Response of Wheat Fungal Diseases to Elevated Atmospheric CO2 Level

Infection with fungal pathogens on wheat varieties with different levels of resistance was tested at ambient (NC, 390 ppm) and elevated (EC, 750 ppm) atmospheric CO2 levels in the phytotron. EC was found to affect many aspects of the plant-pathogen interaction. Infection with most fungal diseases was usually found to be promoted by elevated CO2 level in susceptible varieties. Powdery mildew, leaf rust and stem rust produced more severe symptoms on plants of susceptible varieties, while resistant varieties were not infected even at EC. The penetration of Fusarium head blight (FHB) into the spike was delayed by EC in Mv Mambo, while it was unaffected in Mv Regiment and stimulated in Mv Emma. EC increased the propagation of FHB in Mv Mambo and Mv Emma. Enhanced resistance to the spread of Fusarium within the plant was only found in Mv Regiment, which has good resistance to penetration but poor resistance to the spread of FHB at NC. FHB infection was more severe at EC in two varieties, while the plants of Mv Regiment, which has the best field resistance at NC, did not exhibit a higher infection level at EC. The above results suggest that breeding for new resistant varieties will remain a useful means of preventing more severe infection in a future with higher atmospheric CO2 levels

Assessment of different genetic distances in constructing cotton core subset by genotypic values*

One hundred and sixty-eight genotypes of cotton from the same growing region were used as a germplasm group to study the validity of different genetic distances in constructing cotton core subset. Mixed linear model approach was employed to unbiasedly predict genotypic values of 20 traits for eliminating the environmental effect. Six commonly used genetic distances (Euclidean, standardized Euclidean, Mahalanobis, city block, cosine and correlation distances) combining four commonly used hierarchical cluster methods (single distance, complete distance, unweighted pair-group average and Ward’s methods) were used in the least distance stepwise sampling (LDSS) method for constructing different core subsets. The analyses of variance (ANOVA) of different evaluating parameters showed that the validities of cosine and correlation distances were inferior to those of Euclidean, standardized Euclidean, Mahalanobis and city block distances. Standardized Euclidean distance was slightly more effective than Euclidean, Mahalanobis and city block distances. The principal analysis validated standardized Euclidean distance in the course of constructing practical core subsets. The covariance matrix of accessions might be ill-conditioned when Mahalanobis distance was used to calculate genetic distance at low sampling percentages, which led to bias in small-sized core subset construction. The standardized Euclidean distance is recommended in core subset construction with LDSS method