Periodic Reporting for period 3 - InnoVar (Next generation variety testing for improved cropping on European farmland)
Reporting period: 2022-10-01 to 2023-09-30
Agriculture (including horticulture and other forms of primary production) is increasingly being urged to reduce its dependency on external inputs, lower its environmental footprint and cope with more variable climatic conditions. In this context, plant breeding needs to further evolve and take into account more systematically those characteristics that contribute to crop resilience vis-a-vis biotic and abiotic stresses. This implies that criteria and methods are in place to test the performance of new plant varieties under conditions associated with sustainable and more variable farming practices. Innovations in breeding can be further promoted by increasing the robustness and efficacy of variety testing methods for obtaining marketing authorization and Plant Variety Rights.
Introducing ways to evaluate plant varieties for sustainability and resilience will benefit society by producing food that requires fewer agro-chemical input by promoting varieties that are better adapted to specific growing scenarios. This will create food production systems that are more efficient, sustainable and resilient whilst using fewer chemical inputs.
InnoVar will draw together expertise and knowledge from across crop science, bioinformatics, soil science, meteorology, and computer science to develop and deliver methods and tools to achieve greater efficiency in plant variety testing processes and in the use of resources on-farm, enabling the EU and its farmers to maximise the potential of their land, in terms of both yield and environmental sustainability (including adaptation to climate change and environmental resilience).
The key objectives are to:
1. Identify crop characteristics and sustainability criteria which indicate the capacity of varieties to maintain yield under more variable conditions and more sustainable crop management practices.
2. Develop precise, rapid and automated methods and trialling processes to provide data on characters that contribute to the capacity of new varieties to maintain yield under more variable conditions and sustainable crop management practices.
5. Apply the methods and techniques developed for wheat to other cereals and other crop types, including oilseeds, grasses, legumes, sugar beet, maize, etc.
6. Develop new tools for the evaluation and detection of variety characteristics, using genomic, phenomic and digital technologies.
7. Analyse and review existing systems for providing and delivering information about varieties and facilitate variety specialists in adopting and developing new effective methods and tools for dissemination.
Introducing ways to evaluate plant varieties for sustainability and resilience will benefit society by producing food that requires fewer agro-chemical input by promoting varieties that are better adapted to specific growing scenarios. This will create food production systems that are more efficient, sustainable and resilient whilst using fewer chemical inputs.
InnoVar will draw together expertise and knowledge from across crop science, bioinformatics, soil science, meteorology, and computer science to develop and deliver methods and tools to achieve greater efficiency in plant variety testing processes and in the use of resources on-farm, enabling the EU and its farmers to maximise the potential of their land, in terms of both yield and environmental sustainability (including adaptation to climate change and environmental resilience).
The key objectives are to:
1. Identify crop characteristics and sustainability criteria which indicate the capacity of varieties to maintain yield under more variable conditions and more sustainable crop management practices.
2. Develop precise, rapid and automated methods and trialling processes to provide data on characters that contribute to the capacity of new varieties to maintain yield under more variable conditions and sustainable crop management practices.
5. Apply the methods and techniques developed for wheat to other cereals and other crop types, including oilseeds, grasses, legumes, sugar beet, maize, etc.
6. Develop new tools for the evaluation and detection of variety characteristics, using genomic, phenomic and digital technologies.
7. Analyse and review existing systems for providing and delivering information about varieties and facilitate variety specialists in adopting and developing new effective methods and tools for dissemination.
The first 12 months of InnoVar were dedicated to a planning phase to ensure standardised, harmonised protocols were being used across the InnoVar trial series. The InnoVar trial series is across 5 agro-climatic zones (ACZ), allowing the data generated to identify the capacity of varieties to maintain yield under more variable conditions. For each trial a combination of control, ACZ specific, and site-specific varieties have been chosen to provide sufficient genetic diversity across the trials but will also enable us to assess performance under more variable conditions. The trial design has been chosen to test variety performance using more sustainable crop management practices, utilising a range of agrochemical inputs.
