S04 - Session O1 - Light solutions for Cannabis sativa micropropagation

Authors: Verónica Codesido Sampedro *, José Garrido Gala, Carlos Ferreiro-Vera, Jesús Hidalgo

The high time consuming of data collection and analysis of Cannabis sativa L. in vitro studies, generated an imminent necessity to generate a system that help to take data apporting more objective and sound results. Plants phenotyping is a powerful tool to test phenotypic properties of plants and it also could predict genotype by environment interactions. Imaging techniques such as capturing the red fluorescence emission of chlorophyll, or the green and blue fluorescence emitted by plant defence compounds, coupled with thermal imaging are essential in what is known as non-invasive phenotyping. Moreover, the study of reflectance using multi- and hyperspectral cameras, can be used in the laboratory, or installed in robots or drones for greenhouse and field tests. Phytoplant Research, in collaboration with the company Onimagin, has designed a platform for taking in vitro culture images, developing algorithms that allow the monitoring and calculation of morphological and phenotypical parameters of the plants such as: daily growth rate, leaf area, number of leaves, green intensity of leaves, etc. The final objective is the design and development of a functional prototype of an Image Taking Platform, capable of automatically, uniformly and standardly taking images of the plants as well as obtaining metrics of them, allowing both the characterisation of the different individuals and the extraction of trends on variables that evolve over time. The algorithms developed for the Codessian platform allow us to obtain data, with the necessary scientific rigour, about the growth of the plants, as well as the rest of their phenotypical characteristics. The created image algorithms followed the next steps: record a reference image, illumination correction, colour potentiation, plants segmentation, selection of one plant per image and leaflets detection. The system makes the calculations and returns them in a graphic way. Codessian save time and provide more objective data than measurements made by hand. we re-edited your abstract and propose following changes: Collecting and analysing data from Cannabis sativa L. in vitro studies is very time-consuming and prompted us to develop a phenotyping system. It is a powerful tool for testing phenotypic properties of plants and can also predict genotype x environment interactions. Cameras to capture the red fluorescence emission from chlorophyll, or the green and blue fluorescence emitted by plant defences, coupled with thermal imaging are essential for non-invasive phenotyping. The multi- and hyperspectral cameras can be used in the laboratory or installed on robots or drones to cover greenhouse and field trials. Phytoplant Research, in collaboration with the company Onimagin, has designed a platform for creating in vitro culture images, developing algorithms that allow morphological and phenotypic parameters of the plants to be tracked and calculated, such as: daily growth rate, leaf area, number of leaves, green intensity of the leaves, etc. The final objective is to enable the characterisation of different individuals as the extraction of trends on variables that evolve over time. The image algorithms created take the following steps: acquisition of a reference image, exposure correction, colour potentiation, plant segmentation, selection of one plant per image and leaf detection. The system makes the calculations and displays them graphically. Codessian saves time and provides more objective data than measurements made by hand.