Agricultural Automation and Innovative Agricultural Systems—2nd Edition

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Precision and Digital Agriculture".

Deadline for manuscript submissions: 31 May 2024 | Viewed by 6712

Special Issue Editors


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Guest Editor
Agriculture Academy, Faculty of Agricultural Engineering, Institute of Agricultural Engineering and Safety, Vytautas Magnus University, Studentu Str. 15A, LT-53362 Akademija, Kaunas Distr., Lithuania
Interests: agricultural engineering; environment engineering; reduced tillage technologies; sowing machinery; precision agriculture; sowing and weed control robots; technological, energetic, and environmental assessment of the impact of agricultural technological operations on soil and environmental pollution
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Agriculture Academy, Faculty of Agricultural Engineering, Institute of Agricultural Engineering and Safety, Vytautas Magnus University, Studentu Str. 15A, LT-53362 Akademija, Kaunas Distr., Lithuania
Interests: environmental engineering; agricultural technologies; sustainable animal husbandry; energy cost reduction and environmental sustainability in various agricultural systems; multicriteria bioimpact effectiveness for environmental improvement
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Agroecosystems and Soil Sciences, Faculty of Agronomy, Agriculture Academy, Vytautas Magnus University, Studentu Str. 11, LT-53361 Akademija, Lithuania
Interests: soil, crop and residues management improvement; soil health; soil organic matter; soil biological activity; soil agrochemical and agrophysical parameters; use of bioactivators; meat and bone meal fertilisers in crop growing technologies; crop and weed allelopathy; sustainable agrotechnologies; precision agriculture; ICT in agriculture
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Delivering the European Green Deal and UN Sustainable Development Goals (SDGs) has highlighted the importance of achieving agricultural transition via the employment and realization of innovative agricultural systems, digitalization and automation. At present, technological developments are extremely rapid, but are still not implemented sufficiently in the agricultural sector. Innovations and automation are able to ensure the healthy production of food, the sustainable use of resources, and the adaptation and mitigation of climate change with the aim of saving the planet for future generations. Researchers play a crucial role in answering questions and helping to implement innovative adaptations in practice. In this Special Issue, we invite you to share the results of your high-quality research into innovative agrotechnologies, the application of novel preparations and equipment, automation, robotization, digitalization, ICT, sensors in agricultural systems, the application of precision agriculture, smart agricultural engineering in conventional, sustainable and organic crop production, horticulture, animal husbandry, and primary processing.

Prof. Dr. Egidijus Šarauskis
Dr. Vilma Naujokienė
Dr. Zita Kriauciuniene
Guest Editors

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

  • agricultural machinery
  • automation and robotization
  • digital agriculture
  • precision agriculture
  • organic agriculture
  • innovation in animal husbandry
  • soil management
  • sowing, fertilization, spraying operations
  • plant care
  • harvesting
  • application of innovative bio-products
  • primary processing
  • sensing methods and devices
  • validation of automated methods
  • energy, economic and environmental assessment

Related Special Issue

Published Papers (2 papers)

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Research

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14 pages, 5898 KiB  
Article
Theoretical and Experimental Verification of the Physical–Mechanical Properties of Organic Bone Meal Granular Fertilizers
by Eglė Jotautienė, Vaidas Bivainis, Davut Karayel and Ramūnas Mieldažys
Agronomy 2024, 14(6), 1171; https://doi.org/10.3390/agronomy14061171 - 30 May 2024
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Abstract
Continuous efforts are being made to improve fertilizer efficiency by improving fertilizer technology, quality, and application rates. Granular organic fertilizers are more difficult to achieve uniform application because their physical–mechanical properties differ significantly from mineral fertilizers. The properties of granular organic fertilizers can [...] Read more.
Continuous efforts are being made to improve fertilizer efficiency by improving fertilizer technology, quality, and application rates. Granular organic fertilizers are more difficult to achieve uniform application because their physical–mechanical properties differ significantly from mineral fertilizers. The properties of granular organic fertilizers can best be determined experimentally. However, these studies are often quite complex. Modern engineering modeling software makes it possible to model the properties of granular fertilizers and their dispersion. This study deals with the theoretical and experimental verification of the physical–mechanical properties of organic bone meal granular fertilizer. For the verification of selected properties of bone meal granules, the following studies were carried out on the granules: determination of poured bulk density, static and dynamic angles of repose, static and dynamic friction coefficients of granule surface, etc. The results showed that for modeling fertilizer properties, it is sufficient to carry out a static compression test to determine the modulus of elasticity and a friction test between granules and the contacting surface to determine the static and dynamic friction coefficients. The remaining properties of the granules can be modeled and calibrated with the DEM software Altair EDEM 2023. Full article
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Review

