257 research outputs found
Praedicere Possumus, un’applicazione web per la microbiologia predittiva finalizzata al controllo della salubrità degli alimenti
No full textC039 - 24
Praedicere Possumus, un’applicazione web per la
microbiologia predittiva finalizzata al controllo della
salubrità degli alimenti
Mara Lucia Stecchini,1* Pierluigi Polese,2 Manuela Del Torre1
1Dipartimento di Scienze Agroalimentari, Ambientali e Animali, Università
degli Studi di Udine, Udine; 2Dipartimento Politecnico di Ingegneria e
Architettura, Università degli Studi di Udine, Udine, Italia
*[email protected]
La microbiologia predittiva rappresenta una disciplina ormai riconosciuta
a livello scientifico internazionale. Ciò le ha consentito di
essere considerata, anche nella normativa comunitaria, un valido
strumento a supporto delle garanzie di sicurezza alimentare.
Tuttavia, per rendere maggiormente fruibili le competenze modellistiche,
con evidenti ricadute in termini di ampliamento degli interventi
e di riduzione dei costi, è necessario che la microbiologia predittiva
si converta in procedure semplificate ed organizzate sulle
esigenze degli utenti. Ci si è quindi proposti di sviluppare un’applicazione
WEB di ausilio per i produttori e per gli organi preposti
all’attività di controllo e che sia in grado di corrispondere ad una
esigenza fondamentale del consumatore che richiede alimenti di
comprovata salubrità. L’applicazione in questione, Predicere
Possumus (PP), presente sul sito WEB dell’Ateneo di Udine, contiene
una selezione di modelli che ruotano attorno ad un modello
growth/no growth (Polese et al., 2011) ed è organizzata in moduli
distinti, uno generico, uno specifico ed uno di processo. Il primo
modulo fornisce come output la probabilità (P), la probabilità
tempo-dipendente (Pt) (Polese et al., 2017) e quantifica la crescita
e/o la devitalizzazione di 10 microrganismi patogeni in funzione dei
principali fattori ambientali. Nel secondo modulo possono essere
introdotte informazioni aggiuntive in termini di acidi organici, additivi,
ecc., e l’applicazione restituisce, per ciascun patogeno, oltre
alle informazioni di cui sopra, anche l’opzione (f) che quantifica il
contributo frazionario di ciascun ostacolo alla probabilità di crescita.
Il terzo modulo consente di descrivere un processo attraverso le
fasi di cui è composto, che possono essere modellate con le modalità
prima descritte (Polese et al., 2014).
L’adozione dell’applicazione WEB, che fornisce risposte basate su
elementi oggettivi e confrontabili, si traduce in vantaggi sia per i
produttori, sia per gli organi di controllo, consentendo ai primi di
orientare possibili interventi correttivi, ed ai secondi di avvalersi di
un metodo scientifico per una rapida caratterizzazione dei prodotti
alimentari in base al rischio.
Bibliografia
Polese P, Del Torre M, Spaziani M, Stecchini ML, 2011. A simplified approach
for modelling the bacterial growth/no growth boundary. Food Microbiol
28:384-91.
Polese P, Del Torre M, Venir E, Stecchini ML, 2014. A simplified modelling
approach established to determine the Listeria monocytogenes behaviour
during processing and storage of a traditional (Italian) ready-toeat
food in accordance with the European Commission Regulation N
2073/2005. Food Control 36:166-73.
