ABSTRACT. Brazil is one of the largest agricultural commodities producers in the world. One of its main exportation products is raw sugar. Previous researches have identified that this supply chain has several traceability problems. The use of radio-frequency identification and cloud computing can help solving these problems. However, there is no simulation model that allows the simulation of the implementation of RFID on the raw sugar SC. The objective of this paper is to propose a discrete events simulation model for this purpose. It is composed of two parts: a conceptual model and the simulation model, which is implemented on the SIMUL8 software. We considered the supply chain links as modules, and divided these in seven common components related to the transformation and logistics processes. Each of these components has its own variables related to its processes: number and types of resources to be used, the processes costs, and times. It can be used to analyze the cost of each module and the total system costs, the times of each module and the total system time, and the frequency of human and RFID reading errors. The model can be adapted to other supply chains.

ABSTRACT. Pig livestock farming systems face economic and environmental issues. To cope with these issues, we developed a pig fattening unit model able (i) to simulate individual animal performance in interaction with the farming practices and (ii) to evaluate the effects of practices on the technical, economic and environmental performance. Our objective was to define a calibration procedure of the model inputs for a given farm and to evaluate the predictive ability of the model. Twenty-two farms surveyed in western France were calibrated. Three calibration steps were made using practices and building characteristics issued from the survey with (i) same average initial weight for all the farms, (ii) specific average initial weight for each farm, and (iii) with specific average initial weight and adapted feed intake of pigs. Each step improved the prediction. For feed conversion ratio (FCR), the residual standard deviation was reduced from 11.0 to 3.3% of average FCR. Using the model as a decision support tool requires precise description of animal and building characteristics, and practices of the simulated farm. After calibration, the decision support tool can be used to evaluate the effect of changes in farming practices on performance of the farm and propose improved management strategies.

ABSTRACT. Our goal is to implement the CTR Dairy model (Chilibroste et al, 2008) using the Visual Basic for Application language of Microsoft Excel. The CTR Dairy is a mathematical model that attempts to predict nutrient availability in dairy cows managed under discontinuous feeding systems. The model simulates availability of glycogenic, aminogenic and lipogenic nutrients to lactating dairy cows fed discontinuously. The model structure considers input of up to three different feeds fed independently at any time during the day. Feeds are described by their nitrogen (N), carbohydrate and fatty acid fractions. The model continuously (i.e., by minute) predicts release of soluble components from the feeds in the rumen, concentration and absorption of fermentation end products in the rumen, rumen pools of nutrients and microbial biomass dynamics, as well as passage of microbial biomass and non-fermented nutrients from the rumen, in response to various feeding strategies.

ABSTRACT. After several food, consumers have started asking about their food and where it comes from. Alternatives to the dominant “agro-industrial system”, like short food supply chains, have emerged in this context since the 90’s, with several concepts associated concepts of short agri-food supply chains, e.g. localized food systems, territorialized systems and proximity circuits. Since 2010, a new concept has appeared which is named “Agriculture of the middle”, which describes hybrid systems between short and long supply chains, with large production volumes and a structured logistical organization, to relocate retailers’ food procurement. Using a industrial lean management tool, the Value-Stream Mapping (VSM), we analyze the sharing of the added value between different stakeholders within the value chain at different stages of its evolution. We study specifically the real case of an association created in Isère Department by farmers to target new local markets in order to capture a better added value. This work contributes to the analysis and comprehension of the organization of this type of supply chains. It will lead to establish the key factors of success and permit to identify the improvement areas that we can work on, in order to optimize the implementation of the middle systems.

ABSTRACT. Meteorological data coupled with tactical decision support tools is crucial for a farmer to meet societal, environmental and regulatory expectations while optimizing the economic balance of his farm. In these conditions, accurate and reliable meteorological information at the farm scale, or on a field basis, becomes an essential element.

One of the solutions would be to equip itself with a meteorological station. or to use the data from a station belonging to a network.

An alternative is the spatialization of the stations’data which, through statistical methods, allows to estimate the value of a parameter at any point in a territory. This is the choice made from ARVALIS - Institut du végétal to use its models and tools for decision-making.

