Special Issue "Precision Agriculture Technologies for a Sustainable Future: Current Trends and Perspectives"
Deadline for manuscript submissions: closed (30 September 2017)
Prof. Dr. Konstantinos G. Arvanitis
Director of the Section of Farm Structures & Agricultural Machinery, Laboratory of Agricultural Machinery, Department of Natural Resources Management and Agricultural Engineering, School of Agricultural Production, Engineering and Environment, Agricultural University of Athens, 75 Iera Odos Str., Botanikos 11855, Athens, Greece
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Interests: automation and ICT in agriculture; wireless sensor networks; precision farming; management and control of autonomous smart grids; remote sensing
Dr. Spyros Fountas
Laboratory of Agricultural Machinery, Department of Natural Resources Management and Agricultural Engineering, School of Agricultural Production, Engineering and Environment, Agricultural University of Athens, 75 Iera Odos Str., Botanikos 11855, Athens, Greece
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Interests: precision agriculture; farm machinery; information systems
Precision Agriculture is a management concept focusing on monitoring, measurement and responses to inter- and intra-variability in crops, fields and animals. Precision Agriculture has been made possible by the rapid development of sensing technologies, management information systems, advances in farm machinery and appropriate agronomic and economic models. The benefits of using Precision Agriculture practices include increasing crop yields and animal performance, cost reduction and optimization of process inputs. Thus, Precision Agriculture aims to reduce the environmental impacts of agriculture and farming practices, contributing to the sustainability of agricultural production.
This Special Issue aims to discuss various impacts of precision agriculture technologies and management methods from a sustainability viewpoint. This will include the impact of precision agriculture technologies and applications to the three pillars of sustainability: economic, environmental and social perspectives. We invite you to contribute to this issue by submitting comprehensive reviews, case studies, or research articles that focus on scientific methods, technological tools and innovatively statistical analyses, in order to provide an opportunity for learning the state-of-the-art and for discussion on future directions in Precision and Sustainable Agriculture. Papers selected for this Special Issue are subject to a rigorous peer review procedure with the aim of rapid and wide dissemination of research results, developments, and applications.
Prof. Dr. Konstantinos G. Arvanitis
Dr. Spyros Fountas
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- Spatio-Temporal Variability in Crop, Soil and Natural Resources
- Big Data Mining and Statistical Issues in Precision Agriculture
- Information Systems in Precision Agriculture and Decision Support
- Engineering Technologies and Advances in Precision Agriculture
- Computational Intelligence in Precision Agriculture
- Proximal Sensing in Precision Agriculture
- Remote Sensing Applications in Precision Agriculture
- Variable-Rate Application Equipment in Precision Agriculture
- Food Security and Precision Agriculture
- Precision Agriculture and Climate Change
- Precision Conservation Management
- Precision Crop Protection
- Precision Horticulture
- Precision Dairy and Livestock Management
- Precision Nutrient and Water Management
- Autonomous Vehicles (Ground and Aerial) for Sustainable Agriculture
- Profitability, Sustainability and Adoption Trends
- Education and Training in Precision Agriculture
- Emerging Issues in Precision Agriculture (Energy, Life Cycle Analysis, Carbon and Water Footprints, etc.)
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Life Cycle Assessment of Two Vineyards after the Application of Precision Viticulture Techniques
Author: A.T.Balafoutis1, S. Koundouras2, E. Anastasiou1, S. Fountas1, K.G. Arvanitis1
Affiliations: 1Department of Natural Resources Management & Agricultural Engineering, Agricultural University of Athens, IeraOdos 75, 11855, Athens, Greece
2Laboratory of Viticulture, School of Agriculture, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Abstract: Precision viticulture is the application of site-specific techniques to vineyard production to improve grape quality and yield and minimize the negative effects on the environment. While there are various studies on the inherent spatial and temporal variability of vineyards, and techniques and methods to optimize resource utilization, the assessment of the environmental impact of variable rate applications has attracted limited attention. In this study, two vineyards planted with different grapevine varieties (Sauvignon blanc and Syrah) were managed with precision viticulture techniques during two growing seasons (2013 and 2014) and the environmental impact in terms of energy and greenhouse gas emissions was quantified. The first year, the vineyards were studied in terms of soil properties and crop characteristics, which provided the delineation of two distinct management zones for each vineyard.The second year, variable rate fertilization was applied to each management zone based on leaf nutrient analysis and leaf canopy reflectance, while variable rate irrigation was based on soil moisture sensors, meteorological data and evapotranspiration calculation. Life Cycle Assessment (LCA) was carried out to identify the effect of the application of variable rate applications on vineyard environment. The results indicated that nutrient status management offers the greatest potential for reducing environmental impact in both vineyards.Variable rate irrigation also showed differences in comparison to conventional irrigation treatment, but to a lesser degree than variable rate fertilization, mostly due to the fact that 2014 was a wet season and a limited number of water treatments was carried out.With respects to different vineyard varieties, precision viticulture could have a high environmental impact on Sauvignon blanc, while the situation was less significant, but not negligible, in the Syrah vineyard. This difference between the two varieties wasmainly attributed to the significant fertilizer quantity reduction in Sauvignon blanc in comparison to Syrah.
