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http://hdl.handle.net/2067/46072
Title: | Monitoring the hot-air drying process of organically grown apples (cv. Gala) using computer vision | Authors: | Raponi, Flavio Moscetti, Roberto Nallan Chakravartula, Swathi Sirisha Fidaleo, Marcello Massantini, Riccardo |
Journal: | BIOSYSTEMS ENGINEERING | Issue Date: | 2022 | Abstract: | The feasibility of using a computer-vision (CV) system embedded in a hot-air dryer for non-destructive and real-time monitoring of the drying behaviour of organic apples was investigated in the present study. Apple cylinders were subjected to anti-browning treatments with different dipping solutions (water as control, trehalose (4% w/v) or trehalose + ascorbic acid (4% w/v and 1% w/v)) and dipping pressures (atmospheric, 101.3 kPa and sub-atmospheric pressure, 50 kPa) followed by drying at 60 °C to a final dry basis moisture content of 0.18 g g−1. The CV system was used as an in-line process analytical technology (PAT) tool to capture images reflecting the physico-chemical changes during product drying coupled with in-line mass changes and off-line reference analyses. The spatial and colour changes from the image analysis described well the complex and non-homogenous nature of apple drying. The results of spatial changes allowed successful development of accurate linear prediction models for moisture content as a function of area shrinkage (on scaled variables) with excellent prediction capability (|BIAS| < 8.5 10−3, RMSE < 0.04, Adj-R2 ~ = 99%). Also, the CV system identified the differently pre-treated samples, particularly the dipping pressures as reflected by two linear models and their respective parameters. The obtained results demonstrate the versatile advantages of CV systems as an in-line tool for continuous, real-time monitoring of apples during drying. The insights from this study can provide a platform for applications of CV embedded ‘Smart dryers’ as an efficient monitoring and control system for industrial drying processes. |
URI: | http://hdl.handle.net/2067/46072 | ISSN: | 1537-5110 | DOI: | 10.1016/j.biosystemseng.2021.07.005 |
Appears in Collections: | A1. Articolo in rivista |
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1-s2.0-S1537511021001604-main.pdf | 1.42 MB | Adobe PDF | View/Open |
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