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Prof. Claus Sørensen
Aarhus University, Denmark

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0 System engineering
0 Operations research and optimization
0 Decision support model

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Journal article
Published: 29 August 2021 in Agronomy
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Grain price differences due to protein content can have economic effects on the farm as well as environmental effects when alternative protein sources are imported. Grain protein variability can vary from year to year due to environmental factors and can be addressed by site-specific management practices. Alternatively, it can be addressed at harvest time by selective harvest. Agricultural autonomous robots can accurately follow alternative harvesting routes that are subject to grain quality maps, making them suitable choices for selective harvest. This study addresses therefore the potential revenue of selective harvest performed by the route planner of an autonomous field robot. The harvest capacity and potential economic revenues of selective harvest in a Danish context were studied for a set of 20 winter wheat fields with four hypothetical scenarios. The results showed significant differences in harvest capacity between conventional and selective harvest. Even though in some scenarios selective harvest did not require notable additional harvest times, the cost–benefit analysis showed small economic returns of up to 46 DKK ha−1 for the best scenarios, and for most cases losses up to 464 DKK ha−1. Additionally, the location of the high protein content areas has great influence on the profitability of selective harvest.

ACS Style

Andrés Villa-Henriksen; Gareth Thomas Charles Edwards; Ole Green; Claus Aage Grøn Sørensen. Evaluation of Grain Quality-Based Simulated Selective Harvest Performed by an Autonomous Agricultural Robot. Agronomy 2021, 11, 1728 .

AMA Style

Andrés Villa-Henriksen, Gareth Thomas Charles Edwards, Ole Green, Claus Aage Grøn Sørensen. Evaluation of Grain Quality-Based Simulated Selective Harvest Performed by an Autonomous Agricultural Robot. Agronomy. 2021; 11 (9):1728.

Chicago/Turabian Style

Andrés Villa-Henriksen; Gareth Thomas Charles Edwards; Ole Green; Claus Aage Grøn Sørensen. 2021. "Evaluation of Grain Quality-Based Simulated Selective Harvest Performed by an Autonomous Agricultural Robot." Agronomy 11, no. 9: 1728.

Journal article
Published: 10 July 2021 in Sustainability
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During a baling operation, the operator of the baler should decide when and where to drop the bales in the field to facilitate later retrieval of the bales for transport out of the field. Manually determining the time and place to drop a bale creates extra workload on the operator and may not result in the optimum drop location for the subsequent front loader and transport unit. Therefore, there is a need for a tool that can support operators during this decision process. The key objective of this study is to find the optimal traversal sequence of fieldwork tracks to be followed by the baler and bale retriever to minimize the non-working driving distance in the field. Two optimization processes are considered for this problem. Firstly, finding the optimal sequence of fieldwork tracks considering the constraints of the problem such as the capacity of the baler and the straw yield map of the field. Secondly, finding the optimal location and number of bales to drop in the field. A simulation model is developed to calculate all the non-productive traversal distances by baler and bale retrieval in the field. In a case study, the collected positional and temporal data from the baling process related to a sample field were considered. The output of the simulation model was compared with the conventional method applied by the operators. The results show that application of the proposed method can increase efficiency by 12.9% in comparison with the conventional method with edited data where the random movements (due to re-baling, turns in the middle of the swath, reversing, etc.) were removed from the data set.

ACS Style

Mahdi Vahdanjoo; Michael Nørremark; Claus Sørensen. A System for Optimizing the Process of Straw Bale Retrieval. Sustainability 2021, 13, 7722 .

AMA Style

Mahdi Vahdanjoo, Michael Nørremark, Claus Sørensen. A System for Optimizing the Process of Straw Bale Retrieval. Sustainability. 2021; 13 (14):7722.

Chicago/Turabian Style

Mahdi Vahdanjoo; Michael Nørremark; Claus Sørensen. 2021. "A System for Optimizing the Process of Straw Bale Retrieval." Sustainability 13, no. 14: 7722.

