PPP Projects

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Perennial Ryegrass (Lolium perenne L.) at NordGen’s field.

Plant breeding is long-term work and to reach the goal persistence and long-term cooperation is needed. The projects that have received funding from the Nordic Public-Private Partnership (PPP) for pre-breeding for the period 2018-2020 are all continuations of projects from the previous funding period.

Below you will find a short summary of the four projects that have recieved funding for the period 2018-2020.

Pre-breeding for future challenges in Nordic fruit and berries
The focus in this project is to strengthen pre-breeding cooperation in line with the previous PPP-projects, validate available germplasm resources by genetic and phenotypic characterization in order to widen the parental pool aimed at genetic resources enhancement by increasing diversity for targeted traits. This project also concentrates on enhancement and development on the genetic competence as well as initiating the process of integration of modern genetic tools into the breeding programs. The specially designed multipurpose cultivar panels well representing the genetic variation and novel technologies will serve as a first step towards transition into the genome-informed breeding.

Combining Knowledge from Field and from Laboratory for Pre-breeding in Barley III
The focus within the third period of the PPP barley project will be on the utilization of the MAGIC populations from the two first periods and the setup of genomics assisted pre-breeding using genome-wide association study and genomic selection in pre-breeding. A spring barley core set from gene bank material will also be selected to be used for genomic assisted pre-breeding. For this purpose, we aim to co-operate with NordGen for the selection of a spring barley core set suitable for phenotyping in Nordic countries and to find the best approach for genotyping gene bank materials for future needs. In addition, we will optimize and use image analysis for phenotyping of seedling growth and perform field phenotyping of tillering, close to maturation.

PPP for pre-breeding in perennial ryegrass (Lolium perenne L.) Phase III 2018-2020
The project aims at improving the winter hardiness, persistence and other important traits for perennial ryegrass in northern Europe. It will also make plant breeding in northern Europe more prepared to meet new demands due to climate change, political decisions or consumer demand. Growth conditions in northern Europe differ from other parts of the world due to a unique combination of day length and other environmental variables like temperature. Only breeders in the Nordic and Baltic countries can be expected to breed for these special conditions. With this project, these breeders will get better tools and genetic variation to make adapted varieties. Agriculture in these countries will, despite its northern location be more competitive compared to other countries.

Nordic Public Private Partnership Plant Phenotyping Project – Phase 2
The main activities within 6P-phase 2 consist of two categories – Research & Innovation (R&I) and Networking. R&I activities will involve a continued focus on the use of unmanned aerial systems derived images and the integration of high-throughput phenotyping technology. The specifically targeted crops are barley, oats, wheat, ryegrass and potatoes. The networking activities will effectively be a social platform to integrate ongoing research, strengthen cooperation and facilitate knowledge sharing between research institutions, technology providers, and plant breeders. The benefit to the plant breeding industry arises from either making the current visual phenotype observations faster, more reliable and cost-efficient, or the introduction of new phenotyping traits not possible to score visually with the human eye. In the first case, it is a matter of replacing or complementing the observations done manually by the breeder or co-workers. Automated field phenotyping may in some cases be faster or more precise than even an experienced breeder. The second possibility in automated phenotyping is to use different sensors to rate phenotypic traits not possible to score with visual observations from RGB cameras. It opens to an array of phenotypic traits, some of which are correlated to interesting traits such as biotic and abiotic stress, or even yield. The potential efficiency increases in later processes, such as quicker cultivar selection and relation to genomic markers adds further value. The long-term vision is to be able to use phenomics and genomics in combination, to build prediction models for selection of new candidate cultivars.