Public Funding for Fotenix Limited

Project SIERRA will create digital twins of berry farms and permit asset management optimisation without requiring large capital expenditure. Most importantly it will allow producers to more _accurately model yields_, _find hotspots of problem areas_ and target the reduced workforce to increase efficiency. Notably the project will enable farms to maximise profits in the short term but still remain relevant when automation is able to deliver at a market price point; informing machinery rather than humans. The outputs of the project include: 1. Digital upload of berry farms using existing infrastructure 2. Resource map generation for thinning, harvesting, pest & disease treatment 3. Farm management software integration 4. Data library creation to accelerate detection performance across the latest varieties In summary, project SIERRA looks to develop a platform to empower the UK berry sector with decision intelligence using proven technology at adequate farm margins.

This project addresses UK food security challenges amidst a climate crisis by offering a game-changing solution to **transform inefficient TCEA** (total controlled environment agriculture) operations into sustainable, **energy-efficient crop growing systems**. By collaborating to integrate innovative technologies, the project will characterise and demonstrate novel, responsive TCEA growing methods to optimise the efficiencies of environmental control including lighting, irrigation and nutrient supply to reduce the largest contributors responsible for high carbon footprint. The solution will also automate manual operations and improve the safety/consistency/quality/shelf-life of produce for retailers/consumers, by dynamically altering the growth environment. This innovative project will, for the first time, use the **measurement of crop physiological status**, measured using an **integrated spectral imaging system**, to **inform the illumination intensity/composition**, as well as the energy management (including renewables integration); ultimately using plant health to develop **greener production recipes** using advanced **responsive control** methodologies. The project's impact will be measured by changes to **crop yield versus operational impact** benchmarked over cost/benefit and compared to the existing state of the art. The key crop identified is the high-protein leaf crop Spinach, not only as a test crop to validate this integrated TCEA technology, but as an alternative protein crop to unlock new markets. The project is delivered by a highly competent consortium led by LettusGrow and including another two technology companies: Fotenix and Vertically Urban, an RTO: CHAP, an academic partner: Rothamsted Research and a vertical farm grower: Perfectly Fresh.

The proposed industrial focused research project utilises the consortium's unique expertise and capabilities to develop **cost-effective digital autonomous slug monitoring, forecasting and precision treatment tools,** thus delivering on-farm game-changing solutions to benefit farmers across England. Slugs are major economic pests causing £43.5M crop damage/annum for wheat and oilseed rape in the UK. Traditionally, chemical slug management relied on metaldehyde/methiocarb, however, these actives were banned in the UK due to their impact on the environment. To date, ferric phosphate is the only remaining active chemical molluscicide, but certain pellet ingredients have been noted as impacting earthworms and, when consumed in large quantities, can poison pets. Bio-molluscicides are also available but are uneconomical for use in arable and oilseed systems. Without chemical molluscicides, AHDB estimates total average annual cost to UK crop production \>£100M. Therefore, enhanced stewardship and monitoring is essential. Current monitoring protocols use in-field refuge traps (e.g. plant saucer with bait). Farmers must examine traps regularly, conduct slug counts and compare to AHDB thresholds limits. However, many farmers are not carrying out this laboursome key practice, resulting in unnecessary chemical molluscicide applications. Therefore, precision services are needed to reliably reduce slug pellet usage and implement alternative, biological control in an economically viable way. The outputs of the project have the potential to have a significant impact on the UK economy by helping farms achieve increased yields, productivity, sustainability, net zero targets, environmental benefits and resilience, through enhanced digital autonomous slug monitoring, forecasting and control.

University of Lincoln and Xihelm are collaborating to deliver _Qualicrop_ - aiming to develop crop sorting for produce, lowering costs to consumers. It will build sophisticated sorting systems to disintermediate the supply chain - unlocking technology only available to other sectors, improving the quality of sold fruit & vegetables and lowering prices to consumers and to make automation technology affordable for smaller farmers. Extensive research will be made into using modern imaging technology and machine learning to detect issues with crops in a just-in-time manner. Both partners are dedicated to advancing Equality, Diversity and Inclusion as part of this project. The system once commercialised will allow tight-margin participants in the value chain to increase their margins, lowering chargebacks and wastage, and lower CO2 impact by reducing food miles. Furthermore, it can cost effectively open new markets for different crops, and support farmers in England to accelerate their technology adoption.