Journal article
Published: 10 February 2021 in Field Crops Research
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Cover crops are an important component of sustainable cereal cropping systems by providing nutrient retention and improving soil quality. However, the successful establishment and growth of cover crops depend on a timely harvest of the preceding annual crops. To assess the viability of growing cover crops in Denmark, a phenology model was developed, calibrated, cross-validated and applied to predict the harvest date of spring barley and winter wheat in Denmark using data from field experiments in Denmark during 1991 to 2018. A simple phenology model was used for the period from sowing to maturity, and this was extended to simulate the duration from maturity to harvest. This extended model was used to predict the harvest date in the ongoing season, and it provides the capability for assessing the performance of cover crops as a basis for improved cover crop management. The model uses temperature sums and day length to calculate the developmental rate of spring barley from sowing to harvest and for winter wheat from 1st January to harvest. The standard deviation of the estimated harvest date based on the uncertainty of the model parameters was 10-14 days and 1-4 days for spring barley and winter wheat, respectively. The model was evaluated using historically recorded temperature data (20 years, 1999–2018) to simulate harvest date, which was within the range of observed harvest dates. The interannual range of estimated harvest dates is 7–10 days for spring barley and 5–10 days for winter wheat. This interannual variation of harvest date was lower than the spatial variation across the country. The model can be used for forecasting cereal harvest time and thus readiness for autumn field operations, including the establishment of cover crops. Simulations of growing degree days from date of harvest to 1 November shows that cover crops can be reliably established in southern parts of Denmark to ensure low nitrate leaching. Advancing the harvest date to the date of physiological maturity of the cereals would allow the establishment of efficient cover crops in all years in the entire country.

ACS Style

Johannes W.M. Pullens; Claus A.G. Sørensen; Jørgen E. Olesen. Temperature-based prediction of harvest date in winter and spring cereals as a basis for assessing viability for growing cover crops. Field Crops Research 2021, 264, 108085 .

AMA Style

Johannes W.M. Pullens, Claus A.G. Sørensen, Jørgen E. Olesen. Temperature-based prediction of harvest date in winter and spring cereals as a basis for assessing viability for growing cover crops. Field Crops Research. 2021; 264 ():108085.

Chicago/Turabian Style

Johannes W.M. Pullens; Claus A.G. Sørensen; Jørgen E. Olesen. 2021. "Temperature-based prediction of harvest date in winter and spring cereals as a basis for assessing viability for growing cover crops." Field Crops Research 264, no. : 108085.

Journal article
Published: 22 November 2020 in Land
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Planting criteria of new vineyards should comply with rational and sustainable criteria, taking into account the potential mechanisability of existing viticultural areas. However, an established methodology for this assessment is still lacking. This study aimed at analysing the parameters which influence the vineyard mechanisability, with the objective to propose a new mechanisability index. The mechanisability index proposed was based on GIS-analysis of landscape and management parameters such as mean slope, shape of the vineyard block, length-width ratio, headland size, training system and row spacing. We identified a sample of 3686 vineyards in Italy. Based on the above-mentioned parameters, vineyards were categorised by their level of mechanisability (l.m.) into four classes. Moreover, we analysed the correlation between l.m. and economic indicators (area planted with vineyard and wine production). Results showed that the main factors limiting the mechanisability potential of some Italian regions are the elevated slopes, horizontal training systems and narrow vine spacings. The l.m. showed a moderate positive correlation with the size of vineyards and the volume and value of production. The methodology presented in this study may be easily applied to other viticultural areas around the world, serving as a management decision-making tool.

ACS Style

Alessia Cogato; Andrea Pezzuolo; Claus Grøn Sørensen; Roberta De Bei; Marco Sozzi; Francesco Marinello. A GIS-Based Multicriteria Index to Evaluate the Mechanisability Potential of Italian Vineyard Area. Land 2020, 9, 469 .

AMA Style

Alessia Cogato, Andrea Pezzuolo, Claus Grøn Sørensen, Roberta De Bei, Marco Sozzi, Francesco Marinello. A GIS-Based Multicriteria Index to Evaluate the Mechanisability Potential of Italian Vineyard Area. Land. 2020; 9 (11):469.

Chicago/Turabian Style

Alessia Cogato; Andrea Pezzuolo; Claus Grøn Sørensen; Roberta De Bei; Marco Sozzi; Francesco Marinello. 2020. "A GIS-Based Multicriteria Index to Evaluate the Mechanisability Potential of Italian Vineyard Area." Land 9, no. 11: 469.

Journal article
Published: 20 October 2020 in Agronomy
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Capacitated field operations involve input/output material flows where there are capacity constraints in the form of a specific load that a vehicle can carry. As such, a specific normal-sized field cannot be covered in one single operation using only one load, and the vehicle needs to get serviced (i.e., refilling) from out-of-field facilities (depot). Although several algorithms have been developed to solve the routing problem of capacitated operations, these algorithms only considered one depot. The general goal of this paper is to develop a route planning tool for agricultural machines with multiple depots. The tool presented consists of two modules: the first one regards the field geometrical representation in which the field is partitioned into tracks and headland passes; the second one regards route optimization that is implemented by the metaheuristic simulated annealing (SA) algorithm. In order to validate the developed tool, a comparison between a well-known route planning approach, namely B-pattern, and the algorithm presented in this study was carried out. The results show that the proposed algorithm outperforms the B-pattern by up to 20.0% in terms of traveled nonworking distance. The applicability of the tool developed was tested in a case study with seven scenarios differing in terms of locations and number of depots. The results of this study illustrated that the location and number of depots significantly affect the total nonworking traversal distance during a field operation.

