DARkWIN. Project to improve crops in the face of climate change

The idea is to identify plant varieties that are best adapted to extreme climatic conditions and then use them as a basis for more resilient and productive crops, capable of withstanding the adverse climatic conditions that are expected in the future.

About the DARkWIN project

The project, christened with the acronym DARkWIN, proposes to track pollinator preferences to guide natural selection and plant breeding and aims to address some of the biggest challenges facing agriculture today, such as climate change and biodiversity loss. The project is based on the study of pollinator preferences for certain plants. By knowing these preferences, researchers will be able to select plants that are more attractive to pollinators and therefore have a higher pollination rate. DARkWIN is based on a geo-positioning device specifically designed for bumblebees (Bombus terrestris), which will quantify pollinator preference in a tomato mapping population under combined water and heat stress to mimic a climate change scenario. Project Objectives

• Develop a new geo-positioning device to automatically detect and quantify sequential spatio-temporal interactions between a large number of plants and pollinating insects.
• Develop the world’s first automated platform based on ecological ‘plant x insect’ interactions to phenotype floral metabolic traits for resistance to change for a completely new pollinator-assisted selection and breeding.
• Development of pollinator-assisted plant breeding software as a basis for a new plant breeding technique (NPBT).
• Analysis of pollinator-flower phenotyping in the prediction of agronomic resistance and crop quality.
• Establishment of a unique and unprecedented multi-omics database on nutritional, hormonal, metabolomic and transcriptomic profiling and QTLs and candidate genes.
• Modelling pollinator foraging decisions in response to environment and plant x pollinator networks.
• Develop an unprecedented set of new tomato F1 hybrids based on pollinator-driven selection of parental lines.

Benefits of the project The main application is to secure the world’s food and nutrient supply potential under adverse climatic conditions, as 75% of food crops depend on pollinators, including 84% of the species grown in the EU, generating 31% of the income from agricultural production. By selecting the most resistant plants with the highest pollination rate, the quality and quantity of crops is improved, resulting in higher food production. Selecting plants that are more attractive to pollinators can not only improve crop resilience, but can also help protect and promote biodiversity. The results of this project are expected to have a positive impact on agriculture globally.  

Project partners and funding

The project, which will run for the next three and a half years, is funded by the Pathfinder programme of the European Innovation Council (Horizon Europe). The interdisciplinary consortium includes the participation of five research centres: CEBAS-CSIC, which coordinates the project; the Centro de Automática y Robótica (CAR, CSIC-UPM); the Estación Biológica de Doñana del CSIC (EBD-CSIC); the Centro de Biotecnología y Genómica de Plantas (CBGP, CSIC-UPM); and the Max Planck Institute in Germany, as well as three companies from the agri-food sector, including NOVAGRIC. More information on the project: darkwin.eu