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OPTIcut On route to Market

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Funding Stream:

Award Details

Project Team:

Prof David Elizondo, PI
Dr Lipika Deka, CI
Prof Ezequiel Lopez, CI
Prof Cristobal Carmona, CI
Dr Rafel Luque, CI
Mr Nivar Anwer, AI Developer
Mr Diego Garcia, Software Developer
Mrs Diana Segura, CI

David Elizondo, Professor in Intelligent Transport, De Montfort University
Lead HEI:
De Montfort University
Project dates:
1 April 2025 - 30 September 0026
Project Website:
Geographical focus:
  • UK
  • Costa Rica
Partner HEIs
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De Montfort University, University of Malaga, University of Jaen, CORBANA

OPTIcut is an innovative computational intelligence system that revolutionises banana processing by optimising cutting strategies and reducing fruit waste. Developed through extensive collaboration with key stakeholders, including CORBANA, OPTIcut directly addresses inefficiencies inherent in traditional manual methods, resulting in waste reductions of 5-10% and substantial profitability gains. Independent field trials, supported by CORBANA, validate the technology’s capabilities while positioning OPTIcut as a pivotal tool in sustainable agriculture [8]. A 1% reduction in waste at large plantations can generate approximately $1 million in additional revenue, underscoring the transformative potential of this technology.

Project Activities
The project aims at refining the current proof of concept. The project will deliver an automated system for detecting fruit damages, which is currently done manually and has been identified as a major bottleneck for market entry. Automating this process will accelerate data processing, improve efficiency, and remove a critical barrier to wider adoption of the OPTIcut technology.

We will also continue field trials with CORBANA in Costa Rica, gathering essential data to develop the automated damage detection system. CORBANA is the national banana organisation which supports all banana producers in Costa Rica. As well as testing and trialling OPTIcut, CORBANA acts as the main divulgation body for OPTIcut.

We will also continue engagement with key partners, including the University of Málaga, the University of Jae, Spain, and IMT France, who have been instrumental in building the OPTIcut system. Their expertise will be critical during the current refinement stage, particularly in improving the cutting optimiser to adapt to diverse customer needs.

Field Trials to Costa Rica will take place to manage relationships with key stakeholders, set up new tests, and ensure they are conducted correctly. These visits are essential for validating the data collected during trials, continuing engagement with potential clients, and ensuring smooth project execution and collaboration.

Impact

Impact
Alignment with Innovate UK Priorities
The OPTIcut project aligns with Innovate UK’s strategic goals by fostering innovation that drives economic growth, supports sustainable practices, and strengthens the UK’s position as a leader in cutting-edge agricultural technology. By leveraging advanced AI and automation, OPTIcut contributes to reducing waste, improving efficiency, and creating new revenue opportunities within the banana supply chain. The project exemplifies key Innovate UK themes, including:

Future Economy: Supporting sustainable agricultural practices that reduce waste and optimize resource use, aligning with environmental goals and contributing to a net-zero economy.

• Growth at Scale: Building scalable solutions that can expand beyond the banana industry, with the potential for broader applications in other agricultural sectors, thus driving economic growth.

• Global Opportunities: Establishing strong international collaborations, particularly in Central and South America, and positioning OPTIcut as a global leader in agricultural technology innovation.

Outputs and Outcomes:

Goals and Milestones

Phase 1: System Refinement and Validation
• Enhanced Cutting Optimization: Develop and refine the cutting optimization system to increase accuracy and efficiency, allowing producers to minimize waste and maximize profitability.

• Enhanced Image processing: Refine the current image processing component to enhance accuracy and speed up the process.

• Automated Banana Damage Detection (Identified as the main bottleneck): Complete integration of the automated banana damage detection system, eliminating manual inspections and addressing a major barrier to market entry.

• Product Refinement: Identify and fix all existing bugs to polish the product, ensuring seamless performance during field trials and preparation for market readiness.

Phase 2: Commercial Readiness
• Product Validation: Conduct extensive product validation through trials at CORBANA, ensuring the software meets performance standards and performs effectively in real-world conditions.

• Commercial Readiness: Finalize the software design, incorporating feedback from trials. Develop training modules to onboard new users and implement a pilot program with key stakeholders to demonstrate system effectiveness. Address the current barrier to market entry by integrating automated damage detection, ensuring the system is fully prepared for market launch.

Phase 3: Market Launch
Secure first paying customers, marking the transition from pilot trials to full commercial deployment.

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