Rhizoctonia solani is an aggressive soil-borne pathogen of oilseed rape (OSR) and canola worldwide. It is implicated in the yield decline of the crop when grown with increased frequency in field rotations.
Presently there are no disease resistant varieties, hence the control of the disease relies on the use of chemical seed treatment.
The key objectives of this project are to identify novel resistance traits and loci to R. solani which can be utilised in crop breeding and effective seed treatments that can be registered against the pathogen in OSR and made commercially available to UK growers.
The ultimate output of this multidisciplinary project will be the first integrated guidelines for the control of R. solani incorporating targetted seed treatments and varietal resistance for improved disease management and protection of OSR yield.
Potato late blight is one of the world's most destructive crop diseases, with £3.5Bn annual losses globally in an industry suffering stagnant yields for the last decade. This project will develop a rapid acoustic biosensor device for in-field identification of air-borne sporangia of Phytophthora Infestans (causal agent of late blight), to meet the compelling need for improved disease management & control. Soil Essentials (SE), a precision-farming SME, together with University of Cambridge (UC), the James Hutton Institute (JHI), Mylnefield Research Services (MRS) & Syngenta (SG), will develop an integrated diagnostic tool for early pathogen detection, by coupling low-cost, antibody-coated acoustic sensing consumables with a proven spore-trap. The proposed innovation, enabled only by the interdisciplinary convergence of state-of-the art acousto-electronics, smart materials, biochemistry, late blight epidemiology, advanced ICT & precision agriculture, will enable optimised disease control, reducing potato crop waste & fungicide costs, improving marketable yield & quality. As a platform technology, it can be easily adapted to detect other crop & livestock pathogens for wider agricultural impact.
Virus yellows in sugar beet is a greater problem in the UK than anywhere else in Europe because of our maritime climate, which favours the aphid vector. The UK beet industry invests up to £7M annually on insecticides (seed treatments and foliar sprays) for aphid control, without which virus yellows could cause losses of up to £10million/year. Recent EU restrictions on neonicotinoid use and the development of insecticide resistance in aphids in Europe, threatens to significantly increase virus yellows in UK-grown sugar beet, making the UK crop less competitive in world markets. Development of sugar beet resistant to virus yellows is therefore critical. We have identified wild beet that are resistant to the effects of virus yellows and have crossed this trait into sugar beet. We propose to develop this resistance further by crossing our resistant lines with modern breeding varieties and carry out rigorous testing of our new varieties for virus yellows resistance, plant vigour and sugar yield. This 5yr pre-breeding project will accelerate the production of new virus yellows resistant sugar beet varieties, bringing significant economic and environmental benefits to the UK and Europe.
This proposal aims to develop an automated system for precise application of nitrogen (N) fertiliser and plant growth regulators (PGRs). Algorithms and software will be developed for integrating diverse forms of data from crop sensing instruments, yield maps, soil maps and soil N measurements. This will enable more accurate N fertiliser and PGR management through real-time decision making in the field, both on a field-by-field basis and on a metre-by-metre basis. Adopting this technology will improve crop productivity, increase farm profitability, maximise the efficiency with which N fertiliser and PGRs are used, and minimise pollution such as nitrate leaching and greenhouse gas (GHG) emissions. The project is highly innovative in that it seeks to develop the first technology for variably applying PGRs and it will be the first technology to successfully integrate the complete range of information sources required to reliably predict the crop’s requirement for N fertiliser.
This proposal aims to develop an automated system for precise application of nitrogen (N) fertiliser and plant growth regulators (PGRs). Algorithms and software will be developed for integrating diverse forms of data from crop sensing instruments, yield maps, soil maps and soil N measurements. This will enable more accurate N fertiliser and PGR management through real-time decision making in the field, both on a field-by-field basis and on a metre-by-metre basis. Adopting this technology will improve crop productivity, increase farm profitability, maximise the efficiency with which N fertiliser and PGRs are used, and minimise pollution such as nitrate leaching and greenhouse gas (GHG) emissions. The project is highly innovative in that it seeks to develop the first technology for variably applying PGRs and it will be the first technology to successfully integrate the complete range of information sources required to reliably predict the crop’s requirement for N fertiliser.
This proposal aims to develop an automated system for precise application of nitrogen (N) fertiliser and plant growth regulators (PGRs). Algorithms and software will be developed for integrating diverse forms of data from crop sensing instruments, yield maps, soil maps and soil N measurements. This will enable more accurate N fertiliser and PGR management through real-time decision making in the field, both on a field-by-field basis and on a metre-by-metre basis. Adopting this technology will improve crop productivity, increase farm profitability, maximise the efficiency with which N fertiliser and PGRs are used, and minimise pollution such as nitrate leaching and greenhouse gas (GHG) emissions. The project is highly innovative in that it seeks to develop the first technology for variably applying PGRs and it will be the first technology to successfully integrate the complete range of information sources required to reliably predict the crop’s requirement for N fertiliser.
