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AgriEngineering
Special Issues
Advances in Mechanization and Agricultural Automation
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Advances in Mechanization and Agricultural Automation

A special issue of AgriEngineering (ISSN 2624-7402).

Deadline for manuscript submissions: closed (1 October 2020) | Viewed by 8976

Special Issue Editor

Dr. Travis Esau

E-Mail Website
Guest Editor
Department of Engineering, Dalhousie University Faculty of Agriculture, 39 Cox Road, Truro, NS B2N 5E3, Canada
Interests: mechanized systems; agricultural automation; real-time sensing and control systems; digital agriculture; variable rate technology

Special Issue Information

Dear Colleagues,

Traditional agricultural farming is not sustainable and strongly requires new engineering advancements to remain competitive in both local and global markets. Recent advances in agricultural mechanization and automation have gained the attention of various participants, including academia, government, farmers, manufactures, and food processing industries. Agricultural mechanization and automation have pushed to reduce human labor and increase efficiencies at the same time as creating a safer work environment. Advances in agricultural mechanization and automation are also promising in terms of addressing the challenges of food security and traceability efforts we are facing in the 21st century. The development of advanced sensing systems coupled with intelligent control systems in traditional agricultural operations (tillage, planting, fertilization, weed control, disease control, insect control, irrigation, pesticide applications, nutrient management, etc.) is expanding enormously due to their economic and environmental benefits. This Special Issue covers the recent advances in mechanization and agricultural automation, including technology development and testing, machine design and evaluations, precision agriculture technologies, irrigation and drainage, digital agriculture technologies, variable rate technologies, spatial and temporal variability, smart soil and water management, and smart sensor integration and control systems on farm machinery.

Dr. Travis Esau
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. AgriEngineering is an international peer-reviewed open access quarterly 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 1600 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

  • Mechanization
  • Agricultural automation
  • Technology development and testing
  • Machine design and evaluations
  • Precision and digital agriculture technologies
  • Irrigation and drainage
  • Variable rate technologies
  • Spatial and temporal variability
  • Smart soil and water management
  • Smart sensor integration and control systems on farm machinery

Published Papers (2 papers)

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Research

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14 pages, 3170 KiB  
Article
Development and Evaluation of a Closed-Loop Control System for Automation of a Mechanical Wild Blueberry Harvester’s Picking Reel
by Travis J. Esau, Craig B. MacEachern, Qamar U. Zaman and Aitazaz A. Farooque
AgriEngineering 2020, 2(2), 322-335; https://doi.org/10.3390/agriengineering2020022 - 11 Jun 2020
Cited by 3 | Viewed by 3963
Abstract
Mechanical harvesting of wild blueberries remains the most cost-effective means for harvesting the crop. Harvesting of wild blueberries is heavily reliant on operator skill and full automation of the harvester will rely on precise and accurate determination of the picking reel’s height. This [...] Read more.
Mechanical harvesting of wild blueberries remains the most cost-effective means for harvesting the crop. Harvesting of wild blueberries is heavily reliant on operator skill and full automation of the harvester will rely on precise and accurate determination of the picking reel’s height. This study looked at developing a control system which would provide feedback on harvester picking reel height on up to five harvester heads. Additionally, the control system looked at implementing three quality of life improvements for operators, operating multiple heads until the point when full automation is achieved. These three functions were a tandem movement function, a baseline function, and a set-to-one function. Each of these functions were evaluated for their precision and accuracy and returned absolute mean discrepancies of 3.10, 2.20, and 2.50 mm respectively. Both electric and hydraulic actuators were evaluated for their effectiveness in this system however, the electric actuator was simply too slow to be deemed viable for the commercial harvesters. To achieve the full 203.2 mm stroke required by the harvester head, the electric actuator required 13.96 s while the hydraulic actuator required only 2.30 s under the same load. Full article
(This article belongs to the Special Issue Advances in Mechanization and Agricultural Automation)
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Other

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11 pages, 2566 KiB  
Concept Paper
Predicting Field Efficiency of Round-Baling Operations in High-Yielding Biomass Crops
by Robert “Bobby” Grisso, John S. Cundiff and Erin G. Webb
AgriEngineering 2020, 2(3), 447-457; https://doi.org/10.3390/agriengineering2030030 - 22 Jul 2020
Cited by 1 | Viewed by 3819
Abstract
Model simulations for bioenergy harvest planning need to utilize equipment-capacity relationships for equipment operating under the high-yield conditions typical of a biomass crop. These performance assumptions have a direct bearing on the estimates of machine capacity, the number of machines required, and, therefore, [...] Read more.
Model simulations for bioenergy harvest planning need to utilize equipment-capacity relationships for equipment operating under the high-yield conditions typical of a biomass crop. These performance assumptions have a direct bearing on the estimates of machine capacity, the number of machines required, and, therefore, the cost to fulfill the biorefinery plant demands for a given harvest window. Typically, two major issues in these models have been poorly understood: the available time required to complete the harvest operation (often called probability of workdays) and the capacity of the harvest equipment as impacted by yield. Simulations use annual yield estimates, which incorporate weather events, to demonstrate year-to-year effects. Some simulations also incorporate potential yield increases from genetically modified energy crops. There are limited field performance data for most current forage equipment used for harvesting high-yield biomass crops. Analysis shows that the impact of wrap/eject time for round balers resulted in a 50% reduction in achieved throughput capacity (Mg/h). After the maximum throughput is reached, the cost of the round bale operation (3.23 USD/Mg) is double that of the large-square baler (1.63 USD/Mg). The round baler achieved throughput capacity is 50% less (32.7 Mg/h compared to 71.0 Mg/h) than the large-square baler. Full article
(This article belongs to the Special Issue Advances in Mechanization and Agricultural Automation)
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