ACS Style

Mahdi Vahdanjoo; Kun Zhou; Claus Aage Grøn Sørensen. Route Planning for Agricultural Machines with Multiple Depots: Manure Application Case Study. Agronomy 2020, 10, 1608 .

AMA Style

Mahdi Vahdanjoo, Kun Zhou, Claus Aage Grøn Sørensen. Route Planning for Agricultural Machines with Multiple Depots: Manure Application Case Study. Agronomy. 2020; 10 (10):1608.

Chicago/Turabian Style

Mahdi Vahdanjoo; Kun Zhou; Claus Aage Grøn Sørensen. 2020. "Route Planning for Agricultural Machines with Multiple Depots: Manure Application Case Study." Agronomy 10, no. 10: 1608.

Journal article
Published: 05 October 2020 in Sustainability
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COVID-19 and the restrictive measures towards containing the spread of its infections have seriously affected the agricultural workforce and jeopardized food security. The present study aims at assessing the COVID-19 pandemic impacts on agricultural labor and suggesting strategies to mitigate them. To this end, after an introduction to the pandemic background, the negative consequences on agriculture and the existing mitigation policies, risks to the agricultural workers were benchmarked across the United States’ Standard Occupational Classification system. The individual tasks associated with each occupation in agricultural production were evaluated on the basis of potential COVID-19 infection risk. As criteria, the most prevalent virus transmission mechanisms were considered, namely the possibility of touching contaminated surfaces and the close proximity of workers. The higher risk occupations within the sector were identified, which facilitates the allocation of worker protection resources to the occupations where they are most needed. In particular, the results demonstrated that 50% of the agricultural workforce and 54% of the workers’ annual income are at moderate to high risk. As a consequence, a series of control measures need to be adopted so as to enhance the resilience and sustainability of the sector as well as protect farmers including physical distancing, hygiene practices, and personal protection equipment.

ACS Style

Dionysis Bochtis; Lefteris Benos; Maria Lampridi; Vasso Marinoudi; Simon Pearson; Claus Sørensen. Agricultural Workforce Crisis in Light of the COVID-19 Pandemic. Sustainability 2020, 12, 8212 .

AMA Style

Dionysis Bochtis, Lefteris Benos, Maria Lampridi, Vasso Marinoudi, Simon Pearson, Claus Sørensen. Agricultural Workforce Crisis in Light of the COVID-19 Pandemic. Sustainability. 2020; 12 (19):8212.

Chicago/Turabian Style

Dionysis Bochtis; Lefteris Benos; Maria Lampridi; Vasso Marinoudi; Simon Pearson; Claus Sørensen. 2020. "Agricultural Workforce Crisis in Light of the COVID-19 Pandemic." Sustainability 12, no. 19: 8212.

Journal article
Published: 23 September 2020 in Agronomy
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This study specifies an agricultural field (Latitude = 56°30′0.8″ N, Longitude = 9°35′27.88″ E) and provides the absolute optimal route for covering that field. The calculated absolute optimal solution for this field can be used as the basis for benchmarking of metaheuristic algorithms used for finding the most efficient route in the field. The problem of finding the most efficient route that covers a field can be formulated as a Traveling Salesman Problem (TSP), which is an NP-hard problem. This means that the optimal solution is infeasible to calculate, except for very small fields. Therefore, a range of metaheuristic methods has been developed that provide a near-optimal solution to a TSP in a “reasonable” time. The main challenge with metaheuristic methods is that the quality of the solutions can normally not be compared to the absolute optimal solution since this “ground truth” value is unknown. Even though the selected benchmarking field requires only eight tracks, the solution space consists of more than 1.3 billion solutions. In this study, the absolute optimal solution for the capacitated coverage path planning problem was determined by calculating the non-working distance of the entire solution space and determining the solution with the shortest non-working distance. This was done for four scenarios consisting of low/high bin capacity and short/long distance between field and storage depot. For each scenario, the absolute optimal solution and its associated cost value (minimum non-working distance) were compared to the solutions of two metaheuristic algorithms; Simulated Annealing Algorithm (SAA) and Ant Colony Optimization (ACO). The benchmarking showed that neither algorithm could find the optimal solution for all scenarios, but they found near-optimal solutions, with only up to 6 pct increasing non-working distance. SAA performed better than ACO, concerning quality, stability, and execution time.

