NIROLIVE Operational Group: Portable NIR technology and development of predictive models based on artificial intelligence for real-time quality control of olives and virgin olive oil

This result provides a portable device based on NIR technology for real-time analysis of olive and oil quality, both in the field and at the mill. It allows for the immediate acquisition of key parameters such as fat content, moisture, and other relevant indicators, without the need for laboratory testing or sample transport. The system combines a user-friendly interface with artificial intelligence models that automatically process and interpret measurements, making it easy to use by non-specialized personnel. In practice, farmers, technicians, and mill managers can make faster decisions regarding harvesting, processing, and batch classification, reducing costs and improving daily efficiency. Furthermore, it strengthens traceability, promotes more consistent evaluation criteria, and facilitates the integration of rapid analysis into the routine management of the value chain.

This result validates the portable NIR device using a representative set of olive and oil samples collected over several seasons under real-world production conditions. The measurements obtained are compared with reference analyses performed in a laboratory using standardized methods to ensure their accuracy, reliability, and repeatability. In practice, this validation allows farmers, cooperatives, and mill managers to confidently use the tool as an alternative to traditional methods. This reduces waiting times and analytical costs while maintaining accuracy, and improves harvest planning, processing control, and raw material management. It also facilitates the integration of the technology into daily operations and strengthens confidence in routine decision-making. Furthermore, it enhances traceability, promotes more consistent evaluation criteria, and facilitates the incorporation of rapid analysis into the routine management of the value chain.

This result develops predictive models based on real production data to estimate key olive and oil quality parameters, such as oil yield, moisture, acidity, and peroxide value. These models are integrated into the portable NIR device, allowing for the automatic interpretation of spectral measurements and the generation of immediate and understandable results. In practice, farmers and mill managers can access reliable indicators without the need for laboratory analysis or specialized knowledge, improving decision-making and batch classification. The system also helps optimize processing conditions and improve product homogeneity. Furthermore, the associated database allows for continuous improvement of the model and its adaptation to different harvests, varieties, and production environments. It also strengthens traceability, promotes more consistent evaluation criteria, and facilitates the integration of rapid analysis into the routine management of the value chain.

This outcome guarantees the transfer of the developed solution through demonstration days, training sessions, and technical materials tailored to the sector. These activities allow end users to understand how the system works and its application under real production conditions. In practice, farmers, technicians, and olive mill managers can learn to use the device, interpret its results, and integrate it into their daily processes. This reduces adoption barriers, improves technical skills, and fosters more confident decision-making. It also promotes knowledge sharing among the various stakeholders and facilitates the dissemination of the innovation, encouraging its application in different regions, cooperative environments, and production contexts within the sector. Furthermore, it strengthens traceability, promotes more consistent evaluation criteria, and facilitates the integration of rapid analysis into the routine management of the value chain.

This outcome aims to raise awareness of the project in its initial phase through communication efforts focused on presenting its objectives, methodology, and expected benefits for the sector. To this end, activities such as social media outreach, press releases, website updates, and participation in industry events are being carried out. In practice, this initial visibility allows farmers, cooperatives, technicians, and other stakeholders to understand the project's purpose and its potential impact on improving production processes. Furthermore, it generates interest from the outset, encourages the involvement of key stakeholders, and prepares the sector for the future adoption of the technology, reinforcing the project's transparency. It also strengthens traceability, promotes more consistent evaluation criteria, and facilitates the integration of rapid analysis into the routine management of the value chain.

This outcome ensures continuous communication of project progress through the regular dissemination of activities, milestones, and interim results via social media, websites, and specialized platforms. In practice, this communication allows farmers, technicians, and other stakeholders in the sector to follow the solution's evolution and progressively understand its application in real-world working conditions. Furthermore, it maintains interest and strengthens the involvement of stakeholders, fostering the creation of a community around the project. This strategy facilitates familiarization with the technology, reduces resistance to change, and prepares the sector for its adoption once the project is complete, maintaining ongoing communication with potential users. It also enhances traceability, promotes more consistent evaluation criteria, and facilitates the integration of rapid analysis into the routine management of the value chain. This also improves coordination among operators and reinforces confidence in its daily use.

This outcome disseminates the project's final results, including validated developments, practical guidance, and real-world use cases, through closing events, media outreach, and technical materials targeted at the sector. In practice, farmers, cooperatives, and olive mill managers can access applicable knowledge that improves decision-making, quality control, and operational efficiency. The availability of validated results facilitates the adoption of the solution and its replicability in different production contexts. This final phase maximizes the project's impact, strengthens confidence in the technology, and contributes to the competitiveness and sustainability of the olive oil sector. It also promotes greater visibility and effective transfer of the results obtained. Furthermore, it enhances traceability, fosters more consistent evaluation criteria, and facilitates the integration of rapid analysis into the routine management of the value chain.