1,720,996 research outputs found
LARVA Anisakis IN Sepia officinalis DEL MEDITERRANEO
No full textThe Authors report, for the first time, thepresence of an Anisakis larva in one specimenof Sepia officinalis, describing thecharacteristics of parasitic localization coexisting,moreover, with an Aggregata sp. infection. The AA conclude with some sanitaryand inspective considerations[...
PHYSICO-CHEMICAL AND BIOCHEMICAL MODIFICATIONS OF Mytilus galloprovincialis AFTER HARVESTING
No full textApplication of an interspecific competition model to predict the growth of Aeromonas hydrophyla on fish surfaces during refrigerated storage (Anwendung eines Konkurrenzmodells zwischen zwei Spezies zur Vorhersage des Wachstums von Aeromonas hydrophila auf Fischoberflächen während der Kühlphase)
Full text linkThe growth of Aeromonas hydrophila and the aerobic mesophilic plate count (APC) on gilthead seabream surfaces was evaluated during refrigerated storage (21 days). The related growth curves were compared with those obtained by a conventional third order predictive model obtaining a low agreement between observed and predicted data (Root Mean Squared Error = 1.77 for Aeromonas hydrophila and 0.64 for APC).The Lotka-Volterra interspecific competition model was used in order to calculate the degree of interaction between the two bacterial populations (beta_{Ah/APC} and beta_{APC/Ah}, respectively, the interspecific competition coefficients of APC on Aeromonas hydrophila and vice-versa). Afterwards, the Lotka-Volterra equations were applied as tertiary predictive model, taking into account, simultaneously, the environmental fluctuations and the bacterial interspecific competition. This approach allowed to obtain a best fitting to the observed mean growth curves with a Root Mean Squared Error of 0.09 for Aeromonas hydrophila and 0.28 for APC. Finally, some considerations about the necessary use of competitive models in the context of the new trends in predictive microbiology were taken.Das Wachstum von Aeromonas hydrophila sowie die aerobe mesophile Gesamtkeimzahl auf der Oberfläche von Seebrassen wurden während der Kühlphase (21 Tage) ausgewertet. Die verwandten Wachstumskurven wurden mit solchen verglichen, die durch ein konventionelles Vorhersagemodell dritter Ordnung ermittelt wurden. Letztere zeigten eine geringe Übereinstimmung zwischen vorhergesagten und beobachteten Daten (Standardabweichung = 1,77 für Aeromonas hydrophila und 0,64 für APC). Das Lotka-Volterra Konkurrenzmodell zwischen zwei Spezies wurde zur Berechnung des Grades der Interaktion zwischen den beiden Bakterienpopulationen benutzt (mit den Konkurrenzkoeffizienten für APC gegenüber Aeromonas hydrophila und umgekehrt beta_{Ah/APC} bzw. beta_{APC/Ah}). Danach wurden die Lotka-Volterra Gleichungen als tertiäres Vorhersagemodell angewandt,wobei gleichzeitig Umwelteinflüsse und die Konkurrenz zwischen den Bakterienspezies berücksichtigt wurden.Dieser Ansatz erlaubte einen Fit an die beobachteten mittleren Wachstumskurven mit einer Standardabweichung von 0,25 für Aeromonas hydrophila und 0,28 für APC. Zuletzt folgen einige Betrachtungen zur Anwendung von Konkurrenzmodellen im Kontext neuer Entwicklungen zur vorhersagenden Mikrobiologie
A new approach to modelling the shelf life of Gilthead seabream (Sparus aurata)
Full text linkA total of 217 Gilthead seabreams were subdivided in four groups, according to four different storage conditions. All fish were evaluated by both Quality Index Method (QIM) and microbiological analysis, sampling skin, gills and flesh, separately. A QIM score predictive system was set by modelling the growth of microflora of skin, gills and flesh and coupling these predictions to each related partial QIM score
(QIMSkin, QIMGills, QIMFlesh). The expression of QIM score as a function of bacterial behaviour was carried out by the employment of two coefficients. The predicted mean bacterial concentrations corresponding to the QIM score at 14 days were always near to Log 8 CFU g^{ -1} in the case of 'S' (skin) and 'G' (gills) series. Moreover, predicted QIM scores were in a good agreement with observed data, reproducing the observed mean time of rejection as well as the bacterial spoilage level (Log 8 CFU g^{ -1}), for all kinds of storage condition
A stochastic interspecific competition model to predict the behaviour of Listeria monocytogenes in the fermentation process of a traditional Sicilian salami
