defense. PML is the scaffold protein and is essential for the formation of ND10 because PML knockout cells lack ND10, and inducing exogenous PML into PML knockout cells can restore ND10. SUMOylation is another characteristic of PML and makes it possible for PML to interact with many other nuclear proteins. There are more than 70 different cellular proteins that have been found to be related to ND10, and the proteins that interact with PML have already been reviewed by Dr. Van Ostade1 and colleagues. The most frequently investigated PML-interacting proteins include Daxx and SP100. ND10 structure can be shown by indirect immunofluorescence using anti-PML, -Daxx, and -SP100 antibodies. The inhibitory effects of ND10 proteins on viral infection have been demonstrated on PML, Daxx, and SP100. The effects of the ND10 structure on viral infection have not been determined. ND10’s defensive role in the infection process can be inferred by the fact that several herpesviruses are required to disrupt it. We previously showed that IE1 is the only protein of MCMV that is capable of disrupting the ND10 of mouse cells. In that prior study, we reported that the IE1 of MCMV also colocalized with the ND10 of human cells; however, IE1 lost its ability to disperse ND10 in cytomegalovirus cross-species infections. This discovery supports the theory that ND10 might block the productive crossspecies infection of cytomegalovirus. Consistent with this speculation, we found that human-cell ND10 proteins, such as SP100, PML, and Daxx, strongly suppress MCMV viral gene expression, and mouse cell ND10 protein also represses HCMV gene expression. Interestingly, HCMV laboratory-strain infections in mouse cells can produce IE1 but not IE2, even though IE1 and IE2 share a promoter and the first three exons, all of which suggests that splicing regulation also plays a role in blocking HCMV infection in mouse cells. In summary, we discovered that intrinsic cellular defense mechanisms participate in the blocking of CMV cross-species infection and that CMV IE1 loses its ability to disperse ND10. In HCMV-infected mouse cells, only IE1 can be detected in laboratory-strain-infected mouse cells, but clinical strains and UL128-131-repaired strains can produce many more viral gene products. Future studies will focus on identifying the additional mechanisms that are involved in blocking cross-species infection. Agriculture is an information-intensive industry from an essential point of view. Many factors such as sowing date, soil type, fertilizer, location, hybrid, season duration, etc. influence yield and yield components of a grain crop and they are well needed by agricultural experts. Exploring the agricultural technologies of traits related to the control of crop grain yield reductions has a poor record of application. Furthermore, experimental studies remain at an empirical level in which observational evidence is sought for yield increase by genotypes under limited spatial and temporal tests. The utility of these results is limited because there is usually considerable genotype 6 environment interaction. For example, maize yield is a function of the number harvested kernels per unit land area and the individual kernel weight. Kernel weight and its development show a wide variability due to genotype, environment, crop management, and all possible interactions. Commercial maize hybrids differ markedly in the patterns behind differences in final KW. Some research thus expects to build an intelligent agricultural information system to assist experts and to help improve agricultural technologies. Recently, agricultural and biological research studies have used various techniques of data mining for analyzing large data sets and establishing useful classification patterns within these data sets. However, data mining methods are still expected to bring more fruitful results. Recently, intelligent data mining and knowledge discovery by artificial neural network, decision trees, and feature selection algorithms have become the important revolutionary issues in prediction and modeling. Data mining problems often involve hundreds or even thousands of variables. Machine learning methods have three main steps. The first step is extracting/collecting the n-dimensional features vector in order to reflect different aspects of the conditions with a class label attached.