ACS Style

Erfan Khosravani Moghadam; Mahdi Vahdanjoo; Allan Leck Jensen; Mohammad Sharifi; Claus Aage Grøn Sørensen. An Arable Field for Benchmarking of Metaheuristic Algorithms for Capacitated Coverage Path Planning Problems. Agronomy 2020, 10, 1454 .

AMA Style

Erfan Khosravani Moghadam, Mahdi Vahdanjoo, Allan Leck Jensen, Mohammad Sharifi, Claus Aage Grøn Sørensen. An Arable Field for Benchmarking of Metaheuristic Algorithms for Capacitated Coverage Path Planning Problems. Agronomy. 2020; 10 (10):1454.

Chicago/Turabian Style

Erfan Khosravani Moghadam; Mahdi Vahdanjoo; Allan Leck Jensen; Mohammad Sharifi; Claus Aage Grøn Sørensen. 2020. "An Arable Field for Benchmarking of Metaheuristic Algorithms for Capacitated Coverage Path Planning Problems." Agronomy 10, no. 10: 1454.

Journal article
Published: 14 July 2020 in AgriEngineering
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The problem of finding an optimal solution for the slurry application process is casted as a capacitated vehicle routing problem (CVRP) in which by considering the vehicle’s capacity, it is required to visit all the tracks only once to fully cover the field, as well as complying with a specified targeted application rate. A key objective in this study was to determine an optimized coverage plan in order to minimize the driving distance in the field, while at the same time allowing for varying the application rate. The coverage plan includes the optimal sequence of tracks with a specified application rate for each track. Two algorithms were developed for optimization and simulation of the slurry application cast as capacitated operations. In order to validate the proposed algorithms, a slurry application operation was recorded, and the results of the optimization algorithm were compared with the conventional non-optimized method. The comparison showed that applying the proposed new method reduces the non-working distance by 18.6% and the non-working time by 28.1%.

ACS Style

Mahdi Vahdanjoo; Christian Toft Madsen; Claus Grøn Sørensen. Novel Route Planning System for Machinery Selection. Case: Slurry Application. AgriEngineering 2020, 2, 408 -429.

AMA Style

Mahdi Vahdanjoo, Christian Toft Madsen, Claus Grøn Sørensen. Novel Route Planning System for Machinery Selection. Case: Slurry Application. AgriEngineering. 2020; 2 (3):408-429.

Chicago/Turabian Style

Mahdi Vahdanjoo; Christian Toft Madsen; Claus Grøn Sørensen. 2020. "Novel Route Planning System for Machinery Selection. Case: Slurry Application." AgriEngineering 2, no. 3: 408-429.

Review
Published: 17 May 2020 in Applied Sciences
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The advent of mobile robots in agriculture has signaled a digital transformation with new automation technologies optimize a range of labor-intensive, resources-demanding, and time-consuming agri-field operations. To that end a generally accepted technical lexicon for mobile robots is lacking as pertinent terms are often used interchangeably. This creates confusion among research and practice stakeholders. In addition, a consistent definition of planning attributes in automated agricultural operations is still missing as relevant research is sparse. In this regard, a “narrative” review was adopted (1) to provide the basic terminology over technical aspects of mobile robots used in autonomous operations and (2) assess fundamental planning aspects of mobile robots in agricultural environments. Based on the synthesized evidence from extant studies, seven planning attributes have been included: (i) high-level control-specific attributes, which include reasoning architecture, the world model, and planning level, (ii) operation-specific attributes, which include locomotion–task connection and capacity constraints, and (iii) physical robot-specific attributes, which include vehicle configuration and vehicle kinematics.

ACS Style

Vasileios Moisiadis; Naoum Tsolakis; Dimitris Katikaridis; Claus G. Sørensen; Simon Pearson; Dionysis Bochtis. Mobile Robotics in Agricultural Operations: A Narrative Review on Planning Aspects. Applied Sciences 2020, 10, 3453 .

AMA Style

Vasileios Moisiadis, Naoum Tsolakis, Dimitris Katikaridis, Claus G. Sørensen, Simon Pearson, Dionysis Bochtis. Mobile Robotics in Agricultural Operations: A Narrative Review on Planning Aspects. Applied Sciences. 2020; 10 (10):3453.

Chicago/Turabian Style

Vasileios Moisiadis; Naoum Tsolakis; Dimitris Katikaridis; Claus G. Sørensen; Simon Pearson; Dionysis Bochtis. 2020. "Mobile Robotics in Agricultural Operations: A Narrative Review on Planning Aspects." Applied Sciences 10, no. 10: 3453.