This proposal aims to develop an automated system for precise application of nitrogen (N) fertiliser and plant growth regulators (PGRs). Algorithms and software will be developed for integrating diverse forms of data from crop sensing instruments, yield maps, soil maps and soil N measurements. This will enable more accurate N fertiliser and PGR management through real-time decision making in the field, both on a field-by-field basis and on a metre-by-metre basis. Adopting this technology will improve crop productivity, increase farm profitability, maximise the efficiency with which N fertiliser and PGRs are used, and minimise pollution such as nitrate leaching and greenhouse gas (GHG) emissions. The project is highly innovative in that it seeks to develop the first technology for variably applying PGRs and it will be the first technology to successfully integrate the complete range of information sources required to reliably predict the crop’s requirement for N fertiliser.
This proposal aims to develop an automated system for precise application of nitrogen (N) fertiliser and plant growth regulators (PGRs). Algorithms and software will be developed for integrating diverse forms of data from crop sensing instruments, yield maps, soil maps and soil N measurements. This will enable more accurate N fertiliser and PGR management through real-time decision making in the field, both on a field-by-field basis and on a metre-by-metre basis. Adopting this technology will improve crop productivity, increase farm profitability, maximise the efficiency with which N fertiliser and PGRs are used, and minimise pollution such as nitrate leaching and greenhouse gas (GHG) emissions. The project is highly innovative in that it seeks to develop the first technology for variably applying PGRs and it will be the first technology to successfully integrate the complete range of information sources required to reliably predict the crop’s requirement for N fertiliser.
This proposal aims to develop an automated system for precise application of nitrogen (N) fertiliser and plant growth regulators (PGRs). Algorithms and software will be developed for integrating diverse forms of data from crop sensing instruments, yield maps, soil maps and soil N measurements. This will enable more accurate N fertiliser and PGR management through real-time decision making in the field, both on a field-by-field basis and on a metre-by-metre basis. Adopting this technology will improve crop productivity, increase farm profitability, maximise the efficiency with which N fertiliser and PGRs are used, and minimise pollution such as nitrate leaching and greenhouse gas (GHG) emissions. The project is highly innovative in that it seeks to develop the first technology for variably applying PGRs and it will be the first technology to successfully integrate the complete range of information sources required to reliably predict the crop’s requirement for N fertiliser.
This proposal aims to develop an automated system for precise application of nitrogen (N) fertiliser and plant growth regulators (PGRs). Algorithms and software will be developed for integrating diverse forms of data from crop sensing instruments, yield maps, soil maps and soil N measurements. This will enable more accurate N fertiliser and PGR management through real-time decision making in the field, both on a field-by-field basis and on a metre-by-metre basis. Adopting this technology will improve crop productivity, increase farm profitability, maximise the efficiency with which N fertiliser and PGRs are used, and minimise pollution such as nitrate leaching and greenhouse gas (GHG) emissions. The project is highly innovative in that it seeks to develop the first technology for variably applying PGRs and it will be the first technology to successfully integrate the complete range of information sources required to reliably predict the crop’s requirement for N fertiliser.
This proposal aims to develop an automated system for precise application of nitrogen (N) fertiliser and plant growth regulators (PGRs). Algorithms and software will be developed for integrating diverse forms of data from crop sensing instruments, yield maps, soil maps and soil N measurements. This will enable more accurate N fertiliser and PGR management through real-time decision making in the field, both on a field-by-field basis and on a metre-by-metre basis. Adopting this technology will improve crop productivity, increase farm profitability, maximise the efficiency with which N fertiliser and PGRs are used, and minimise pollution such as nitrate leaching and greenhouse gas (GHG) emissions. The project is highly innovative in that it seeks to develop the first technology for variably applying PGRs and it will be the first technology to successfully integrate the complete range of information sources required to reliably predict the crop’s requirement for N fertiliser.
This proposal aims to develop an automated system for precise application of nitrogen (N) fertiliser and plant growth regulators (PGRs). Algorithms and software will be developed for integrating diverse forms of data from crop sensing instruments, yield maps, soil maps and soil N measurements. This will enable more accurate N fertiliser and PGR management through real-time decision making in the field, both on a field-by-field basis and on a metre-by-metre basis. Adopting this technology will improve crop productivity, increase farm profitability, maximise the efficiency with which N fertiliser and PGRs are used, and minimise pollution such as nitrate leaching and greenhouse gas (GHG) emissions. The project is highly innovative in that it seeks to develop the first technology for variably applying PGRs and it will be the first technology to successfully integrate the complete range of information sources required to reliably predict the crop’s requirement for N fertiliser.
