Special Issue "Precision Agriculture"

A special issue of Agronomy (ISSN 2073-4395).

Deadline for manuscript submissions: 30 August 2019

Special Issue Editors

Guest Editor
Prof. Spyros Fountas

Laboratory of Agricultural Machinery, Department of Natural Resources Management and Agricultural Engineering, School of Agricultural Production, Engineering and Environment, Agricultural University of Athens, 75 Iera Odos Str., Botanikos 11855, Athens, Greece
Website | E-Mail
Phone: +30-210-5294035
Interests: precision agriculture; farm machinery; information systems
Guest Editor
Dr. Frits van Evert

Wageningen University & Research, Droevendaalsesteeg 1, 6708PB Wageningen, The Netherlands
Website | E-Mail
Interests: Precision agriculture, weed science, sustainability, potatoes, nitrogen, robotics, crop growth models, information systems
Guest Editor
Dr. Thanos Balafoutis

Researcher C', Institute for Bio-Economy & Agro-Technology, Centre of Research & Technology Hellas, Dimarchou Georgiadou 118, 38333 Volos, Greece
Website | E-Mail
Interests: smart farming; agricultural machinery; biomass utilization for energy purposes

Special Issue Information

Dear Colleagues,

Precision agriculture is a management strategy that focuses on monitoring, measurement, and responses to inter- and intra-variability in cropping systems. Precision agriculture is based on the rapid deployment of sensing technologies, management information systems, and variable rate technologies with appropriate agronomic and economic models. The benefits of using precision agriculture solutions include the optimization of process inputs, production cost reduction, and potentially increasing crop yields and quality, while reducing the environmental impact.

This Special Issue aims to discuss various aspects of precision agriculture applications, technologies, and management methods. This will include the state-of-the-art on technologies applied in different cropping systems, agronomic models to interpret precision agriculture measured data, economic implications and adoption of precision agriculture technologies, and precision agriculture applications. The latter includes areas in all agricultural activities, such as precision irrigation, precision fertilization, and selective harvesting. Studies on applications regarding all cropping systems are invited to be submitted.

We invite you to contribute to this Issue by submitting comprehensive reviews, case studies, or research articles that focus on scientific methods, technological tools, and innovative statistical analyses, in order to provide an opportunity for learning the state-of-the-art and for discussion on future directions in precision agriculture. Papers selected for this Special Issue are subject to a rigorous peer review procedure with the aim of rapid and wide dissemination of research results, developments, and applications.

Dr. Spyros Fountas
Dr. Frits van Evert
Dr. Thanos Balafoutis
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 papers will be 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 1000 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
  • applications, technologies and management methods
  • all cropping systems

Published Papers (4 papers)

