pfa

https://ec.europa.eu/programmes/horizon2020/en/news/modelling-climate-impacts-crops-and-pests

Dear Geetika,m any crop models integrate the possibility to combine pest models and try to analyze the impact of pest and diseases, see more about this e.g.:

http://conference.ifas.ufl.edu/pest/index.html https://communications.ext.zalf.de/sites/crop-

modelling/SitePages/iCROPM2016.aspx

However there are some problems to make it perfect now. Some reasons for this are the impossibility to predict changes of pests themselves, the insufficient representation of the complexities of the relations in the system „climate-plant-pest-soil-socio-economic implications“, still too large uncertainties of climate and crop models, still too large spatial and temporal scales of used climate models and missing important physiological processes, like compensation and stimulation responses in crop models. These processes are the causes for changes in function norms and norms of responses to the environment of the new system “diseased plant”. Source-sink relationships are integrated inadequate and the influences of plant pests and diseases also. Many plant pests and diseases are capable of manipulating host plants’ source-sink-relationships, directly or indirectly. See more:

https://link.springer.com/article/10.1007/s10343-017-0383-y https://www.researchgate.net/publication/318339252_Impacts_of_plant_pests_on_the_yield_forming_process_taken_as_a_basis_for_simulation_with_crop_growth_models_New_challenges_-_old_problems

But it is a very interesting field of research. To solve the problems is urgently needed. Try it!

Right now we can use pest weather forewarning models in realistic manner using stastical models

Multiple regression model a simple approach-

You can take the daily weather data for during the progress of wheat crop at specific intervals, say weekly, forenightly or stage wise, and also record the pest population data for corresponding periods. Also collect the weather data for Study the relationship between the weather parameters and the pest population. Take significant weather variables and develop the multiple regression models using pest population as dependent and significant weather variables as independent variables. But, it is essential to validate the model before confirming the model for decision making and pest forewarning with good accuracy.

Thank you all for your suggestions