Abstract
Deterministic and stochastic versions of the logistic model were applied for describing increase of plant diseases. The stochastic version of the logistic model is based on the addition of a random component to the growth rate per unit infection, as previously used for analysis of insect population abundance. The models were fitted to disease progress curves derived from a real data set consisting of disease assessments of melon plants in Israel infected by zucchini yellow mosaic virus (ZYMV). The results showed that the random component in the stochastic version was estimated as being small. The autocorrelations of the residuals were lower for the stochastic version of the logistic model than the corresponding values of the deterministic logistic model. For small data sets the statistical advantages of the stochastic version of the logistic model over the (simpler) deterministic version were not significant.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