Research paper
Published: 15 April 2020 in Systems Research and Behavioral Science
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The information of how the high climatic variability in the south‐west Buenos Aires Province (SWBS) region, Argentina, impacts on existing cow–calf operations is needed. This research uses a combination of quantitative (modelling) and qualitative (workshops) methodologies. The objective was to assess, under interannual climate variability, the productive and economic performance and greenhouse gas emissions and the marginal value of additional feed of four cow–calf systems arranged as a potential farm innovation path in the SWBS, Argentina. Modelling results showed that along this technological path where forage crops are decreased, perennial pastures are increased and anticipated weaning is included, productive and economic outcomes increased and the emission intensity decreased. How extra feeds may be used to cope with seasonal and interannual feeding was also identified. Moreover, barriers to adopt the suggested farm innovation path were identified by farmers, consultants and extensionists and strategies and their implication discussed.

ACS Style

Catalina Fernández Rosso; Franco Bilotto; Andrea Lauric; Gerónimo A. De Leo; Carlos Torres Carbonell; Mauricio A. Arroqui; Claus G. Sørensen; Claudio F. Machado. An innovation path in Argentinean cow–calf operations: Insights from participatory farm system modelling. Systems Research and Behavioral Science 2020, 38, 488 -502.

AMA Style

Catalina Fernández Rosso, Franco Bilotto, Andrea Lauric, Gerónimo A. De Leo, Carlos Torres Carbonell, Mauricio A. Arroqui, Claus G. Sørensen, Claudio F. Machado. An innovation path in Argentinean cow–calf operations: Insights from participatory farm system modelling. Systems Research and Behavioral Science. 2020; 38 (4):488-502.

Chicago/Turabian Style

Catalina Fernández Rosso; Franco Bilotto; Andrea Lauric; Gerónimo A. De Leo; Carlos Torres Carbonell; Mauricio A. Arroqui; Claus G. Sørensen; Claudio F. Machado. 2020. "An innovation path in Argentinean cow–calf operations: Insights from participatory farm system modelling." Systems Research and Behavioral Science 38, no. 4: 488-502.

Journal article
Published: 10 February 2020 in Energies
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The calculation of the energy cost of a cultivation is a determining factor in the overall assessment of agricultural sustainability. Most studies mainly examine the entire life cycle of the operation, considering reference values and reference databases for the determination of the machinery contribution to the overall energy balance. This study presents a modelling methodology for the precise calculation of the energy cost of performing an agricultural operation. The model incorporates operational management into the calculation, while simultaneously considering the commercially available machinery (implements and tractors). As a case study, the operation of tillage was used considering both primary and secondary tillage (moldboard plow and field cultivator, respectively). The results show the importance of including specific operation parameters and the available machinery as part of determining the accurate total energy consumption, even though the field size and available time do not have a significant effect.

ACS Style

Maria Lampridi; Dimitrios Kateris; Claus Grøn Sørensen; Dionysis Bochtis. Energy Footprint of Mechanized Agricultural Operations. Energies 2020, 13, 769 .

AMA Style

Maria Lampridi, Dimitrios Kateris, Claus Grøn Sørensen, Dionysis Bochtis. Energy Footprint of Mechanized Agricultural Operations. Energies. 2020; 13 (3):769.

Chicago/Turabian Style

Maria Lampridi; Dimitrios Kateris; Claus Grøn Sørensen; Dionysis Bochtis. 2020. "Energy Footprint of Mechanized Agricultural Operations." Energies 13, no. 3: 769.

Journal article
Published: 24 January 2020 in Livestock Science
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In recent years, broiler meat consumption and trade have undergone considerable growth. Due to this reason, particular attention has been paid to the management of its production process with the aim of reaching a high quality, short process time and low-cost production. This study attempts to use fuzzy logic mathematics as part of a decision support system for managing time, cost and quality in broiler production. For having an effective management system, process uncertainties have been taken into account This approach considers the process as an interval with fuzzy numbers and, for managing the risks, it uses the variable α, a parameter determined by the manager in an interval between 0 and 1. Non-dominated Sorting Genetic Algorithm-II (NSGA-II) with fuzzy input has been used to optimize the entire broiler production. Due to a large number of activities and logical options available, this process has more possible solutions. To achieve an optimal unique solution, an objective function has been used and, weights for time, cost and quality have been assigned. Based on the results, in conditions of uncertainty (Fuzzy α Cut = 0), the amount of time, cost and quality, have been calculated respectively as 1792.836 h, 260573.04 $ and 49.6%, while, in conditions of certainty (Fuzzy α Cut = 1), they have been computed as 1789.194 h, 260392.34 $ and 52.85%.

