Abstract The TSB project is a business led collaborative project involving an SME, Rail Vision Europe Ltd (RVL), a not for profit RTO, Rothamsted Research (RR) & a large crop production company, Certis UK Ltd (CUK) a UK subsidiary of Certis Europe BV. The project will be led by RVL. The project brings together a consortium comprising highly established crop specialists from RR and CUK, and electronic sensor, photonics, data processing and analytics systems specialism from RVL. The project is targeted at improving the efficieny of food production by engineering a novel, flexible multi sensor imaging system (HD, IR, flourescence) for mounting on a mobile platform (manual or robotic) for use initially in a protected crop environment. The imaging system will work with an advanced data analytics system to automatically detect and alert identified plant stresses and present the results and reports to end users in a traceable & recordable manner for automated crop monitoring & stress detection. The system will initially be targeted at protected tomato crop stresses, but is expected to be rapidly expanded to additional protected crops including cucumbers, fruits etc and eventually to an increasing range of crops. By facilitating increased crop monitoring, automated analysis and an earlier detection of crop stresses, the project facilitates enhanced efficiency in use of resources by reducing the use of herbicides/pesticides, more targeted application of resources and increased yield for a given acreage. The project supports integrated pest management in the protected crop environment and will minimise the potentially negative impacts associated with food production. The project will provide new information on the phenotyping of crop stresses, including the timescales for development of certain symptoms under different conditions to allow production of simple epidemiology models to predict risk of disease spread around detect foci. Summary The TSB project is a business led collaborative project that addresses the three strands of the scope, enhancing efficiency, maximising market yield and minimising potential negative environmental impacts. The project involves an SME, Rail Vision Europe Ltd (RVL), a not for profit RTO, Rothamsted Research (RR) & a large crop production company, Certis UK Ltd (CUK) a UK subsidiary of Certis Europe BV. The project will be led by RVL. The project brings together a consortium with highly established crop specialists from RR and CUK, and electronic sensor, photonics, data processing and analytics systems specialism from RVL. The industrial research project is targeted at improving the efficieny of food production by engineering a novel, flexible multi sensor imaging system (HD, IR, flourescence) for mounting on a mobile platform (manual or robotic) for use initially in a protected crop environment. The imaging system will work with an advanced data analytics system to automatically detect and alert identified plant stresses and present the results and reports to end users in a traceable & recordable manner for automated crop monitoring & stress detection. The system will initially be targeted at protected tomato crop stresses, but is expected to be rapidly expanded to additional protected crops including cucumbers, fruits etc and eventually to an increasing range of crops. By facilitating increased crop monitoring, automated analysis and an earlier detection of crop stresses, the project facilitates enhanced efficiency in use of resources by reducing the use of herbicides/pesticides, more targeted application of resources and increased yield for a given acreage. The project supports the application of increasing integrated pest management in the protected crop environment and minimising the potentially negative impacts associated with food production. Within just the tomato growing market in the UK, worth £175m p.a., a minimum of 10% losses costs growers £17.5m per aum. Improving yield in this sector by only 2% increases tomato yields by £3.5m p.a. UK market is small proportion of EU potential. The project engineers a solution for pest and disease control building on RR and other recent research into the use of intelligent multi-sensors for the detection of crop diseases (West et al 2003; Moshou et al 2011; Sankaran et al 2010) and RVL's expertise in the development of sensor platforms design, sensor analytics, image processing and presentation (Warsop & Singh (VISAPP, 2009), Singh et al (CIS 2009 - 8th IEEE Intnl Conf. on Cybernetic Intelligent Systems). The project combines these areas of expertise to provide a unique capability for automated crop monitoring initially within a protected crop environment. The project will provide new information on the phenotyping of crop stresses, including the timescales for development of certain symptoms, including at microscopic scales and using fluorescence imaging, which could provide methods for assessing cultivar resistance. The timescales for detection thresholds will be identified under different conditions to allow production of simple epidemiology models to predict risk of disease spread around detected foci. Impact Summary Plant stresses cause a substantial loss of food production globally (Strange et al (2005), Oerke (2005)). Competing demands for increased productivity, reduced cost & environmental impact, increasing pathogen resistance & legislation (e.g. Sustainable Use Directive, 2009/128/EC), are leading to increased use of integrated pest management (IPM). Early stress detection leads to more effective intervention. Currently, monitoring is carried out by regular visual inspections either by farm workers or by specialised inspectors. Inspections are laborious, time consuming & expensive, limiting frequency & effectiveness. The proposed project develops a novel, flexible multi-sensor imaging system (HD, IR & fluorescence) for application on a mobile platform (manual or robotic) for use initially in a protected crop environment. The system will be initially aimed at protected tomato crops. Total UK glass house area is 1,779ha (Defra, 2013), of which ~200ha is for tomatoes, by 40 key growers. UK tomato production is worth £175m. Losses amount to at least 10%, worth £17.5m p.a. (£87,500/ha/p.a.). Global tomato production increasing, 36% up 2002-2011. EU & UK production stable at ~16m Tonnes. China grows 30% of global demand. CUK provides crop protection solutions for 70% of UK growers. The sector is capital intensive, scientifically progressive, technically advanced & environmentally responsible. Tomato Growers Assoc. identify increasing IPM & reduced pesticide use as key objectives. CUK have team of specialist crop inspector's on client's sites on a 2 weekly cycle. A remote monitoring system accurately auto-assessing, alerting & presenting crop stress incidents & identified anomalies is extremely attractive to end users, it does not currently exist & will be transformational. With a target cost per platform with equipment: £70k, plus S/W £25K for focussed crops version (£50K for multiple crop). Projected sales yr 1 £450K, yr 2 £1m, & yr 3 £2.5m providing ROI for the projefrom product launch with <40% of CUK's existing UK tomato growers. The solution will rapidly expand to more crops & new markets. The industrial partners of the project will benefit immediately. For RVL & CUK it provides a new product/service range in a large & growing global market, with expected T/O in the UK of > £2.5m within 3 years of product launch. Operations are planned to be at RVL's & CUK's current facilities & are expected to create >12 new high skilled jobs, plus additional revenues for h/w supply chain companies. For RR it provides additional research opportunities and these could lead to improved methods for plant health inspectors to detect potentially infected plant material that can then be targeted for sampling and application of diagnostic tests (see also Academic Beneficiaries Section). For end users it provides reduced losses from crop stresses, a 2% increase in tomato yields ~ £3.5m/p.a increase in revenue. Additional benefits are expected from expansion into further crops. Social Benefits-existing surveys are undertaken manually, these are time consuming & labour intensive in a sector with skill shortages. This new approach reduces the manual labour content whilst improving outcomes & allowing highly skilled employees to accurately assess crop stresses. Environmental benefits are also expected - the project increases yield of locally grown produce, reducing food miles. Continuous monitoring, early identification & intervention for crop stresses reduces requirements for herbicides/ pesticides supporting localised crop intervention. Remote monitoring reduces transport CO2 for specialist inspectors. Additional crop monitoring opportunities are envisaged e.g. growth/yield from automated surveys can focus fertiliser inputs.