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Sustainable Precision Agriculture: Latest Advances and Prospects

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Agriculture".

Deadline for manuscript submissions: 30 May 2025 | Viewed by 6976

Special Issue Editors


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Guest Editor
CREA Research Centre for Engineering and Agro-Food Processing, Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria, Via Milano 43, 24047 Treviglio, Italy
Interests: precision agriculture; digital farming; decision support systems; safety and ergonomic issues; sustainable mechanization
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Guest Editor
CREA Research Centre for Engineering and Agro-Food Processing, Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria, Via Milano 43, 24047 Treviglio, Italy
Interests: mechanization; livestock automation; precision farming
Special Issues, Collections and Topics in MDPI journals

E-Mail
Guest Editor
CREA Research Centre for Engineering and Agro-Food Processing, Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria, Via Milano 43, 24047 Treviglio, Italy
Interests: precision agriculture; climate change; holistic approach to sustainability; life-cycle assessment; ecosystem services
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Agriculture, Food and Environment, Agricultural Machinery and Mechanization Section, University of Catania, Via S.Sofia, 100-95123 Catania, Italy
Interests: safety health welfare agrosystems; precision farming; agricultural crops mechanization
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Agriculture, Food and Environment, University of Catania, Via S.Sofia 100, 95123 Catania, Italy
Interests: soil conservation tillage; labour and energy requirement in agricultural; plant protection with sprayers in greenhouse and open field; mechanical distribution of natural arthropods in greenhouse and in open field; biomass and bioenergy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, we have observed a significant increase in the management of agricultural practices through precision agriculture strategies. On-farm applications include varying intensities and modes depending on farm size, crop choice, and livestock, with technologies ranging from the simplest guidance assistance to site-specific management. The public policies of nations have also favored the spread of 4.0 machines able to perform agricultural procedures based on information coming from the field, such as soils and crops.

Research is constantly evolving with experimental activities concerning technologies and the interaction between them, the soil, the crop, and humans. Interest is aroused by the investigation of the effect on the environmental, economic, and social sustainability of the techniques and technologies used by precision agriculture.

Therefore, this Special Issue is mainly aimed at collecting manuscripts on the latest advances in precision agriculture with a focus on their positive effect on sustainability, agrochemicals, and fuel reduction for improved future scenarios.

This Special Issue welcomes original articles, research, research reflections, and reviews concerning strategic items. It focuses on the application of innovative precision agriculture strategies, in particular (i) the study and the use of agricultural practices managed according to soil and crop variability; (ii) the study of precision livestock farming—PLF; (iii) the research of the processing methods and algorithms helpful for supporting site-specific management; (iv) all evaluations of the transfer processes of elaboration by humans to agricultural machinery 4.0, including the Farm Machinery Management Information Systems (FMMIS) platforms. Researchers are encouraged to send their valuable contributions.

The topic also includes manuscripts related to issues that highlight the difficulties in the deployment of precision agriculture, which also involve critical points in information or technology management. The common thread of the Special Issue is sustainability, so we invite a critical evaluation of the effect of one's research toward sustainability from environmental, economic, or social points of view or even all three aspects simultaneously.

Research areas aimed at improving sustainability may include (but are not limited to) the following:

- Precision Agriculture (PA) strategies;

- Precision Livestock Farming (PLF) strategies;

- Variable Rate Technology (VRT) and techniques;

- Remote Sensing (RS);

- Algorithms to prepare prescription maps;

- Human–machine information transfer;

- Critical points in Precision Agriculture management;

- Crop condition monitoring (spectral indices and application);

- Plant disease detection at different scales (proximal sensors, drones, satellites);

- AI (Artificial Intelligence)-based methods and techniques as well as Machine and deep learning;

- Plant phenotyping;

- Robotics and automation;

- Decision Support System (DSS);

- Multi-temporal analysis;

- Life Cycle Assessment (LCA);

- Farm Machinery Management Information Systems (FMMIS).

We look forward to receiving your contributions.

