FONTAGRO recently led a webinar emphasizing the need for digital tools in sustainable agricultural management, presenting an effective combination of Python, R, and Google Earth Engine for processing and analyzing large agricultural datasets. Dr. Martín Durante, senior researcher at INTA, Argentina, highlighted how these tools enable researchers to tackle complex problems by analyzing historical data and validating theories through identified patterns.
During the session, various data visualization techniques were discussed, including the use of Flex Dashboard in R to enhance graphical representation of data and optimize statistical analysis. Organizing agricultural data using entity-attribute concepts was presented as an effective way to improve productivity analysis, facilitating comparisons between different regions and sites.
Additionally, automating data retrieval using APIs was recognized as a beneficial practice, eliminating repetitive manual tasks and allowing efficient access to information. The capabilities of Google Earth Engine were emphasized as essential for handling the vast amounts of agricultural data generated, providing a cloud-based platform for interactive satellite image processing.
The event also explored the integration of real-time data for pasture management, using satellite data to estimate growth rates and facilitate decision-making for livestock management. Through interactive visualizations and tools like Google Sheets, users can input information on remaining forage, contributing to more accurate simulation models.
Finally, the role of artificial intelligence and applications like Appsheet in improving agricultural data management was a relevant topic, showcasing the shift toward more efficient methodologies in agricultural research and practice.
To access the recording of this webinar, visit: https://www.youtube.com/live/0DG6QkSZnzU?si=xiH86C1IW-fGbAXx
The post Webinar de FONTAGRO destacó herramientas como Python, R y Google Earth para la Innovación Agrícola appeared first on FONTAGRO.