Pest Forecasting

One of the most important approaches of managing pests & diseases particularly those of economic importance is forecasting as it can predict the likelihood of occurrence of a pest and disease outbreak. Techniques such as Artificial Neural Network (ANN) is used to develop an algorithm that will forecast the population of pest and diseases based on the forecasted weather condition such as maximum temperature, minimum temperature, humidity, wind speed, rainfall, pressure, and solar radiation. Such algorithm is considered as a pests & disease – warning system that gives information to the farmers of the coming pest and disease, the infestation and the infection period, hence, farmers can be able to develop control measures to prevent further damage and spread of pest and diseases.
Pest and Disease Weather Parameter Conditions Pest Infection
Banana Flower Thrips    
Bugdok Disease    
     
Pest and Disease Weather Parameter Conditions Pest Infection
Cacao Pod borer    
Cacao pod rot    
     
Pest and Disease Weather Parameter Conditions Pest Infection
Coffee berry borer    
Coffee rust    
     
Pest and Disease Weather Parameter Conditions Pest Infection
Lanzones Mussel Scale Insect    
Lanzones Leaf Bright    
     
Pest and Disease Weather Parameter Conditions Pest Infection
none    
rubber corynespora leaf fall disease    
     
Pest and Disease Weather Parameter Conditions Pest Infection
Citrus Rind Borer    
sooty mold of pomelo