Polese P, Del Torre M, Stecchini ML, 2017. Prediction of the impact of processing
critical conditions for Listeria monocytogenes growth in artisanal dryfermented
sausages (salami) through a growth/no growth model applicable
to time-dependent conditions. Food Control 75:167-80
A further extension of the evergreen Gamma concept for modelling the non-thermal inactivation of a variety of foodborne pathogens
No full textAbstract Content: Consumer demand for safe and extended storage-life foods has encourage the industry
to market products at conditions close to the growth/no-growth boundary of each pathogen of concern. It
is therefore of importance to estimate if the pathogen growth is likely (P >0.1) or, vice versa, if the pathogen
will die over time (P≤0.1; Polese et al. 2016). Both growth and inactivation behaviours are dependent on a
variety of environmental factors, with temperature introducing the greatest variation in growth and death
parameters. The Gamma concept has been successfully applied for non-thermal inactivation of Escherichia
coli (Le Marc et al., 2011), Listeria (Coroller et al., 2012) and Salmonella, the latter also in dynamic process
conditions (Coroller et al., 2015). In the attempt to support small producers in the safe management of
foods, this work presents a non-thermal inactivation model, simulated through a conservative Gamma-like
model, to be included in the simplified web-based application termed Praedicere Possumus. The kinetics of
inactivation was predicted with the model of McQuestin et al., (2009) and the estimated bacterial behaviour
was then modelled as a function of the specific sensitivity of each pathogen to temperature, pH and aw,
and as a function of the two actual later explanatory factors. Datasets of S. enteritidis, L. monocytogenes
and E. coli O157:H7 behaviours were collected from published data (Gabriel and Nakano, 2010) and used
to evaluate the performance of the model. The correct inactivation prediction was 89%, whereas incorrect
predictions were only fail-dangerous, which reflected the conservative performance of the non-thermal
inactivation model. This model, allowing the quantification of a pathogen decrease for a given formulation or
storage condition, could be a further element in the Praedicere Possumus aimed to assist users in attaining
the desirable food safety level
A web-based application customized to food safety requirements of small-sized enterprises
No full textToday, European legislation considers predictive microbiology as a tool to define food safety. People in the food industry, including those in small-sized enterprises, even if they are unable to avail themselves of specific knowledge, are encouraged to use the same approach. To extend a bridge between both sides, a user-friendly, simplified, web-based application (Praedicere Possumus, PP) has been developed. Through this application, users have access to different modules, which apply a set of models, some of them already validated and considered reliable for determining the compliance of a food product with EU safety criteria(1). In particular, the PP applies the growth/no-growth boundary model(2), coupled with a three-phase linear growth model and thermal/non-thermal models. Two complementary functionalities, such as the fractional contribution of each inhibitory factor to growth probability (f) and the time evolution of the growth probability (P-t) have also been included(3). The PP application is expected to assist users in defining processing and storage conditions to attain a desirable food safety level and to support food safety authorities in demonstrating compliance with legislation
Quality principles for cultural Web sites: a Handbook
No full textprinted and on-line versions, co-author with Eelco Bruinsma, Christophe Dessaux, Ciaran Clissman, Jean-Pierre Dalbéra, David Dawson, Isabelle Dujacquier, Axel Ermert, Pierluigi Feliciati, Fedora Filippi, Muriel Foulonneau,
Antonella Fresa, Monika Hagedorn-Saupe, Annette Kelly, Brian Kelly, Daniel Malbert, Andrea Mulrenin, Stefan Rhode-Enslin, Marius Snyders, Gert Van Tittelboom, Frank von Hage
Efficient Cleavage of Carboxylic tert-Butyl and 1-Adamantyl Esters, and N-Boc-Amines using H2SO4 in CH2Cl2
No full textA new procedure for the deprotection of carboxylic tert-butyl and 1-adamantyl esters, and N-Boc-amines using H2SO4 in
CH2Cl2 is described. The proposed method is simple, cheap, eco-friendly and represents a valid alternative to existing ones, with
special significance in large scale applications.
2005 Elsevier Ltd. All rights reserved
Thermodynamics of complex formation of silver(I), cadmium(II) and cobalt(II) with open-chain polyamines in dimethyl sulfoxide and molecular dioxygen binding to cobalt(II) complexes
No full textAn integrated simplified modelling approach established to fulfil safety requirements of ready-to-eat (RTE) products
No full textThe COM-Poisson process for stochastic modeling of osmotic inactivation dynamics of Listeria monocytogenes
No full textControlling harmful microorganisms, such as Listeria monocytogenes, can require
reliable inactivation steps, including those providing conditions (e.g., using high salt
content) in which the pathogen could be progressively inactivated. Exposure to osmotic
stress could result, however, in variation in the number of survivors, which needs to
be carefully considered through appropriate dispersion measures for its impact on
intervention practices. Variation in the experimental observations is due to uncertainty
and biological variability in the microbial response. The Poisson distribution is suitable
for modeling the variation of equi-dispersed count data when the naturally occurring
randomness in bacterial numbers it is assumed. However, violation of equi-dispersion
is quite often evident, leading to over-dispersion, i.e., non-randomness. This article
proposes a statistical modeling approach for describing variation in osmotic inactivation
of L. monocytogenes Scott A at different initial cell levels. The change of survivors over
inactivation time was described as an exponential function in both the Poisson and in the
Conway-Maxwell Poisson (COM-Poisson) processes, with the latter dealing with over
dispersion
through a dispersion parameter. This parameter was modeled to describe the
occurrence of non-randomness in the population distribution, even the one emerging
with the osmotic treatment. The results revealed that the contribution of randomness
to the total variance was dominant only on the lower-count survivors, while at higher
counts the non-randomness contribution to the variance was shown to increase the total
variance above the Poisson distribution. When the inactivation model was compared
with random numbers generated in computer simulation, a good concordance between
the experimental and the modeled data was obtained in the COM-Poisson process
- …
