Estimation of area under the disease progress curves in a rice-blast pathosystem from two data points

Attempts were made to estimate the area under the disease progress curve (AUDPC) of rice blast disease caused by Pyricularia grisea from two data points on the disease progress curve. Forty-two rice genotypes were exposed to high disease pressure in a nursery over nine seasons. A conducive condition was created for maximum disease development through high nitrogen application, close spacing and maintenance of high relative humidity. Disease severity was recorded on alternate days beginning from disease initiation until the end of the epidemic. The estimation of AUDPC, and logistic and Gompertz apparent infection rates using either all-points (AP) or two-point (TP) methods revealed significant correlations among them. This was also confirmed through regression analysis and factor analysis. Hence, the estimation of AUDPC from two data points i.e. initial and final disease scores of the disease progress curves is recommended as providing information similar to that from all the data points; this should save valuable time, labour and economic resources.