MultiStress Research Overview
From DNA/genome to field-scale ecophysiological dynamics: integrated research to understand complex multiple stress interactions and genotype-specific stress responses in maize.
Problem Statement
The research is framed within two major interconnected global challenges, i.e. food security in the face of environmental threats:
(1) to meet projected food demand for a world population of 9.8 billion by 2050, agricultural productivity must increase by 35-56%.
(2) climate change and resource scarcity (water, fertile soil) are simultaneously undermining agricultural production capacity and yield stability. Progressive global warming has intensified extreme and adverse weather events in most agricultural regions and is expected to amplify yield instability. Additionally, pest and disease distributions are shifting and expanding, further threatening crop production. Food security is in particular threatened through yield failures occurring simultaneously across major cereal-growing regions.
Historically, scientific research has compartmentalized plant-stress interactions, studying abiotic constraints—such as drought and nitrogen deficiency—entirely in isolation from biotic threats like pathogens and herbivores. However, under actual field conditions, whether in the tropics or in temperate regions, crops are usually subjected to a combination of multiple abiotic and biotic stressors.
Instead, stress interactions are typically multiple, concurrent, and highly interactive. Funded by the German Research Foundation (DFG) with approximately €5.4 million for an initial four-year period (2026–2030), the MultiStress Research Unit (RU 6101) addresses this critical knowledge gap. Coordinated by the University of Göttingen, the international consortium investigates how the growth, yield, and stover quality of maize (Zea mays L.) are affected by the concurrent interactions of drought and nitrogen deficiency with the foliar disease Setosphaeria turcica and stem borer infestations. By bridging the gap between empirical field observations and advanced computational algorithms, the MultiStress consortium aims to provide a first-of-its-kind mechanistic understanding of combined stress impacts.
A Holistic Approach: From Genetic Sequence to Ecosystem Simulation
Pillar 1: Central Field Experiments via Rain-Out Shelters (ROUTS)
At the core of the empirical data generation are highly standardized field experiments conducted simultaneously in Germany (temperate) and Kenya (tropical). Utilizing state-of-the-art Rain-Out Shelters (ROUTS), researchers manipulate water availability and soil nitrogen levels while systematically introducing biotic stressors, specifically stem borer larvae and Setosphaeria turcica inoculations. By testing selected commercial hybrids in a full-factorial design across 216 plots per site, the team captures extensive parameters, including photosynthetic capacity, stomatal conductance, root-zone microbiome activity, and structural disease damage under authentic field conditions.
Pillar 2: High-Throughput Diversity Screening (DSa & DSb)
To map the precise genetic architecture of stress response, the consortium conducts comprehensive diversity screening. The research evaluates 600 highly diverse inbred maize lines, comprising a EuroSet adapted to European climates and a KenSet sourced via CIMMYT, adapted to tropical environments. Through controlled greenhouse experiments that map transcriptomic and metabolomic responses, followed by extensive field evaluations of 2 x 100 newly developed F1 hybrids, the project identifies the specific gene regulatory mechanisms and polygenic adaptations that confer multi-stress tolerance.
Pillar 3: The MultiStress Modeling Platform
The vast influx of high-resolution empirical and multi-omics data converges within the overarching synthesis modelling framework. The consortium builds on a base crop simulation model (SSM-iCrop) and modifies it by explicitly integrating mathematical algorithms describing the interactions of concomitant abiotic and biotic stressors and their impacts on carbon allocation, maize yields and yield quality. By directly linking genotypic parameters to ecophysiological rate variables, the novel MultiStress modelling platform will be capable of predicting genotype-specific crop performance, yield penalties, and resource use efficiency under highly complex, interacting environmental threat scenarios.
Bridging Hemispheres
Maize serves as a foundational pillar of global food security, providing critical resources for human nutrition and livestock production across (sub-)tropical and temperate climates. As agricultural production is inevitably forced to expand into marginal, suboptimal lands characterized by severe water and nutrient limitations, overcoming the cultivation challenges of maize offers the greatest potential benefits for productivity increases, yield stability and, hence, global food security.
The MultiStress Research Unit tackles this challenge through a deeply embedded North-South scientific partnership. By linking advanced research centers in Germany—including the University of Göttingen, Technical University of Munich (TUM), University of Cologne, University of Hohenheim, University of Kiel and IPK Gatersleben—with pivotal East African institutions such as Jaramogi Oginga Odinga University of Science and Technology (JOOUST) in Siaya, Kenya, the consortium forms a strategic alliance capable of true global impact. Additional partnerships with CIMMYT, the University of Milano and AGRA ensure that the generated knowledge directly feeds into international agricultural development.
The ultimate vision of the consortium transcends mere data collection. The formalization of this mechanistic understanding into an advanced crop simulation modelling platform—the MultiStress Model—will allow researchers to extrapolate findings across time and geographic space. During the envisioned Phase 2 of the RU, this platform will be utilized to conduct in silico model-aided ideotype design. By understanding which biological traits disrupt the cascading impacts of multiple stresses, the project empowers future breeding programs to develop highly resilient, multi-stress-tolerant maize cultivars tailored for the changing target environments of the future.
Vision of MultiStress Research Unit
The schematic below illustrates the different research foci, convergence of data and knowledge and, outputs and interconnections between Phase 1 (years 1-4) and the envisaged Phase 2 (years 5-8) of MultiStress RU.
In Phase 1, the central experiment (CE) utilizes a limited genetic basis of 2 x 6 commercial hybrids (DE and KE), to improve mechanistic understanding of multiple abiotic + biotic stress interactions across various organisational levels. The experimental findings will be formalized in the mechanistic MultiStress crop model that targets the field scale. In Phase 2, the main goal is to improve the MultiStress model and apply it for designing scenario-specific maize ideotypes, while advancing the mechanistic understanding beyond the knowledge gained in Phase 1. For this a diverse genetic basis of 2 x 12 experimental hybrids (DE and KE) will be subjected to well-defined environmental stress scenarios, specific for the two research sites/recommendation domains.
Interconnections Between Subprojects
Schnellnavigation → MultiStress Forschungsverbund
Entdecken Sie das zentrale Projekt, das Koordinationsprojekt und 6 Teilprojekte
ZP – Zentrales Projekt
Experimente, Daten-Hub und Synthese von Erkenntnissen
SP1
Auswirkungen von Stress-Genotyp-Interaktionen auf die ober- und unterirdische Kohlenstoffallokation, die Nährstoffnutzungseffizienz und Prozesse in der Wurzeltiefe
SP2
Untersuchung der physiologischen, biochemischen und molekularen Reaktionen von Mais auf gleichzeitige biotische und abiotische Stressfaktoren
SP3
Molekulare Anpassung an kontrastierende Stressregime
SP4
Kombinierte Auswirkungen von Maiszünsler und abiotischen Stressfaktoren auf kommerzielle Maishybriden
SP5
Kombinierte Effekte von Setosphaeria turcica und abiotischen Stressfaktoren auf
Maissorten
SP6
Integration der Genetik in Pflanzenwachstumsmodelle zum Verständnis der Genotyp-Reaktion auf kombinierte (abiotische + biotische) Stressfaktoren und Synthese von Modellierungen
COP – Koordinationsprojekt
Strategie, Verbreitung und Kapazitätsaufbau
