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Agronomy
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The Future of Agriculture: Towards Automation
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The Future of Agriculture: Towards Automation

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Agricultural Biosystem and Biological Engineering".

Deadline for manuscript submissions: closed (15 July 2021) | Viewed by 13330

Special Issue Editor

Prof. Dr. Claus Grøn Sørensen

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, Aarhus University, 8000 Aarhus, Denmark
Interests: system technology; operations management; modelling optimization and evaluation of production systems and decision support related to operations; logistics and supply chain management; resource analyses and optimizations; novel information technologies for data acquisition; integration of technical management evaluations for whole farm analyses and optimizations; evaluation of innovative agricultural production systems; the feasibility of introducing robotic systems in agriculture

Special Issue Information

Dear Colleagues,

The challenges facing the agro-food system include improving efficiency, mitigating climate change, and sustaining sustainability and resilience, etc. The responses to these challenges must embrace digitalization and automation. Digital technologies and automation including robots are identified as a key opportunity to revolutionize agriculture, by increasing productivity and reducing the environmental impacts of farming and also by enabling completely new farming systems. The latter is important, as innovations such as automation should be seen not only as a one-to-one replacement of old technologies with new ones. Additionally, the technology must be reimagined as part of the whole farm system, where its implementation relates to the broader context and is actively part of forming the praxis, of which it is itself a part. This will affect how embedded knowledge and work procedures are changed, including changing the basic understanding of the work and the professional identity of the user. 

In this Special Issue, we are open to contributions (research papers and a limited number of reviews) exploring the advancement of innovative automation for smart farming, including agri-food supply chains. This includes both the physical development of automation technologies and system engineering, including how technology affects and changes the whole production system, and how technology is part of ongoing sustainability efforts. In addition, studies on the integration of automation with the advent of digitalization and the identification of incentives and barriers for the adoption of automation technologies are also welcome.

Prof. Dr. Claus Grøn Sørensen
Guest Editor

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 submissions that pass pre-check are 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. Agronomy 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 2600 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.

Keywords

  • automation
  • robots
  • sustainability
  • adoption
  • system engineering
  • digitalization

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Published Papers (4 papers)

