FruitMeasureApp: the AI-powered app developed by IRTA and UdL to estimate apple size using a mobile phone

The digitalization of pre-harvest agronomic tasks continues to provide tools for optimizing decision-making in the fruit sector. Against this backdrop, the Institute of Agrifood Research and Technology (IRTA), in collaboration with the University of Lleida (UdL), has developed FruitMeasureApp a mobile application based on computer vision algorithms and artificial intelligence designed to automate fruit sizing and growth monitoring directly in the orchard.

Automated size estimation and offline operation

Traditional methods for monitoring fruit size in the orchard require manual measurement using calipers or ring gauges—a labor-intensive process prone to statistical bias. FruitMeasureApp replaces this analog process with digital image capture:

• Real-time multi-fruit detection: The tool processes individual images using deep learning models capable of simultaneously identifying and segmenting multiple fruits within a cluster or the foliage.
• Integration of a 3D-printed reference mount: The app uses a 3D-printed mount attached to the mobile device to standardize the capture distance and enable precise metric calculation of the diameter.
• Local processing without connectivity: The computer vision algorithm runs directly on the smartphone (offline), facilitating use in orchard plots or agricultural areas lacking network coverage.

The app, the 3D-printable mount model, and user documentation are available free of charge, making this technology accessible for field measurements.

Optimizing Agronomic Management and Harvest Planning

Mass, digitized capture of biometric data enables the generation of precise growth curves during the fruit development phase. This information is crucial for planning thinning strategies, optimizing irrigation scheduling, and forecasting the size distribution expected at harvest.

Furthermore, having objective yield estimates available before the fruit reaches the packing house facilitates storage logistics, commercial grading, and cold chain management, thereby improving supply predictability for distributors.

This tool was the focus of a session held on September 10 at the University of Lleida, featuring specialists from IRTA and UdL/Agrotecnio. The program included an explanation of how the tool works, a comparison of use cases against other methodologies, and a practical field workshop.

This work was part of a validation and prototyping demonstration activity co-financed by the European Union under the 2023–2027 CAP Strategic Plan.

More information