Latest Advances in Sensor Applications in Agriculture

Sensor applications are impacting the everyday objects that enhance human life quality. In this special issue, the main objective was to address recent advances of sensor applications in agriculture covering a wide range of topics in this field. A total of 14 articles were published in this special issue where nine of them were research articles, two review articles and two technical notes. The main topics were soil and plant sensing, farm management and post-harvest application. Soil-sensing topics include monitoring soil moisture content, drain pipes and topsoil movement during the harrowing process while plant-sensing topics include evaluating spray drift in vineyards, thermography applications for winter wheat and tree health assessment and remote-sensing applications as well. Furthermore, farm management contributions include food systems digitalization and using archived data from plowing operations, and one article in post-harvest application in sunflower seeds.

[1]  Marcus Bellett-Travers,et al.  THE RELATIONSHIP BETWEEN SURFACE TEMPERATURE AND RADIAL WOOD THICKNESS OF TWELVE TREES HARVESTED IN NOTTINGHAMSHIRE , 2010 .

[2]  Francesco Pirotti,et al.  Monitoring Within-Field Variability of Corn Yield using Sentinel-2 and Machine Learning Techniques , 2019, Remote. Sens..

[3]  Hans W. Griepentrog,et al.  Determination of Cultivated Area, Field Boundary and Overlapping for A Plowing Operation Using ISO 11783 Communication and D-GNSS Position Data , 2019 .

[4]  Rui Pitarma,et al.  Infrared Thermography Applied to Tree Health Assessment: A Review , 2019, Agriculture.

[5]  Roland Gerhards,et al.  Potential use of ground-based sensor technologies for weed detection. , 2014, Pest management science.

[6]  G. Wang,et al.  Hyperspectral data mining to identify relevant canopy spectral features for estimating durum wheat growth, nitrogen status, and grain yield , 2017, Comput. Electron. Agric..

[7]  Barry J. Allred,et al.  A GPR Agricultural Drainage Pipe Detection Case Study: Effects of Antenna Orientation Relative to Drainage Pipe Directional Trend , 2013 .

[8]  David Reiser,et al.  Development of an Autonomous Electric Robot Implement for Intra-Row Weeding in Vineyards , 2019, Agriculture.

[9]  Luigi Sartori,et al.  Assessing Topsoil Movement in Rotary Harrowing Process by RFID (Radio-Frequency Identification) Technique , 2019, Agriculture.

[10]  Ruzairi Abdul Rahim,et al.  Sensing Wood Decay in Standing Trees: A Review , 2018 .

[11]  Takeshi Fujino,et al.  Calibration and Validation of a Low-Cost Capacitive Moisture Sensor to Integrate the Automated Soil Moisture Monitoring System , 2019, Agriculture.

[12]  Rui Pitarma,et al.  Contribution to Trees Health Assessment Using Infrared Thermography , 2019, Agriculture.

[13]  Maxim Shishaev,et al.  Food System Digitalization as a Means to Promote Food and Nutrition Security in the Barents Region , 2019, Agriculture.

[14]  Shamaila Zia-Khan,et al.  Early Detection of Zymoseptoria tritici in Winter Wheat by Infrared Thermography , 2019, Agriculture.

[15]  Barry J. Allred,et al.  Delineation of Agricultural Drainage Pipe Patterns Using Ground Penetrating Radar Integrated with a Real-Time Kinematic Global Navigation Satellite System , 2018, Agriculture.

[16]  Chi-Chih Chen,et al.  DETECTION OF BURIED AGRICULTURAL DRAINAGE PIPE WITH GEOPHYSICAL METHODS , 2004 .

[17]  Lammert Kooistra,et al.  High-Resolution Multisensor Remote Sensing to Support Date Palm Farm Management , 2019, Agriculture.

[18]  Yafit Cohen,et al.  A Novel Cosmic-Ray Neutron Sensor for Soil Moisture Estimation over Large Areas , 2019, Agriculture.

[19]  José Dorado,et al.  An Approach to the Use of Depth Cameras for Weed Volume Estimation , 2016, Sensors.

[20]  M. Payá,et al.  Synthesis and enzyme inhibitory activities of a series of lipidic diamine and aminoalcohol derivatives on cytosolic and secretory phospholipases A2. , 2000, Bioorganic & medicinal chemistry letters.

[21]  Dimitrios Argyropoulos,et al.  Acquisition of Sorption and Drying Data with Embedded Devices: Improving Standard Models for High Oleic Sunflower Seeds by Continuous Measurements in Dynamic Systems , 2018, Agriculture.

[22]  Johanna Link,et al.  Utilisation of Ground and Airborne Optical Sensors for Nitrogen Level Identification and Yield Prediction in Wheat , 2018, Agriculture.

[23]  S. Fountas,et al.  Development and Field Evaluation of a Spray Drift Risk Assessment Tool for Vineyard Spraying Application , 2019, Agriculture.