Community Research and Development Information Service - CORDIS


PCT Report Summary

Project ID: 666534

Periodic Reporting for period 1 - PCT (Plant CT - Making Plants Healthier)

Reporting period: 2015-04-01 to 2015-09-30

Summary of the context and overall objectives of the project

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 CT™ 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 CT™ 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 SmartVineyard™ system developed to increase production yield and reduce wasteful and expensive fungicide spraying in vineyards. Using high-tech sensors, SmartVineyard™’s technology allows for the precise measurement of the climate and microclimate parameters which play an important role in the development and spreading of four key grape diseases (powdery mildew, downy mildew, black rot, grey mold). 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.
The Plant CT™ project intends to scale up the existing sensing and disease forecasting SmartVineyard™ system into a comprehensive Plant CT™ solution by adapting the currently existing system to additional plants (e.g. apples, tomatoes, potatoes, strawberries) that are sensitive to diseases and are frequently treated with chemicals and by designing and building additional sensors as well as advanced forecasting models. Development of the webclient allows thst business and production related opportunities are revealed by customers via the user interface. The Plant CT™ solution allows farmers to gain considerable benefits from a fully reliable decision support system: they will be able to make fact-based decisions on selecting the proper treatment

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

The kickoff of the project started 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. Besides the implementation of an Advanced Field book has also been started with multiple functions for logging production-related data. This module is strongly related to the SmartPhone Scouting Module which allows users to record any kind of on-site observations and not only upload the information to the related user account but to share them with other professionals. The two modules add the capabilities of recording, analyzing human related parameters.
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.
To communicate the project results, a dissemination platform was created to enable users and leads to share their ideas and gain valuable information about the project.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

The Plant CT™ project intends to scale up the existing sensing and disease forecasting SmartVineyard™ system into the comprehensive Plant CT™ 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 CT™ 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. This results in reduced use of chemical sprayings, resulting in healthier crops and reduced costs.

The development of the Plant CT™ involves three main areas of which the following tasks were started / completed during the first reporting period:
Firstly, the development of advanced sensors that are currently unavailable / unreliable / big / heavy, and their integration into a compact, self-contained device will contribute to larger agro-data sets to be analyzed, which could play a key role in the prediction of fungal diseases. Within the first reporting period the implementation of the prototype of advanced sensors has been started. The so-called LHT sensors was designed to measure Leaf moisture, humidity and temperature. GEO sensor captures multiple soil parameters like humidity, Ph level or temperature. The first reporting period involved the design of the hardware platform, the delivery of state-of-the-art IoT communication as well as the prototype of advanced sensors listed above. All in all, tasks included the development of the mechanics, electronics and the communication protocol and will deliver prototypes to be tested and validated on the field by the end of the first year in the project.
Secondly, as additional hardware components and advanced sensors mean qualitatively and quantitatively more advanced data, opportunities for analytics and prediction will significantly increase. Within the reporting period the core software framework has been developed. The objective of the extendible platform is to serve as the basis of an ultimate agro decision dashboard. During the reporting period the user interface design has been completed. During the development, principles of User Experience as well as feedback of early adopters were taken into consideration.
Thirdly, a wide range of new prediction / forecasting models are to be developed which incorporate new forms of data and allow farmers to make more accurate decisions. Forecasts will help planning plant protection activities as well as budgeting.
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 seeking 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. Plant CT™’s novelty lies in:
• Remote diagnostics of diseases through direct and indirect methods
• 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
• Real time, actionable information on diseases available online on desktops or smartphones
• ’Easy Deployment’ enabling installation of Plant CT™ systems by a single person, without any IT or engineering

Related information

Record Number: 186589 / Last updated on: 2016-07-14