The use of spatialized data enable the improvement of the reliability of our decision-making tools outputs in order to deliver a tactical advice more relevant. Nevertheless, the difficulty of modeling some meteorological phenomena like high intensity rainfalls and their potentially strong impact on the results, make it necessary to consider taking into account other data sources

ABSTRACT. Our goal is to describe a new decision support tool (Mermaid) used to manage shellfish growing areas. The most important issue in managing shellfish growing areas is the decision of when to open or close an area for harvest. Mermaid helps the regulatory agencies in making these decisions. If an area is open for harvest when pathogens are present, the decision adversely affects public health; however, if the area remain closed too long, the decision adversely affects grower profits. The program is written in Visual Basic for Application (VBA) language and uses Microsoft Excel for input, calculation, and output modules. Figure 1 shows the main menu of the Mermaid program. The program automatically imports the regulatory agency’s data and generates scattergrams that can be used as decision support tools to help decide which shellfish growing areas should be closed and which ones should be open for harvest. An important aspect of the program is that it can be customized for any specific shellfish regulatory agency. In this paper, we employ an edition customized for the Virginia (USA) Department of Shellfish Sanitation (VDSS).

ABSTRACT. Farm contractors have the necessity to quickly know if an agricultural operation request is convenient or not, using their agricultural machineries. Field dimension, shape and slope are key factors to determine operations costs. In addition, high machinery power and characteristics, spare parts, and energy consumption are main components difficult to quickly evaluate to understand the operation benefit or loss. The possibility to estimate such costs beforehand is a critical factor for strategic and tactical decision making. Nowadays there are few web-based mobile applications for agricultural machinery cost estimation to help farm contractors in their decision. Aim of this work is to present a quick and easy-to-use mobile web app, that allow the users to insert their machineries, the shape and the area of the field to evaluate the economic feasibility of a specific field operation. The app was built using the open-source Drupal framework with a module that use a cross-platform approach. Outputs of this app are multiple scenarios with combinations of tractors and equipment inserted by the users with a detailed cost and time analysis based on the requested field operation . The tool is free and does not require any installation on the end-users mobile devices.

ABSTRACT. In this work, the V-Agrifleet tool is presented and demonstrated. V-Agrifleet is developed to provide a “hands-free” interface for information exchange and an “Olympic view” to all coordinated users giving them the ability for decentralized decision making. More specifically, V-Agrifleet can be used by the end users (e.g. farmers, contractors, farm associations, agri-products storage and processing facilities, etc.) in the framework of optimizing task and time management. The use of the V-Agrifleet for the multiple-machinery coordination provide substantial savings of input time. Furthermore, the visualized documentation of the fleet performance provides valuable information for the evaluation management level giving the opportunity for improvements in the planning of next operations.

ABSTRACT. The actors in the field of aromatic and medicinal plants (MAP), due to lack of exhaustive information in space and time are facing nowadays in great issues in terms of management, exploitation and valorization of these resources. Existing inventory methods such as the botanical or spatial observation methods because of their technical, financial and human limitations, cannot offer exhaustive information in space and time. In this context, we proposed a modeling method for exploited habitats based on GPS tracks of local gatherers. GPS tracks are processed and analyzed by a model that applies a set of filters to retain only the portions of the track concerned by gathering activities in the strict sense of the term. Determining the action of gathering comes down to indirectly detecting the location of a plant species. The design of the theoretical model was translated into SQL language and incorporated in a spatial database to facilitate automated data processing. This model was tested on three types of plant species: sage, rosemary and lime blossom. The modeling results, represented through synthetic maps and field data (geo-referenced photos), enable to further develop the model and pave the way for an observatory prefiguring the adaptive management of MAP’s.

ABSTRACT. Authors’ models, algorithms and software for analysis of heat and water transport in agri-food and forest products were essentially enhanced and supplemented with respect to: a) representing geometry of agricultural products by improved Canny edge detector applied to images of product sections; b) 3D geometry modeling of investigated products in order to represent the geometry and changes in the properties in space and time during drying, heating and cooling operations; c) identifying product properties and predicting performance of dryers and bins – new optimization algorithms were inserted to our inverse Finite Element Analysis algorithms to improve knowledge of model coefficients, and to use their values in predicting behavior of examined products. Empirical data were acquired in experimental procedures to validate the predictions. Ontologies were developed to describe grain store equipment. They were represented in Turtle RDF, RDFS and OWL and made available for querying. Results reduced uncertainty of predictions and enabled better understanding the behavior of cereal grains and other agri-food and forest products in drying and storage operations implemented in agriculture and wood industry. The following technologies were used: C# and Visual Studio 2017, Windows Presentation Foundation, ASP.NET Core MVC and Xamarin.