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Research

Open AccessArticle
Mapping the Depth-to-Soil pH Constraint, and the Relationship with Cotton and Grain Yield at the Within-Field Scale
Agronomy 2019, 9(5), 251; https://doi.org/10.3390/agronomy9050251
Received: 20 March 2019 / Revised: 13 May 2019 / Accepted: 15 May 2019 / Published: 21 May 2019
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Abstract
Subsoil alkalinity is a common issue in the alluvial cotton-growing valleys of northern New South Wales (NSW), Australia. Soil alkalinity can cause nutrient deficiencies and toxic effects, and inhibit rooting depth, which can have a detrimental impact on crop production. The depth at [...] Read more.
Subsoil alkalinity is a common issue in the alluvial cotton-growing valleys of northern New South Wales (NSW), Australia. Soil alkalinity can cause nutrient deficiencies and toxic effects, and inhibit rooting depth, which can have a detrimental impact on crop production. The depth at which a soil constraint is reached is important information for land managers, but it is difficult to measure or predict spatially. This study predicted the depth in which a pH (H2O) constraint (>9) was reached to a 1-cm vertical resolution to a 100-cm depth, on a 1070-hectare dryland cropping farm. Equal-area quadratic smoothing splines were used to resample vertical soil profile data, and a random forest (RF) model was used to produce the depth-to-soil pH constraint map. The RF model was accurate, with a Lin’s Concordance Correlation Coefficient (LCCC) of 0.63–0.66, and a Root Mean Square Error (RMSE) of 0.47–0.51 when testing with leave-one-site-out cross-validation. Approximately 77% of the farm was found to be constrained by a strongly alkaline pH greater than 9 (H2O) somewhere within the top 100 cm of the soil profile. The relationship between the predicted depth-to-soil pH constraint map and cotton and grain (wheat, canola, and chickpea) yield monitor data was analyzed for individual fields. Results showed that yield increased when a soil pH constraint was deeper in the profile, with a good relationship for wheat, canola, and chickpea, and a weaker relationship for cotton. The overall results from this study suggest that the modelling approach is valuable in identifying the depth-to-soil pH constraint, and could be adopted for other important subsoil constraints, such as sodicity. The outputs are also a promising opportunity to understand crop yield variability, which could lead to improvements in management practices. Full article
(This article belongs to the Special Issue Precision Agriculture)
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Open AccessArticle
Assessment of the Cutting Performance of a Robot Mower Using Custom Built Software
Agronomy 2019, 9(5), 230; https://doi.org/10.3390/agronomy9050230
Received: 22 March 2019 / Revised: 30 April 2019 / Accepted: 1 May 2019 / Published: 6 May 2019
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Abstract
Before the introduction of positioning technologies in agriculture practices such as global navigation satellite systems (GNSS), data collection and management were time-consuming and labor-intensive tasks. Today, due to the introduction of advanced technologies, precise information on the performance of agricultural machines, and smaller [...] Read more.
Before the introduction of positioning technologies in agriculture practices such as global navigation satellite systems (GNSS), data collection and management were time-consuming and labor-intensive tasks. Today, due to the introduction of advanced technologies, precise information on the performance of agricultural machines, and smaller autonomous vehicles such as robot mowers, can be collected in a relatively short time. The aim of this work was to track the performance of a robot mower in various turfgrass areas of an equal number of square meters but with four different shapes by using real-time kinematic (RTK)-GNSS devices, and to easily extract data by a custom built software capable of calculating the distance travelled by the robot mower, the forward speed, the cutting area, and the number of intersections of the trajectories. These data were then analyzed in order to provide useful functioning information for manufacturers, entrepreneurs, and practitioners. The path planning of the robot mower was random and the turfgrass area for each of the four shapes was 135 m2 without obstacles. The distance travelled by the robot mower, the mean forward speed, and the intersections of the trajectories were affected by the interaction between the time of cutting and the shape of the turfgrass. For all the different shapes, the whole turfgrass area was completely cut after two hours of mowing. The cutting efficiency decreased by increasing the time, as a consequence of the increase in overlaps. After 75 minutes of cutting, the efficiency was about 35% in all the turfgrass areas shapes, thus indicating a high level of overlapping. Full article
(This article belongs to the Special Issue Precision Agriculture)
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Open AccessArticle
Effect of Tillage Systems on Spatial Variation in Soil Chemical Properties and Winter Wheat (Triticum aestivum L.) Performance in Small Fields
Agronomy 2019, 9(4), 182; https://doi.org/10.3390/agronomy9040182
Received: 6 March 2019 / Revised: 1 April 2019 / Accepted: 9 April 2019 / Published: 10 April 2019
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Abstract
To investigate how tillage intensity modifies the small-scale spatial variability of soil and winter wheat parameters, field trials were conducted on small plots (12 m × 35 m) in three temperate environments in the Swiss midlands: Zollikofen in 1999 (loamy silt soil; Gleyic [...] Read more.
To investigate how tillage intensity modifies the small-scale spatial variability of soil and winter wheat parameters, field trials were conducted on small plots (12 m × 35 m) in three temperate environments in the Swiss midlands: Zollikofen in 1999 (loamy silt soil; Gleyic Cambisol) and Schafisheim in 1999 and in 2000 (sandy loam soil; Orthic Luvisol). Total soil nitrogen (Ntot), total carbon (Ctot) and pH were assessed after harvest. A regular nested grid pattern was applied with sampling intervals of 3 m and 1 m at 0–30 cm on a total of nine no-tillage (NT) and nine conventional tillage (CT) plots. At each grid point, wheat biomass, grain yield, N uptake and grain protein concentration were recorded. Small-scale structural variance of soil Ntot, Ctot and pH was slightly larger in NT than in CT in the topsoil in the tillage direction of the field. Wheat traits had a slightly greater small-scale variability in NT than in CT. Spatial relationships between soil and crop parameters were rather weak but more pronounced in NT. Our results suggest limited potential for variable-rate application of N fertilizer and lime for NT soils. Moderate nugget variances in soil parameters were usually higher in CT than in NT, suggesting that differences in spatial patterns between the tillage systems might occur at even smaller scales. Full article
(This article belongs to the Special Issue Precision Agriculture)
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Open AccessArticle
A Case-Based Economic Assessment of Robotics Employment in Precision Arable Farming
Agronomy 2019, 9(4), 175; https://doi.org/10.3390/agronomy9040175
Received: 28 February 2019 / Revised: 25 March 2019 / Accepted: 3 April 2019 / Published: 5 April 2019
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Abstract
The need to intensify agriculture to meet increasing nutritional needs, in combination with the evolution of unmanned autonomous systems has led to the development of a series of “smart” farming technologies that are expected to replace or complement conventional machinery and human labor. [...] Read more.
The need to intensify agriculture to meet increasing nutritional needs, in combination with the evolution of unmanned autonomous systems has led to the development of a series of “smart” farming technologies that are expected to replace or complement conventional machinery and human labor. This paper proposes a preliminary methodology for the economic analysis of the employment of robotic systems in arable farming. This methodology is based on the basic processes for estimating the use cost for agricultural machinery. However, for the case of robotic systems, no average norms for the majority of the operational parameters are available. Here, we propose a novel estimation process for these parameters in the case of robotic systems. As a case study, the operation of light cultivation has been selected due the technological readiness for this type of operation. Full article
(This article belongs to the Special Issue Precision Agriculture)
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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.

