Non-destructive assessment of kiwifruit physico-chemical parameters to optimise the osmotic dehydration process: A study on FT-NIR spectroscopy

Non-destructive rapid method based on FT-NIR spectroscopy is assessed to predict the processing response of raw materials at different ripening stages. During osmotic dehydration (61.5% sucrose solution, 5 h) ripe and unripe kiwifruits were analysed with FT-NIR spectroscopy and the most representati...

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Bibliographic Details
Authors: Santagapita, Patricio Roman, Tylewicz, Urszula, Panarese, Valentina, Rocculi, Pietro, Dalla Rosa, Marco
Format: article
Status:Published version
Publication Date:2016
Country:Argentina
Institution:Consejo Nacional de Investigaciones Científicas y Técnicas
Repository:CONICET Digital (CONICET)
Language:English
OAI Identifier:oai:ri.conicet.gov.ar:11336/59495
Online Access:http://hdl.handle.net/11336/59495
Access Level:Open access
Keyword:Kiwifruit
Nir Spectroscopy
Non-Destructive Techniques
Osmotic Dehydration
Ripening Level
https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
Description
Summary:Non-destructive rapid method based on FT-NIR spectroscopy is assessed to predict the processing response of raw materials at different ripening stages. During osmotic dehydration (61.5% sucrose solution, 5 h) ripe and unripe kiwifruits were analysed with FT-NIR spectroscopy and the most representative physico-chemical parameters to osmotic dehydration (dry matter, soluble solids content, water self-diffusion coefficient and firmness) were assessed by destructive measurements. Predictive models were successfully built by means of partial least square regression (PLSR) analysis (R2 > 0.772, test set validations) for all the four parameters destructively measured. The application of vector normalisation pre-processing was critical to eliminate spectral information that did not relate to the OD process. FT-NIR spectroscopy can successfully predict the evolution of kiwifruit physico-chemical parameters during osmotic dehydration. Thus it can be used as a tool to tune online the process parameters (e.g. time and temperature) to obtain a standardised final product starting from non-homogeneous raw materials.