eprintid: 34390
rev_number: 12
eprint_status: archive
userid: 45668
dir: disk0/00/03/43/90
datestamp: 2019-02-06 09:21:04
lastmod: 2019-02-06 09:21:04
status_changed: 2019-02-06 09:21:04
type: conference_item
metadata_visibility: show
doclang: en
projects: SusOrganic
projects: it-uni-tuscia
confdates: June 7 to 9, 2017
conference: SECOND NORDIC BALTIC DRYING CONFERENCE
confloc: Hamburg, Germany
refereed: yes
budget: 0
publicfulltext: TRUE
presentationtype: workshop
creators_name: Roberto, Moscetti
creators_name: Riccardo, Massantini
creators_id: massanti@unitus.it
creators_id: rmoscetti@unitus.it
creators_orcid: 0000-0002-2034-8536
creators_orcid: 0000-0001-6517-3162
title: Smart drying: use of sensors and machine learning for the supervision and control of drying processes
ispublished: pub
subjects: 1organics
subjects: 7food
keywords: chemometrics, artificial intelligence, deep learning
abstract: 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&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.
date: 2017-06
date_type: published
institution: University of Tuscia (Italy)
department: Department for Innovation in Biological, Agro-food and Forest systems
full_text_status: public
thesis_type: masters
contact_email: rmoscetti@unitus.it
conf_subm: not_subm
fp7_project: no
access_rights: info:eu-repo/semantics/openAccess
citation:    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.          
document_url: /id/eprint/34390/1/Document_8.pdf