ACS Style

Erfan Khosravani Moghadam; Mohammad Sharifi; Shahin Rafiee; Claus Aage Grøn Sørensen. Broiler management using fuzzy multi-objective genetic algorithm: A case study. Livestock Science 2020, 233, 103941 .

AMA Style

Erfan Khosravani Moghadam, Mohammad Sharifi, Shahin Rafiee, Claus Aage Grøn Sørensen. Broiler management using fuzzy multi-objective genetic algorithm: A case study. Livestock Science. 2020; 233 ():103941.

Chicago/Turabian Style

Erfan Khosravani Moghadam; Mohammad Sharifi; Shahin Rafiee; Claus Aage Grøn Sørensen. 2020. "Broiler management using fuzzy multi-objective genetic algorithm: A case study." Livestock Science 233, no. : 103941.

Journal article
Published: 07 January 2020 in Agronomy
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Advanced systems for manned and/or agricultural vehicles—such as systems for auto-steering, navigation-adding, and autonomous route planning—require new capabilities in terms of the internal representation for the autonomous system of the working space; that is, the generation of a metric map that provides by numerical parameters any operation-related entity of the working space. In this paper, a real-time approach was developed for the generation of the field metric map, based on a row generation method (polygons-based geometry). The approach can deal with fields with or without in-field obstacles, where the generated field-work tracks can be either straight or curved. The functionality of the approach was demonstrated on 12 fields with different number of obstacles ranging from one to six. The test results showed that the computational times were in the range of 0.26–24.51 s. The presented tool brings a number of advancements on the process of generating a metric map for arable farming field operations, including the real-time generation feature, the potential to deal with multiple-obstacle areas, and the reduction in the overlapped area.

ACS Style

Kun Zhou; Allan Leck Jensen; Dionysis Bochtis; Michael Nørremark; Dimitrios Kateris; Claus Grøn Sørensen. Metric Map Generation for Autonomous Field Operations. Agronomy 2020, 10, 83 .

AMA Style

Kun Zhou, Allan Leck Jensen, Dionysis Bochtis, Michael Nørremark, Dimitrios Kateris, Claus Grøn Sørensen. Metric Map Generation for Autonomous Field Operations. Agronomy. 2020; 10 (1):83.

Chicago/Turabian Style

Kun Zhou; Allan Leck Jensen; Dionysis Bochtis; Michael Nørremark; Dimitrios Kateris; Claus Grøn Sørensen. 2020. "Metric Map Generation for Autonomous Field Operations." Agronomy 10, no. 1: 83.

Journal article
Published: 01 January 2020 in Applied Sciences
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The evaluation and prediction of the agricultural machinery field efficiency is essential for agricultural operations management. Field efficiency is affected by unpredictable (e.g., machine breakdowns) and stochastic (e.g., yield) factors, and thus, it is generally provided by average norms. However, the average values and ranges of the field efficiency are of limited value when a decision has to be made on the selection of the appropriate machinery system for a specific operational set up. To this end, in this paper, a new index for field operability, the field traversing efficiency (FTE), a distance-based measure, is introduced and a dedicated tool for estimation of this measure is presented. In order to show the degree of the dependence of the FTE index on the operational features, a number of 864 scenarios derived from the consideration of six sample field shapes, three conventional fieldwork patterns, four driving directions, and twelve combinations of machine unit kinematics and implement width were evaluated by the developed tool. The test results showed that variation of FTE was up to 23% in the tested scenarios when using different operational setups.

ACS Style

Kun Zhou; Dionysis Bochtis; Allan Leck Jensen; Dimitrios Kateris; Claus Grøn Sørensen. Introduction of a New Index of Field Operations Efficiency. Applied Sciences 2020, 10, 329 .

AMA Style

Kun Zhou, Dionysis Bochtis, Allan Leck Jensen, Dimitrios Kateris, Claus Grøn Sørensen. Introduction of a New Index of Field Operations Efficiency. Applied Sciences. 2020; 10 (1):329.

Chicago/Turabian Style

Kun Zhou; Dionysis Bochtis; Allan Leck Jensen; Dimitrios Kateris; Claus Grøn Sørensen. 2020. "Introduction of a New Index of Field Operations Efficiency." Applied Sciences 10, no. 1: 329.