Dr. Elio Romano
Dr. Carlo Bisaglia
Dr. Andrea Bragaglio
Prof. Giampaolo Schillaci
Dr. Sabina Iole Giuseppina Failla
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. Sustainability is an international peer-reviewed open access semimonthly 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 2400 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

  • precision agriculture
  • remote and proximal sensing
  • sustainability
  • impact reduction
  • awareness of variability
  • customized management

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Published Papers (4 papers)

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Research

22 pages, 4273 KiB  
Article
Design and Evaluation of a Precision Irrigation Tool’s Human–Machine Interaction to Bring Water- and Energy-Efficient Irrigation to Resource-Constrained Farmers
by Georgia D. Van de Zande, Fiona Grant, Carolyn Sheline, Susan Amrose, Jeffery Costello, Aditya Ghodgaonkar and Amos G. Winter V
Sustainability 2024, 16(19), 8402; https://doi.org/10.3390/su16198402 - 27 Sep 2024
Viewed by 915
Abstract
As freshwater supplies decrease, adopting sustainable practices like water- and energy-efficient irrigation is crucial, particularly in resource-constrained regions. Here, farmers often cannot purchase precision irrigation equipment, which achieves high water and energy efficiencies via full automation. Currently, no irrigation methods exist that combine [...] Read more.
As freshwater supplies decrease, adopting sustainable practices like water- and energy-efficient irrigation is crucial, particularly in resource-constrained regions. Here, farmers often cannot purchase precision irrigation equipment, which achieves high water and energy efficiencies via full automation. Currently, no irrigation methods exist that combine automatic scheduling of events with manual operation of valves, familiar hardware on low-income farms. This work synthesizes functional requirements for a tool that could address efficiency needs while integrating into current manual practices. Then, a design concept for an automatic scheduling and manual operation (AS-MO) human–machine interaction (HMI) that meets these requirements is proposed. Two design stages of the AS-MO HMI were evaluated by farmers and market stakeholders in three countries. Results show that farmers in Kenya and Jordan valued the proposed AS-MO HMI because they could increase efficiency on their farms without the cost or complexity of automatic valves. In Morocco, a possible market was found, but a majority of participants preferred full automation. Interviewees provided feedback on how to improve the tool’s design in future iterations. If adopted at scale, the proposed AS-MO tool could increase efficiency on farms that otherwise cannot afford current precision irrigation technology, improving sustainable agriculture worldwide. Full article
(This article belongs to the Special Issue Sustainable Precision Agriculture: Latest Advances and Prospects)
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18 pages, 5007 KiB  
Article
Static Task Allocation Method for Multi-Machines in Cooperative Operations Combining OGFR-GA and MLW-Prim
by Yuezhong Wu, Ya Wen, Yingbo Wu, Yungang Li, Xiangming Zheng and Lingjiao Chen
Sustainability 2024, 16(14), 6199; https://doi.org/10.3390/su16146199 - 19 Jul 2024
Viewed by 820
Abstract
Aiming at the operational efficiency of small farm machinery groups in cooperative operations in hilly areas, this study proposes a static task allocation model. This method combines the optimal gene fragment retention method based on a genetic algorithm (OGFR-GA) and the method for [...] Read more.
Aiming at the operational efficiency of small farm machinery groups in cooperative operations in hilly areas, this study proposes a static task allocation model. This method combines the optimal gene fragment retention method based on a genetic algorithm (OGFR-GA) and the method for generating multi-loop weighted connected graphs based on Prim’s algorithm (MLW-Prim). The collaborative objective function for the harvester group was established by considering factors such as operation time, fuel consumption, and distance. The OGFR-GA was designed and applied multiple times to obtain several optimal gene fragments corresponding to the number of farm machines. These fragments were used as critical paths in the weighted connected graph generated based on farm machinery performance parameters and task parameters. The MLW-Prim method was proposed to construct this weighted connected graph and realize the static task allocation model for multi-machine cooperative operations. Simulation experiments showed that the model combining OGFR-GA and MLW-Prim achieved optimal values with fewer iterations, and reduced both group cost and cost variance compared to traditional algorithms. This method meets the static task allocation needs for multi-machine cooperative operations in agricultural production and can be integrated with intelligent operations in mountainous and hilly regions, laying a theoretical foundation for improving efficiency. Full article