This proposal aims to develop an automated system for precise application of nitrogen (N) fertiliser and plant growth regulators (PGRs). Algorithms and software will be developed for integrating diverse forms of data from crop sensing instruments, yield maps, soil maps and soil N measurements. This will enable more accurate N fertiliser and PGR management through real-time decision making in the field, both on a field-by-field basis and on a metre-by-metre basis. Adopting this technology will improve crop productivity, increase farm profitability, maximise the efficiency with which N fertiliser and PGRs are used, and minimise pollution such as nitrate leaching and greenhouse gas (GHG) emissions. The project is highly innovative in that it seeks to develop the first technology for variably applying PGRs and it will be the first technology to successfully integrate the complete range of information sources required to reliably predict the crop’s requirement for N fertiliser.
This proposal aims to develop an automated system for precise application of nitrogen (N) fertiliser and plant growth regulators (PGRs). Algorithms and software will be developed for integrating diverse forms of data from crop sensing instruments, yield maps, soil maps and soil N measurements. This will enable more accurate N fertiliser and PGR management through real-time decision making in the field, both on a field-by-field basis and on a metre-by-metre basis. Adopting this technology will improve crop productivity, increase farm profitability, maximise the efficiency with which N fertiliser and PGRs are used, and minimise pollution such as nitrate leaching and greenhouse gas (GHG) emissions. The project is highly innovative in that it seeks to develop the first technology for variably applying PGRs and it will be the first technology to successfully integrate the complete range of information sources required to reliably predict the crop’s requirement for N fertiliser.
This proposal aims to develop an automated system for precise application of nitrogen (N) fertiliser and plant growth regulators (PGRs). Algorithms and software will be developed for integrating diverse forms of data from crop sensing instruments, yield maps, soil maps and soil N measurements. This will enable more accurate N fertiliser and PGR management through real-time decision making in the field, both on a field-by-field basis and on a metre-by-metre basis. Adopting this technology will improve crop productivity, increase farm profitability, maximise the efficiency with which N fertiliser and PGRs are used, and minimise pollution such as nitrate leaching and greenhouse gas (GHG) emissions. The project is highly innovative in that it seeks to develop the first technology for variably applying PGRs and it will be the first technology to successfully integrate the complete range of information sources required to reliably predict the crop’s requirement for N fertiliser.
This proposal aims to develop an automated system for precise application of nitrogen (N) fertiliser and plant growth regulators (PGRs). Algorithms and software will be developed for integrating diverse forms of data from crop sensing instruments, yield maps, soil maps and soil N measurements. This will enable more accurate N fertiliser and PGR management through real-time decision making in the field, both on a field-by-field basis and on a metre-by-metre basis. Adopting this technology will improve crop productivity, increase farm profitability, maximise the efficiency with which N fertiliser and PGRs are used, and minimise pollution such as nitrate leaching and greenhouse gas (GHG) emissions. The project is highly innovative in that it seeks to develop the first technology for variably applying PGRs and it will be the first technology to successfully integrate the complete range of information sources required to reliably predict the crop’s requirement for N fertiliser.
This proposal aims to develop an automated system for precise application of nitrogen (N) fertiliser and plant growth regulators (PGRs). Algorithms and software will be developed for integrating diverse forms of data from crop sensing instruments, yield maps, soil maps and soil N measurements. This will enable more accurate N fertiliser and PGR management through real-time decision making in the field, both on a field-by-field basis and on a metre-by-metre basis. Adopting this technology will improve crop productivity, increase farm profitability, maximise the efficiency with which N fertiliser and PGRs are used, and minimise pollution such as nitrate leaching and greenhouse gas (GHG) emissions. The project is highly innovative in that it seeks to develop the first technology for variably applying PGRs and it will be the first technology to successfully integrate the complete range of information sources required to reliably predict the crop’s requirement for N fertiliser.
This proposal aims to develop an automated system for precise application of nitrogen (N) fertiliser and plant growth regulators (PGRs). Algorithms and software will be developed for integrating diverse forms of data from crop sensing instruments, yield maps, soil maps and soil N measurements. This will enable more accurate N fertiliser and PGR management through real-time decision making in the field, both on a field-by-field basis and on a metre-by-metre basis. Adopting this technology will improve crop productivity, increase farm profitability, maximise the efficiency with which N fertiliser and PGRs are used, and minimise pollution such as nitrate leaching and greenhouse gas (GHG) emissions. The project is highly innovative in that it seeks to develop the first technology for variably applying PGRs and it will be the first technology to successfully integrate the complete range of information sources required to reliably predict the crop’s requirement for N fertiliser.