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27 pages, 792 KiB  
Review
Machine Learning Applications in Agriculture: Current Trends, Challenges, and Future Perspectives
by Sara Oleiro Araújo, Ricardo Silva Peres, José Cochicho Ramalho, Fernando Lidon and José Barata
Agronomy 2023, 13(12), 2976; https://doi.org/10.3390/agronomy13122976 - 1 Dec 2023
Cited by 3 | Viewed by 6146
Abstract
Progress in agricultural productivity and sustainability hinges on strategic investments in technological research. Evolving technologies such as the Internet of Things, sensors, robotics, Artificial Intelligence, Machine Learning, Big Data, and Cloud Computing are propelling the agricultural sector towards the transformative Agriculture 4.0 paradigm. [...] Read more.
Progress in agricultural productivity and sustainability hinges on strategic investments in technological research. Evolving technologies such as the Internet of Things, sensors, robotics, Artificial Intelligence, Machine Learning, Big Data, and Cloud Computing are propelling the agricultural sector towards the transformative Agriculture 4.0 paradigm. The present systematic literature review employs the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to explore the usage of Machine Learning in agriculture. The study investigates the foremost applications of Machine Learning, including crop, water, soil, and animal management, revealing its important role in revolutionising traditional agricultural practices. Furthermore, it assesses the substantial impacts and outcomes of Machine Learning adoption and highlights some challenges associated with its integration in agricultural systems. This review not only provides valuable insights into the current landscape of Machine Learning applications in agriculture, but it also outlines promising directions for future research and innovation in this rapidly evolving field. Full article
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Planned Papers

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: The influence of the biological preparation on the productivity of tomatoes
Authors: Sidona Buragienė; Aida Adamavičienė
Affiliation: Affiliation 1: Faculty of Engineering, Agriculture Academy, Vytautas Magnus University, Studentu Str. 15A, Kaunas District, LT-53362 Akademija, Lithuania, [email protected], Affiliation 2: Faculty of Agronomy, Agriculture Academy, Vytautas Magnus University, Studentu Str. 11, LT-53361 Akademija, Kaunas District, Lithuania, [email protected]
Abstract: A tentative abstract: Preliminary summary: Tomato (Solanum lycopersicum L), a flowering plant of the Solanaceae family, is widely cultivated for its edible fruits. Although botanically a fruit, it is commonly eaten and prepared as a vegetable. Studies show that tomatoes and tomato products can reduce the risk of heart disease and lung cancer. As tomatoes are valuable and popular, our research aims to increase yields using a molasses-based biologic. The study was conducted at the Academy of Agriculture of Vytautas the Great University (Lithuania). Tomatoes 'Betalux' are artificially grown under constant environmental conditions. Tomatoes were grown individually in special containers in 5 different soils and substrates: loam (L), clay (C), sandy loam (SL), compost soil (CS) and coconut fiber (CF). The experiment was performed with 5 treatments and 4 replicates. Two weeks after planting the seedlings, the height, width, chlorophyll index of the plants were measured and their relationship with the yield was analyzed. Measurements were carried out during the entire tomato vegetation.

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