Impacts of Smart Farming Technologies on Agricultural Systems Sustainability

Athanasios T. Balafoutis 1,*, Frits Van Evert 2 and Spyros Fountas 3
1 Institute of Bio-Economy & Agro-Technology, Centre of Research & Technology Hellas, Dimarchou Georgiadou 118, 38333 Volos, Greece
2 Agrosystems Research, Wageningen University & Research, P.O. Box 16, 6700 AA Wageningen, The Netherlands
3 Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 11855 Athens, Greece
* Corresponding Author email: [email protected]

Development and Evaluation of A Mobile Thermotherapy Technology for In-Field Treatment of HLB-Infected Trees

Shirin Ghatrehsamani 1, Jaafar Abdulridha 1, Athanasios T. Balafoutis 2, Reza Ehsani 3 and
Yiannis Ampatzidis 1,*
1 Agricultural and Biological Engineering department, University of Florida, Gainesville, Florida, USA
2 Institute for Bio-Economy & Agro-Technology, Centre of Research & Technology Hellas, Dimarchou Georgiadou 118, 38221 Volos, Greece
3 Mechanical Engineering department, University of California, Merced 5200 N. Lake Road Merced, CA, USA
* Corresponding Author email: [email protected]

Evaluation of the Effects of Reduced Tillage and Reduced Herbicide Rates on Wheat Growth and Weed Flora by Means of Vegetation Indices

Spyros Fountas 1,*, Ilias Travlos 2, Dimitrios Bilalis 2, Vasilis Psiroukis 1, Nikolina Cheimona 2, Athanasios T. Balafoutis 3 and Evangelos Anastasiou 1
1 Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 11855 Athens, Greece
2 Department of Crop Science, Agricultural University of Athens, 11855 Athens, Greece
3 Institute of Bio-Economy & Agro-Technology, Centre of Research & Technology Hellas, Dimarchou Georgiadou 118, 38333 Volos, Greece
* Corresponding Author email: [email protected]

Estimating the Canopy Volume in Apple Trees Using a 2D LiDAR

Nikos Tsoulias 1,*, Dimitris S. Paraforos 2, Spyros Fountas 3 and Manuela Zude-Sasse 1
1 Department of Agricultural Engineering and Bioeconomy - ATB, Max-Eyth-Allee, 14469 Potsdam, Germany
2 University of Hohenheim, Schloss Hohenheim 1, 70599, Stuugart
3 Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 11855 Athens, Greece
* Corresponding Author email: [email protected]

A Case-Based Economic Assessment of Robotics Employment in Precision Arable Farming

Maria G. Lampridi 1,2,*, Dimitrios Kateris 1, Georgios Vasileiadis 1,2, Vasiliki Marinoudi 3, Simon Pearson 3, Athanasios T. Balafoutis 1 and Dionysis Bochtis 1
1 Center for Research & Technology Hellas – CERTH, Institute for Bio-economy and Agri-technology – iBO, 10th km Thessalonikis - Thermis, BALKAN Center, BLDG D, 57001, Greece
2 Aristotle University of Thessaloniki, Faculty of Agriculture, Forestry and Natural Environment, School of Agriculture, 54124, Thessaloniki, Greece
3 Lincoln Institute for Agri-Food Technology, University of Lincoln, Brayford Pool, Lincoln LN6 7TS, UK
* Corresponding Author email: [email protected]

 

Title: Spatial variation in soil chemical properties and winter wheat (Triticum aestivum L.) performance in small fields as affected by tillage

Authors: Ruth-Maria Hausherr Lüder1, Ruijun Qin 2, Walter Richner 3, Peter Stamp 1, Bernhard Streit 4, Christos Noulas 5

 1  Department of Environmental Systems Science (D-USYS), Institute of Agricultural Sciences, Swiss Federal Institute of Technology (ETH), Zürich, Switzerland

2  Hermiston Agricultural Research & Extension Center, Oregon State University, Hermiston, USA

3 Agroscope Reckenholz - Tänikon Research Station ART, Reckenholzstrasse 191, CH-8046 Zurich, Switzerland

4 School of Agricultural, Forest and Food Sciences HAFL, Bern University of Applied Sciences, Länggasse 85, 3052, Zollikofen, Switzerland

5 Department of Soil and Water Resources, Institute of Industrial and Forage Crops, Hellenic Agricultural Organization – “Demeter”, 41335, Larissa, Greece

 

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