ABSTRACT. There are multiple sources of impetus - environmental and economic - for increasing efficiency of agriculture production. One popular approach to reach this goal is the application of precision agriculture (PA). In order to reveal the current state and understand the potential benefits of PA among Hungarian arable farms we followed a two-step process: First perceptions of Hungarian FADN arable farms are explored through a survey obtained in 2016. This was followed by a cost-benefit analysis of farms already applying certain parts of precision agriculture technology. The results of survey shed the light of the media used to get information about PA, barriers of diffusion of PA, the current stage of different PA applications and revealed benefits. The detail cost-benefit analysis includes input and machinery cost, yield and profit comparison between PA and matching conventional farms for the most important arable crops (wheat, maize, barley, sunflower, rapeseed).

ABSTRACT. To ensure the safety of operators working in farms the employment regulation imposes the equipment of self-propelled vehicles by protective structures. The protective structures of a new designed machine require a proof of compliance before being proposed in the market. For that, these structures undergo a standardized full scale destructive test. In the case of tractor in use for which manufacturers do not offer Falling object protective structure (FOPS), there is no method to evaluate the performance of a designed FOPS, other than this destructive procedure. The purpose of the work described in this paper, is to develop a computer tool to be used as a guide helping in designing and implementing FOPS on in use tractors. The methodology used to establish the computer tool is developed. Based on qualitative and quantitative data provided by the user, the computer tool check the possibility to equip a tractor by a cantilever FOPS. It selects the detailed architecture that adapted to this tractor, dimensions the different parts to be manufactured and gives the steps of forming and fixing the FOPS. A validation study, based on numerical simulations and full-scale impact tests, is carried out to ensure the performance of the proposed structures.

ABSTRACT. For the optimization of farms in the sense of sustainable development, software systems must fulfill special requirements. Within a research project, over 30 requirements for such systems were systematically gathered. The scope of this contribution is to discuss requirements and demonstrate selected requirements by examples.

ABSTRACT. Huge number of directives and regulations, which are hardly to be overseen, an increase of complexity can be furthermore expected. In the past this required considerable investment of time and money, e.g. checking miscibility or application on the field. With Connected Crop Protection the described steps become almost obsolete. Connected Crop Protection was developed by a consortium of public and private organizations to support the end user by giving an overview of legal regulations for planning, application and documentation of crop protection products. By connecting the involved partners, all necessary information from crop protection recommendation, buffer zone generation and documentation within Farm Management System or MyJohnDeere.com can be covered. The advantage for the user is moving from a manual- to an automatized process and therefore optimizes his practices and saved time. At the same time the likelihood of errors is decreasing, while still complying with regulations and law. Connected Crop Protection is the first system as such to integrate different industry and private Partners, supports user with agricultural regulations and manage increasing complexity.

ABSTRACT. Abstract: Decision making in crop protection requires the difficult interpretation of the interactions between the crop, pest and environment. Due to the constantly changing of these interactions, farmers are forced to make manly short term decisions. To offer the best possible crop protection consulting, industry strives for a fast and efficient processing of crop protection recommendation requests. Hereby, computer based decision models show a huge potential to support this goal if they are designed to fully match the requirements of agricultural practice. In the present work decision algorithms for the selection of practical and specific crop protection advices in winter wheat, winter oil seed rape and corn were designed and has been successfully transferred in a programming logic. The resulting model takes 205 pests, 266 tank mix recommendations, 12 different advisory regions and 29 agronomical parameters for decision making into consideration. In comparison to previous solution the practicability of the current model is mainly improved, due to the consequent recommendation of specific crop protection advices across indications and the option of automated input data acquisition from field management and information systems (FMIS). Furthermore, it was focused on an integrability of the generated advices in the whole agricultural action chain.