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Research

22 pages, 29285 KiB  
Article
In-Field Route Planning Optimisation and Performance Indicators of Grain Harvest Operations
by Michael Nørremark, René Søndergaard Nilsson and Claus Aage Grøn Sørensen
Agronomy 2022, 12(5), 1151; https://doi.org/10.3390/agronomy12051151 - 10 May 2022
Cited by 10 | Viewed by 3278
Abstract
Operational planning, automation, and optimisation of field operations are ways to sustain the production of food and feed. A coverage path planning method mitigating the optimisation and automation of harvest operations, characterised by capacity limitations and features derived from real world scenarios, is [...] Read more.
Operational planning, automation, and optimisation of field operations are ways to sustain the production of food and feed. A coverage path planning method mitigating the optimisation and automation of harvest operations, characterised by capacity limitations and features derived from real world scenarios, is presented. Although prior research has developed similar methods, no such methodologies have been developed for (i) multiple field entrances as line segments, (ii) the feasibility of stationary and on-the-go unloading in the headland and main field, (iii) unloading timing independent of the full bin level of the harvester, and (iv) the transport unit operational time outside the field. To find the permutation that best minimises the costs in time and distance, an artificial bee colony (ABC) algorithm was used as a meta-heuristic optimisation method. The effectiveness of the method was analysed by generating simulated operational data and by comparing it to recorded data from seven fields ranging in size (5–26 ha) and shape. The implementation of controlled traffic farming (CTF) in the coverage path planning method, but not with the recorded data, resulted in a reduced risk of soil compaction of up to 25%, and a reduction in the in-field total travel distance of up to 15% when logistics was optimised simultaneously for two transport units. A 68% increase in the full load frequency of transporting vehicles and a 14% reduction in the total number of field to storage transports was observed. For fields located at outermost edges of the storage facility (>5 km), the increase in full load frequency, average load level, and decrease in in-field travel distance resulted in a reduction in fuel consumption by 7%. Embedding the developed coverage path planning software as a service will improve the sustainability of harvest operations including a fleet of one to many harvesting and transporting units, as the system in front of the vehicle operator calculates and displays all required actions from the operator. Full article
(This article belongs to the Special Issue The Future of Agriculture: Towards Automation)
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15 pages, 3019 KiB  
Article
Evaluation of Grain Quality-Based Simulated Selective Harvest Performed by an Autonomous Agricultural Robot
by Andrés Villa-Henriksen, Gareth Thomas Charles Edwards, Ole Green and Claus Aage Grøn Sørensen
Agronomy 2021, 11(9), 1728; https://doi.org/10.3390/agronomy11091728 - 29 Aug 2021
Cited by 2 | Viewed by 2587
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue The Future of Agriculture: Towards Automation)
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24 pages, 9614 KiB  
Article
Diaphragm-Type Pneumatic-Driven Soft Grippers for Precision Harvesting
by Eduardo Navas, Roemi Fernández, Manuel Armada and Pablo Gonzalez-de-Santos
Agronomy 2021, 11(9), 1727; https://doi.org/10.3390/agronomy11091727 - 29 Aug 2021
Cited by 14 | Viewed by 3326
Abstract
Soft actuator technology and its role in robotic manipulation have been rapidly gaining ground. However, less attention has been given to the potential advantages of its application to the agricultural sector, where soft robotics may be a game changer due to its greater [...] Read more.
Soft actuator technology and its role in robotic manipulation have been rapidly gaining ground. However, less attention has been given to the potential advantages of its application to the agricultural sector, where soft robotics may be a game changer due to its greater adaptability, lower cost and simplicity of manufacture. This article presents a new design approach for soft grippers based on modules that incorporate the concept of bellows and combine it with the versatility and replicability of a 3D printed structure. In this way, the modules can be freely configured to obtain grippers adaptable to crops of different diameters. Furthermore, the definition of a method to determine the soft grippers features is also presented, with the aim of serving as the basis for a future benchmarking study on soft actuators. The experimental tests carried out demonstrated the feasibility and capability of the end-effectors to manipulate various fruits, ensuring a sufficient contact area for the safe handling of the targets and avoiding damaging the products. Full article
(This article belongs to the Special Issue The Future of Agriculture: Towards Automation)
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17 pages, 3522 KiB  
Article
Results of Laboratory Studies of the Automated Sorting System for Root and Onion Crops
by Alexey Dorokhov, Alexander Aksenov, Alexey Sibirev, Nikolay Sazonov, Maxim Mosyakov and Maria Godyaeva
Agronomy 2021, 11(6), 1257; https://doi.org/10.3390/agronomy11061257 - 21 Jun 2021
Cited by 7 | Viewed by 3282
Abstract
The roller and sieve machines most commonly used in Russia for the post-harvest processing of root and tuber crops and onions have a number of disadvantages, the main one being a decrease in the quality of sorting due to the contamination of working [...] Read more.
The roller and sieve machines most commonly used in Russia for the post-harvest processing of root and tuber crops and onions have a number of disadvantages, the main one being a decrease in the quality of sorting due to the contamination of working bodies, which increases the quantity of losses during sorting and storage. To obtain high-quality competitive production, it is necessary to combine a number of technological operations during the sorting process, such as dividing the material into classes and fractions by quality and size, as well as identifying and removing damaged products. In order to improve the quality of sorting of root tubers and onions by size, it is necessary to ensure the development of an automatic control system for operating and technological parameters, the use of which will eliminate manual sorting on bulkhead tables in post-harvest processing. To fulfill these conditions, the developed automatic control system must have the ability to identify the material on the sorting surface, taking into account external damage and ensuring the automatic removal of impurities. In this study, the highest sorting accuracy of tubers (of more than 91%) was achieved with a forward speed of 1.2 m/s for the conveyor of the sorting table, with damage to 2.2% of the tubers, which meets the agrotechnical requirements for post-harvest processing. This feature distinguishes the developed device from similar ones. Full article
(This article belongs to the Special Issue The Future of Agriculture: Towards Automation)
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