Extreme meteorological disaster effects on grain production is mainly determined by the interaction between danger degree of hazard-induced factors and vulnerability degree of hazard-affected bodies.  This paper treats physical exposure, sensitivity of the response to the impact, and capabilities of disaster prevention and mitigation as a complex system for vulnerability degree of hazard-affected bodies, which included the external shocks and internal stability mechanism.  Hazard-induced factors generate external shocks on grain production systems though exposure and sensitivity of hazard-affected body, and the result can be represented as affected area of grain.  By quantile regression model, this paper depicts the quantitative relationship between hazard-induced factors of extreme meteorological disaster and the affected area in the tail of the distribution.  Moreover, the model of production function have also been utilized to expound and prove the quantitative relationship between the affected area and final grain output under the internal stability mechanism of the agricultural natural resources endowment, the input factors of agricultural production, and the capacity of defending disaster.  The empirical study of this paper finds that impact effects of drought disaster to grain production system presents the basic law of “diminishing marginal loss”, namely, with the constant improvement of the grade of drought, marginal affected area produced by hazard-induced factors will be diminishing.  Scenario simulation of extreme drought impact shows that by every 1% reduction in summer average rainfall, grain production of Jilin Province will fell 0.2549% and cut production of grain 14.69% eventually.  In response to ensure China’s grain security, the construction of the long-term mechanism of agricultural disaster prevention and mitigation, and the innovation of agricultural risk management tools should be also included in the agricultural policy agenda.

To evaluate the possible genetic interrelationships between flour components and the sedimentation volume (SD), a doubled haploid (DH) population comprising 168 lines were used to identify the conditional quantitative trait loci (QTLs) for SD in three environments. Ten additive QTLs and 15 pairs of epistatic QTLs were detected for SD through unconditional and conditional QTL mapping. Three major additive QTLs were detected for SD conditioned on the seven quality traits. Two additive QTLs were found to be independent of these traits. Three additive QTLs were suppressed by three of the seven traits because of non-detection in unconditional mapping. Three pairs of epistatic QTLs were completely affected by the seven traits because of detection in unconditional mapping but no-detection in conditional mapping. Twelve pairs of epistatic QTLs were detected in conditional mapping. Our results indicated that conditional mapping could contribute to a better understanding of the interdependence of different and closely correlated traits at the QTL molecular level, especially some minor QTLs were found. The conditional mapping approach provides new insights that will make it possible to avoid the disadvantages of different traits by breeding through molecular design.