Plant-Based, High-Quality and Functional Italian-style Ice Cream by synergizing Seasonality, Circular Economy, and Artificial Intelligence

The artisanal ice cream sector is still largely empirical, fragmented, and poorly digitalized.
Major gaps concern:

• limited predictive control of rheology–microstructure–sensory relationships;
• short texture shelf-life (ice recrystallization);
• lack of AI-assisted process monitoring;
• limited inclusion of plant-based functional ingredients;
• absence of safe ice cream solutions for dysphagic subjects;
• poor integration of circular economy principles;
• need for clean label formulations (without additives).

SusPlantIC4.5 addresses these gaps by combining plant-based clean-label formulation, clinical validation, advanced rheology/tribology, IoT sensors, and machine learning for predictive process control.

The project integrates:

• Ingredient valorization (seasonal plants, by-products)
• Functional formulation design (clean-label, probiotic, dysphagia-oriented)
• Physical characterization (thermal, rheological, tribological)
• Clinical and microbiota validation
• Sensor integration in batch and continuous freezers
• AI model development (ML-based predictive models)
• Digital platform development for real-time decision support
• Scale-up from lab to industrial level (TRL 5–7)

Work Packages Involved

• WP1 – Project Management and Coordination
  Administrative, financial, ethical and technical coordination.
• WP2 – Participatory Innovation & Stakeholder Engagement
  Creation of the Participatory Innovation Team (PIT), public engagement, co-design with industrial partners.
• WP3 – Functional Ingredient Development & Health Validation
  Recovery and characterization of plant-based ingredients; microbiota studies; probiotic validation; clinical and dysphagia-oriented assessment.
• WP4 – AI Model Development
  Development and validation of machine learning models to predict technological and quality properties.
• WP5 – Multisensory Monitoring & Process Digitalization
  Sensor integration (temperature, conductivity, mechanical stress), data acquisition, TRL progression (5→7).
• WP6 – Scale-up & Industrial Validation
  Validation in batch and continuous systems; artisanal and industrial scale implementation; clinical swallowing safety trials.
• WP7 – Technology Transfer & Exploitation
  Transfer of validated AI-assisted digital platform; industrial uptake; valorization of results; preparation for engineering, scale-up and commercialization.
• WP8 – Communication, Dissemination & Public Engagement
  Scientific publications, stakeholder communication, institutional endorsement, open science dissemination.

Tasks Involved

• Development of clean-label plant-based recipes
• Instrumental characterization (thermal, rheology, tribology, microstructure)
• Polyphenol and antioxidant quantification
• In vitro microbiota simulations (INFOGEST protocol)
• Probiotic survival studies under freeze–thaw cycles
• Sensory analysis (400+ healthy subjects; 70 dysphagic patients)
• Clinical swallowing safety assessment
• Installation of wired and wireless sensors (temperature, conductivity, shear)
• RFID feasibility study for harsh environments
• Development and training of multivariate ML models
• Creation of modular AI-driven digital platform
• Industrial validation in batch and continuous plants

• Development of clean-label, plant-based functional ice creams
• Demonstrated prebiotic and probiotic compatibility
• Identification of physical drivers of sensory liking and swallowing comfort
• Clinical validation for dysphagic subjects
• Definition of rheological and tribological thresholds for safety
• Digitalization chain implemented (sensor-to-ML integration)
• Predictive ML models validated
• TRL advancement from 5 to 7
• Software platform enabling real-time artisanal decision support
• Established Participatory Innovation Team (PIT) with industrial stakeholders