Novel seed-based treatment for tackling flea beetle damage to protect the UK's oilseed rape production
Lead Research Organisation:
National Institute of Agricultural Botany
Department Name: Centre for Research
Abstract
Rapeseed (Brassica napus subsp. napus; also known as oilseed rape) is the second most important arable crop in the UK. Uses of oilseed rape range from edible vegetable oils to biodiesel and animal feed. The recent disruption of international supply chains caused by the Russia-Ukraine conflict has resulted in the prices of oilseed rape nearly doubled between February and April 2022, demonstrating the global demand of the crop and benefits for the UK growers to increase its production. However, pest pressure in the UK (e.g. cabbage stem flea beetle, CSFB) has led to 15-20% yield losses annually. Due to difficulties with crop establishment caused by CSFB and subsequent poor grower returns, rapeseed crop area has been decreasing from 530,000 ha in 2019 to 307,000 ha in 2021. Because lack of fully effective crop protection control of CSFB, growers are relying on cultural Integrated Pest Management (IPM) techniques such as later drilling and companion cropping to control the pest but had limited success. In the proposed project, we plan to test and verify a novel seed-based treatment to prevent further CSFB feeding and damage to the rapeseed tissues with extremely low agrochemical inputs, providing crop protection to mitigate pest damage for an important UK crop - oilseed rape.
Technical Summary
Rapeseed (Brassica napus subsp. napus; also known as oilseed rape) is the second most important arable crop in the UK. The recent disruption of international supply chains caused by the Russia-Ukraine conflict has resulted in the prices of oilseed rape nearly doubled, demonstrating the global demand of the crop and benefits for the UK growers to increase its production. However, pest pressure in the UK (e.g. the main pest threat is cabbage stem flea beetle, CSFB; Psylliodes chrysocephala) has led to 15-20% yield losses annually.
We plan to test a novel seed-based JA treatment and its effectiveness to mitigates CSFB damage in both controlled and field conditions, using UK recommended oilseed rape varieties and treated with four treatment combinations (i.e. untreated control, seed treatment only, foliar treatment only, and both treatments). In this 6-month project, we propose to (1) test and evaluate whether the seed-based JA treatment is an economically viable tool that can be employed alone or in conjunction with other IPM-based methods to offer sufficient crop protection to selected UK recommended winter oilseed rape lines; (2) quantify the efficiency of the seed-based JA treatment individually and on UK recommended oilseed rape varieties; (3) verify whether the treatment impacts seed germination and early establishment and the effectiveness of the treatment that mitigates the CSFB damage at establishment, stem elongation and flowering under field conditions.
We will examine whether JA treatment will have impacts on oilseed rape seeds using seed germination- and establishment traits powered by SeedGerm and Videometer (WP1), establish field-based trials to study the effectiveness of the treatment that mitigates the CSFB damage using RGB and multispectral drones and the AirMeasurer platform (WP2), and collate research results for verification and dissemination to maximise impacts.
We plan to test a novel seed-based JA treatment and its effectiveness to mitigates CSFB damage in both controlled and field conditions, using UK recommended oilseed rape varieties and treated with four treatment combinations (i.e. untreated control, seed treatment only, foliar treatment only, and both treatments). In this 6-month project, we propose to (1) test and evaluate whether the seed-based JA treatment is an economically viable tool that can be employed alone or in conjunction with other IPM-based methods to offer sufficient crop protection to selected UK recommended winter oilseed rape lines; (2) quantify the efficiency of the seed-based JA treatment individually and on UK recommended oilseed rape varieties; (3) verify whether the treatment impacts seed germination and early establishment and the effectiveness of the treatment that mitigates the CSFB damage at establishment, stem elongation and flowering under field conditions.
We will examine whether JA treatment will have impacts on oilseed rape seeds using seed germination- and establishment traits powered by SeedGerm and Videometer (WP1), establish field-based trials to study the effectiveness of the treatment that mitigates the CSFB damage using RGB and multispectral drones and the AirMeasurer platform (WP2), and collate research results for verification and dissemination to maximise impacts.
