Data/hora: 12/06/2024 13:55:09

Provedor de dados: 	21	
País: 	Germany	
Título: 	Smart drying: use of sensors and machine learning for the supervision and control of drying processes	
Autores: 	Roberto, Moscetti; Riccardo, Massantini.	
Data: 	2017-06	
Ano: 	2017	
Palavras-chave: 	"Organics" in general; Food systems.	
Resumo: 	Globalization of  market entails the availability of  produces  regardless their production date, pursued through innovation in products and processes to obtain meat, fish and fruit vegetables with improved shelf-life, organoleptic quality, nutritional value, safety and healthiness during the  whole  agrofood  chain.  Consequently,  market  value  of  perishable  commodity  mainly depends  on  the  preservation  method  used  to  guarantee  food  stability  and  thus  to  delay physicochemical,  biochemical  and  microbiological  spoilage.  Among  processing  methods, drying is one of the oldest, typical, effective and viable preservation process throughout the world,  which  allow  to  prevent  food  spoilage  and  decay  through  moisture  removal.  It  is  a relatively complex, dynamic, unsteady and nonlinear process that, when not optimized, may be responsible  for  (1)  quality  degradation  of  food  and  (2)  energy wastage.  Consequently,  new drying technologies must be designed to assure valuable products at the lowest carbon footprint. Among emerging drying technologies, smart drying is one of the newest and promising ones. It has potential to guarantee high-value end products, while enhancing drying efficiency, by implementing innovative and reliable sensors, resources, tools and practices. Moreover, smart drying  can be  cost-effective in both  real-time  monitoring of  foodstuffs  quality  and  dynamic controlling of operating conditions along the whole drying process. Smart drying is a multi- and inter-disciplinary sector and its recent developments embrace the following R&amp;D areas: artificial intelligence, biomimetic, computer vision, microwave/dielectric spectroscopy, visible and  near-infrared  spectroscopy,  hyper/multispectral  imaging,  magnetic  resonance  imaging, ultrasound imaging, electrostatic sensing and control system for the drying environment.	
Tipo: 	Conference paper, poster, etc.	
Idioma: 	Inglês	
Identificador: 	http://orgprints.org/34390/1/Document_8.pdf

Roberto, Moscetti and Riccardo, Massantini    (2017) Smart drying: use of sensors and machine learning for the supervision and control of drying processes.       Workshop at:   SECOND NORDIC BALTIC DRYING CONFERENCE, Hamburg, Germany, June 7 to 9, 2017.	
Relação: 	http://orgprints.org/34390/	
Formato: 	application/pdf	
Fonte: 	cc_by