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Über dieses Buch

This book constitutes the thoroughly refereed post-conference proceedings of the 8th International Conference on Information and Communication Technologies in Agriculture, Food and Environment, HAICTA 2017, held in Chania, Crete, Greece, in September 2017.

The 14 revised full papers presented in this book were carefully selected from the 55 accepted full papers out of 124 submissions. The selected papers span across various subjects, from ICT innovations and smart farming, to decision support systems, as well as precision farming, disease diagnosis using mobile devices, IoT for monitoring and controlling animal production, sensor-based solutions, GIS-based water management, environmental planning, information systems for monitoring of fish stocks and fisheries, information management in the agri-food sector, and forestry planning and management.



ICT Innovations and Smart Farming

Agriculture plays a vital role in the global economy with the majority of the rural population in developing countries depending on it. The depletion of natural resources makes the improvement of the agricultural production more important but also more difficult than ever. This is the reason that although the demand is constantly growing, Information and Communication Technology (ICT) offers to producers the adoption of sustainability and improvement of their daily living conditions. ICT offers timely and updated relevant information such as weather forecast, market prices, the occurrence of new diseases and varieties, etc. The new knowledge offers a unique opportunity to bring the production enhancing technologies to the farmers and empower themselves with modern agricultural technology and act accordingly for increasing the agricultural production in a cost effective and profitable manner. The use of ICT itself or combined with other ICT systems results in productivity improvement and better resource use and reduces the time needed for farm management, marketing, logistics and quality assurance.
Claus Aage Grøn Sørensen, Dimitrios Kateris, Dionysis Bochtis

Methods and Tools for Supporting the Integration of Stocks and Fisheries

The collation of information for the monitoring of fish stocks and fisheries is a difficult and time-consuming task, as the information is scattered across different databases and is modelled using different formats and semantics. Our purpose is to offer a unified view of the existing stocks and fisheries information harvested from three different database sources (FIRMS, RAM and FishSource), by relying on innovative data integration and manipulation facilities. In this paper, we describe the building blocks in terms of methods and software components that are necessary for integrating stocks and fisheries data from heterogeneous data sources.
Yannis Tzitzikas, Yannis Marketakis, Nikos Minadakis, Michalis Mountantonakis, Leonardo Candela, Francesco Mangiacrapa, Pasquale Pagano, Costantino Perciante, Donatella Castelli, Marc Taconet, Aureliano Gentile, Giulia Gorelli

Semiotic-Sociological Textures of Landscape Values. Assessments in Urban-Coastal Areas

One of the most relevant issues of planning in the most landscape valuable locations, especially along the coastal areas, is to define the assessment support to be performed in order to balance the preservation of the main landscape features, and the local economic development. By referring to the case of the waterfront of Syracuse (Italy), this contribution introduces a semiotic-sociological pattern for accounting and assessment concerning the main topics of the Sustainable Development Plan currently in force. The assessment takes into account the connection of the multiple thematic layers grouping the different functional/symbolic land units that are characterised by a semantic link, within an assessment pattern working as a syntactic field, highlighting the interactions between them. The pattern involves the social relevance of the different criteria featuring this landscape unit by making the “facts of nature” and the “narrations of culture” worth together.
Salvatore Giuffrida, Maria Rosa Trovato, Annalaura Giannelli

A Systematic Review on Collective Awareness Platforms

In order to improve the agricultural production an important issue is to change farmers’ behavior leading them towards sustainability. Altering farmers’ behavior is the first step is the first step towards a general societal change. In order to achieve this goal it is vital to involve as many parts of the society as possible. The existing production and consumption model, is not capable to offer such a boost to society. The current financial and social crisis demands on one hand innovative solutions and on the other hand to move beyond the closed Research and Development models to open and collaborative models, such as Collective Awareness Platforms. Collective Awareness Platforms are Information and Communications Technology (ICT) systems leveraging the emerging “network effect” by combining open online social media, distributed knowledge creation and data from real environments, in order to create awareness of problems and possible solutions requesting collective efforts, enabling new forms of social innovation. This paper presents the results of a systematic review that has been based on an analysis of published works on the subject of Collective Awareness Platforms.
Thomas Kappas, Thomas Bournaris, Evangelia Economou, Christina Moulogianni

Using Geostatistics and Multicriteria Spatial Analysis to Map Forest Species Biogeophysical Suitability: A Study Case for the Centro Region of Portugal

