ترغب بنشر مسار تعليمي؟ اضغط هنا

Modeling of Sensory Characteristics Based on the Growth of Food Spoilage Bacteria

199   0   0.0 ( 0 )
 نشر من قبل Davide Valenti
 تاريخ النشر 2016
  مجال البحث علم الأحياء فيزياء
والبحث باللغة English




اسأل ChatGPT حول البحث

During last years theoretical works shed new light and proposed new hypothesis on the mechanisms which regulate the time behaviour of biological populations in different natural systems. Despite of this, the role of environmental variables in ecological systems is still an open question. Filling this gap of knowledge is a crucial task for a deeper comprehension of the dynamics of biological populations in real ecosystems. In this work we study how the dynamics of food spoilage bacteria influences the sensory characteristics of fresh fish specimens. This topic is crucial for a better understanding of the role played by the bacterial growth on the organoleptic properties, and for the quality evaluation and risk assessment of food products. We therefore analyze the time behaviour, in fresh fish specimens, of sensory characteristics starting from the growth curves of two spoilage bacterial communities. The theoretical study, initially based on a deterministic model, exploits experimental temperature profiles. As a first step, a model of predictive microbiology is used to reproduce the experimental behaviour of the two bacterial populations. Afterwards, the theoretical bacterial growths are converted, through suitable differential equations, into sensory scores, based on the Quality Index Method (QIM), a scoring system for freshness and quality sensory estimation of fishery products. As a third step, the theoretical curves of QIM scores are compared with the experimental data obtained by sensory analysis. Finally, the differential equations for QIM scores are modified by adding terms of multiplicative white noise, which mimics the effects of uncertainty and variability in sensory analysis. A better agreement between experimental and theoretical QIM scores is observed, in some cases, in the presence of suitable values of noise intensity respect to the deterministic analysis.

قيم البحث

اقرأ أيضاً

Metabolism and evolution are closely connected: if a mutation incurs extra energetic costs for an organism, there is a baseline selective disadvantage that may or may not be compensated for by other adaptive effects. A long-standing, but to date unpr oven, hypothesis is that this disadvantage is equal to the fractional cost relative to the total resting metabolic expenditure. This hypothesis has found a recent resurgence as a powerful tool for quantitatively understanding the strength of selection among different classes of organisms. Our work explores the validity of the hypothesis from first principles through a generalized metabolic growth mode
83 - A. Pc{e}kalski 2007
We investigate in detail the model of a trophic web proposed by Amaral and Meyer [Phys. Rev. Lett. 82, 652 (1999)]. We focused on small-size systems that are relevant for real biological food webs and for which the fluctuations are playing an importa nt role. We show, using Monte Carlo simulations, that such webs can be non-viable, leading to extinction of all species in small and/or weakly coupled systems. Estimations of the extinction times and survival chances are also given. We show that before the extinction the fraction of highly-connected species (omnivores) is increasing. Viable food webs exhibit a pyramidal structure, where the density of occupied niches is higher at lower trophic levels, and moreover the occupations of adjacent levels are closely correlated. We also demonstrate that the distribution of the lengths of food chains has an exponential character and changes weakly with the parameters of the model. On the contrary, the distribution of avalanche sizes of the extinct species depends strongly on the connectedness of the web. For rather loosely connected systems we recover the power-law type of behavior with the same exponent as found in earlier studies, while for densely-connected webs the distribution is not of a power-law type.
408 - Dario A. Leon 2016
This thesis is aimed at studying mutations, understood as trajectories in the DNA configuration space. An evolutive model of mutations in terms of Levy flights is proposed. The parameters of the model are estimated by means of data from the Long-Term Evolution Experiment (LTEE) with {it E. Coli} bacteria. The results of simulations on competition of clones, mean fitness, etc are compared with experimental data. We discuss the qualitative analogy found between the bacterial mutator phenotype and the cancerous cells. The role of radiation as source of mutations is analyzed. We focus on the case of Radons decay in the lungs in breathing.
Bacteria and their bacteriophages are the most abundant, widespread and diverse groups of biological entities on the planet. In an attempt to understand how the interactions between bacteria, virulent phages and temperate phages might affect the dive rsity of these groups, we developed a novel stochastic network model for examining the co-evolution of these ecologies. In our approach, nodes represent whole species or strains of bacteria or phages, rather than individuals, with speciation and extinction modelled by duplication and removal of nodes. Phage-bacteria links represent host-parasite relationships and temperate-virulent phage links denote prophage-encoded resistance. The effect of horizontal transfer of genetic information between strains was also included in the dynamical rules. The observed networks evolved in a highly dynamic fashion but the ecosystems were prone to collapse (one or more entire groups going extinct). Diversity could be stably maintained in the model only if the probability of speciation was independent of the diversity. Such an effect could be achieved in real ecosystems if the speciation rate is primarily set by the availability of ecological niches.
Cancer cell population dynamics often exhibit remarkably replicable, universal laws despite their underlying heterogeneity. Mechanistic explanations of universal cell population growth remain partly unresolved to this day, whereby population feedback between the microscopic and mesoscopic configurations can lead to macroscopic growth laws. We here present a unification under density-dependent birth events via contact inhibition. We consider five classical tumor growth laws: exponential, generalized logistic, Gompertz, radial growth, and fractal growth, which can be seen as manifestations of a single microscopic model. Our theory is substantiated by agent based simulations and can explain growth curve differences in experimental data from in vitro cancer cell population growth. Thus, our framework offers a possible explanation for the large number of mean-field laws that can adequately capture seemingly unrelated cancer or microbial growth dynamics.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا