New sensors and data-driven approaches - a path to Next Generation Phenomics
journal contribution
posted on 2023-05-03, 22:10authored byThomas Roitsch, Llorenc Cabrera-Bosquet, Antoine Fournier, Kioumars Ghamkhar, Jose Jimenez-Berni, Francisco Pinto, Eric Ober
At the recent 4th International Plant Phenotyping Symposium meeting of the International Plant Phenotyping Network (IPPN) at CIMMYT in Mexico, a workshop was convened to consider ways forward with sensors for phenotyping. The increasing number of field applications provides new challenges and requires specialised solutions. There are many traits that are vital to plant growth and development, which demand phenotyping approaches that are still at early stages of development or elude current capabilities. Further, there is growing interest in low-cost sensor solutions, and mobile platforms that can be transported to the experiments, rather than the experiment coming to the platform. Various types of sensors are required to address the very diverse needs with respect to targets, precision and ease of operation and readout. Converting data into knowledge, and ensuring that those data (and the appropriate metadata) are stored in such a way that they will be sensible and available to others now and for future analysis is also vital. Here we are proposing mechanisms for “next generation phenomics” based on our learning in the past decade and current practice and discussions at the IPPN Symposium, to encourage further thinking and collaboration by plant scientists, physicists and engineering experts.
History
Rights statement
Open access. Under a Creative Commons license - http://creativecommons.org/licenses/by/4.0/
Language
English
Does this contain Māori information or data?
No
Publisher
Elsevier
Journal title
Plant Science
ISSN
0168-9452
Citation
Roitsch, T., Cabrera-Bosquet, L., Fournier, A., Ghamkhar, K., Jimenez-Berni, J., Pinto, F., & Ober, E. (2019). New sensors and data-driven approaches - a path to Next Generation Phenomics. Plant Science, 282, 2–10. doi:10.1016/j.plantsci.2019.01.011