[Objective] The paper was to study the disease grading criterion and assess the yield loss caused by maize rough dwarf disease. [Method] The ear lengths and yields of each healthy and infected plant of 5 cultivars wer...[Objective] The paper was to study the disease grading criterion and assess the yield loss caused by maize rough dwarf disease. [Method] The ear lengths and yields of each healthy and infected plant of 5 cultivars were measured during 2009 and 2010. The severity grading criterion was deduced according to the ear length ratios. [Result]When the ratios were 0.92-1.00, 0.67-0.91, 0.41-0.66, 0.10-0.40 and 0, its corresponding disease grading criterions were 0, 1, 3, 5 and 7, respectively. The severity grading criterion was closely correlated to the yield loss. By analyzing the data of disease indexes and yield loss rates of 27 cultivars with DPS （Data Processing System）, the regression equations were established respectively. According to the comparison with each other, the Weibull Model was proved to have the highest fitting degree. Validating with the disease indexes of 27 cultivars in 2010, the equation supported the feasibility of the equation to predict the yield loss caused by maize rough dwarf disease. [Conclusion] The paper provided theoretical basis for further study on maize rough dwarf disease.展开更多
基金Supported by "the Eleventh Five Year" Science and Technology Project of Anhui Province(08010302172)
文摘[Objective] The paper was to study the disease grading criterion and assess the yield loss caused by maize rough dwarf disease. [Method] The ear lengths and yields of each healthy and infected plant of 5 cultivars were measured during 2009 and 2010. The severity grading criterion was deduced according to the ear length ratios. [Result]When the ratios were 0.92-1.00, 0.67-0.91, 0.41-0.66, 0.10-0.40 and 0, its corresponding disease grading criterions were 0, 1, 3, 5 and 7, respectively. The severity grading criterion was closely correlated to the yield loss. By analyzing the data of disease indexes and yield loss rates of 27 cultivars with DPS （Data Processing System）, the regression equations were established respectively. According to the comparison with each other, the Weibull Model was proved to have the highest fitting degree. Validating with the disease indexes of 27 cultivars in 2010, the equation supported the feasibility of the equation to predict the yield loss caused by maize rough dwarf disease. [Conclusion] The paper provided theoretical basis for further study on maize rough dwarf disease.
