Studies On The Evaluating Models Of Crop Resistance To Disease And Pest

Crop production has being bothered by disease and pest for a long time, which sometime cause a disastrous result. To overcome this difficulty, international and internal agronomists and crop breeders have done many works, and gained some good effects. Lots of researching results and productive practice both point out that, for solving disease and/or pest disserving crop production, it is the most essential, most effectual, and most economical method to breed and popularize crop varieties which have the characteristics of resistance to disease and/or pest. Because of these factors such as the variation of strain isolates, the differentiation of pathogenicity, the possible interaction between the host and pathogeny, and the migration of the pest, and their improvement of drug-fast ability, et al, none of the released crop varieties have the durable resistance to disease and/or pest, which is in no favor to the sustainable agricultural development. So, it becomes the current goal for breeders to select and breed such crop cultivars which not only have the characteristics of high yield, good quality, and the ability of resistance to disease and/or pest in current year, but also do this in the coming years.Currently, the evaluation of yield, quality and resistance to disease and/or pest of the tested cultivars in the regional trials are progressing separated, and cannot combine them together because no methods of statistical analysis for synthesis are perfect. This could cause the embarrassed complexion which some released varieties passed the resistance test express no or lower capability of resistance to disease and/or pest in the actual production (Ma Chun et al, 1999). Therefore, to evaluate the tested varieties in the regional trials and achieve more exact results, it is necessary to combine the yield, quality and resistance together. Moreover, in the regional trials, there are old varieties exchanged by the new ones, and the tested sites may bedifferent among years, even sometimes there are missing data in some tested sites. Therefore, to study the evaluating models based on such unbalanced data; it is significant in both theoretics and crop productive practice. Consequently, this is very important to identify the resistance of crop varieties, analyze the capability of durable resistance, examine and approve varieties with resistance to disease and/or pest, and draw strategies of sustainable management of the disease and pest.The main innovations of this paper are the following. (1) Based on the regional trails of the transgenic cotton varieties with resistance to bollworm [Helicoverpa armigera (Hubner)]. a new method of factor regression model (FRM) analysis was put forward to combine the characteristics of yield, quality and the resistance to pest together for evaluating the tested varieties. This method can also be used in evaluating the resistance to disease of the tested varieties, combined with yield and quality, if there were some susceptible cultivars planted with the tested ones. (2) Algorithms for sums of squares and covariance matrices using Kronecker products (Moser & Sawyer, 1998) were extended to three and more factor design of experiments. Kronecker product algorithms have some advantages such as straightness, briefness and easy realization by computer. The algorithms can be applied to fixed, random, or mixed linear models and then be extended for use in one-factor randomized block design and the cotton regional trials with missing data of the Yellow River region as examples of application in unbalanced data. (3) Generalized linear models (GLM) were used to study the interaction between cotton cultivars and Verticilium dahliae strains, which was compared with both the ordinary analysis of variance (ANOVA) and the additive main effects and multiplicative interaction (AMMI) analysis. The results showed that there was significant interaction between cotton cultivars and Verticilhim dahliae strains. GLM analysis is an effective statistical tool for analyzing the interaction of the two-fac...