10 Apr 2019

Please register for FF4Us 2019. Use of computer vision as process analytical technology (PAT) tool for food drying on Apr 10, 2019 1:00 PM CEST at:

Drying is an effective and viable preservation process and is among the oldest and most widespread of all postharvest operations. Drying significantly extends the shelf-life and nutritional quality of fruit, vegetables, spices and herbs as well as meat and fish. The drying process consists of three main interlinked steps that can be summarized as: (1) product formulation or treatment selection, (2) dehydration process and (3) quality and properties assessment. In the absence of sufficient moisture, microorganisms grow slowly and moisture-mediated reactions responsible for undesirable chemical changes do not function properly. Beyond extending shelf life, drying can substantially reduce storage and shipping costs by enabling storage at room temperature and reducing weight and packaging volume.
Drying technology varies from simple methods such as sun drying to more sophisticated techniques such as instant controlled pressure drop drying. Surprisingly, modern drying technology does not always produce the highest commodity quality or value. Drying is a relatively complex, dynamic, unsteady and nonlinear process that is affected by the properties of the wet material, the scale of production and compliance with regulations (e.g. European Organic Regulation), as well as operating and environmental conditions. Such factors can impact quality traits including colour, texture, size and shape as well as organoleptic, nutritional and functional properties and thus result in reduced consumer acceptance. Drying is one of the most energy-intensive processes in the food industry and potentially contributes to climate change as most dryers use fossil fuels.
In order to alleviate these issues, the goal of new drying technologies should be to simultaneously maintain product quality and value, maximize drying rate and minimize environmental impact. “Smart drying”, one of the newest and most promising of emerging drying techniques, involves the use of sensors, tools (e.g. emerging non-destructive technologies) and practices (e.g. monitor and control of quality and drying parameters and/or the conditions of the dryer, etc.) for enhancing drying efficiency. Moreover, smart drying can be cost-effective in both real-time monitoring of food quality and dynamic controlling of operating conditions through the entire drying process. Smart drying is a multi- and inter-disciplinary sector and its recent developments embrace the following R&D areas: artificial intelligence, biomimetic, computer vision, microwave/dielectric spectroscopy, hyper-/multispectral imaging, magnetic resonance imaging, ultrasound imaging, electrostatic sensing and control systems for the drying environment.
The webinar aims at giving an overview on new emerging computer vision technologies applied to proactively and non-destructively detect and monitor changes in quality parameters of food during drying. The webinar provides knowledge and information to encourage additional research to develop low-cost dynamic multi factorial process control strategies (based on a Quality by Design approach) using machine learning architectures to produce quality dried products while reducing the environmental impact of the drying processes.

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