ABSTRACT. Many countries in the world are facing water crises hence optimal and efficient usage of water resources especially irrigation water is essential to meet the rapidly increasing food demands of the growing population. The main objective of our work is to develop a real time irrigation scheduling system using weather based soil water balance approach for efficient water management. Information Communication Technologies (ICT's) including human participatory sensing, wireless sensor network (WSN), geospatial technologies have been used for information gathering, analysis and dissemination of related services to the end users in an integrated manner. Soil water balance approach has been used to estimate the daily Available Profile Moisture (APM), irrigation interval and time of operating irrigation equipment. Farmers feedback on irrigation runtime was converted into irrigation depth and considered in the consequent soil water balance. Results show the good correlation (0.79) between WSN based observed soil moisture and estimated daily APM. Also seasonal citrus water requirement estimated using our approach is 1135.43 mm whereas FAO suggests it to be 900-1200 mm which shows good match and irrigation interval estimated by the system was found fairly matching with the recommended schedule decided for citrus by Central Citrus Research Institute (CCRI), Nagpur, India.

ABSTRACT. This paper presents a DSS for sustainable planning of agricultural production and optimization of agricultural resources of a region. The main components of the DSS are a data base (DB) and a model base (MB). The DB is used to enter and store into the system the technical and economic data of crops and the available resources of the agricultural region under study. The MB includes a Linear Programming model and a Multicriteria Linear Programming model for the optimization of a single objective or the simultaneous optimization of more conflicting objectives combined in one utility function under a set of constraints for land, labor, available capital, market and the Common Agricultural Policy (CAP). The stakeholders of the region, taking in account the economic, social and environmental parameters, can use the DSS to design alternative production plans and agricultural land uses that achieve greater gross margin, less labor use, nitrate reduction and less irrigation water consumption than the existent production plan. The DSS can be used for the analysis and simulation of agricultural production plans under various scenarios regarding different policies, different values and utilization level of agricultural resources. The proposed DSS was applied to a region in Central Greece.

ABSTRACT. The research presented is a contribution to the development of command methods for vine sprayers in order to optimize spraying according to the vegetation. The question was: considering the control dynamics of a sprayer, is it possible to apply a previously determined map of pesticide dose and sprayer control set points?

This paper presents the AMPS (Automata Modeling for Precision Spraying) method which has been developed in order to support control design. The method takes 2D ground-based LiDAR data of the canopy as input and computes a command sequence optimized for a cost criterion. AMPS is based on 3 steps: (1) define a function that maps each vegetation state to the desired control set point for this state, (2) apply this mapping to localized vegetation state data, (3) compute and verify control using a model based on timed automata (Alur & Dill, 1994) and the UppAal-CORA model-checking tool, which has an optimization feature (Behrmann et al., 2005).

ABSTRACT. In the proposed paper, data and expertise were collected to provide information and arguments about several issues: about the main criteria of good bread in terms of environmental, nutritional, sensory and sanitary aspects; then, about ways to achieve them in the wheat-to-bread chain, while maintaining affordable prices. Computation for determining the best compromise between the various desired criteria is a challenge, since not all of them are compatible. Several scenarios are explored to highlight tensions between desired criteria, problem formulation and solution analysis such as best- and worst-case scenarios. Hence the approach demonstrates the interest of information systems and computational methods for decision support in agricultural and food policies.

ABSTRACT. Traceability can be defined as tracing and monitoring a product through all the links of its supply chain, allowing for critical control points identification. In the case problems do occur, it is possible to identify its sources and make decisions that will reduce their impact in the future. Wine for exportation purposes is an important product for Brazil, as the country is developing its wine SCs worldwide. However, there are still traceability problems in this SC, that are related both to its processes and to the technologies used. In this paper, we propose a traceability model for this product considering the technologies of Radio-Frequency Identification for tracking and tracing, and wireless sensor networks to monitor the product environment. The model encompasses the whole supply chain, and tracks the products while monitoring temperature, relative humidity and lightness. It considers current traceability problems and is composed of seven links. It uses a cloud database which receives data periodically from all these links. If a problem is detected, a message is sent to the responsible link in the chain, so that she can analyze the possible options to reduce the quality impacts of the problem.

ABSTRACT. Water quality is still getting worse, despite decades of public policy attempting to reverse this decline. Farming activities are a major impact on diffuse pollution by pesticides. Qualifying the current and future agriculture is a major concern for water managers as well as for farming representatives who negotiate mitigation measures within agro-environmental action plans. Stakeholders need to evaluate the potential impacts of mitigation measures on water resources. The aim of our work is to propose an integrated and collaborative information system to organize information provided by experts and stakeholders in the context of agro-environmental action plans. Data warehousing is used to provide indicators and outputs at various thematic, temporal or spatial aggregated levels using Spatial On-Line Analytical Processing (SOLAP) tools. Several multidimensional cubes are fed with data collected within a pesticide action plan defined to restore the water quality in a drinkable water catchment area (Charente river basin, SW France. Trajectories to develop organic agriculture on the area and their impact on water resources (Vernier et al, 2016) are detailed and several examples of SOLAP requests, built and validated with stakeholders, are presented.

