Objectives

Our research proposed objectives are fully aligned with the priority objectives of the EC 8th Environment Action Programme, CAP and the EU Taxonomy Regulation.

Our aim is to develop a unique phenotyping and selection platform for pollinator-assisted breeding. DARkWIN is based on a geo-positioning device specifically designed for bumblebees (Bombus terrestris), that will quantify pollinator preference in a tomato mapping population under combined water x heat stress, to mimic a climate change scenario.The specific technical objectives are:

  1. Develop a new geo-positioning device to automatically detect and quantify the sequential spatial-temporal interactions between a high number of plants and the pollinating insects that feed on them.
  2. Develop the first worldwide-automated platform based on ecological "plant x insect" interactions to phenotype floral metabolic traits of resilience to climate change (water x temperature stress) for a completely new pollinator-assisted selection and breeding.
  3. Development of a pollinator-assisted plant breeding software, as a basis for a new plant breeding technique (NPBT).
  4. Analysis of pollinator-floral phenotyping in predicting agronomic resilience and crop quality.
  5. Establish a unique and unprecedented multi-omics database on the nutritional, hormonal, metabolomic, and transcriptomic profile and underlying QTLs and candidate genes related to pollinator-driven natural selection in tomato under a climate change scenario.
  6. Modelling pollinator's foraging decisions in response to the environment, and plant x pollinators networks.
  7. Develop an unprecedented set of new tomato F1 hybrids based on pollinator-driven selection of parental lines under combined drought-high temperature stress (like climate change scenario).