(This article belongs to the Special Issue Sustainable Precision Agriculture: Latest Advances and Prospects)
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12 pages, 732 KiB  
Article
Massese, Sarda and Lacaune Dairy Sheep Breeds: An Environmental Impact Comparison
by Irene Sodi, Mina Martini, Neus Sanjuàn, Sergio Saia, Iolanda Altomonte, Andrea Andreucci, Baldassare Fronte, Francesca Pedonese, Lorella Giuliotti, Roberta Ciampolini and Federica Salari
Sustainability 2024, 16(12), 4941; https://doi.org/10.3390/su16124941 - 8 Jun 2024
Viewed by 1440
Abstract
The dairy sheep sector is an important sector in semiarid and arid areas. So far, the environmental impact of sheep milk production in these areas is scarcely known. This study aimed to assess the environmental impact of milk production on three farms that [...] Read more.
The dairy sheep sector is an important sector in semiarid and arid areas. So far, the environmental impact of sheep milk production in these areas is scarcely known. This study aimed to assess the environmental impact of milk production on three farms that differ in the breed reared, namely Sarda (S), Lacaune (L) and Massese (M), in Tuscany (a Mediterranean region in central Italy). The Life Cycle Assessment methodology was applied to calculate the environmental performance of the farms, and the following impact categories were studied: climate change, freshwater, marine and terrestrial eutrophication, acidification, water use and land use. The L farm showed the lowest values for most impact categories and the M farm the highest. These results can be attributed to the greater productivity and efficiency of the L breed compared to the other two. Only for water use did the M farm cause a lower impact, underscoring the importance of applying characterization factors at the sub-watershed level. Full article
(This article belongs to the Special Issue Sustainable Precision Agriculture: Latest Advances and Prospects)
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16 pages, 7571 KiB  
Article
Case Study on the Economic and Environmental Impact of the Introduction of the Variable-Rate Distribution of Fertilizer in Wheat (Triticum aestivum L.) Cultivation
by Elio Romano, Andrea Bragaglio, Carlo Bisaglia, Alberto Assirelli, Elia Premoli and Simone Bergonzoli
Sustainability 2024, 16(4), 1612; https://doi.org/10.3390/su16041612 - 15 Feb 2024
Cited by 1 | Viewed by 2738
Abstract
Fertilization plays a strategic role in the cultivation of wheat, contributing to harvest yield, both in quantitative and qualitative terms. However, similarly to all farm inputs, it has both economic and environmental impacts due to fertilizer dispersion into the environment during its distribution, [...] Read more.
Fertilization plays a strategic role in the cultivation of wheat, contributing to harvest yield, both in quantitative and qualitative terms. However, similarly to all farm inputs, it has both economic and environmental impacts due to fertilizer dispersion into the environment during its distribution, as well as any excess fertilizer not used by the crop. Precision agriculture, which introduces the possibility of distributing fertilizer following prescription maps, has an immediate effect on dosage compliance according to the request and potential for use by each homogeneous area of the crop. An experimental field (about 15 hectares) at the Council for Agricultural Research and Economics (CREA) of Treviglio (BG) in Northern Italy was fertilized using a centrifugal fertilizer spreader combined with a tractor, equipped with a satellite system to distribute urea led by prescription maps. The purposes of this research were to verify (i) the effect of fertilization, performed with precision agriculture (PA) criteria at a variable rate; (ii) the comparison of the economic impact of the quantities of fertilizer required by precision agriculture compared to the distribution required in previous years (fertilizers administered according to conventional agriculture). The treated areas showed a significant yield improvement (almost 14%) when fertilization was performed according to the prescription map. With a negligible margin of error of less than 0.001, the total amount of fertilizer used was the same in both years. Full article
(This article belongs to the Special Issue Sustainable Precision Agriculture: Latest Advances and Prospects)
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