This project develops an integrated, digital crop management approach for the early detection of glasshouse pests and diseases, utilising the latest diagnostic technology and agronomic knowledge in a commercial production setting. The objective is to co-develop a crop scouting service, informed by spectral diagnostics that can detect the early establishment of yield impacting events, and integrate directly with agronomic input providers. Substantial losses can be prevented through early curative action, improving conventional and biological control efficacy. The work will catalyse grower, agronomy, technology and plant science advancements to progress the envelope of digital agronomy services and sustainable glasshouse production. The change of scope proposed is for the agronomy partner to no longer supply the digital platform and move from the market exploitation focal point to a reseller and data user of a reviewed platform. The project will then focus on the diagnostics and redirect what is left of the agronomy platform resources into integrating with existing market leaders of farm management platforms (SourceAG, Koppert IPM - both currently used by the growers in the consortium). Fargro will remain as a champion of the technology, an independent trials assessor and provide crop walk support for commercial trials. The project deliverables in respect of the digital platform will be limited to the MVP of the Grofar App, which was delivered earlier in the project.

FOTENIX has helped support recent advancements in the agricultural technology sector, working as an ability provider for some of the biggest agrirobotics providers in the UK. These interactions have shaped the development of precision agriculture, pushing the boundaries of production capability and performance amidst the fourth agricultural revolution. The added differentiation to equipment using targeted vision technology helps to reinforce a market offer with significant environmental and operational benefits, with market traction demonstrated through 2020 sales. However, the key inflection point, for majority adoption, requires value aggregated across the supply chain, compounding the offers of machinery, agronomy, and agrichemical sectors. The solution to food security amidst changing climatic and political conditions will not be cheap, but with the cost shared across stakeholders, can be economically attractive and environmentally sustainable. A resilient future for high-value horticulture will require robust monitoring and automation, and a viable route for more specialised biological treatments to be deployed effectively. This crucial area of the production system demands an integrated solution to enable improvements in operation and reduction in scouting costs, through digital agronomy and resource targeting. The project will have a valuable export potential to large production markets, such as the Netherlands and United States.

This project provides step-change advances towards enabling Vertical farming (VF) technologies. In comparison to traditional agriculture, these systems reduce water usage, eliminate the use of agrochemicals and provide year-round, local production. We look to increase the adoption of sustainable food growing systems, which reduces the environmental impact of crop production and create opportunities for the growth and export of UK agricultural technologies. The focus of the project is to reduce the operational costs of VF systems and enable the wealth of UK technical and growing know-how in an optimised growing system. The key objectives are: improve yield by 30%; and reduce operational costs by 25%. It will integrate leading innovations into a scalable, commercially viable, turn-key solution demonstrator. This system will reduce the complexity and costs of constructing, controlling and monitoring optimal growth conditions. It will provide growers with better information and the right data to make decisions and automate responses to changes detected, enabling higher quality, higher yield produce, while better equipping them to adapt to market demand and reducing the risks of business failures. FOTENIX incorporate their active multispectral vision capabilities into the VF system, enabling real-time data feedback on crop health and growth status. This technology allows the development of an integrated decision-support system for the automated control of the lighting, nutrients and climate.

Since their widespread commercialisation in the 1930's, the use of pesticides has driven increased yields in agriculture that have allowed us to feed an ever-growing human population. However, with raised awareness of the potentially negative environmental impacts of these products, future food production systems will need to continue to sustain our dietary needs whilst using fewer chemical inputs. This cannot currently be achieved by ceasing pesticide use however, as without the protection they offer global yields would be reduced 30-40% at a time when we must produce more food than ever before. Nevertheless, by utilising modern developments in 'agri-technology' it should be possible to reduce the amount of pesticide that we need to apply to protect our crops by applying it in a more targeted and well-timed manner. Many pesticides, and especially fungicides (that target crop diseases) are currently applied to crops using 'calendar-based' approaches as blanket applications. This means that whole fields are subject to fungicide treatment, regardless of whether crop diseases themselves are present, or only pose a risk in parts of the crop. More targeted 'variable rate' applications are currently used for other crop inputs such as fertilisers, allowing production to be maintained (or increased) using a fraction of the chemical input. However, it is not currently possible to emulate this 'variable rate' approach for fungicide use, as detecting and mapping crop disease is technologically more challenging than detecting and mapping crop nutrient stress. Accurately applying fungicides at different rates to small areas of a crop field is also a barrier, requiring 'smart' application technology. By combining recent advances in disease sensing technology, disease imaging capability, spray application science and autonomous robotics-based farm machinery development, it is now possible to envisage an end-to-end system capable of meeting the challenge and driving forward 'precision fungicide' application. The current project aims to develop and integrate available cutting-edge science and technology solutions in these areas to both realise this vision for current conventional crop chemistry, and review its future potential to deliver emerging crop protection products such as biopesticides.

This project entails the construction of the ALPHA AI cloud platform for the precision agriculture sector. FOTENIX currently produces multispectral 3D cameras with particular use cases, e.g. disease detection in strawberries. The products are developed in conjunction with machinery/robotics providers and trained on trial data before being deployed in the field. This project focusses on a cloud architecture to sit between the camera systems and the customer's dashboard, which will enable an additional revenue stream that supports the translation of FOTENIX's software and data analytics capabilities to its customers (machinery) and end-users (growers).

