Mirko, Grilli; Riccardo, Massantini and Roberto, Moscetti (2016) DEVELOPMENT OF PREDICTIVE MODELS FOR QUALITY CONTROL OF GALA APPLES 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 [Unpublished]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 apple wedges (Malus domestica B., var. Gala) during hot-air drying process (horizontal flow) up to 8 h. Hot-water and microwave blanching were both tested at 95°C for 5 min and 850 W for 45 sec, respectively, as pre-treatments to control the occurrence of enzymatic browning during drying. However, hot-water blanching had a negative impact on the appearance of the apple wedges, which were subjected to non-enzymatic discoloration (e.g. Maillard’s reaction).
PLS regression showed good performances for the prediction of aw (RMSE = 0.03-0.04; R2 = 0.97-0.98), moisture (RMSE = 0.04-0.05; R2 = 0.97-0.98), SSC (RMSE = 4.54-4.99 °Brix; R2 = 0.96-0.97) and changes in chroma (RMSE = 2.31-2.75; R2 = 0.81-0.86) during drying. Also PLSDA classification showed very good metrics (total accuracy > 95%) in recognising 3-drying steps, both for control and microwave-treated 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 |
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Thesis Type: | Masters |
Keywords: | apple, NIR, drying, prediction models, PLS, PLSDA |
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: | 34386 |
Deposited On: | 06 Feb 2019 08:53 |
Last Modified: | 06 Feb 2019 08:53 |
Document Language: | English |
Status: | Unpublished |
Refereed: | Peer-reviewed and accepted |
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