ABSTRACT. The proposed approach takes advantage of argumentation analysis to identify arguments and plausible options available to stakeholders, as well as plausible hypotheses related to external factors. Using the system dynamic model, simulations are performed for different scenarios corresponding to different value combinations of external and controlled variables in order to evaluate the outcomes of the options supported by arguments. Moreover, while considering the same alternative options, the system dynamic model can be customized to reflect the particular situations of different groups of stakeholders. Hence, the system dynamic simulations and scenario assessments can show how these different groups would be impacted by the different options. Sharing these results among the different groups of stakeholders certainly helps build consensus toward the adoption of more satisfying solutions.

ABSTRACT. Fresh produce are rich in sensory attributes. However, when buying online, the nature of e-commerce limits consumers’ ability to examine the sensory attributes of the products and leads to different perceptions of product quality. That is, only limited intrinsic cues of fresh produce (i.e., color, taste) are given to customers online. With limited intrinsic cues, consumers are more likely to use information given)—so called “extrinsic cues”—to assess product quality regarding fresh produce. This study aims to investigate the effects of extrinsic cues on online shopping context when selling fresh produce. We used data from an online marketplace for fresh produce. The results show that the products with more socially recognized geographical origins sold more in volume per order, but were not ordered more frequently. The price has a negative effect on the amount of orders. The volume of review has a significant positive effect on the amount of orders and sales, but the rating itself does not have an effect. Lastly, the number of certifications has a significant positive effect on the number of orders and sales volume.

ABSTRACT. FAO and ITU developed the e-agriculture strategy guide to assist countries in shaping their national e-agriculture strategy, identifying and developing sustainable services and solutions based on ICTs in agriculture. E-agriculture involves designing, developing and applying innovative ways to use ICTs in the rural domain, with a primary focus on agriculture, including fisheries, forestry and livestock. The aim is to boost agricultural and rural development by improving access to valuable information that can help people whose livelihoods depend on agriculture to make the best possible decisions, and use the resources available in the most productive and sustainable manner. A national strategy can prevent e-agriculture projects from being implemented in isolation, avoiding duplication of efforts and resources. It helps to develop efficiency gains from intra-sector and cross-sector synergy. An e-agriculture strategy can pave the way for policy options to bridge the technology divide in rural areas, and ensure equal prospects for rural men and women, young and old, to access ICTs – quickening the pace of innovations, increasing incomes and job opportunities in the process.

ABSTRACT. Vintel is an online software based decision-making tool. It is designed to assist winegrowers in making effective irrigation management decisions. It enables following the water status of vineyard per block on a daily basis.Vintel is based on an agro-climatic analytics that models on a daily basis an average value per block of predawn leaf water potential, plant available water in the soil and midday leaf water potential. An irrigation recommendation is proposed per day by comparing the current value of predawn leaf water potential with the value targeted by the grower, that we call the green zone itinerary. The irrigation recommended is defined as the amount of water required to maintain the predawn potential in the middle of the green zone. Given weather forecast, Vintel predicts upcoming vine water status and irrigation requirements. This demonstration will show up the main features of the tool, such as data provided to winegrowers to take irrigation decision, block creation and in-season block management. By contrast to most existing decision support tools, Vintel does not require any field sensors once the model has been calibrated on the plot. It also takes into account specific block characteristics such as vine varieties, cultural practices and irrigation.

ABSTRACT. The demonstration will focus on the functionality and reach of VITIS, a toolkit that entails technologies for discovering, analyzing and linking information related to the usage and exploitation of data related to viticulture research and practices

ABSTRACT. BD Avicole is French professional and volunteer initiative of the poultry sector to implement global traceability all along the production chain in a national Database thanks to innovative tools to supply the database.

The system is already deployed : thousands of actors are involved and register more than 40 000 movements since its launch 6 months ago.

The demonstration will consist in presenting all fonctionnalities of the BD Avicole web portal by wich users can declare easily their information on themselves and their traceability in the national Database.

