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 | ||