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"Vertical farming (VF) has the potential to revolutionise food production. The industry is experiencing enormous growth, propelled by the increased demand for pesticide-free foods, rising global populations, decreased availability of land and demand for year-round food production worldwide. It delivers numerous benefits versus traditional farming methods including lower water usage, reduced dependence on agrochemicals and the ability to produce high quality, consistent, year-round crop production. Developing the VF sector holds the promise of significant benefits to society and the farming industry. By growing an ever-increasing percentage of the food that we consume in VF systems, pressures on farmland will reduce, and year-round local food production can be enabled while improving the outlook for permanent jobs in the farming sector. However, the industry requires further innovations to reduce operational costs and improve yields to allow it to be commercially viable beyond the production of high-value, niche, crops. VF production systems bring together an array of different technologies, many of which have been adapted from the glasshouse-based horticultural industry. Currently, these technologies have reduced integration and are lacking optimisation for crop yield, quality and control. This project brings together a multidisciplinary consortium of partners, representing a wide range of technologies and expertise, all of whom have significant experience in the VF market. The outcome of the project will be a fully optimised prototype VF growing system. It will offer a high-tech, turn-key solution that will reduce the complexity and costs of building, and adjusting and monitoring for optimal growth conditions in VF production systems. It will provide growers with better control, through data-driven information, and automate responses to changes detected, enabling them to deliver higher quality, higher yield produce, whilst better equipping them to adapt to market demand and reducing the risks of business failures. The technology will facilitate the transfer of scientific knowledge in crop production into benefits for growers. The system will include low-cost LED-lighting, that match ideal growing conditions throughout the plant growth cycle and improved nutrient control and delivery system, for increased plant yield and quality. We will evaluate the feasibility of incorporating vision sensing capabilities at large-scale which can provide valuable real-time feedback on crop health. This, in turn, will allow the development of a decision support system for the automated control of the atmospheric environment. Grower engagement in the development of a single user-friendly control system for control of all operations will be a central outcome."

"The UK soft fruit market is now worth well over £1.3 billion at retail sales values (Source: Kantar) per annum. The UK grows over 160,000 tonnes of fruit and employs 32,000 seasonal and, typically, migrant pickers. Approximately 50% of the total production cost is for labour. The soft fruit industry is extremely concerned with the both the availability of picking and husbandry labour and labour cost inflation. The impact of Brexit is already affecting labour supply and the opportunities to pass on labour cost inflation are weak and challenging. The soft fruit sector is a UK success story and there are still opportunities for expansion and to reduce fruit imports. However, it is very clear that to thrive the industry needs to drive every possible means to improve to labour productivity. Robots for soft fruit production clearly offers great opportunity in the sector. Here we will develop the world's first fleet of multi-modal robots that can carry out a wide variety of tasks in the field. Strawberry production is a complex task, and several different tasks need to be performed throughout the season. This is the first project that reflects this, in that we aim to develop robots that are completely autonomous that can carry out several different tasks in the field. We will build on current research by Saga Robotics, Berry Gardens and the University of Lincoln (UoL), complimenting the team for the first time with the inclusion of the University of Oxford and NIAB. Saga have already demonstrated world leading picking performance (in terms of vision system accuracy and picking speed) for their fruit picking robot. The system will then be integrated into the world leading Thorvald robotic platform that has been developed by Saga with UoL. In addition, we will develop a wide range of other tools that will be integrated with the robots. The robots will autonomously pick up the tools from a tool changer, and they will also charge and dock autonomously. This is a much-needed project that will transform robotic strawberry production from the laboratory bench to a commercially relevant system. The world-wide market for these machines and IP is very significant."

In light of the increasing difficulty for fruit farmers to source manual workers to pick soft fruits, there is an increasing need for the development of automatic picking systems, for fruit. This project is focused on assessing the advantages and suitability of a 3D multiSpectral imaging system for use in automatic picking systems. A reduction in manual labour to pick fruit will in turn require that an automated system also needs to play a role in disease surveillance on leaves and fruit. The development of new sensors using 3D imaging may allow detection of pre-symptomatic disease presence and improve the scheduling of fruit harvesting. The project is to assess the feasibility of this new sensor technology with both laboratory and field fruit growing applications and compare to existing technology, using the assessment expertise of Rothamsted Research and the facilities and equipment of Crop Health and Protection Ltd (CHAP) - one of the UK Agri Tech centres This project will trial and test an innovative 3D imaging tool to explore its potential to determine the initial development of diseases in key crops and fruit ripening. This will also be of use to fruit growers, researchers and plant breeders requiring phenotyping.