Review
Published: 19 September 2019 in Sustainability
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This paper presents a methodological framework for the systematic literature review of agricultural sustainability studies. The framework synthesizes all the available literature review criteria and introduces a two-level analysis facilitating systematization, data mining, and methodology analysis. The framework was implemented for the systematic literature review of 38 crop agricultural sustainability assessment studies at farm-level for the last decade. The investigation of the methodologies used is of particular importance since there are no standards or norms for the sustainability assessment of farming practices. The chronological analysis revealed that the scientific community’s interest in agricultural sustainability is increasing in the last three years. The most used methods include indicator-based tools, frameworks, and indexes, followed by multicriteria methods. In the reviewed studies, stakeholder participation is proved crucial in the determination of the level of sustainability. It should also be mentioned that combinational use of methodologies is often observed, thus a clear distinction of methodologies is not always possible.

ACS Style

Maria Lampridi; Claus Sørensen; Dionysis Bochtis. Agricultural Sustainability: A Review of Concepts and Methods. Sustainability 2019, 11, 5120 .

AMA Style

Maria Lampridi, Claus Sørensen, Dionysis Bochtis. Agricultural Sustainability: A Review of Concepts and Methods. Sustainability. 2019; 11 (18):5120.

Chicago/Turabian Style

Maria Lampridi; Claus Sørensen; Dionysis Bochtis. 2019. "Agricultural Sustainability: A Review of Concepts and Methods." Sustainability 11, no. 18: 5120.

Journal article
Published: 05 April 2019 in Agronomy
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The need to intensify agriculture to meet increasing nutritional needs, in combination with the evolution of unmanned autonomous systems has led to the development of a series of “smart” farming technologies that are expected to replace or complement conventional machinery and human labor. This paper proposes a preliminary methodology for the economic analysis of the employment of robotic systems in arable farming. This methodology is based on the basic processes for estimating the use cost for agricultural machinery. However, for the case of robotic systems, no average norms for the majority of the operational parameters are available. Here, we propose a novel estimation process for these parameters in the case of robotic systems. As a case study, the operation of light cultivation has been selected due the technological readiness for this type of operation.

ACS Style

Maria G. Lampridi; Dimitrios Kateris; Giorgos Vasileiadis; Vasso Marinoudi; Simon Pearson; Claus G. Sørensen; Athanasios Balafoutis; Dionysis Bochtis. A Case-Based Economic Assessment of Robotics Employment in Precision Arable Farming. Agronomy 2019, 9, 175 .

AMA Style

Maria G. Lampridi, Dimitrios Kateris, Giorgos Vasileiadis, Vasso Marinoudi, Simon Pearson, Claus G. Sørensen, Athanasios Balafoutis, Dionysis Bochtis. A Case-Based Economic Assessment of Robotics Employment in Precision Arable Farming. Agronomy. 2019; 9 (4):175.

Chicago/Turabian Style

Maria G. Lampridi; Dimitrios Kateris; Giorgos Vasileiadis; Vasso Marinoudi; Simon Pearson; Claus G. Sørensen; Athanasios Balafoutis; Dionysis Bochtis. 2019. "A Case-Based Economic Assessment of Robotics Employment in Precision Arable Farming." Agronomy 9, no. 4: 175.

Conference paper
Published: 12 February 2019 in Communications in Computer and Information Science
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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.

ACS Style

Claus Aage Grøn Sørensen; Dimitrios Kateris; Dionysis Bochtis. ICT Innovations and Smart Farming. Communications in Computer and Information Science 2019, 1 -19.

AMA Style

Claus Aage Grøn Sørensen, Dimitrios Kateris, Dionysis Bochtis. ICT Innovations and Smart Farming. Communications in Computer and Information Science. 2019; ():1-19.

Chicago/Turabian Style

Claus Aage Grøn Sørensen; Dimitrios Kateris; Dionysis Bochtis. 2019. "ICT Innovations and Smart Farming." Communications in Computer and Information Science , no. : 1-19.

Chapter
Published: 16 November 2017 in Progress in Precision Agriculture
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Agriculture nowadays includes automation systems that contribute significantly to many levels of the food production process. Such systems include GPS based systems like auto-steering and Controlled Traffic Farming (CTF). These systems have led to many innovations in agricultural field area coverage design. Integrating these advancements, two different route planning designs, a traditional and an optimised one, are outlined and explained in this chapter. Four different machinery scenarios were tested in four fields each, and the main aim was to compare the two different route planning systems under economic criteria and identify the best operational route coverage design criterion. The results show that there are significant reductions in operational costs varying from 9 to 20%, depending on the specific machinery and field configurations. Such results show the considerable potential of advanced route planning designs and further optimization measures. They indicate the need for research efforts that quantify the operational and economic benefits by optimising field coverage designs in the headlands, turnings or obstacles avoidance according to the actual configuration to minimize the non-working activities and, as a consequence, the overall operational cost.

