Sheath blight of rice, caused by Rhizoctonia solani AG 1. 1a, has become the most important disease and caused serious yield losses in some major rice-growing regions in China in recent years. In the present study, fi...Sheath blight of rice, caused by Rhizoctonia solani AG 1. 1a, has become the most important disease and caused serious yield losses in some major rice-growing regions in China in recent years. In the present study, field plot experiment was conducted to examine the relationships between disease intensity and inoculum density （ID）, the seasonal disease epidemic dynamics, and yield reductions due to disease damages. Results from the experiment demonstrated that the areas under progress curves of disease severity and those of percent rice tillers diseased were positively and closely related to the relative initial ID of the pathogen. The inoculum density-disease （IDD） relationships were simulated and the impractical linear models were obtained. Both logistic and Gompertz functions could be used to simulate the disease progress dynamics in time, but the progress curves of the disease severity were modeled better by the Gompertz than by logistic function. However, the Richards function was found to be the best in simulating the disease progress curves when a most appropriate value was chosen for the shape parameter m by using the computer software Epitimulator. Sheath blight infection decreased rice yield very significantly and a yield reduction of 40% was recorded in rice crop with the highest inoculum density. Rice yield was linearly and negatively correlated with the disease severity and the percent tillers affected. The simulated models for all these relationships were computed through executing Epitimulator software and were presented in this paper.展开更多
The objective of the present study was to develop a computer software for simulating the temporal development of plant disease epidemics using Richards, logistic, Gompertz, monomolecular, and exponential functions, re...The objective of the present study was to develop a computer software for simulating the temporal development of plant disease epidemics using Richards, logistic, Gompertz, monomolecular, and exponential functions, respectively, and for predicting disease with a fitted model. The software was programmed using Visual Basic （VB6.0） and packaged with the Wise Installation System. The Fibonacci （＇0.618＇） section strategy was used to find out the most appropriate value for the shape parameter （m） in Richards function simulation through looping procedures. The software program was repeatedly tested, debugged and edited until it was run through favorably and produced ideal outputs. It was named Epitimulator based on the phrase ＇epidemic time simulator＇ and has been registered by the National Copyright Department of China （Reg. no. 2007SR18489）. It can be installed and run on personal computers with all versions of Windows operational systems. Data of disease index and survey time are keyed in or imported from Access files. The output of fitted models and related data of parameters can be pasted into Microsoft Excel worksheet or into Word document for editing as required and the simulated disease progress curves can be stored in separate graphic files. After being finally tested and completed, Epitimulator was applied to simulate the epidemic progress of corn northern leaf blight （Exserohilum turcicum） with recorded data from field surveys of corn crops and the fitted models were output. Comparison of the simulation results showed that the disease progress was always best described by Richards function, which resulted in the most accurate simulation model. Result also showed that forecast of northern leaf blight development was highly accurate by using the computed progress model from Richards function.展开更多
文摘Sheath blight of rice, caused by Rhizoctonia solani AG 1. 1a, has become the most important disease and caused serious yield losses in some major rice-growing regions in China in recent years. In the present study, field plot experiment was conducted to examine the relationships between disease intensity and inoculum density （ID）, the seasonal disease epidemic dynamics, and yield reductions due to disease damages. Results from the experiment demonstrated that the areas under progress curves of disease severity and those of percent rice tillers diseased were positively and closely related to the relative initial ID of the pathogen. The inoculum density-disease （IDD） relationships were simulated and the impractical linear models were obtained. Both logistic and Gompertz functions could be used to simulate the disease progress dynamics in time, but the progress curves of the disease severity were modeled better by the Gompertz than by logistic function. However, the Richards function was found to be the best in simulating the disease progress curves when a most appropriate value was chosen for the shape parameter m by using the computer software Epitimulator. Sheath blight infection decreased rice yield very significantly and a yield reduction of 40% was recorded in rice crop with the highest inoculum density. Rice yield was linearly and negatively correlated with the disease severity and the percent tillers affected. The simulated models for all these relationships were computed through executing Epitimulator software and were presented in this paper.
基金supported by the National Programs of Public-Beneficiary Sectors Funds,Ministryof Science and Technology,China(200803024)
文摘The objective of the present study was to develop a computer software for simulating the temporal development of plant disease epidemics using Richards, logistic, Gompertz, monomolecular, and exponential functions, respectively, and for predicting disease with a fitted model. The software was programmed using Visual Basic （VB6.0） and packaged with the Wise Installation System. The Fibonacci （＇0.618＇） section strategy was used to find out the most appropriate value for the shape parameter （m） in Richards function simulation through looping procedures. The software program was repeatedly tested, debugged and edited until it was run through favorably and produced ideal outputs. It was named Epitimulator based on the phrase ＇epidemic time simulator＇ and has been registered by the National Copyright Department of China （Reg. no. 2007SR18489）. It can be installed and run on personal computers with all versions of Windows operational systems. Data of disease index and survey time are keyed in or imported from Access files. The output of fitted models and related data of parameters can be pasted into Microsoft Excel worksheet or into Word document for editing as required and the simulated disease progress curves can be stored in separate graphic files. After being finally tested and completed, Epitimulator was applied to simulate the epidemic progress of corn northern leaf blight （Exserohilum turcicum） with recorded data from field surveys of corn crops and the fitted models were output. Comparison of the simulation results showed that the disease progress was always best described by Richards function, which resulted in the most accurate simulation model. Result also showed that forecast of northern leaf blight development was highly accurate by using the computed progress model from Richards function.