There are various methodologies for defining soil uses to promote sustainable utilization of rural land. Many of these methods rely on decision support systems based on multicriteria spatial analysis. In this study, a two-step spatial approach was performed to produce forest species suitability maps. The objectives of the study were: (1) to produce bioclimatic indices maps using a geostatistical approach based on climate data; (2) to produce biogeophysical suitability maps for the main Portuguese forest species by multicriteria spatial analysis using the analytic hierarchy process (AHP) integrating three factors (terrain slope, soil diagnostic features and bioclimatic indices); and (3) to conduct a comparative analysis of the current forest species area distributions to these species biogeophysical suitability areas. With these objectives, the Centro region of Portugal was used as the study area. Our methodological approach allowed us to assess the biogeophysical suitability of Maritime pine, Eucalyptus, Cork oak and Holm oak in the Centro region of Portugal. The findings in this study emphasize the potential that the Centro region of Portugal has for expanding the spread of native oaks as recommended by the National Strategy for Forests to respond to climate changes, improve landscape biodiversity and mitigate fire hazards. The species biogeophysical suitability maps may be important tools for decision support in landscape planning to define species’ priority afforestation areas. From an instrumental point of view, the use of this methodology may interest stakeholders and others with roles in planning and land management. Further investigation is needed to integrate the impact of climate change in forest species spatial modeling to assist in supporting future national strategies for forests.
Luís Quinta-Nova, Natália Roque, Isabel Navalho, Cristina Alegria, Teresa Albuquerque

CAP 2020 Regionalization Design: A Decision Support System

The latest Common Agricultural Policy reform provides national authorities with several implementation options for fine tuning individual goals. Among other, member states can opt for regionalization, i.e. vary the basic payment unit value between national agronomic or administrative regions that have been defined at the beginning of the programming period. We present a Decision support System that support national authorities to implement regionalization in a transparent way facilitating collaboration with different shareholders.
Dimitris Kremmydas, Michael Malliapis, Leyteris Nellas, Apostolos Polymeros, Stelios Rozakis, Kostas Tsiboukas

Strategic Decision Making and Information Management in the Agrifood Sector

In recent years, many economic, technological and societal changes have transformed the agrifood sector. Such transformations significantly influence the entire food processing chain which includes agricultural production, food processing and distribution of food to customers. As Supply Chain Management (SCM) emphasizes on seeing the whole supply chain as one system, Decision Support Systems (DSSs) are Information Systems that help managers in logistics to identify the most effective processes with the highest strategic impact on the logistics that have to be implemented. Managers try to deal with the current complex environment using the Strategic Information Systems Planning (SISP) process. The purpose of this chapter is to propose a strategic DSS model based on the strategic management process and the SISP process to provide a holistic approach to effective decision making in logistics in the agrifood sector. The proposed model is based on the strategic process of DSSs and it involves the phases which are based on the formulation of business and IT strategy.
Maria Kamariotou, Fotis Kitsios, Michael Madas, Vicky Manthou, Maro Vlachopoulou

Water Data Sharing in Italy with SIGRIAN WebGIS Platform

SIGRIAN (National Information System for Agriculture Water Management) is a web GIS platform developed and managed by the Council for Agricultural Research and Economics, Centre for Politics and Bio economics (CREA-PB). This GEOdatabase is operating since 1998 and recently it has been established by the Italian Ministry of Agriculture (MIPAAF) as the reference repository for the irrigation data collection at national scale. SIGRIAN collects both geographical information concerning the hydraulic network schemes of the national water boards (Consortia and Water Associations) and information technically and economically related to the management of water resources in agriculture. SIGRIAN will be used as database for economic evaluations to address policy related to water resources in agriculture and to support the assessment of optimal water resource allocation.
Raffaella Zucaro, Gianfranco Giannerini, Antonio Gerardo Pepe, Fabrizio Luigi Tascone, Marco Martello

Towards the Commercialization of a Lab-on-a-Chip Device for Soil Nutrient Measurement

In this paper, we present a soil nutrient sensor based on the capillary electrophoresis chip technology. As a product intended for commercial use in soil nutrient analysis, we focused on the analysis of -NO3 and -SO4. The sensing core of the device is the microfluidic chip. The design of chip, adapted to the needs of a portable handheld device, hinders the flow of sample in the detection area - due to non-planarity of instalment or pressure differences - via a narrow injection channel. A known issue, is the injection discrepancies caused by chip-to-chip variances and overall ion strength, thus turning quantitative analysis into a challenge. We overcame this by adopting bromide as an internal standard. In order to discriminate bromide from ubiquitous chloride in soil samples we used polyvinylpyrrolidone (PVP) as a separation additive in our background electrolyte. An in-house algorithm was developed for the identification of the measurement peaks, consisting of a baseline smoothing and subtraction along with an optimized quantification of the area under the peaks and thus the ion concentration. For the detection of the ion concentration on-chip electrodes were utilized for a capacitively coupled conductivity measurement. Tests were performed with soil sample extractions from different regions and the results were cross-referenced with an ion chromatographer. The sensor’s response had to be corrected for different ions and it exhibited a second order polynomial response with an average absolute error of 5%.
Georgios Kokkinis, Guenther Kriechhammer, Daniel Scheidl, Bianca Wilfling, Martin Smolka