Title: Precision Farming and Advanced ICT Solutions are Required to Make Agricultural Buildings more Sustainable
Authors: T. Norton1, T. Bartzanas2, D. Berckmans1
Affiliations: 1 Katholieke Universiteit Leuven, Division Animal & Human Health Engineering, M3-BIORES, Kasteelpark Arenberg 30, Leuven, Belgium
2 Center for Research and Technology – Hellas, Institute for Research and Technology of Thessaly, Dimitriados 95, 38333, Volos, Greece
Abstract: As the demands from a growing global population increase, modern ICT-based solutions will become mainstream in the support sustainable building-based horticultural and livestock farming practices. In livestock farming, the evolution of Precision Livestock Farming (PLF) has seen new systems for the automatic monitoring and management of production practices being investigated and brought to the market. These solutions need to be implemented within livestock buildings, and they replace the eyes and ears of the producers and can potentially optimise the process while farmers are not present. Recent research has shown how PLF solutions can improve the sustainability of livestock buildings with respect to precision ventilation, precision health and welfare monitoring, as well as precision waste management. In protected horticulture, Precision Farming (PF) is now becoming a greater focus for research and technical implementation. Advanced climate, water and nutrient control systems are being developed to tune the microclimate to the continuous needs of the plants, taking plant signals as the input to control systems. Recent ICT-based solutions are also being used to develop technologies to integrate the production of algae and fish, with this shown great potential in this sector. The aim of this paper is to review the recent PF and PLF solutions that contribute to sustainable agricultural buildings. The final message will be that PF/PLF and making advanced ICT is key to agricultural buildings sustainable into the future, but that these solutions must integrate the response of animals and crops to their environment to achieve this objective.
Title: Exploring Precision Farming Scenarios using Dynamic Fuzzy Cognitive Maps for Decision Support
Authors: Asmaa Mourhir1, Elpiniki I. Papageorgiou2,*, K. Aggelopoulou3, K. Kokkinos4, Tajjeeddine Rachidi1 and G.D. Nanos3
Affiliations: 1 Computer Science Department, School of Science and Engineering, Al Akhawayn University in Ifrane, Morocco, A.Mourhir@aui.ma, T.Rachidi@aui.ma
2Computer Engineering Department, Technological Education Institute (TEI) of Central Greece, Greece, firstname.lastname@example.org
3University of Thessaly, Department of Agriculture, Crop Production & Rural Environment, Fytoko Street, N. Ionia, Magnesia, 38446, Greece, email@example.com
4Computer Science Department, University of Thessaly, Lamia, Greece, email: firstname.lastname@example.org
Abstract: One of the most challenging problems confronted in precision farming is the exact knowledge of how the yield on a certain area responds to diminishing or marginal application of specific nutrients. Dynamic Rule-based Fuzzy Cognitive Maps (DRBFCMs) is a Fuzzy Cognitive Map variant that allows modeling of dynamic causal maps where, influence weights are determined dynamically at simulation time using fuzzy inference systems, in order to adapt to new conditions. In this work we propose the DRBFCM soft computing technique that: (i) implements yield prediction and hence enables managers to analyze yield variations across a field thus, they can determine how to vary the management options, and (ii) provide managers with a tool to perform simulations in precision farming that can be used to identify the effects of fertilizer or pesticide quantity variations on yield. Experts from the precision agriculture domain have been pooled to provide the necessary knowledge and design the proposed FCM model. An illustrative precision farming example is used to predict and experimentally verify the impact of certain management options on yield according to expert perceptions using proactive scenarios.
Keywords: fuzzy cognitive maps, fuzzy inference systems, Dynamic Rule-based Fuzzy Cognitive Maps, yield prediction, scenarios.
Title: Automated Navigation for Field Machinery: An Assessment on the Energy Savings
Authors: Dionysis Bochtis1; Remigio Berruto2; Patrizia Busato2; Efthimis Rodias2; Kun Zhou3
Affiliations: 1 Institute for Research and Technology - Thessaly IRETETH / Centre for Research & Technology Hellas –CERTH, Dimitriados Str. 95, GR 38333, Volos, Greece
2 University of Turin, Faculty of Agriculture, DISAFA Department Via Leonardo da Vinci 44, 10095, Grugliasco, Turin, Italy
3 Aarhus University, Faculty Science and Technology, Dept. of Engineering, Inge Lehmanss Gade 10, 8000 Aarhus C, Denmark
Abstract: Conventional filed area coverage is based on routes followed by agricultural vehicles which are formed as repetitions of standard motifs. This practice is not based on any kind of optimization necessities, in terms of any criterion, e.g. cost, energy savings, or soil compaction prevention, but rather on the human operator factor. A human operator lacks the ability to distinguish the field-work tracks on a morphologically uniform field area. The implementation of sensor systems, such as geographical positioning systems and machine vision systems, for navigation adding of agricultural vehicles, combined with on-board decision making systems and interfaces has removed the dependence of the field area coverage planning and execution from human capabilities. These automation technologies has enforced the potential for the generation of optimized field area coverage practices, such as the B-patterns based coverage where the sequence of the field-work tracks for a complete area coverage are algorithmically-computed under one or more selected criteria. It has been shown that the implementation of B-patterns result to savings in non-working distance up to and 58%, increases in area capacity up to 19%, and reduction of the soil compaction probability up to 60%. In this paper, a methodology for the generation of B-patterns under the criterion of energy consumption is presented. The energy consumption of agricultural vehicles during field operation is compared between the cases of the B-patterns generated routes and the conventional ones. Based on the results, the optimized routes reduces the energy consumption of agricultural vehicles up to 9%.
