Special Issue "Advanced Instrumentation for an Intelligent Agriculture: Current Trends and Perspectives"

A special issue of Instruments (ISSN 2410-390X).

Deadline for manuscript submissions: closed (28 February 2019)

Special Issue Editors

Guest Editor
Prof. Dr. Konstantinos G. Arvanitis

Laboratory of Farm 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 1 | Website 2 | E-Mail
Phone: +302015294034
Interests: instrumentation and automation in agriculture; advanced process control; optimization techniques and computational intelligence; wireless sensor networks; ICT applications in agriculture; energy management and control of autonomous smart grids; Internet of things and cloud computing
Guest Editor
Dr. Dimitrios S. Paraforos

Section Technology in Crop Production, Institute of Agricultural Engineering, Faculty of Agricultural Sciences, University of Hohenheim, Garbenstr. 9, 70599, Stuttgart, Germany
Website | E-Mail
Phone: +4971145924556
Interests: digital farming; control applications in machine automation; durability of agricultural machinery; ISOBUS data analytics; agricultural robotics; machine learning for data-driven agriculture

Special Issue Information

Dear Colleagues,

Agriculture is rapidly changing in order to fulfil the increasing demand for higher productivity and better food quality. We are already witnessing a functional transition of instruments, devices and sensors, from traditional data acquisition devices to information providers with high processing capabilities. This is bringing us one step closer to the digital transformation of how common agricultural practices are being performed. The innovative framework of intelligent agriculture aims at incorporating advanced instrumentation and sophisticated algorithms for addressing issues, such as increased crop yields and animal performance, cost reduction, resource efficiency, environmental pollution, and food security.

This overarching aim of this Special Issue is to bring together recent development related to advanced instrumentation utilized in agriculture. 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 innovatively statistical analyses, in order to provide an overview of the current trends but also discuss future perspectives that are expected to have a profound impact. The focus of the issue is on the actual instrumentation and not on the mere agricultural issues. Contributions are expected to deal with, but are not limited to, the following areas:

  • Proximal sensors and instruments for soil characterization
  • Sensors and instruments for water characterization
  • Biological sensors and instruments
  • Instruments for multispectral imaging
  • Instruments and devices for hyperspectral data collection
  • Instrumentation for variable rate irrigation
  • Production yield measurement devices and instruments
  • Dry weight measuring instruments and devices
  • Instruments and devices for weed recognition
  • Instruments and devices for pest recognition
  • Immunosensors
  • Devices for disease detection
  • Sensors and devices for fluorescence and thermal imaging
  • Livestock sensors
  • Mobile diagnostic sensors for animal health detection
  • Acoustic, Noise and Vibration sensors and devices
  • Optical sensors
  • Nanobiosensors and nano devices for plants and animals
  • Theranostics and implantable sensors and devices
  • Instrumentation for selective harvesting
  • Electronic noses, tongues and eyes in the agrifood industry
  • ISOBUS-enabled sensors and devices
  • Instrumentation for intelligent silos and warehouses
  • Lab-on-chip
  • Intelligent sensing
  • Signal Transduction Technology
  • Drones
  • Microsatellites
  • Mobile antennas
  • Multi-source data and data fusion
  • Accurate dynamics in-field positioning
  • Agricultural robotics
  • Variable-rate application equipment
  • Telemetering
  • Big data analytics
  • Machine learning
  • Internet-based and other Remote Data Acquisition
  • Wireless Sensors and Sensor Networks
  • Internet of Things (IoT)

Prof. Dr. Konstantinos G. Arvanitis
Dr. Dimitrios S. Paraforos
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. Instruments is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) is waived for well-prepared manuscripts submitted to this issue. 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.

Published Papers (2 papers)

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Research

Open AccessCommunication
Monitoring Moisture Content for Various Kind of Tea Leaves in Drying Processes Using RF Reflectometer-Sensor System
Instruments 2018, 2(3), 18; https://doi.org/10.3390/instruments2030018
Received: 13 August 2018 / Revised: 9 September 2018 / Accepted: 13 September 2018 / Published: 17 September 2018
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Abstract
This paper presents tea leaves moisture monitoring system based on RF reflectometry techniques. The system was divided into two parts which are the sensor and reflectometer parts. The large coaxial probe was used as a sensor for the system. The reflectometer part plays [...] Read more.
This paper presents tea leaves moisture monitoring system based on RF reflectometry techniques. The system was divided into two parts which are the sensor and reflectometer parts. The large coaxial probe was used as a sensor for the system. The reflectometer part plays a role as signal generator and also data acquisition. The reflectometer-sensor system was operated with a graphical user interface at 1.529 GHz at room temperature. The system was able to measure the moisture content of tea leaves ranging 0% m.c to 50% m.c on a wet basis. In this study, up to five kinds of tea leaves bulk were tested. The mean of absolute errors in the moisture measurement for tea leaves was ±2. Full article
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Open AccessArticle
PaddyCheck—An Instrument for Rice Quality Determination
Instruments 2018, 2(3), 11; https://doi.org/10.3390/instruments2030011
Received: 26 April 2018 / Revised: 26 June 2018 / Accepted: 2 July 2018 / Published: 3 July 2018
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Abstract
Several of the rice quality parameters are nowadays determined manually or partly manually, which leads to subjective results. In order to analyse the rice quality and avoid most of the manual handling, the PaddyCheck instrument was mainly developed to measure the paddy/rough rice [...] Read more.
Several of the rice quality parameters are nowadays determined manually or partly manually, which leads to subjective results. In order to analyse the rice quality and avoid most of the manual handling, the PaddyCheck instrument was mainly developed to measure the paddy/rough rice kernels. However, the design and technique of the instrument are also suitable for brown rice kernels. The PaddyCheck instrument measures the physical properties of the rice kernels as well as texture properties and translucency. Initial calibrations have been developed to correlate these properties with the Head Rice Yield and Chalkiness, which are two of the most common and important quality parameters for rice. Full article
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