What was the challenge/problem addressed?
Maturity and health monitoring of the crop by automated and non destructive means, and estimation of optimal harvesting date and final production. Different actors participated, providing different technologies, agronomical knowledge and parcels to perform the experiments and validate the system
How did you solve the problem?
We used IOT systems on the field, hyperspectral pictures of soil and plants, thermal images taken from drones and Business Intelligence and AI tools to generate useful information from all those data
What is innovative in your practical case?
The use of hyperspectral images to measure quality parameters and the generation of alarms and recommendations about fertirrigation and harvesting based on data from many different sources
What are the success factors in solving the problem?
The collaboration of all partners with their specific expertise was key
Lessons learned
Detection of quality parameters of tomatoes and soil composition from hyperspectral pictures taken on the field. Algorithms to predict final production and define optimal harvesting date using pictures taken on the field.
What role does the advisor or advisory service play with the practical case?
Innovation broker
Can your approach be transferred and/or adapted for other innovation challenges and regions?
Yes
Estimated transferability on a scale from 1 to 5
(where 1 is easy and 5 very difficult)
3
For sharing the experience on the good practice, please contact
Jesús Gil
jgilsoto@ctaex.com
Link to external information
https://www.youtube.com/channel/UCFiyU3cOyuX4A2SGFvOP0xw