A non destructive approach for the determination of quality and safety parameters of agri-food products was developed. The main objective is the elaboration of reliable methods that could improve the efficiency, the quality and the safety of different processes in the food supply chain. The focus is put on these main topics: quality aspects (harvesting, variety identification), process control (harvesting and drying) and safety aspects (food contaminants). Different spectroscopic techniques are involved (Near Infrared spectroscopy, Ultra Violet and Visible spectroscopy, Fluorescence spectroscopy). Special attention is given to the mathematical and statistical treatment of data: predictive models are elaborated applying on raw data chemometric treatment. For every dataset, different pre-treatments are tested and performances are compared. Multivariate analysis is applied to obtain chemometric model from raw data, that will describe analyzed parameters and processes. Selected models are tested in a following working step aiming to verify the feasibility of the method on unknown samples.

Instrumental methods for quality and safety control in agro-food products” / Bertone, Elisa. - (2013).

Instrumental methods for quality and safety control in agro-food products”

BERTONE, ELISA
2013

Abstract

A non destructive approach for the determination of quality and safety parameters of agri-food products was developed. The main objective is the elaboration of reliable methods that could improve the efficiency, the quality and the safety of different processes in the food supply chain. The focus is put on these main topics: quality aspects (harvesting, variety identification), process control (harvesting and drying) and safety aspects (food contaminants). Different spectroscopic techniques are involved (Near Infrared spectroscopy, Ultra Violet and Visible spectroscopy, Fluorescence spectroscopy). Special attention is given to the mathematical and statistical treatment of data: predictive models are elaborated applying on raw data chemometric treatment. For every dataset, different pre-treatments are tested and performances are compared. Multivariate analysis is applied to obtain chemometric model from raw data, that will describe analyzed parameters and processes. Selected models are tested in a following working step aiming to verify the feasibility of the method on unknown samples.
2013
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2518560
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