By month 48 of the project, all DUS and VCU field trials have been completed. In addition to the core VCU trials, two years of organic trials, and one year of Nitrogen trials have been completed. Upload of trial data is near completion. Phenomic data has been collected from selected DUS and VCU trials and a pipeline for integration into the InnoVar database is complete. Genome-wide SNP analysis for all genotypes is complete and GWAS analysis is in progress. Phenotyping, phenomic and genomic data, together with the soil and weather data from the trial sites, is being analysed using the new machine learning models produced within the project. These models are ready to be deployed once the database has been full populated with the extensive data generated by the project
Evaluation of current recommendation systems has been completed and provides a valuable summary for post-registration VCU testing. The High-Performance Low-Risk (HPLR) categorisation system has been progressed and is being refined and tested using data generated by the project.
Dissemination and communication of the project is progressing. An interactive website has been launched with relevant information for the variety community, the seed community and the agri-food value chain across Europe, alongside other stakeholders interested in innovations in plant variety testing. InnoVar's social media presence has been very successful to date and the project has a presence on Facebook, Twitter, LinkedIn and YouTube. An IP management and exploitation plan is in place to optimise the value project data.
By month 48 of the project, all DUS and VCU field trials have been completed. In addition to the core VCU trials, two years of organic trials, and one year of Nitrogen trials have been completed. Upload of trial data is near completion. Phenomic data has been collected from selected DUS and VCU trials and a pipeline for integration into the InnoVar database is complete. Genome-wide SNP analysis for all genotypes is complete and GWAS analysis is in progress. Phenotyping, phenomic and genomic data, together with the soil and weather data from the trial sites, is being analysed using the new machine learning models produced within the project. These models are ready to be deployed once the database has been full populated with the extensive data generated by the project
Evaluation of current recommendation systems has been completed and provides a valuable summary for post-registration VCU testing. The High-Performance Low-Risk (HPLR) categorisation system has been progressed and is being refined and tested using data generated by the project.
Dissemination and communication of the project is progressing. An interactive website has been launched with relevant information for the variety community, the seed community and the agri-food value chain across Europe, alongside other stakeholders interested in innovations in plant variety testing. InnoVar's social media presence has been very successful to date and the project has a presence on Facebook, Twitter, LinkedIn and YouTube. An IP management and exploitation plan is in place to optimise the value project data.
InnoVar will test an ambitious concept to introduce innovations in variety testing using data science, genomics, phenomics and machine learning. InnoVar will review, evaluate and update DUS and VCU protocols for bread and durum wheat, identifying synergies between the two processes, to achieve improved efficiency in variety testing systems. Underpinning InnoVar will be a unique database which will be created and populated with historical data augmented during the project with significant genomic, phenomic, environmental and crop de novo data. Genetic profiling will be used to calculate Genetic Similarity Value (GSV) thresholds which will be used to determine which varieties will be sown in a series of EU-wide trials. Trials in DUS will include training and test populations for development of new and complex models involving genomics, phenomics and environmental factors to improve the usefulness of these factors for variety testing. Approaches combining advanced genotyping and transcriptomics will define new DUS characters of value in both DUS and VCU testing. An extensive VCU trial series across a range of agro-climatic regions will develop the concept of varietal yield penalty due to disease, drought and in organic growing scenarios. The VCU trial series will provide de novo data to test the ability of environmental, genomic and phenomic models to predict VCU performance and will also form the foundation for the concept of yield penalty and the HPLR. This new brand of varietal categorisation will be developed and presented in the form of the InnoVar App for review by growers to empower them to select varieties suited to their ‘growing scenarios’ with greater resilient to climate change, thus moving towards sustainability across the EU for wheat. The InnoVar approach will be used to provide templates for other crops providing road maps for DUS and VCU evaluation, update and synergies.