The objectives of the demonstration are to show : -how users can connect to web portal -how users can declare information on their structure (farm, producers organization, hatchery, etc.) and their production area (buildings, outdoor area, etc.) -how users can declare movements of their living animals for traceability and the links with previous/following movements -how users can dematerialize some administrative procedures

ABSTRACT. Data Crop project: a prototype of a model for predicting wheat quality and yield, based on a big data platform.

ABSTRACT. Abstract. Informational needs of agricultural consultants are in increasing complex. Advising farmers on the appropriate measures for optimizing cropping yields demands access to custom data archives and analytics tools. Inline with the increasing number of archives, the expertise required of consultants is goes beyond the capabilities of these non-technical agri-specialists. These end users have diverse ad-hoc query needs and require tools that provide simple access to distributed data silos and easy ways to integrate relevant information. In this paper we report on a pilot deployment of SADI semantic web services for the federation and computation of agricultural data. We demonstrate that the deployment of SADI services facilitates the ad-hoc creation and execution of a number of a number of workflows targeting use cases in Agricultural Operations Management. Using HYDRA, a query engine for SADI semantic web services and a custom built GUI, agricultural consultants can identify optimal crop varieties, compute profit margins of each variety using a complex cost model, and further determine the appropriate pesticides for the optima crop variety and its impact on non-target species.

ABSTRACT. An innovative DSS for olive orchard management has been developed bringing together the results of research activity of Aedit srl in collaboration with the Institute of Life Science of Scuola Superiore Sant’Anna in olive fruit fly management and fruit quality. The olive DSS aims to assist growers and technicians in the management of the several agronomic aspects of the production, making them aware of proper decision paths. The DSS is composed by modular and distributed applications with the following components: a weather data provider, a set of web services to access the crop and pest models, an interactive dashboard customizable by the users to interact with the models, and a Farm Management System to allow the integration of data and monitoring activities on-farm in the DSS. The modelling section holds the following models: olive tree phenology based on cumulative degree day, irrigation and fertilization requirements, olive fruit fly generation and phenology, olive fruit fly mortality because of summer high temperatures, olive fruit fly fertility due to environmental conditions, olive fruit fly adult emergence of overwintering generation, risk of infestation by the first summer generation of olive fruit fly estimated with temperatures of winter and spring.

ABSTRACT. The demonstration aims to introduce Bluleaf, a cloud-based Decision Support System (DSS) integrated with smart sensors for the efficient irrigation/fertilization management at farm scale, as developed in Italy by Sysman Progetti & Servizi Ltd, in collaboration with local scientific institutions. The demonstration will include: a) a brief introduction to the technical features of the DSS, based on the integration of agronomic modeling, cloud-based services and wireless sensors technologies; b) the description of the computer/tablet/smartphone software interfaces and tools, to be used by farmers and technicians for the daily crop irrigation/fertilizer management; c) a ‘real-time’ connection with relevant case-studies in Italy, to display both the web/App versions of the DSS, referring to a wide number of crops and irrigation management strategies (wine and table grape, fruit crops, field crops, etc.).

ABSTRACT. Discover the API-AGRO platform: data and services platform for agricultural stakeholders. This platform favors data and services (like Decision Support System) spreading, in total control for providers, through web API, mature technologies approved in others economic sectors.

The demonstration will show both points of view of the agricultural stakeholders: assets providers and assets users. Moreover, concrete reuse of assets realized in hackathons events will be presented.

ABSTRACT. In this demonstration, we show how web technologies, geospatial analysis (GIS) and big data analysis are combined in order to develop an online tool for policymakers, towards estimating the impact of agriculture on the environment. The case study would be the area of Catalonia in Spain, by collaborating with the Ministry of Agriculture of Catalonia, which supported the project by advice/consulting and by providing relevant data. The demo involves an online calculator for GHG emissions and nitrates/phosphorous excreted, network analysis for manure management, as well as various geospatial visualizations that indicate the environmental impact of livestock agriculture from various perspectives. This online tool assists both farmers' decision-making and administration planning/policy making.

ABSTRACT. CropWin® is a customizable online decision support system designed to help growers securing their yield and the final product quality, minimizing their environmental impact. It allows to forecast crop growth (Corn, Soybean and Wheat) and final yield depending on climate, soil properties and agricultural practices. Based on these forecasts, growers can determine with precision when a practice (irrigation, fertilization, sowing, …) should be done, adjusting at the best the amount of inputs used.

