Investigating the physiological, biochemical, and molecular responses of maize to concurrent biotic and abiotic stresses (SP2)

• Applicants: Professor Dr. Mutez Ali Ahmed; Irsa Ejaz, Ph.D.
• Subject Area: Plant Cultivation, Plant Nutrition, Agricultural Technology
• Term: since 2026
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 571153016

Maize, a staple crop globally, faces increasing yield constraints due to the combined impacts of climate-related abiotic stresses and biotic stresses. Current maize yields remain well below potential due to limited understanding of how maize tolerates simultaneous biotic and abiotic stress. Subproject 2 aims to unravel the physiological, biochemical, and molecular responses of maize under combined stress conditions. SP2 is structured into five interconnected work packages (WPs). Each WP targets a distinct but complementary aspect of the multistress response, ranging from soil-plant hydraulics and root function to signaling mechanisms as well as high-resolution phenotyping and machine learning algorithms. In WP1, we will combine an automated root pressure chamber with novel rehydration experiments to decipher the key above and/or belowground hydraulic limitations to transpiration under combined stress. WP2 aims to leverage two non-destructive imaging techniques, namely micro-computed tomography and neutron radiography, to investigate the role of root resilience under combined abiotic and biotic stress. These non-invasive imaging tools will allow analysis of roots under combined stress. To explore the molecular basis of stress signaling, we will focus on abscisic acid as a central integrator (WP3). Endogenous ABA levels will be quantified, and functional assays using transient expression in maize and Arabidopsis protoplasts will be performed to characterize allelic variation in core ABA signaling components under multi-stress conditions. For non-invasive detection and classification of plant responses, we will establish a hyperspectral imaging pipeline (WP4) integrated with physiological and biochemical measurements. Machine learning algorithms will be applied to associate specific spectral patterns with physiological and molecular stress responses. Under natural field conditions, WP5 aims to evaluate the physiological and biochemical responses of selected commercial maize hybrids under single and combined stress conditions. SP2 will provide a mechanistic framework for understanding maize tolerance to complex environmental stress. The resulting data will support modeling efforts within the Research Unit and contribute to predictive tools for maize performance under climate-relevant multi-stress scenarios.

• DFG Programme: Research Units
• Subproject of: FOR 6101: Concurrent multiple abiotic and biotic stress interactions in maize: impacts and mechanisms (MultiStress)
• Co-Investigator: Dr. Zhenyu Yang