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DEVELOPMENT OF PREDICTIVE MODELS FOR QUALITY CONTROL OF CARROTS DURING DRYING

Chiara, Di Pietro; Riccardo, Massantini and Roberto, Moscetti (2016) DEVELOPMENT OF PREDICTIVE MODELS FOR QUALITY CONTROL OF CARROTS DURING DRYING. Masters thesis, University of Tuscia (Italy) , Department for Innovation in Biological, Agro-food and Forest systems. . [Unpublished]

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Summary

This thesis research project is aimed at setting up prediction models based on NIR spectroscopy, for quality control of organic carrot discs (Daucus carota L., var. Romance) during hot-air drying process (horizontal flow) up to 8 h. Hot-water blanching was tested at 95°C for 1.5 min, as pre-treatment to control the occurrence of enzymatic browning during drying. Hot-water blanching had a positive impact on the appearance of the carrot discs.
PLS regression showed good performances for the prediction of aw (RMSE = 0.04; R2 = 0.96), moisture (RMSE = 0.04; R2 = 0.98), SSC (RMSE = 4.32-4.40 °Brix; R2 =0.88), carotenoids (RMSE = 21.75-23.10; R2 = 0.96) and changes in color (RMSE = 1.40-1.46; R2 = 0.85-0.86) during drying. Also PLSDA classification showed very good metrics (total accuracy 92.38%) in recognising 3-drying steps, both for control and hot-water blanched samples. Features selection by iPLS and iPLSDA algorithms showed results better/equal than models based on full spectrum. For these results, the implementation of low-cost NIR sensors on drier device, seems feasible.


EPrint Type:Thesis
Keywords:carrot, NIR, drying, prediction models, PLS, PLS-DA
Subjects:"Organics" in general
Food systems
Research affiliation: European Union > CORE Organic Plus > SusOrganic
Italy > Univ. Tuscia
Deposited By: Moscetti, Ass. Prof. Roberto
ID Code:34384
Deposited On:06 Feb 2019 08:46
Last Modified:06 Feb 2019 08:46
Document Language:English
Status:Unpublished
Refereed:Peer-reviewed and accepted

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