The demonstration will present main functionalities of the tool: - Dashboard view and multi-field setting or management - Plot and crop setting - Field presentation: biomass accumulation, stresses indicators (nitrogen, potassium and water), potential yield and yield gap, and practices recording (irrigation or fertilization). - Ground-truthing opportunities - Practices simulation with Return On Investment computation - Multiple scenario testing with Return On Investment computation - Final yield integration - Calibration from tissue analysis

ABSTRACT. Agronomy is an overarching field that consists of various areas of research such Genetics, Plant Molecular Biology, Ecology and Earth Science. At the Institute of Computational Biology (IBC), we are currently building a RDF knowledge base, Agronomic Linked Data (AgroLD – www.agrold.org). The knowledge base is designed to integrate data from various publically available plant centric data sources. The aim of AgroLD project is to provide a portal for bioinformatics and domain experts to exploit the homogenized data model towards filling the knowledge gaps. To this end, we plan to engage with stakeholders in demonstrating the advantages of SW in answering complex domain relevant questions that were unapproachable using traditional methods, strategically filling knowledge gaps.

ABSTRACT. PICORE is an innovative embedded ICT tools for characterizing, optimizing and make it possible the automatic traceability of pesticide spraying. PICORE provides farmers with a tool to help them to manage and optimize crop protection treatments (up to 15% reduction). They can monitor spraying operations in real time, detect sprayer's dysfunctions, while saving time and enhancing precision during the preparation and treatment phases.PICORE achieves the automatic traceability of pesticide treatment. This system uses ICT technologies (GSM mobile phones and WiFi) to convey automatic instructions and specifications for plots via a web server, a portable measuring device and a Smartphone HMI display. In the near future, PICORE will integrate features to actuate the sprayer and to tune the parameters of treatment.

ABSTRACT. Many vocabularies and ontologies are produced to represent and annotate agronomic data. Therefore, there is a need of a common platform to identify, host and use them in agro-informatics application. By reusing the NCBO BioPortal technology, we have designed AgroPortal an ontology repository for the agronomy domain. The AgroPortal project aims at reusing the scientific outcomes and experience of the biomedical domain in the context of plant, agronomy, food, and biodiversity. We offer an ontology portal which features ontology hosting, search, versioning, visualization, comment, recommendation, enables semantic annotation, as well as storing and exploiting ontology alignments. All of these within a fully semantic web compliant infrastructure. The AgroPortal specifically pays attention to respect the requirements of the agronomic community in terms of ontology formats (e.g., SKOS, trait dictionaries) or supported features. In this demonstration, we will present our platform currently open and accessible at http://agroportal.lirmm.fr.

ABSTRACT. This demonstrator demonstrates the use of Hyperledger blockchain technology for the management of food certificates in the table grape supply chain. We show how chaincode (i.e. smart contracts) can be used to manage the issuing, tracking and validation of certificates both by the original issuer and delegated issuers. We show how different actors in the supply chain can have access to this data using a web interface that interacts with an underlying permissioned private blockchain. The demonstrator shows that the application of such technology to certain parts of the agrifood system will be beneficial in reducing the complexity of transactions and providing a permanent record of the issuing of certifications. The demonstrator is the result of collaborative research between TNO and WUR and funded by the Dutch Ministry of Economic Affairs, together with a number of NGOs and business partners.

ABSTRACT. Agrifind: "Shared Farming Expertise” the farming skills’ market place for farmers to get practical, technical and feedback advices. They will benefit from the expertise of farmers who have already successfully undertaken concrete actions on their farms and also consultants and agricultural advisors. Each performance will be evaluated and commented by their beneficiaries. Agrifind.fr allows any farmer or agricultural advisers to monetize their skills by a dedicated website. They can propose E-learning, video, tutos, courses, training, and consultancy services to supplement their income, or creating their own job. AGRIFIND allows creativity in the creation of services, completely personnalized and payed either by day, hour, package, or document. We guarantee the payment of the services by a automated and secured system of payment. The expert registered on AGRIFIND thus benefits from an active national and soon international coverage, with a market of connected farmers and willing to get or improve their skills. In few months AGRIFIND will propose online farmer groups management.