People |
ORCID iD |
| Ji Zhou (Principal Investigator) |
 http://orcid.org/0000-0002-5752-5524
|
| Description | 204: 450 nm (blue), 890 nm and 970 nm (NIR) are highly correlated with seed quality and can be used for screening seeds with better uniformity and potentially vigour. Research is still ongoing as we are planning to combine several target wavelengths to study JA treatments during seed germination. Feb-2025: we also found that the multispectral can lead to more precise genetic mapping studies. For example, from red to red edge and near infrared channels can be soundly used to identify different spectral reflectances of genotypes in the Wheat MAGIC Diversity Panel developed by NIAB. We identified several novel and published genetic loci, some of which (e.g. Tamyb10-B1, reported to change grain colour from red to white, showing higher grain dormancy) took plant researcher 7 years to identify. The GWAS result was only 5kb away from the cloned gene, suggesting the breeding value of this approach. |
| Exploitation Route | Besides the publication being prepared, we shall expand the scale of the research (this awarded work was pump priming) with more rigorous testing in the lab and in the field. We are discussing with OMEX for large-scale seed testing using the findings of this short project, which will cover Brassica, barely and broad beans, a great connection from lab-based research to real-world applications. |
| Sectors | Agriculture Food and Drink Digital/Communication/Information Technologies (including Software) |
| Description | AI in Digital Agriculture and Sustainable Agriculture |
| Geographic Reach | Multiple continents/international |
| Policy Influence Type | Influenced training of practitioners or researchers |
| Impact | One CGIAR is a global research partnership for a food secure future, dedicated to transforming food, land and water systems in a climate crisis through a $1 billion annual research portfolio. The partnership unites 15 international organisations and has 10,000 staff working across 89 different countries, producing science that has brought benefits to hundreds of millions of people around the world. One CGIAR supports innovative solutions to improve food security, increase biodiversity, stimulate economic growth and strengthen resilience of farming systems. AI-powered toolkit was developed to facilitate the accurate measurement of adoption rates of CGIAR varietal technologies and the prediction of yield to better measure genetic gain in farmer fields. And this is where the AI/Data Sciences team at NIAB comes in. Currently, NIAB has pioneered AI-models to assess key yield components in wheat and are developing AI-based image recognition algorithms and open-source software. With One CGIAR the ambition is to integrate this into VarScout, a digital ecosystem designed to record, store, and visualise crop varietal data on a local, national and international scale. |
| URL | https://www.niab.com/news-views/blogs/using-artificial-intelligence-variety-identification |
| Description | Talks with UK farmers through NIAB's membership forum |
| Geographic Reach | Local/Municipal/Regional |
| Policy Influence Type | Influenced training of practitioners or researchers |
| Description | Developing AI to bridge lab and field plant research |
| Amount | £253,560 (GBP) |
| Funding ID | BB/Y513969/1 |
| Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 02/2024 |
| End | 08/2025 |
| Title | GSP-AI model |
| Description | We uploaded the latest version of GSP-AI model, iPython, testing data, and other supporting datasets (see the Assets section below) that could be used to reproduce the results presented in the article titled "GSP-AI: An AI-Powered Platform for Identifying Key Growth Stages and the Vegetative-to-Reproductive Transition in Wheat Using Trilateral Drone Imagery and Meteorological Data" (DOI: 10.34133/plantphenomics.0255; https://spj.science.org/doi/10.34133/plantphenomics.0255). Other data and user guides are openly available on request. The latest AirMeasurer platform can be downloaded via https://github.com/The-Zhou-Lab/UAV-AirMeasurer/releases). |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2024 |
| Provided To Others? | Yes |
| Impact | Testing datasets, software, wheat growth stage prediction modelling, and manually scored flowering date provided in this release are available for academic use only. Other data and user guides are openly available on request. When using the Zhou lab's work, please do cite our paper "GSP-AI: An AI-powered platform for identifying key growth stages and the vegetative-to-reproductive transition in wheat based on trilateral and multi-seasonal drone phenotyping", as well as the AirMeasurer platform (DOI: 10.1111/nph.18314). |
| URL | https://github.com/The-Zhou-Lab/GSP-AI/releases |
| Title | New drone based method has been developed to study seedling with drone-collected images |
| Description | OMEX supplied four UK recommended varieties with different yield production (e.g. Dart, Flemming, and Aurelia), with or without JA treatment. In the pre-germinating assessment, we used the Videometer system and its 19 probes to produce wavelengths from 365 nm to 970 nm plus fluorescence to image dry and imbibed seeds. These spectral traits were then used as proxies to correlate with seed quality (e.g. uniformity, etc.) and thus the classification of seed quality for the four UK varieties with or without JA treatment. This was then used as benchmark data for the field-based seedling establishment analysis. |
