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Agriculture
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Innovations in Precision Farming for Sustainable Agriculture
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Innovations in Precision Farming for Sustainable Agriculture

A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Digital Agriculture".

Deadline for manuscript submissions: 15 February 2025 | Viewed by 5126

Special Issue Editors

Dr. Eugenio Cavallo

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Guest Editor
Institute of Sciences and Technologies for Sustainable Energy and Mobility (STEMS) of the Italian National Research Council (CNR), Strada delle Cacce 73, 10135 Torino, Italy
Interests: agriculture; innovation; sustainability; soil management; natural resources; occupational safety and health; ergonomics
Special Issues, Collections and Topics in MDPI journals
Dr. Carlo Bisaglia

E-Mail Website
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
Prof. Dr. Francesco Marinello

E-Mail Website1 Website2
Guest Editor
Department of Land, Environment, Agriculture and Forestry, University of Padova, 35020 Legnaro, Padova, Italy
Interests: precision agriculture; agricultural mechanization; sensors; automation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, researchers have assisted in the spectacular and unprecedented development and application of breakthrough technologies that significantly enhance agricultural engineering and contribute to these systems’ productivity, competitiveness, and sustainability.

This Special Issue (SI) aims to collect contributions from scholars reporting their achievements, state-of-the-art experimentations, and novel and cutting-edge technologies to identify the future direction of precision farming to enhance its global sustainability.

This SI is expected to host papers dealing with breakthrough innovations and advanced applications in the mechanization of agriculture; automation and robotics; remote and proximal sensor development and applications for farming and breeding; agricultural resource management for site-specific agriculture; variable rate principles and techniques for waste management and recycling, as well as for pesticide and fertilizer applications; electrification and electricity management in agricultural machinery and facilities; ICT and artificial intelligence development and applications; decision support systems; technologies and solutions for precision, digital and smart agriculture for soil management and conservation; occupational safety and health and ergonomics; and economic and social assessment of barriers, drivers and incentives for the adoption of novel and sustainable technologies. Papers giving experimental evidence integrating different solutions and technologies are particularly encouraged. Contributions focusing on engineering technologies that can help achieve the United Nations' Sustainable Development Goals, addressing food sovereignty, and improving sustainability in developing countries are welcome.

Dr. Eugenio Cavallo
Dr. Carlo Bisaglia
Dr. Francesco Marinello
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. Agriculture 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

  • agriculture mechanization
  • automation and robotics
  • remote sensing
  • agricultural resource management
  • waste management and recycling
  • precision livestock production and management
  • ICT
  • artificial intelligence
  • decision support systems
  • technologies and solutions for precision, digital and smart agriculture
  • occupational safety and health
  • ergonomics

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (4 papers)