No full textThe present article discusses the use of modified Lotka–Volterra equations in order to stochastically simulate the behaviour of Listeria monocytogenes and lactic acid bacteria (LAB) during the fermentation period (168 h) of a typical Sicilian salami. For this purpose, the differential equation system is set considering temperature (T), pH, water activity (aw) as stochastic variables. Each of them is governed by dynamics that involve a deterministic linear decrease as a function of the time t and an ‘‘additive noise’’ term which instantaneously mimics the fluctuations of T, pH and aw. The choice of a suitable parameter accounting for the interaction of LAB on L. monocytogenes as well as the introduction of appropriate noise levels allows to match the observed data, both for the mean growth curves and for the probability distribution of L. monocytogenes concentration at 168 h
PATOLOGIA DA PROTOZOI DEL GENERE Aggregata E BIOMETRIA in Sepia officinalis
No full textA research on Aggregata sp. infection inSepia officinalis and the influence of parasitosison biometrics was carried out. Parasiteswere found in the 100% of samples(gills 96.7%, caeca 90%, intestina 43.3%).The frequency and gravity of infection werenot related to mantel length, weight andthickness. Finally, potential implications ofinfection on cephalopods quality were discussed.[...
Echinophallus wageneri (Monticelli, 1890) and Amphycotile heteropleura (Diesing, 1850) (Pseudophyllidea: Echinophallidae) signalling in Centrolophus niger (Gmelin, 1788)
No full textStochastic model for a biological complex system: analysis of the bacterial growth in food products
No full textThe Physics of Complex Systems has recently taken a more and more important role in the description of natural systems because of the interactions, both deterministic and noisy, between such systems and the environment. In particular the noise plays a relevant role in biological systems, whose dynamics is strongly influenced by environmental variables subject to random fluctuations. In this work a stochastic model is exploited to reproduce the growth of bacteria in food of animal origin. Specifically the dynamics of a bacterial species, Listeria monocytogenes, is analyzed in the presence of lactic acid bacteria (LAB) during the period of the fermentation of meat products. The model, based on a generalization of the Lotka-Volterra equations in the presence of noise sources, takes into account the random fluctuations of physical and chemical variables such as temperature, pH and activity water, which are treated as stochastic variables. The presence in the model of appropriate levels of noise allows to obtain theoretical results in a good agreement with experimental data
Study on the application of an interspecific competition model for the prediction of microflora behaviour during the fermentation process of S. Angelo PGI salami
No full textThe use of predictive microbiology models able to evaluate bacterial behaviour as a function of environmental conditions and, at the same time, of natural microflora competition was considered by several authors with different approaches. Some authors modelled bacterial competition as a function of metabolic product with particular regard to lactic acid and modelled interspecific bacterial competition introducing a term into a conventional primary predictive model, which gives account for the interaction between two populations, so that they inhibit each other to the same extent that they inhibit their own growth
Impiego di un modello predittivo per la microflora del salame S. Angelo in corso di asciugature
No full textThe authors carried out a study in order to apply an interspecific competition model to predict the microflora behaviour of S.Angelo IGP salami during the ripening. They consider 3 bacterial population (Lactic Acid Bacteria, Enterobacteria and Listeria monocytogenes – LAB, Ent and Lmo) using the observed curves obtained in a previous work as validation. The model applied setting to 0 all interaction terms does not fit the observed curves while the introduction of 3 interaction terms (betaLmo/LAB = 0.65; betaEnt/LAB = 0.4; betaLmo/Ent = 0.18) produce a good agreement with the observed behaviour of all populations
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