Proyectos vigentes

Advanced phenomics for screening physiological traits in cereals aimed at quantification and early detection of leaf fungal diseases and of water stress

Equipo

Instituto de Agricultura Sostenible (IAS)

Acrónimo

CERESTRES

IP

Jose A. Jiménez-Berni

Resumen

This proposal will encompass a multidisciplinary approach to reach new technology and scientific knowledge to improve cereal production systems in irrigated and rainfed scenarios. The most important cereals for human consumption are wheat and rice, and any technological progress in these two crops could benefit millions of people around the world. In the rainfed systems there is a need for new varieties adapted to drought, resistant to diseases, and with suitable end-use quality. In the irrigated crops, strategies to save water and greenhouse gasses emissions (GHG) while preserving yield, and biodiversity need to be studied to infer all the side-effects that water reduction may bring. New technologies, such as phenomics may help in all these goals, as a transversal tool, suitable for high-throughput screening and precision agriculture.
The subproject 3 (SP3), led by IAS-CSIC, will be transversal across the other subprojects, and will develop innovative phenomic solutions to characterize physiological disease responses, to detect and quantify leaf rust in wheat, to monitor water stress under various water management strategies, and to provide novel techniques to assist selection in wheat breeding.

Actividades del proyecto

1. Development of remote and proximal sensing tools for phenotyping across multiple sites. This will require inter-calibration of instrumentation, standarised metadata and reproducible data processing pipelines.
2. Development of phenotypic traits for screening plant water status and drought tolerance in wheat based on energy balance and physiological estimates from hyperspetral and thermal imaging
3. Development of early detection and phenomic scoring for leaf fungal diseseses in wheat based on a combination of hyperspectral imaging and physiological modeling
4. Development of an automated data processing pipeline for seamless integration of field and sensor-based traits

Fecha inicio

09/2021

Fecha finalización

08/2024

Organismo financiador

AEI (PID2020-118650RR-C33)

Cuantía