GET PUBLISHED: Uniting minds for “Emerging Sensor Technology in Agriculture”

Sensors 1

For the application of sensor technology and sensor networks in Agriculture, systems will need to provide an automated and integrated set of tools capable of standardising the key components of aerial and ground sensor data processing. What this results in is near-real-time distribution of monitored aspects (e.g. soil-plants), and the atmospheric factors for data mapping and its delivery via mobile devices/apps.

Thus, if topics such as:

  • New sensor development and applications for agriculture and forestry trials;
  • Sensor network development, data transmission, self-healing & redundancy considerations;
  • Machine learning modelling for geospatial information targeting agricultural decision making criteria;
  • Remote sensing using UAVs with sensor network technology;
  • Visualisation systems and software platforms to integrate sensor networks for decision making processes;
  • Low-cost smart sensors for agriculture; and
  • Development of integrated models with sensor networks and applications in agriculture and forestry environments;

…are what you do, excel at, and are passionate about, head over to http://www.mdpi.com/journal/sensors/special_issues/ESTA for manuscript submission information. 

And as the Guest Editors of the sensors Journal Special Issue: Emerging Sensor Technology in Agriculture highlights:

In order to be successful in overcoming the effects of climate change, and to remain competitive and sustainable as a country in the agricultural sector, there is a need to acknowledge these challenges and support research and applications in the development of new and emerging sensor technologies and their applications in agriculture.

And don’t forget to send it in before 30 March 2019 – all the best!

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Invited Speaker: 10th International Symposium on Viticulture and Oenology 2017

Dr Sigfredo Fuentes has been invited to the 10th International Symposium on Viticulture and Oenology to be held in Wuzhong, Ningxia – China from the 20th to the 22nd of April 2017.

Presentation: Detection of berry cell death and smoke contamination in berries using near infrared spectroscopy and machine learning algorithms.

New Paper: Plant water stress detection based on aerial and terrestrial infrared thermography: a study case from vineyard and olive orchard

Authors: C. Poblete-Echeverrı́a1,a, D. Sepulveda-Reyes2, S. Ortega-Farias2, M. Zuñ iga1 and S. Fuentes3

1Escuela de Agronomı́a, Pontificia Universidad Católica de Valparaı́so, Quillota, Chile; 2Research and Extension Center for Irrigation and Agroclimatology (CITRA), Universidad de Talca, Chile; 3The University of Melbourne, Melbourne School of Land and Environment, Victoria 3010, Australia.

Abstract: 

Irrigation scheduling is critical for vineyards and olive orchards, since it directly affects yield and fruit composition. Regulated deficit irrigation (RDI) strategies have been applied on both crops with positive results in the past. However, to successfully regulate stress levels, it is necessary to have accurate measurements of plant water status, which is usually achieved using a pressure chamber. In this regard, canopy temperature (Tc) has been shown to be an accurate indicator of plant water stress. Therefore, the objective of this study was to evaluate the accuracy of water stress detection based on aerial and terrestrial infrared thermography for a vineyard and an olive orchard. Lateral infrared thermal images were obtained using a handheld infrared camera and nadir-view infrared thermal images were obtained using an unmanned aerial vehicle (UAV). In addition, measurements of midday stem water potential (Ψstem) from olives trees (Olea europaea L. ‘Arbequina’) and grapevines (Vitis vinifera L. ‘Carménère’) were taken under different RDI strategies during the 2013- 2014 growing season. The image analysis was performed using a customized code written in Mathlab® defining thresholds to exclude non-plant elements. Results showed that the use of infrared thermal images aided in recognizing the differences in the water availability for irrigation treatments when the plants were under stress conditions.

Keywords: unmanned aerial vehicle (UAV), lateral infrared thermal images, nadir-view infrared thermal images

Irrigation scheduling is critical for vineyards and olive orchards, since it directly affects yield and fruit composition. Regulated deficit irrigation (RDI) strategies have been applied on both crops with positive results in the past. However, to successfully regulate stress levels, it is necessary to have accurate measurements of plant water status, which is usually achieved using a pressure chamber. In this regard, canopy temperature (Tc) has been shown to be an accurate indicator of plant water stress. Therefore, the objective of this study was to evaluate the accuracy of water stress detection based on aerial and terrestrial infrared thermography for a vineyard and an olive orchard. Lateral infrared thermal images were obtained using a handheld infrared camera and nadir-view infrared thermal images were obtained using an unmanned aerial vehicle (UAV). In addition, measurements of midday stem water potential (Ψstem) from olives trees (Olea europaea L. ‘Arbequina’) and grapevines (Vitis vinifera L. ‘Carménère’) were taken under different RDI strategies during the 2013- 2014 growing season. The image analysis was performed using a customized code written in Mathlab® defining thresholds to exclude non-plant elements. Results showed that the use of infrared thermal images aided in recognizing the differences in the water availability for irrigation treatments when the plants were under stress conditions.

Keywords: unmanned aerial vehicle (UAV), lateral infrared thermal images, nadir-view infrared thermal images