NIRCROP: Digitalizing Tomato Quality

The agri-food sector consistently faces the challenge of acquiring accurate, real-time information on crop ripeness and quality from the field through to the final product. This challenge is particularly critical for industrial tomatoes, where optimal harvest timing directly influences processing efficiency, energy consumption, and the ultimate quality of the end product. The NIRCROP Operational Group’s innovative project tackled this issue head-on by leveraging portable Near-Infrared Spectroscopy (NIRS) technology and advanced digital solutions to significantly enhance quality control and harvest prediction.

Project Objectives: Enhancing Precision and Profitability

The central aim of the NIRCROP project was to develop non-invasive NIRS-based technological solutions for on-site quality control of industrial tomatoes (alongside olives and grapes) across the pre-harvest, harvest, and post-harvest phases. This initiative sought to fundamentally digitally transform agriculture by creating a new tool for rapid, non-invasive field measurements. A key goal was to provide farmers with real-time data on critical crop quality indicators, thereby facilitating more informed decision-making, optimizing resource management, and ultimately improving production yields. The project also aimed to build a dedicated database for industrial tomatoes, enabling better future strategic decisions and to correlate field parameters with the quality of the final processed product. Finally, a crucial objective was the development of robust predictive models for harvest timing and the creation of an intuitive digital platform for real-time crop parameter monitoring, which would enhance both traceability and quality control.

Key Results for Industrial Tomatoes

The project successfully developed and validated a novel methodology utilizing portable NIRS technology specifically tailored for industrial tomatoes. Samples were systematically collected throughout various stages of the tomato growing cycle, with key indicators such as Brix (soluble solids content), acidity, lycopene, and texture (firmness) being meticulously measured. Observations throughout the season revealed a progressive increase in lycopene concentration, a clear sign of advancing fruit ripening, while firmness showed a notable decrease due to cell wall degradation. Soluble solids (°Brix) exhibited a slight upward trend. Crucially, lycopene content and texture (firmness) demonstrated the strongest correlation at harvest time, establishing them as highly reliable indicators for predicting optimal harvest. This is particularly significant as lycopene directly impacts color and antioxidant properties, while texture is vital for firmness and overall sensory quality.

The predictive models developed for Brix, lycopene, and texture exhibited high predictive capacity, underscoring their potential for routine application in industrial settings. While Brix and texture models showed satisfactory validation with low mean deviation, there’s acknowledgment that acidity and lycopene models indicated areas for further refinement in this specific instance. A key finding was that these predictive harvest models allow for a dynamic quality profile of tomatoes, facilitating both agronomic and commercial decision-making throughout the production cycle. Harvesting at the ideal ripeness point ensures a higher concentration of soluble solids (°Brix). For processing, especially in the production of tomato paste or sauce, this translates directly into reduced time and energy needed for water evaporation, leading to substantial improvements in industrial efficiency, lower energy consumption, and a higher-quality final product with enhanced organoleptic characteristics and better yield per processed ton.

Implications for the Industrial Tomato Industry

The outcomes of the NIRCROP project bear profound implications for the processing tomato industry, promising a more efficient and sustainable future. The capacity to ensure differentiated product quality and guaranteed traceability significantly boosts market competitiveness. The adoption of non-destructive NIRS technology optimizes analysis processes, leading to substantial reductions in costs associated with traditional sampling and laboratory analysis. Real-time data coupled with predictive models enable optimized harvest planning, which in turn decreases operational costs and mitigates the need for expensive post-harvest corrective measures in the factory.

Furthermore, by facilitating harvesting at optimal ripeness, the raw material quality is inherently improved, resulting in superior final products in terms of taste, color (thanks to lycopene content), and overall consistency. This precision contributes to sustainability and energy savings, as higher soluble solids content directly translates into lower energy consumption during industrial processing. The project’s developed digital application (POC) represents a significant stride in digital transformation and decision support, allowing agricultural technicians and production managers to monitor plot data, variety, quality parameters, and even estimate remaining days until harvest. This digital tool provides real-time, georeferenced information, streamlining decision-making from the field to the factory and enhancing the entire supply chain. Finally, the system significantly improves traceability of plots and their production, reinforcing consumer confidence and ensuring adherence to stringent food safety regulations. In essence, the NIRCROP project offers a robust framework for a more data-driven, efficient, and ecologically mindful future for the industrial tomato sector, effectively bridging the gap between field conditions and industrial processing demands through advanced technology.

Source: https://observatorioagroalimentario.com/proyectos/GOR/nircrop/resultados