| Type Of Material | Physiological assessment or outcome measure |
| Year Produced | 2024 |
| Provided To Others? | No |
| Impact | Established seedling phenotyping in the field, with seedling trait analysis generated for different rapeseed varieties, with or without JA. |
| Title | Hyperspectral seed imaging analysis |
| Description | To safeguard wheat seed quality and vigour for better crop performance, it is important to assess seed morphological features and internal contents reliably and at a large scale, resulting in the importance of rapid and non-destructive seed analysis and the necessity of advancing analytical methods in this research domain. We have combined multispectral seed imaging, computer vision and automated image processing techniques to address methodological problems in seed phenotyping and seed-based phenotypic analysis in terms of throughput and accuracy. We have developed an automated algorithm that can segment individual seed from hundreds of wheat seeds acquired by multispectral imaging device, through which morphological traits (e.g. seed area, length, width, and roundness) and internal components (e.g. plant pigments, starch, vegetable oil and water content, etc.) can be quantified. We utilised morphological and spectral traits in clustering and principal component analysis, establishing a classification method to differentiate wheat seed varieties. |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2024 |
| Provided To Others? | No |
| Impact | The paper has published in 2024 |
| URL | https://d.wanfangdata.com.cn/periodical/zwslxtx202404013 |
| Description | Developed an industry partner, Mr David Booty at OMEX Agriculture |
| Organisation | Omex Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | OMEX Agriculture is a major manufacturer of liquid fertilisers in the UK and a world leader in the formulation and manufacture of innovative plant nutrient fertilizers, biostimulants and seed treatments, with its products exported to over 80 countries around the world. We worked with OMEX's research and development (R&D) team and tested JA-treated crops reduced negative impacts of flea beetle infestation under field conditions, which helps sustainably produce healthy food whilst taking steps to improve the environment. |
| Collaborator Contribution | Provided seeds and in-field seedling experiments and ground-truthing for the correlation analysis. |
| Impact | This collaboration is multi-disciplinary and we worked on examining whether JA treatment will have impacts on oilseed rape seeds based on seed germination- and establishment traits using SeedGerm and Videometer, followed by the field-based trials to study the effectiveness of the treatment that mitigates the cabbage stem flea beetle (CSFB) damage. |
| Start Year | 2023 |
| Title | Hyperspectral imaging for seed quality |
| Description | Established hyperspectral seed imaging and time-series seed germination experiments, with radical and seedling trait analysis generated for different rapeseed varieties, with or without JA. The development is on going... |
| Type Of Technology | New/Improved Technique/Technology |
| Year Produced | 2024 |
| Impact | Time-series seed imaging will demonstrate a new approach for us to assess radical and seedling trait analysis generated for different rapeseed varieties., which can be expanded to other crop species. |
| URL | https://www.geves.fr/research-development/research-activities/seed-quality-testing/ |
| Description | Digital Agriculture For A Sustainable Future |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | I was invited to present Multi-scale crop phenotyping and AI-powered trait analysis to connect latest technologies with farmers as a keynote speaker. The event is called "Digital Agriculture For A Sustainable Future" which was jointly organised by Hutchinson Limited and Defra in London UK. |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://www.hutchinsons.co.uk/digital-tools-drive-for-a-more-profitable-and-sustainable-farming-futu... |
| Description | Novo Nordisk Foundation presentation |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | As an invited speaker, I was presented at the Novo Nordisk Foundation workshop at the University of Cambridge UK. The title is "From image to loci: Multi-scale phenotyping and AI-powered trait analysis to enable diversity analysis and genetic mapping of performance traits in wheat". |
| Year(s) Of Engagement Activity | 2025 |
| Description | Presented the work at the Asia Pacific Plant Phenomics conference |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | The 3rd Asia-Pacific Plant Phenomics International Conference (APPPcon) promotes the most advanced research progresses in plant phenotyping, the 3rd Asia- Pacific Plant Phenomics Conference (http://www.appp-con.com) will be held on July 7-10, 2023 in Sanya, a beautiful coastal city. We warmly welcome all scientists or representatives who are interested in plant phenotyping to participate the conference where plant phenotyping professionals can gather and exchange ideas, present their latest findings, and to network with their peers, so as to advance the field further towards a sustainable future. |
| Year(s) Of Engagement Activity | 2023 |
| URL | https://www.plant-phenotyping.org/index.php?index=580&event=3rd_Asia_Pacific_Plant_Phenomics_Interna... |