Title: Operational estimation of soil moisture, evapotranspiration and related parameters for agricultural crops in support of sustainable water management: state of the art and future outlook
Authors: Maria Piles1, Prashant K. Srivastava2, David Chaparro3, Kiril Manevski4, George P. Petropoulos5, Hywel Griffiths6
Affiliations: 1Barcelona Expert Centre, Institute of Marine Sciences (ICM), CSIC, Pg. Marítim Barceloneta 37-49, E-08003 Barcelona, Spain
2 National Centre for Medium Range Weather Forecasting (NCMRWF), Ministry of Earth Sciences, Noida, India
3Universitat Politècnica de Catalunya, IEEC/UPC, Jordi Girona 1-3, E-08034 Barcelona, Spain
4Aarhus University, Tjele, Denmark
5Aberystwyth University, Geography & Earth Sciences, UK
Title: Quantifying the Effect of Precision Agriculture Using an Integrated Measure of Sustainability
Authors: Frits K. Van Evert1, Daniel Gaitan-Cremaschi2, Spyros Fountas3, Peter M. Kyveryga4, Corné Kempenaar1
Affiliations: 1 Wageningen University and Research Center, Wageningen Plant Research, Agrosystems Research, PO Box 16, 6700AA, Wageningen, The Netherlands
2 Wageningen University and Research Center, Wageningen School of Social Sciences, Leeuwenborch, building number 201, 6700AA, Wageningen, The Netherlands
3 Agricultural University of Athens, Natural Resources Management and Agricultural Engineering, Iera Odos 75, 11855 Athens, Greece
4 Iowa Soybean Association, 1255 SW Prairie Trail Pkwy, Ankeny, Iowa 50023, USA
Abstract: Precision Agriculture (PA) is the scientific domain that deals with management of spatial and temporal variability to improve economic returns and reduce environmental impact. For farmers, PA is expected to lead to an increase in profitability. For society, PA is expected to lead to increased sustainability. The objective of this paper is to rank a number of common PA practices in terms of how much they increase profitability and sustainability. For potato production in The Netherlands, we considered variable rate application (VRA) of lime and sidedress application of N. For olive production in Greece, we considered spatially variable application of P and K fertilizer. For maize/soybean production in the mid-Western United States, we considered VRA of N, as well as skipping areas with consistently low yields (so-called potholes). For each of the above scenarios, we quantified the change in inputs, outputs, and the environmental impact resulting from the application of the PA practice. Production data were obtained from commercial growers where possible and otherwise from experiments. Environmental impacts considered were GHG (on-farm energy use and embedded energy of inputs), nitrogen losses, and toxicity effects of pesticides. Local prices were used to determine the value of inputs and outputs. We used various methods to determine shadow prices for environmental impacts. This allowed us to calculate social profit, which is defined as revenues minus conventional costs minus the external costs of production – social profit can be considered an overall measure of sustainability.
Title: Low-Power Wide-Range Wireless Communication Technologies for Sustainable Precision Agriculture at a Regional Level
Authors: Dimitrios D. Piromalis 1,2, *, Konstantinos G. Arvanitis 1 , Stelios Mitilineos, 3 Panagiotis G. Papageorgas3
Affiliations: 1 Department of Natural Resources and Agricultural Engineering, Agricultural University of Athens, Iera Odos 75, 11855, Athens, Greece
2 Department of Automation Engineering, Piraeus University of Applied Sciences (TEI of Piraeus), P. Ralli and Thivon 250, 12244, Egaleo,Greece
3 Department of Electronics Engineering, Piraeus University of Applied Sciences (TEU of Piraeus), P. Ralli and Thivon 250, 12244, Egaleo, Greece
Abstract: In a fast changing and competitive technological environment, Wireless Sensors Networks systems and applications are seriously affected. This paper focuses on the revolutionary technologies for long range communications and presents how the post-mesh era of wireless networks can help sustainable precision agriculture. Specifically, ultra narrow-band and low-power Wide-Area-Networks, such as the LoRa and Sigfox, etc., can support the transition from local to regional systems and applications. Moreover, this paper presents the implementation of experiments in laboratory environment regarding the measurements of throughput and packet error rate versus signal strength. In particular, the experiment is conducted using 868 MHz LoRa and ZigBee based nodes. Several useful conclusions regarding to the potential strengths of new communication technologies for low-power Wide-Area-Networks are emphatically presented in the last part of the paper.
Keywords: Low-Power WAN, LoRa, Sigfox, ZigBee, Precision Agriculture, Long-Range, Narrow-Band Communications