Overview
This service validates the performance of multivariate predictive models that utilise nondestructive spectral sensor data, such as NIR and hyperspectral imaging. Through statistical and chemometric analysis, the service assesses model accuracy and provides recommendations for optimization. Clients benefit from access to a comprehensive software suite dedicated to chemometrics and statistical studies, as well as options for database transfer to adapt models across devices. The service also includes access to a large agri-food sample bank for model evaluation and refinement.
More about the service
How can the service help you?
By evaluating the predictive power of spectral models, this service aids companies in ensuring the accuracy of agrifood quality and safety assessments. It supports model updates to account for changes in production conditions or instrumentation, allowing clients to maintain reliable model performance over time. Additionally, database transfer options enhance model usability across different sensor platforms.
How the service will be delivered
The service is conducted remotely with digital support for database transfers and model analysis. Deliverables include performance reports, recommendations for model improvements, and database adaptation protocols. Clients may access chemometric software and sample bank data for targeted studies.
Service customisation
Customisation includes specifying predictive metrics, choosing relevant agri-food samples, and tailored chemometric or statistical analyses. Clients may also request instrumental cloning protocols to replicate databases for new sensors.
Sector
Food processing
Horticulture
Tree Crops
Viticulture
Test type
Software or AI model
Other
Type of service
AI model training
Collection of test data
Conformity assessment
Data analysis
People training
Performance evaluation
Country of delivery
Country of delivery:
Service provider(s):
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University of Cordoba (UCO)
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