Opendata, web and dolomites

Report

Teaser, summary, work performed and final results

Periodic Reporting for period 5 - PCT (Plant CT - Making Plants Healthier)

Teaser

The single largest problem in agriculture today is that farmers lack a method of accurately, efficiently and swiftly evaluating plant health. In order to avoid disease related yield loss, agricultural producers use expensive and environmentally harmful pesticides. Numerous...

Summary

The single largest problem in agriculture today is that farmers lack a method of accurately, efficiently and swiftly evaluating plant health. In order to avoid disease related yield loss, agricultural producers use expensive and environmentally harmful pesticides. Numerous studies have linked the use of these chemicals to a myriad of social and environmental problems, ranging from decreased long term soil fertility or rapid decrease of bee populations. As a consequence, oversparying is prevalent as an important method of preventing crop diseases. Ideally, the decision of when to spray should be dependent on the highly complex interaction of a wide range of environmental and phenological factors. The problem is further strengthened by farmlands’ size and microclimate variability which could vary even within a smaller area of a few hectares. As a result, minor differences in humidity or temperature may modify the appearance and the intensity of diseases.

Due to a lack of time, information and appropriate solutions, most farmers are unable to monitor the farmland microclimates when planning their plant protection strategy and consequently are exposed to yield loss and overspraying. Since producing the highest quality crop with a maximized yield requires the real-time measurement and actionable analysis of a large number of plant-related external factors. These factors are meteorological, geological, and human-related. Measuring and processing such parameters is at the core of any decision-support system intending to streamline the production of farmlands. By doing so, it could stop superfluous use of expensive and environmentally harmful chemical agents while reducing yield loss, saving European farmers billions.

The Plant CTâ„¢ project intends to address the major challenges of plant protection directives, like cost efficiency or sustainability. The outcome of the Horizon 2020 SME Instrument project is expected to be the release and commercialization of the Plant CTâ„¢ solution, a network of compact measuring devices on cultivated areas, which arms agricultural producers with precise, individualized data and recommendations. By deploying devices at several locations it is possible to quantify agronomically important factors and to precisely determine the exact plant disease risk (and other important metrics, such as irrigation) at any particular location on a farmland.
The proof of concept is SmartVineyardâ„¢ system developed to increase production yield and reduce wasteful and expensive fungicide spraying in vineyards. Devices upload the measured data onto the server, where scientifically validated algorithms and mathematical models are applied to determine the probability of infection in a given territory. This information can be accessed by the user on any internet connected device, providing farmers with a decision support system with forecasts and alerts on diseases to assist in plant protection.

As the output of the project, a commercialisable smart agriculture system will be developed which not only increases the yield of European agricultural producers, but also promotes a more sustainable and ecologically friendly form of farming throughout the EU.
Professional agricultural producers are in seek of applying a system that helps reducing costs and increasing yield. Remote data access and farmland monitoring are also in demand by agents working lands in multiple areas.
The main advantage of the Plant CTâ„¢ system is that it is an easily deployable smart agriculture system which provides a constant source of real time actionable data that helps reduce production costs and increase yield in a user friendly, accessible way. The outcome of the project is a system of small, easily installable, compact and inexpensive precision sensors delivering easy-to-understand actionable information including highly reliable automated diagnostics.

Work performed

The project tasks distributed into six work packages as described in the Technical Annex. The well-organized management style contributed to the smooth workflow in software and hardware development as well as to the quick implementation and application of scientific results. Hardware development tasks involved both the upgrading of existing sensors (the LHT and precipitation) and the prototyping of a wide range of more advanced ones not existing in the previous Smart Vineyard system. To connect these sensors and provide an appropriate unit for data-transfer, engineers of the project designed and developed a fully operational, solar powered central unit.
On the software side, the User Interface was designed to support decision making, as well as to display data captured by the sensor units. During the development, principles of User Experience as well as feedback of early adopters were taken into consideration. The user interface was designed upon the preferences of existing customers (early adopters) of Smart Vineyard with many options for visualizing and filtering information. Meanwhile, professional workshops were organized with the aim of reaching agreement with professionals and farmers on testing. The events organized for professionals and farmers helped the company to inform the press and create a database about potential early-adopters. Our cooperation with the academic field has proved to be most effective when bringing a researcher part-time on board, working at the company’s premises on plant disease models.

Final results

The Plant CTâ„¢ project intends to scale up the existing sensing and disease forecasting SmartVineyardâ„¢ system into the comprehensive Plant CTâ„¢ solution by extending the existing system with additional sensors and to support more plants (e.g. apples, tomatoes, strawberries) that are also sensitive to diseases and are frequently treated with chemicals.
The Plant CTâ„¢ solution allows farmers to gain considerable benefits from a fully reliable decision support system: they get explicit recommendations for action from the decision support system based on prediction models, but also able to drill down into the captured data and make decisions on selecting the proper treatment, gaining precise information on the status of diseases on their land.

As the output of the project, a commercialisable smart agriculture system will be developed which not only increases the yield of European agricultural producers, but also promotes a more sustainable and ecologically friendly form of farming throughout the EU.
Plant CT™’s novelty lies in:
• Scientifically validated models that turn data into actionable disease forecasts and explicit action recommendations
• Highly precise parcel-level data acquisition, microclimate monitoring and weather forecasting
• Data based decision support to optimize yield, quality, and pesticide use
• User-friendly, intuitive interface to display disease predictions with options for filtering and analysis
• ’Easy Deployment’ enabling installation of Plant CT™ systems by a single person, without any IT or engineering skills

The end-user\'s return on investment on the Plant CTâ„¢ system will consist of:
• Primary elements
o The value of the avoided yield loss
o Increased efficiency of pesticide use
o Increased crop quality
• Secondary elements
o Cuts in traveling costs due to remote diagnostics and data access
o Decreasing working hours spent with plant protection
o Increased efficiency of irrigation
o Decreased chemical residues in end-product

Website & more info

More info: http://smartvineyard.com/horizon-2020/.