SheepIT, an IoT-Based Weed Control System

The SheepIT project aims at developing a solution for monitoring and controlling grazing sheep in vineyards and similar cultures. The system should operate autonomously and guarantee that sheep only feed from infestant weeds, leaving untouched the vines and their fruits. Moreover, the system should also collect data about sheep activity for logging and analysis purposes. This paper presents the overall system’s architecture and its rationale, with focus on the posture monitoring and control subsystem. It includes practical results, obtained from a use case. These results are encouraging, showing that the developed system is able to estimate the sheep’s posture with a high accuracy, that the stimuli are applied efficiently and that sheep have sufficient cognitive capacity to learn quickly which behaviours they should avoid. Despite being preliminary, these results provide good indications regarding the practicableness of the system.
Luís Nóbrega, Paulo Pedreiras, Pedro Gonçalves

Techniques for Plant Disease Diagnosis Evaluated on a Windows Phone Platform

The recognition of plant diseases is a responsibility of professional agriculture engineers. Intelligent systems can assist plant disease diagnosis in the early stages with low cost. User descriptions and image comparison are exploited in some expert systems that are already available. More sophisticated techniques like the one presented in this paper are based on features extracted from the symptoms (e.g., lesions) of a plant disease that appear on the leaves, the fruits, etc. The color, the dimensions and the number of these lesion spots can be used in some cases to discriminate the disease that has mortified a plant. In this paper, we describe a smart phone application that measures the features of the plant lesions with higher than 90% precision. The accuracy in the recognition of grapevine or citrus diseases that have been used as case studies is higher than 70% in most of the cases using only 5 photographs for the definition of each disease. The most important advantage of the proposed method is that the set of the supported diseases can be easily extended by the end-user.
Nikos Petrellis

Different Remote Sensing Data in Relative Biomass Determination and in Precision Fertilization Task Generation for Cereal Crops

Recently, the area of passive remote sensing in agricultural fields has been developing fast. The prices of RPAS (remotely piloted aircraft system) equipment has gone down, new suitable sensors are coming into markets while simultaneously new and free relevant satellite data has become available. One of the most used applications for these methodologies is to calculate the relative biomass as a basis for additional nitrogen fertilization. In this work, we study the difference of biomass estimations based on Sentinel-2 imagery, tractor implemented commercial measurement system, a low-cost RPAS equipment with commercial software and a hyperspectral imaging system implemented in a professional RPAS system in the fertilization planning. There was a 23% spatial variation in our malt barley yield. Different relative biomass estimations produced similar and sufficient results and the observation time or the used methodology was not very critical. Also none of the methodologies were remarkably better. When we generated the nitrogen fertilization application tasks, different reasonable parameters conducted very different application tasks. This means that in our case, the relative biomass does not provide sufficient information for nitrogen shortage variation. Knowledge of the local conditions is essential.
Jere Kaivosoja, Roope Näsi, Teemu Hakala, Niko Viljanen, Eija Honkavaara

Unmanned Ground Vehicles in Precision Farming Services: An Integrated Emulation Modelling Approach

Autonomous systems are a promising alternative for safely executing precision farming activities in a 24/7 perspective. In this context Unmanned Ground Vehicles (UGVs) are used in custom agricultural fields, with sophisticated sensors and data fusion techniques for real-time mapping and navigation. The aim of this study is to present a simulation software tool for providing effective and efficient farming activities in orchard fields and demonstrating the applicability of simulation in routing algorithms, hence increasing productivity, while dynamically addressing operational and tactical level uncertainties. The three dimensional virtual world includes the field layout and the static objects (orchard trees, obstacles, physical boundaries) and is constructed in the open source Gazebo simulation software while the Robot Operating System (ROS) and the implemented algorithms are tested using a custom vehicle. As a result a routing algorithm is executed and enables the UGV to pass through all the orchard trees while dynamically avoiding static and dynamic obstacles. Unlike existing sophisticated tools, the developed mechanism could accommodate an extensive variety of agricultural activities and could be transparently transferred from the simulation environment to real world ROS compatible UGVs providing user-friendly and highly customizable navigation.
Dimitrios Bechtsis, Vasileios Moisiadis, Naoum Tsolakis, Dimitrios Vlachos, Dionysis Bochtis

Precision Poultry Farming: Software Architecture Framework and Online Zootechnical Diary for Monitoring and Collaborating on Hens’ Health

Livestock farming needs to reach superior productivity levels in an environmentally sustainable manner. In order to accelerate the development of the livestock industry, it is important to make optimal use of farming knowledge and provide farmers with adequate information technologies. This article describes the realisation of a precision livestock management information technology framework that can serve as a practical guide for the development of new and various livestock management software products. The business domain focus is on the egg industry with a detailed precision poultry farming example and real realization. The online platform specified hereafter as zootechnical diary delivers monitoring and collaborative capabilities to improve laying hens’ health and welfare at industrial poultry farms. It connects egg and breeding farms through cloud technologies to provide continuous data recording, automatic comparisons between actual and expected production indicators, e-networking and integrated data-flow between the two parties. Breeding farms benefit from enhanced competitiveness, improved supplier-client relationships, while egg farms enjoy management precision, timely feedback on animals’ health and economic benefits.
Magdalena Stefanova


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