Crop phenotyping assisted by drones, IoT and AI
The Serida Plant Genetics group participates in the European Bresov research project to genetically improve the organic horticultural production of more than 200 varieties of beans.
The objective of the project is to check the health status of the crops and identify the phenotypic differences between the varieties monitored. Specifically, in Asturias, the aim was to improve the viability of three vegetable crops: broccoli, green beans and tomato, within a framework of ecological and sustainable production with the environment.
Izertis, which collaborates with Serida in this project, has used different image analysis algorithms, as well as artificial intelligence to integrate the different results based on indicators on the state of the crops and on meteorological and climatological variables with which to test new ones phenotyping techniques.
Capturing images of the crops in two different physiological states.
Developing software for RGB and multi-spectral image processing.
Monitoring climate data.
Reporting with the correlated data dump.
In the agricultural field, the climate and meteorological forecasts are critical to optimize the processes of irrigation, collection and care of crops. The use of environmental sensors together with the monitoring of crops with images captured by drones constitutes the ideal combination to control pests, detect water needs and identify other types of problems that affect crops.
Through the use of drones and meteorological stations located in the crop fields and connected by IoT, a meteorological record has been kept in situ and valuable data related to the flowering and fruiting of the plants have been extracted with RGB and multispectral images. captured by drones at different times. All these data and images have been recorded, processed, analysed and interpreted in order to achieve a more efficient horticultural production.
In this way, by combining IoT and AI technology developed by Izertis engineers together with the use of drones and connected weather stations, Serida will be able to identify the varieties best adapted to organic production, locate the genes with the greatest weight in adapting to the organic production and develop tools to accelerate the obtaining of new varieties by genetic improvement, as well as a more efficient and sustainable organic horticultural production.
For this, SERIDA has been provided with a report with all the values obtained for each plot, properly correlated with the genotype distribution map existing on the farm. A control panel has also been included to facilitate the consultation of the data and make comparisons for the same plot in each of the two physiological states of the crops.