This proposal aims to develop an automated system for precise application of nitrogen (N) fertiliser and plant growth regulators (PGRs). Algorithms and software will be developed for integrating diverse forms of data from crop sensing instruments, yield maps, soil maps and soil N measurements. This will enable more accurate N fertiliser and PGR management through real-time decision making in the field, both on a field-by-field basis and on a metre-by-metre basis. Adopting this technology will improve crop productivity, increase farm profitability, maximise the efficiency with which N fertiliser and PGRs are used, and minimise pollution such as nitrate leaching and greenhouse gas (GHG) emissions. The project is highly innovative in that it seeks to develop the first technology for variably applying PGRs and it will be the first technology to successfully integrate the complete range of information sources required to reliably predict the crop’s requirement for N fertiliser.
This proposal aims to develop an automated system for precise application of nitrogen (N) fertiliser and plant growth regulators (PGRs). Algorithms and software will be developed for integrating diverse forms of data from crop sensing instruments, yield maps, soil maps and soil N measurements. This will enable more accurate N fertiliser and PGR management through real-time decision making in the field, both on a field-by-field basis and on a metre-by-metre basis. Adopting this technology will improve crop productivity, increase farm profitability, maximise the efficiency with which N fertiliser and PGRs are used, and minimise pollution such as nitrate leaching and greenhouse gas (GHG) emissions. The project is highly innovative in that it seeks to develop the first technology for variably applying PGRs and it will be the first technology to successfully integrate the complete range of information sources required to reliably predict the crop’s requirement for N fertiliser.
This proposal aims to develop an automated system for precise application of nitrogen (N) fertiliser and plant growth regulators (PGRs). Algorithms and software will be developed for integrating diverse forms of data from crop sensing instruments, yield maps, soil maps and soil N measurements. This will enable more accurate N fertiliser and PGR management through real-time decision making in the field, both on a field-by-field basis and on a metre-by-metre basis. Adopting this technology will improve crop productivity, increase farm profitability, maximise the efficiency with which N fertiliser and PGRs are used, and minimise pollution such as nitrate leaching and greenhouse gas (GHG) emissions. The project is highly innovative in that it seeks to develop the first technology for variably applying PGRs and it will be the first technology to successfully integrate the complete range of information sources required to reliably predict the crop’s requirement for N fertiliser.
This proposal aims to develop an automated system for precise application of nitrogen (N) fertiliser and plant growth regulators (PGRs). Algorithms and software will be developed for integrating diverse forms of data from crop sensing instruments, yield maps, soil maps and soil N measurements. This will enable more accurate N fertiliser and PGR management through real-time decision making in the field, both on a field-by-field basis and on a metre-by-metre basis. Adopting this technology will improve crop productivity, increase farm profitability, maximise the efficiency with which N fertiliser and PGRs are used, and minimise pollution such as nitrate leaching and greenhouse gas (GHG) emissions. The project is highly innovative in that it seeks to develop the first technology for variably applying PGRs and it will be the first technology to successfully integrate the complete range of information sources required to reliably predict the crop’s requirement for N fertiliser.
Fusarium head blight (FHB) disease caused by Fusarium and Microdochium spp. can result in significant reductions of yield and quality of cereals. The incidence of FHB disease is on an upwards trend and the strains implicated in the infection are diversifying. Such trends are predicted to continue as the effects of global warming become apparent. Mycotoxin levels in UK malting barley have been reported to be below the EU legislative safety limits, but the effect of sub-acute Fusarium infection on the viability and functional quality of UK malting barley has remained relatively unclear. Currently there is insufficient information and knowledge of the links between key agronomic variables (e.g. selection of barley variety/ agronomic and weather conditions) and the resultant severity of FHB in malting barley. Furthermore, the impact of infection with Fusarium species on the malting and brewing quality of the barley crop remains to be elucidated.
The SAFEMalt project (Strategies Against Fusarium Effective in MALTing barley) is a 3-year multi-partner research initiative spanning the malting barley supply chain from barley breeder through barley grower and merchant to brewer. SAFEMalt will aim to determine the links throughout the supply chain from evaluating the impact of a series of agronomic variables on the incidence of FHB, through identification of the causal pathogens of FHB implicated to the subsequent impact on the functional properties of barley for malting and brewing. The role and contribution of varietal resistance in UK barley and timing of fungicide application against FHB will be determined. This project is a collaboration between partners with expertise in key sectors such as crop breeding, crop protection, agrochemical industry, farm management, malting and brewing in order to ensure that future agricultural production meets the needs of UK industry. The final output will provide new knowledge and practice incroporated into a growers toolkit with which to protect yield, quality and safety of malting barley in the production chain.