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Research

13 pages, 4164 KiB  
Article
Possible Enhancing of Spraying Management by Evaluating Automated Control in Different Training Systems
by Jurij Rakun, Peter Lepej, Rajko Bernik, Jelisaveta Seka Cvijanović, Miljan Cvetković and Erik Rihter
Agriculture 2024, 14(12), 2371; https://doi.org/10.3390/agriculture14122371 - 23 Dec 2024
Viewed by 459
Abstract
This study explores the feasibility of an automated sensor system for precise plant protection product application in plum orchards, aiming to address issues related to inefficient spraying practices, environmental pollution, and reduced crop quality associated with traditional training systems. The research focuses on [...] Read more.
This study explores the feasibility of an automated sensor system for precise plant protection product application in plum orchards, aiming to address issues related to inefficient spraying practices, environmental pollution, and reduced crop quality associated with traditional training systems. The research focuses on detecting tree canopy presence, evaluating electromagnetic valve actuation in different plum training systems, and optimizing plant protection product usage. Sensor-based spraying demonstrates its potential to improve operational efficiency, reduce product losses, and foster environmentally responsible agricultural practices, contributing to the broader field of precision agriculture. For the selected scene, the results show the possibility of a substantial savings of 71.37%, 47.17%, 58.59%, and 55.06% for the One-axis, Bi-axis, UFO, and Combine systems, respectively. Implementing this technology can potentially lead to significant improvements in plum orchard operations while minimizing the industry’s ecological impact on the environment. Full article
(This article belongs to the Special Issue Innovations in Precision Farming for Sustainable Agriculture)
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24 pages, 2511 KiB  
Article
Remote Sensing Dynamics for Analyzing Nitrogen Impact on Rice Yield in Limited Environments
by David Fita, Alberto San Bautista, Sergio Castiñeira-Ibáñez, Belén Franch, Concha Domingo and Constanza Rubio
Agriculture 2024, 14(10), 1753; https://doi.org/10.3390/agriculture14101753 - 4 Oct 2024
Viewed by 1486
Abstract
Rice production remains highly dependent on nitrogen (N). There is no positive linear correlation between N concentration and yield in rice cultivation because an excess of N can unbalance the distribution of photo-assimilates in the plant and consequently produce a lower yield. We [...] Read more.
Rice production remains highly dependent on nitrogen (N). There is no positive linear correlation between N concentration and yield in rice cultivation because an excess of N can unbalance the distribution of photo-assimilates in the plant and consequently produce a lower yield. We intended to study these imbalances. Remote sensing is a useful tool for monitoring rice crops. The purpose of this study was to evaluate the effectiveness of using remote sensing to assess the impact of N applications on rice crop behavior. An experiment with three different doses (120, 170 and 220 kg N·ha−1) was carried out over two years (2021 and 2022) in Valencia, Spain. Biomass, Leaf Area Index (LAI), plants per m2, yield, N concentration and N uptake were determined. Moreover, reflectance values in the green, red, and NIR bands of the Sentinel-2 satellite were acquired. The two data matrices were merged in a correlation study and the resulting interpretation ended in a protocol for the evaluation of the N effect during the main phenological stages. The positive effect of N on the measured parameters was observed in both years; however, in the second year, the correlations with the yield were low, being attributed to a complex interaction with climatic conditions. Yield dependence on N was optimally evaluated and monitored with Sentinel-2 data. Two separate relationships between NIR–red and NDVI–NIR were identified, suggesting that using remote sensing data can help enhance rice crop management by adjusting nitrogen input based on plant nitrogen concentration and yield estimates. This method has the potential to decrease nitrogen use and environmental pollution, promoting more sustainable rice cultivation practices. Full article
(This article belongs to the Special Issue Innovations in Precision Farming for Sustainable Agriculture)
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25 pages, 7883 KiB  
Article
Estimation of Dry Matter Yield in Mediterranean Pastures: Comparative Study between Rising Plate Meter and Grassmaster II Probe
by João Serrano, Júlio Franco, Shakib Shahidian and Francisco J. Moral
Agriculture 2024, 14(10), 1737; https://doi.org/10.3390/agriculture14101737 - 2 Oct 2024
Viewed by 750
Abstract
This study evaluates two expedient electronic sensors, a rising plate meter (RPM) and a “Grassmaster II” capacitance probe (GMII), to estimate pasture dry matter (DM, in kg ha−1). The sampling process consisted of sensor measurements, followed by pasture collection and a [...] Read more.
This study evaluates two expedient electronic sensors, a rising plate meter (RPM) and a “Grassmaster II” capacitance probe (GMII), to estimate pasture dry matter (DM, in kg ha−1). The sampling process consisted of sensor measurements, followed by pasture collection and a laboratory reference analysis. In this comparative study, carried out throughout the 2023/2024 pasture growing season, a total of 288 pasture samples were collected in two phases (calibration and validation). The calibration phase (n = 144) consisted of measurements on three dates (6 December 2023, 29 February and 10 May 2024) in 48 georeferenced sampling areas of the experimental field “Eco-SPAA” (“MG” field), located at Mitra farm (Évora, Portugal). This pasture is a permanent mixture of various botanical species (grasses, legumes, and others) grazed by sheep, and is representative of biodiverse dryland pastures. The validation phase (n = 144) was carried out between December 2023 and April 2024 in 18 field tests (each with eight pasture samples), in three types of representative pastures: the same mixture for grazing (“MG” field), a commercial and annual mixture for cutting (mowing) and conservation (“MM” field), and legumes for grazing (“LG” field). The best estimation model for DM was obtained based on measurements carried out in February in the case of the GMII probe (R2 = 0.61) and December 2023 and February 2024 in the case of RPM (R2 = 0.76). The estimation decreased very significantly for both sensors based on measurements carried out in May (spring). The validation phase showed greater accuracy (less RMSE) in “MG” field tests (RMSE of 735.4 kg ha−1 with GMII and 512.3 kg ha−1 with the RPM). The results open perspectives for other works that would allow the testing, calibration, and validation of these electronic sensors in a wider range of pasture production conditions, in order to improve their accuracy as decision-making support tools in pasture management. Full article
(This article belongs to the Special Issue Innovations in Precision Farming for Sustainable Agriculture)
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13 pages, 3558 KiB  
Article
Sheep Wool Waste Availability for Potential Sustainable Re-Use and Valorization: A GIS-Based Model
by Giusi Midolo, Simona M. C. Porto, Giovanni Cascone and Francesca Valenti
Agriculture 2024, 14(6), 872; https://doi.org/10.3390/agriculture14060872 - 30 May 2024
Viewed by 1234
Abstract
Worldwide, 1.3 to 2.1 billion tons of agricultural waste are generated yearly, including livestock wastes (i.e., sheep wool), which create several critical environmental issues if not properly treated. In order to reduce the environmental issues related to the management and disposal, their use [...] Read more.
Worldwide, 1.3 to 2.1 billion tons of agricultural waste are generated yearly, including livestock wastes (i.e., sheep wool), which create several critical environmental issues if not properly treated. In order to reduce the environmental issues related to the management and disposal, their use as natural fibers for green building components has notably developed over the last years. Indeed, sheep wool, which is a natural animal fiber that comes from shearing sheep fleece, is considered to be a problem of increasing concern due to its complex and difficult disposal management. Recently, several researchers have demonstrated that “low-quality wool” (i.e., not appropriate for textile uses) is suitable for the thermal and acoustic insulation of buildings. Indeed, thanks to its thermo-hygrometric and acoustic characteristics, it can be used as a reinforcing fiber for composite materials. In this study, a Geographic Information System (GIS)-based model to locate and quantify both the yearly amount of livestock waste, i.e., sheep wool, and the territorial distribution of sheep farms through their Global Positioning System (GPS) coordinates, was developed and applied within the selected study area (i.e., the Sicily region). The aim was to identify the territorial areas highly characterized by this kind of waste and therefore most suitable for localizing new shared sheep wool collection centers to sustainably manage the reuse of this waste as a potential green building component. Full article
(This article belongs to the Special Issue Innovations in Precision Farming for Sustainable Agriculture)
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