Leveraging Agro-Informatics and Big Data Applications to Improve Crop Production and Farmers’ Livelihood
Convener: Shai Sela, Agmatix
Agro-informatics leverages different sources of agronomic data layers and advanced modeling to aid growers, agronomists and other stakeholders in decision making. Agriculture research has become data-driven, with the typical agronomic study utilizing data from a myriad of sources, such as field and lab experiments, remote sensing, soil sensors, machinery data, or weather data. Climate variability imposes challenges in implementing agronomic tools, since crop, soil and weather interactions must be accounted for. There is huge potential to unlock value from the abundance of agronomic data, together with machine learning algorithms and physically based models, to develop practical agronomic applications that are adaptive to climate variability.
This session will present recent advancements in agro-informatics research. The scope of the session is wide and expected topics can include (among others) precision irrigation, precision fertilization, yield optimization, plant health applications, crop phenotyping, robotic applications in agriculture, agronomic soil erosion processes, and more. We especially encourage submissions that focus and demonstrate agro-informatics research for developing countries.
Showing all 6 results
- Leveraging Agro-Informatics and Big Data Applications to Improve Crop Production and Farmers’ Livelihood
Dr. Aviva Peeters
A Decision Support Tool for Optimizing Spatial Sampling in Precision Agriculture
TerraVision Lab and SCE Shamoon College of Engineering, Israel
- Leveraging Agro-Informatics and Big Data Applications to Improve Crop Production and Farmers’ Livelihood
Dr. Oded Liran
Remote Sensing Index of Electron Transport Rate Relates to Light Use Efficiency and Biomass Production
MIGAL Research Institute, Israel
- Leveraging Agro-Informatics and Big Data Applications to Improve Crop Production and Farmers’ Livelihood
Dr. Shai Sela
Leveraging Data Standardization Tools for Better Collaboration and Agronomic Big Data Analysis
Agmatix, Israel
- Leveraging Agro-Informatics and Big Data Applications to Improve Crop Production and Farmers’ Livelihood
Dr. Tarin Paz-Kagan
Tree-Based Multilevel Spatial Decision Support Systems to Close the Yield Bap in Almond Orchards
Ben Gurion University of the Negev, Israel
- Leveraging Agro-Informatics and Big Data Applications to Improve Crop Production and Farmers’ Livelihood
Prof. Gerrit Hoogenboom
Data Standards for Model Development and Data Analytics for Decision Support
University of Florida, USA
- Leveraging Agro-Informatics and Big Data Applications to Improve Crop Production and Farmers’ Livelihood
Prof. Tal Svoray
Quantifying Spatial Soil Health Trends at the Catchment Scale
Ben Gurion University of the Negev, Israel