ACS Style

Claus G. Sørensen; Efthymios Rodias; Dionysis Bochtis. Auto-Steering and Controlled Traffic Farming – Route Planning and Economics. Progress in Precision Agriculture 2017, 129 -145.

AMA Style

Claus G. Sørensen, Efthymios Rodias, Dionysis Bochtis. Auto-Steering and Controlled Traffic Farming – Route Planning and Economics. Progress in Precision Agriculture. 2017; ():129-145.

Chicago/Turabian Style

Claus G. Sørensen; Efthymios Rodias; Dionysis Bochtis. 2017. "Auto-Steering and Controlled Traffic Farming – Route Planning and Economics." Progress in Precision Agriculture , no. : 129-145.

Journal article
Published: 27 October 2017 in Sustainability
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Various types of sensors technologies, such as machine vision and global positioning system (GPS) have been implemented in navigation of agricultural vehicles. Automated navigation systems have proved the potential for the execution of optimised route plans for field area coverage. This paper presents an assessment of the reduction of the energy requirements derived from the implementation of optimised field area coverage planning. The assessment regards the analysis of the energy requirements and the comparison between the non-optimised and optimised plans for field area coverage in the whole sequence of operations required in two different cropping systems: Miscanthus and Switchgrass production. An algorithmic approach for the simulation of the executed field operations by following both non-optimised and optimised field-work patterns was developed. As a result, the corresponding time requirements were estimated as the basis of the subsequent energy cost analysis. Based on the results, the optimised routes reduce the fuel energy consumption up to 8%, the embodied energy consumption up to 7%, and the total energy consumption from 3% up to 8%.

ACS Style

Efthymios Rodias; Remigio Berruto; Patrizia Busato; Dionysis Bochtis; Claus Grøn Sørensen; Kun Zhou. Energy Savings from Optimised In-Field Route Planning for Agricultural Machinery. Sustainability 2017, 9, 1956 .

AMA Style

Efthymios Rodias, Remigio Berruto, Patrizia Busato, Dionysis Bochtis, Claus Grøn Sørensen, Kun Zhou. Energy Savings from Optimised In-Field Route Planning for Agricultural Machinery. Sustainability. 2017; 9 (11):1956.

Chicago/Turabian Style

Efthymios Rodias; Remigio Berruto; Patrizia Busato; Dionysis Bochtis; Claus Grøn Sørensen; Kun Zhou. 2017. "Energy Savings from Optimised In-Field Route Planning for Agricultural Machinery." Sustainability 9, no. 11: 1956.

Review
Published: 23 March 2017 in Soil Use and Management
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Soil workability and friability are required parameters to consider when creating suitable seedbeds for crop establishment and growth. Knowledge of soil workability is important for scheduling tillage operations and for reducing the risk of tillage‐induced structural degradation of soils. A reliable evaluation of soil workability implies a distinctive definition of the critical water content (wet and dry limits) for tillage. In this review, we provide a comprehensive assessment of the methods for determining soil workability, and the effects of soil properties and tillage systems on soil workability and fragmentation. The strengths and limitations of the different methods for evaluating the water content for soil workability, such as the plastic limit, soil water retention curve (SWRC), standard Proctor compaction test, field assessment, moisture‐pressure‐volume diagram, air permeability and drop‐shatter tests are discussed. Our review reveals that there is limited information on the dry limit and the range of water content for soil workability for different textured soils. We identify the need for further research to evaluate soil workability on undisturbed soils using a combination of SWRC and the drop‐shatter tests or tensile strength; (i) to quantify the effects of soil texture, organic matter and compaction on soil workability; and (ii) to compare soil water content for workability in the field with theoretical soil workability, thereby improving the prediction of soil workability as part of a decision support system for tillage operations.

ACS Style

P. B. Obour; Mathieu Lamandé; G. Edwards; Claus Grøn Sørensen; L. J. Munkholm. Predicting soil workability and fragmentation in tillage: a review. Soil Use and Management 2017, 33, 288 -298.

AMA Style

P. B. Obour, Mathieu Lamandé, G. Edwards, Claus Grøn Sørensen, L. J. Munkholm. Predicting soil workability and fragmentation in tillage: a review. Soil Use and Management. 2017; 33 (2):288-298.

Chicago/Turabian Style

P. B. Obour; Mathieu Lamandé; G. Edwards; Claus Grøn Sørensen; L. J. Munkholm. 2017. "Predicting soil workability and fragmentation in tillage: a review." Soil Use and Management 33, no. 2: 288-298.