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Sensor-Based Agrivoltaic Technology and Crop Monitoring Systems for Greater Sustainability
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Sensor-Based Agrivoltaic Technology and Crop Monitoring Systems for Greater Sustainability

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Smart Agriculture".

Deadline for manuscript submissions: 25 August 2024 | Viewed by 1546

Special Issue Editors

Dr. Andrea Colantoni

E-Mail Website
Guest Editor
Department of Agricultural and Forestry Sciences (DAFNE), Tuscia University of Viterbo, Via San Camillo de Lellis, snc, 01100 Viterbo, Italy
Interests: energy; environment; agriculture
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Enrico Maria Mosconi

E-Mail Website
Guest Editor
Department of Economics and Entrepreneurship (DEIM), University of Tuscia, Via del Paradiso, 01100 Viterbo, Italy
Interests: technology evaluation and corporate innovation strategies; environmental aspects and production processes; economic study and implementation of new organizational models; quality instruments for the enterprise innovation management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The need for increased renewable energy production has increased due to socio-political conditions and the related energy crisis. The main international and European policies encourage new technologies to produce green energy with significant funding.

Agrivoltaic (AGV) represents an innovative technology to create a synergy between energy and agricultural production without generating soil consumption. To ensure this energy, to increase knowledge of the interaction of this technology with soil, crops and the level of mechanization, however, crop monitoring tools and the main agronomic parameters, such as multispectral cameras, drones and remote sensing, vegetation indices are needed in relation to the AGV systems. These monitoring systems are essential to guarantee continuous and constant control and to guarantee a high level of sustainability of AGV.

Dr. Andrea Colantoni
Prof. Dr. Enrico Maria Mosconi
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. Sensors 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 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

  • energy
  • agriculture
  • mechanization
  • crop
  • monitoring systems
  • policy

Published Papers (2 papers)

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Research

16 pages, 4543 KiB  
Article
Relationship between Height and Exposure in Multispectral Vegetation Index Response and Product Characteristics in a Traditional Olive Orchard
by Carolina Perna, Andrea Pagliai, Riccardo Lisci, Rafael Pinhero Amantea, Marco Vieri, Daniele Sarri and Piernicola Masella
Sensors 2024, 24(8), 2557; https://doi.org/10.3390/s24082557 - 16 Apr 2024
Viewed by 292
Abstract
The present research had two aims. The first was to evaluate the effect of height and exposure on the vegetative response of olive canopies’ vertical axis studied through a multispectral sensor and on the qualitative and quantitative product characteristics. The second was to [...] Read more.
The present research had two aims. The first was to evaluate the effect of height and exposure on the vegetative response of olive canopies’ vertical axis studied through a multispectral sensor and on the qualitative and quantitative product characteristics. The second was to examine the relationship between multispectral data and productive characteristics. Six olive plants were sampled, and their canopy’s vertical axis was subdivided into four sectors based on two heights (Top and Low) and two exposures (West and East). A ground-vehicle-mounted multispectral proximal sensor (OptRx from AgLeader®) was used to investigate the different behaviours of the olive canopy vegetation index (VI) responses in each sector. A selective harvest was performed, in which each plant and sector were harvested separately. Product characterisation was conducted to investigate the response of the products (both olives and oils) in each sector. The results of Tukey’s test (p > 0.05) showed a significant effect of height for the VI responses, with the Low sector obtaining higher values than the Top sector. The olive product showed some height and exposure effect, particularly for the olives’ dimension and resistance to detachment, which was statistically higher in the upper part of the canopies. The regression studies highlighted some relationships between the VIs and product characteristics, particularly for resistance to detachments (R2 = 0.44–0.63), which can affect harvest management. In conclusion, the results showed the complexity of the olive canopies’ response to multispectral data collection, highlighting the need to study the vertical axis to assess the variability of the canopy itself. The relationship between multispectral data and product characteristics must be further investigated. Full article
(This article belongs to the Special Issue Sensor-Based Agrivoltaic Technology and Crop Monitoring Systems for Greater Sustainability)
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23 pages, 8112 KiB  
Article
Design and Performance Analysis of Foldable Solar Panel for Agrivoltaics System
by Ramesh Kumar Lama and Heon Jeong
Sensors 2024, 24(4), 1167; https://doi.org/10.3390/s24041167 - 10 Feb 2024
Cited by 1 | Viewed by 729
Abstract
This study investigates the use of a foldable solar panel system equipped with a dynamic tracking algorithm for agrivoltaics system (AVS) applications. It aims to simultaneously meet the requirements for renewable energy and sustainable agriculture. The design focuses on improving solar energy capture [...] Read more.
This study investigates the use of a foldable solar panel system equipped with a dynamic tracking algorithm for agrivoltaics system (AVS) applications. It aims to simultaneously meet the requirements for renewable energy and sustainable agriculture. The design focuses on improving solar energy capture while facilitating crop growth through adjustable shading. The results show that foldable panels, controlled by the tracking algorithm, significantly outperform fixed panels in energy efficiency, achieving up to a 15% gain in power generation and uniform power generation throughout the day. Despite the presence of shadows of adjacent panels in the early morning and late evening, the system’s effectiveness in creating microclimates for diverse crops demonstrates its substantial value. The foldable design not only protects crops from adverse climate conditions across different seasons but also generates energy efficiently. This demonstrates a step forward in sustainable land use and food security. Full article
(This article belongs to the Special Issue Sensor-Based Agrivoltaic Technology and Crop Monitoring Systems for Greater Sustainability)
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