So, what's the problem
An estimated 30-40% of crops are lost each year to pests. Reducing this loss by just 1% could feed millions more people. Over a third of the world’s population – set to reach 9 billion by 2050 – is supported by 500 million smallholder farmers, so supporting farmers in their fight against pests is a global food security emergency. The key is knowledge.
What is this project doing?
With this in mind, and understanding how important food security is to developing nations, this project aim to investigate the feasibility of developing an early warning system to alert both farmers and relevant stakeholders of crop pest and disease outbreaks. This project is being carried out in collaboration with Assimila Ltd; experts in environmental monitoring, modelling and prediction.
Local data on the distribution of crops, pests and diseases are captured at plant clinics which are run regularly in set locations around the world. These data are stored within the Plantwise Knowledge Bank following every clinic, capturing temporal, validated data on pest and disease occurrence. In addition, the Knowledge Bank is populated with pest and disease records from literature, CABI’s projects and datasets from partners. The project, aims to investigate the feasibility of providing early advice on the likely occurrence of pests and disease outbreaks by integrating weather and EO (Earth Observation) data from satellites with day-degree pest development models from the literature and using the Knowledge Bank to validate the model outputs. Additionally, we wanted to investigate forecasting systems which were currently in use in Africa and obtain feedback from potential end users on the likelihood of uptake of the proposed system.
Kenya was chosen as the test country to develop our concepts based on the strength of validation data available in the Knowledge Bank. Initial survey results from plant health stakeholders from both government and industry, highlighted there are relatively few existing systems providing timely early warning advice about the likelihood of particular pest and disease outbreaks to both them and farmers.
A prototype online system was developed specifically for predicting the occurrence of selected maize pests. Outputs of the model were then displayed through an online portal giving information of likelihood of occurrence of different pests. The system aimed to highlight potential problems which farmers may face in the field given recent weather conditions, and directed end users towards extension advice held within the Knowledge Bank. Feedback from potential end-users in Kenya was well received. Sessions highlighted the requirement for a tool to aid decision making given recent climate variability.
This project showed that a simple pest prediction system would be useful to a variety of end users in Kenya and aid in the implementation of IPM. We aim to follow on from this feasibility study in the future with related projects to develop such a system.
Head of Technical Solutions, Plantwise knowledge bank
Director, Plantwise Knowledge Bank
Knowledge Bank Coordinator, East Africa
Content Developer, Plantwise Knowledge Bank