14TSB_DataExpl Crowd-Sourced Prediction of Plant Pest and Disease Occurrence using Mobile Apps

Growing Interactive, the industrial lead partner of the project, produces the leading on-line software and apps that gardeners and small-scale farms use to plan the edible crops they grow and achieve increased levels of success. Over a quarter million gardeners and farmers have used their software and apps. They hold a wealth of location-based information on which crops, varieties and quantities gardeners are growing in their location and this year they are extending the recording to include dated observations of pests and diseases on crops (launching May 2014). Event-based journalling has been the most requested new feature for their software and they will be adding social feedback elements to reward reporting.

We propose that this data be statistically analysed in conjunction with meteorological information to develop predictive models for pest and disease emergence on crops. By developing advanced map-based visualisations, the vast quantity of crowd-sourced data can be analysed in depth and used to refine predictive models. Meteorological information and weather forecasts can then provide significantly improved pest prediction for growers for the current growing season specific to their location.

Growing Interactive (GI), the industrial lead partner of the project, produces leading online software and apps that gardeners and small-scale farms use to plan the edible crops they grow and achieve increased levels of success. Over one quarter million gardeners and farmers have used the software and apps. GI holds a wealth of location-based information on which crops, varieties and quantities gardeners are growing in their location and they are extending the recording to include dated observations of pests and diseases on crops.

This project will statistically analyse the crowd-sourced pest and disease observations recorded in their apps in conjunction with meteorological information to develop much more accurate predictive systems along with innovative visualisations to help predict pest and disease emergence on crops. Meteorological information and weather forecasts can then be used to provide significantly improved pest prediction for growers for the current growing season specific to their location. These will form the basis of new services for GI's customers, the horticultural industry and agriculture, helping growers to reduce losses due to plant pests and diseases.

1. Economic Impact: Within the consortium, supplying data feeds from the pest prediction models opens up new markets - an estimated 33% increase in revenue to Growing Interactive, growing to 43% over 5 years and new data products. Beyond the consortium, increased efficiency (though decreased losses) in agriculture has wide ranging benefits, lowering prices and providing even greater benefit to the economy as a whole. On completion of the project, we would like to extend the system to developing countries where mobile phones deliver the internet, working with NGOs to tackle the problem of insect damage in subsistence farming.

2. Social Impact: The 2008 Cabinet Office Study 'Food Matters' highlights the health gains associated with fresh produce:
"Reaching the 5 A DAY target for fruit and vegetable consumption could mean that around 42,000 premature deaths are avoided each year... [the Government] will adopt a specific target of increasing fruit and vegetable consumption in low-income young families." [section ES36]. Growing Interactive's garden planning apps, when combined with the pest and disease prediction service, dramatically increase the success of home growing, providing access to fresh, healthy produce at minimal cost. Studies have also shown that growing food brings substantial benefits across a wide range of health and social issues.

3. Environmental Impact: The 'Food Matters' study states: "The food chain has huge environmental impacts. Reducing the food chain's dependence on energy, water and other resources will reduce its exposure to future increases in resource prices. Reducing the quantity of waste and GHG emissions can improve resource efficiency and anticipate the changes required for the transition to a low-carbon economy."
Improved plant pest and disease prediction impacts almost all of the factors which contribute to the food system's environmental impact: increased efficiency through decreased crop spoilage, reduced exposure to resource price fluctuations, less dependence on expensive pesticides and fungicides and the negative environmental impact of such inputs. More localised pest predictions help make local food systems more productive and competitive, lowering environmental impact as transportation costs are reduced. Pest and disease prediction is particularly useful for organic
production techniques, which by nature have considerably lower environmental impact and form an important part of the transition to a low-carbon economy.