Monitor Environment and Leaf-Growth Dynamics with Multi-Spectral Imaging and IoT

Within the PHE4OLIVE project, CommonsLab and XpectralTEK are developing and evaluating a system to monitor olive trees growth environment and leaf-growth dynamics. This system can assess the root performance of olive tree cuttings.

Specifically, the system provides multispectral optical monitoring of leaf the growth dynamics. This way, it can determine the root performance of multiple varieties of olive tree stem cuttings. The new prototype is based on the XpeCAM X01 imaging system by XpectralTEK and on the IoT sensor system by CommonsLab.

The multispectral images will provide all the known phenotype indices related to abiotic plant stress. The IoT sensors allow to gather and continuously update the information collected during the entire pre-breeding process, to ensure high-fidelity monitoring of environmental and soil stress.

The main challenge is to make use of the speed of high-throughput phenotyping under a controlled environment, to fit with mass plant propagation with improved (pre-)breeding efficiency.

We expect to be able to correlate the the breeding environment with the plant rooting efficiency. We also plan to provide early diagnosis of the plant rooting success or failure, by means of machine-learning assisted multi-spectral imaging. Eventually we will report on a complete methodology to monitor environment and leaf-growth dynamics for a controlled pre-breeding process.

Specialized agriculture experts and greenhouse operators are validating this technology through direct application in pilot test cases using three different olive tree varieties. Together with potential customers, we assess the application of this method regarding its value and market relevance.

The research and development leading to these results has received funding from the European Union Horizon2020 Program GEN4OLIVE project under Grant Agreement 101000427.