DigiNut
Scheda del progetto
Università Cattolica del Sacro Cuore
Professor Daniele Rama
The hazel tree is the fourth most widely cultivated tree species in Italy, and hazelnuts are a strategic raw material for the Italian and European confectionery industries, which import about 70% of production from outside the EU. However, the hazelnut sector lacks decision support tools for agronomic and industrial practices. This proposal aims to create a digital twin model that simulates the growth of the plant in 3D throughout the season and assesses the impact of various cultivation operations on productivity. Additionally, the tool will provide information on the shelf life of hazelnuts and alternative processing methods for utilizing batches with low shelf life. It will also integrate the economic assessment of the techniques used, allowing stakeholders in the supply chain to evaluate the impact of their choices. The model is based on a Functional Structural Plant Model (FSPM) currently applied to one of the most widely cultivated hazelnut varieties globally, with plans to include other varieties and cultivation techniques, as well as a predictive shelf life model. Results will be validated using data collected from experimental fields at UCSC in Piacenza. The project, conducted by a multidisciplinary team from UCSC, will have complementary components with a proposal presented by the University of Pavia (DEMETRA).
Contacts:
Contact person
Sergio Tombesi
Email
sergio.tombesi@unicatt.it
Tel
+39 0523 599221
The hazelnut sector and its processing face a series of challenges related to changing climatic and socio-economic conditions. These challenges require the adaptation of cultivation techniques and conservation strategies based on increasingly variable seasonal trends and the costs of production factors such as fertilizers and energy. The project's goal is to create an integrated model that allows for simulating the plant's growth based on the environment and technical conditions in which the hazelnut develops, predicting the shelf life of product batches, and identifying techniques to extend this duration. Additionally, it will evaluate the costs and benefits of each technique to facilitate an accurate assessment of its applicability.
Currently, the hazelnut sector and the processing of hazelnuts lack digital twin models or decision support systems. The project aims to fill this gap with a supply chain approach that integrates both production and processing, also evaluating the economic sustainability throughout the entire chain. This will enable technicians to assess different management and processing techniques, with the goal of increasing the economic efficiency of the system. The project is also twinned with the DEMETRA project at the University of Pavia, which is developing models based on virtual reality to integrate the information and outputs from the model generated by the current project.
The tool will have a significant impact on farmers, field technicians, and companies of all sizes. Considering that hazelnut cultivation is widespread across four continents and covers approximately 900,000 hectares worldwide, the transferability of the tool will be facilitated by the mechanistic models on which it is based. During the transformation phase, the tool can be used by medium and large companies to manage different types of batches throughout the year. In particular, it will allow medium-sized companies to utilize raw material batches with greater precision, reducing waste and the withdrawal of products that have reached the end of their shelf life. This functionality is crucial, as hazelnuts are among the most expensive raw materials and are key to the quality of the finished product. Proper management of hazelnuts is essential for positioning the product in the correct market segment and defining the profit margin.