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Special Issue "Precision Agriculture and Sensor Systems"

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

Deadline for manuscript submissions: closed (31 August 2020).

Special Issue Editors

Prof. Dr. Viacheslav Adamchuk
Website
Guest Editor
Department of Bioresource Engineering, 21,111 Lakeshore Road, Ste-Anne-de-Bellevue, QC, H9X 3V9, Canada
Interests: development of soil and plant sensor systems, geospatial data processing, navigation of agricultural vehicles, implementation of precision agriculture
Special Issues and Collections in MDPI journals
Prof. Dr. Abdul M. Mouazen
Website SciProfiles
Guest Editor
Group Leader Precision Soil and Crop Engineering (Precision SCoRing), Faculty of Bioscience Engineering, Department of Environment, Ghent University, Coupure Links 653, Blok B, 1st Floor 9000 Gent, Belgium
Interests: proximal soil sensing; precision agriculture; soil analysis, data fusion
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

You are invited to submit a manuscript to a special issue of Sensors. This issue will summarize cutting-edge research on the development and application of new sensor systems to support precision agriculture. We are especially interested in contributions on novel approaches to characterize soil, plants and animals as well as new ways to use sensor data to support the decision-making process.

Prof. Dr. Viacheslav Adamchuk
Prof. Dr. Abdul Mouazen
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. 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 2000 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
  • proximal soil sensing
  • crop canopy sensors
  • precision livestock management
  • sensor networks
  • multi sensor
  • data fusion
  • machine learning
  • chemometrics
  • decision support
  • geostatistics

Published Papers (2 papers)

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Research

Open AccessArticle
Real-Time Detection on SPAD Value of Potato Plant Using an In-Field Spectral Imaging Sensor System
Sensors 2020, 20(12), 3430; https://doi.org/10.3390/s20123430 - 17 Jun 2020
Cited by 2
Abstract
In this study, a SPAD value detection system was developed based on a 25-wavelength spectral sensor to give a real-time indication of the nutrition distribution of potato plants in the field. Two major advantages of the detection system include the automatic segmentation of [...] Read more.
In this study, a SPAD value detection system was developed based on a 25-wavelength spectral sensor to give a real-time indication of the nutrition distribution of potato plants in the field. Two major advantages of the detection system include the automatic segmentation of spectral images and the real-time detection of SPAD value, a recommended indicating parameter of chlorophyll content. The modified difference vegetation index (MDVI) linking the Otsu algorithm (OTSU) and the connected domain-labeling (CDL) method (MDVI–OTSU–CDL) is proposed to accurately extract the potato plant. Additionally, the segmentation accuracy under different modified coefficients of MDVI was analyzed. Then, the reflectance of potato plants was extracted by the segmented mask images. The partial least squares (PLS) regression was employed to establish the SPAD value detection model based on sensitive variables selected using the uninformative variable elimination (UVE) algorithm. Based on the segmented spectral image and the UVE–PLS model, the visualization distribution map of SPAD value was drawn by pseudo-color processing technology. Finally, the testing dataset was employed to measure the stability and practicality of the developed detection system. This study provides a powerful support for the real-time detection of SPAD value and the distribution of crops in the field. Full article
(This article belongs to the Special Issue Precision Agriculture and Sensor Systems)
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Open AccessArticle
Analysis of Tillage Depth and Gear Selection for Mechanical Load and Fuel Efficiency of an Agricultural Tractor Using an Agricultural Field Measuring System
Sensors 2020, 20(9), 2450; https://doi.org/10.3390/s20092450 - 26 Apr 2020
Cited by 2
Abstract
This study was conducted to analyze the effects of tillage depth and gear selection on the mechanical load and fuel efficiency of an agricultural tractor during plow tillage. In order to analyze these effects, we developed an agricultural field measuring system consisting of [...] Read more.
This study was conducted to analyze the effects of tillage depth and gear selection on the mechanical load and fuel efficiency of an agricultural tractor during plow tillage. In order to analyze these effects, we developed an agricultural field measuring system consisting of a load measurement part (wheel torque meter, proximity sensor, and real-time kinematic (RTK) global positioning system (GPS)) and a tillage depth measurement part (linear potentiometer and inclinometer). Field tests were carried out using moldboard plows with a maximum tillage depth of 20 cm and three gear selections (M2H, M3L, and M3H) in a rice stubble paddy field for plow tillage. The average travel speed and slip ratio had the lowest M2H and the highest M3L. M3H had the highest theoretical speed, but the travel speed was 0.13 km/h lower than M3L due to the reduction in the axle rotational speed at deep tillage depth. Regarding engine load, the higher the gear, the greater the torque and the lower the axle rotation speed. The front axle load was not significantly affected by the tillage depth as compared to other mechanical parts, except for the M3H gear. The rear axle load generated about twice the torque of the front wheel and overall, it tended to show a higher average rear axle torque at higher gear selection. The rear axle load and fuel rate were found to be most affected by the combination of the tillage depth and gear selection combination. Overall, field test results show that the M3H had the highest fuel efficiency and a high working speed while overcoming high loads at the same tillage depth. In conclusion, M3H is the most suitable gear stage for plow cultivation, and the higher the gear stage and the deeper the tillage depth during plowing, the higher the fuel efficiency. The results of this study will be useful for analyzing mechanical load and fuel efficiency during farm operations. In a future study, we will conduct load analysis studies in other farming operations that consider various soil mechanics factors as well as tillage depths and gear selections. Full article
(This article belongs to the Special Issue Precision Agriculture and Sensor Systems)
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