Sub-optimal Temperature Range Research Articles

Growth ofStaphylococcus aureus2064 described by predictive microbiology: From primary to secondary models

AbstractThe growth ofStaphylococcus aureus2064 isolate in model nutrient broth was studied as affected by temperature and water activity using principles and models of predictive microbiology. Specific rates resulting from growth curves fitted by the Baranyi model were modelled by the secondary Ratkowsky model for suboptimal temperature range (RTKsub) as well as the Ratkowsky extended model (RTKext) and cardinal model (CM) in the whole temperature range. With the biological background of the RTKext model, cardinal values of temperatureTmin= 6.06 °C andTmax= 47.9 °C and water activityaw min= 0.859 were calculated and validated with cardinal values estimated by CM (Tmin= 7.72 °C,Tmax= 46.73 °C,aw min= 0.808). CM also provided other cardinal values,Topt= 40.63 °C,awopt= 0.994, as well as optimal specific growth rate of 1.97 h–1(atToptandawopt). To evaluate the goodness of fit of all models, mathematical and graphical validation was performed and the statistical indices proved appropriateness of all the secondary models used.

Chum salmon migrating upriver adjust to environmental temperatures through metabolic compensation.

Ectotherms adjust their thermal performance to various thermal ranges by altering their metabolic rates. These metabolic adjustments involve plastic and/or genetic traits and pathways depend on species-specific ecological contexts. Chum salmon (Oncorhynchus keta) are ecologically unique among the Pacific salmonids as early-run and late-run populations are commonly observed in every part of their range. In the Sanriku coastal area, Japan, early-run adults experience high water temperatures (12-24°C) during their migration, compared with those of the late-run adults (4-15°C), suggesting that the two populations might have different thermal performance. Here, we found population-specific differences in the thermal sensitivities of metabolic rates [resting metabolic rate, RMR, and maximum (aerobic) metabolic rate, MMR] and critical temperature maxima. Using these parameters, we estimated thermal performance curves of absolute aerobic scope (AAS). The populations had different thermal performance curves of AAS, and in both populations high values of AAS were maintained throughout the range of ecologically relevant temperatures. However, the populations did not vary substantially in the peak (AAS at optimal temperature, ToptAAS) or breadth (width of sub-optimal temperature range) of the performance curves. The AAS curve of early-run fish was shifted approximately 3°C higher than that of late-run fish. Furthermore, when the data for RMR and MMR were aligned to the thermal differences from ToptAAS, it became clear that the populations did not differ in the temperature dependence of their metabolic traits. Our results indicate that chum salmon thermally accommodate through compensatory alterations in metabolic rates. Our results imply that metabolic plasticity and/or the effect of genetic variance on plasticity might play a pivotal role in their thermal accommodation.

Empirical Model With Excellent Statistical Properties for Describing Temperature-Dependent Developmental Rates of Insects and Mites

AbstractPrevious empirical models for describing the temperature-dependent development rates for insects include the Briére, Lactin, Beta, and Ratkowsky models. Another nonlinear regression model, not previously considered in population entomology, is the Lobry–Rosso–Flandrois model, the shape of which is very close to that of the Ratkowsky model in the suboptimal temperature range, but which has the added advantage that all four of its parameters have biological meaning. A consequence of this is that initial parameter estimates, needed for solving the nonlinear regression equations, are very easy to obtain. In addition, the model has excellent statistical properties, with the estimators of the parameters being “close-to-linear,” which means that the least squares estimators are close to being unbiased, normally distributed, minimum variance estimators. The model describes the pooled development rates very well throughout the entire biokinetic temperature range and deserves to become the empirical model of general use in this area.

Alternating temperature combined with darkness resets base temperature for germination (Tb ) in photoblastic seeds of Lippia and Aloysia (Verbenaceae).

Thermal time models for seed germination assume a continuum of rate responses in the sub-optimal temperature range. Generally, the models describe germination performance in non-dormant seeds at constant temperatures, yetalternating temperature (AT) is a feature of many natural environments. We studied the possible interacting effects of AT on germination progress in photoblastic seeds of three aromatic-medicinal Verbenaceae species in the genera Lippia and Aloysia. For Lippia turbinata f. turbinata and L.turbinata f. magnifolia seed, germination only occurred in light conditions, while for L.integrifolia and Aloysia citriodora it was significantly higher in the light than in darkness. Although relative light germination (RLG) was not different between constant and AT in the sub-optimal range, AT raised the base temperature for germination progress (Tb ) from ca. 3-6°C in constant temperature to 7-12°C in AT. Among the species, thermal time for 50% seed germination [θT(50) ] was 55-100°Cd at constant temperature. Although AT resulted in slight modifications to θT(50) , the germination rate at comparable average temperatures in the sub-optimal range was slower than under constant temperatures. For all species, the proportion of germinated seeds was similar for constant and AT. Our results suggest that an interaction between cool temperature and darkness during AT treatment limits the temperature range permissive for germination in these positively photoblastic seed, reflecting both close adaptation to the natural ecology and niche requirements of the species.

On the effect of sampling rate and experimental noise in the discrimination between microbial growth models in the suboptimal temperature range

Biochemical and microbial processes benefit from mathematical models. Often microbial kinetics are described as a function of environmental conditions in models exploited in predictive microbiology. Based on the organism different model structures are available. However, the aim is to determine the model that describes the system best.This work deals with secondary models describing microbial kinetics in the suboptimal temperature range and their possibility to be discriminated. The used models are the cardinal temperature model with inflection and its adapted version. The method of Optimal Experiment Design for Model Discrimination is used to investigate the practical (in)feasibility of model discrimination given different noise and sampling frequency values.Results point out the required steps and the possibilities of the method for model discrimination. It has been observed that discrimination is possible at various noise and sampling frequency levels. Moreover, also the corresponding increase in required experimental effort has been obtained.

Effect of cell immobilization on the growth dynamics of Salmonella Typhimurium and Escherichia coli at suboptimal temperatures

Predictive microbiology has recently acknowledged the impact of the solid(like) food structure on microbial behavior. The presence of this solid(like) structure causes microorganisms to grow as colonies and no longer planktonically as in liquid. In this paper, the growth dynamics of Salmonella Typhimurium and Escherichia coli were studied as a function of temperature, considering different growth morphologies, i.e., (i) planktonic cells, (ii) immersed colonies and (iii) surface colonies. For all three growth morphologies, both microorganisms were grown in petri dishes. While E. coli was grown under optimal pH and water activity (aw), for S. Typhimurium pH and aw were adapted to 5.5 and 0.990. In order to mimic a solid(like) environment, 5% (w/v) gelatin was added. All petri dishes were incubated under static conditions at temperatures in the range [8.0°C–22.0°C]. Cell density was determined via viable plate counting. This work demonstrates that the growth morphology (planktonic vs. colony) has a negligible effect on the growth dynamics as a function of temperature. The observation of almost equal growth rates for planktonic cultures and colonies is in contrast to literature where, mostly, a difference is observed, i.e., μplanktonic cells≥μimmersed colonies≥μsurface colonies. This difference might be due to shaking of the liquid culture in these studies, which results in a nutrient and oxygen rich environment, in contrast to the diffusion-limited gel system. Experiments also indicate that lag phases for solid(like) systems are similar to those for the planktonic cultures, as can be found in literature for similar growth conditions. Considering the maximum cell density, no clear trend was deducted for either of the microorganisms.This study indicates that the growth parameters in the suboptimal temperature range do not depend on the growth morphology. For the considered experimental conditions, models previously developed for liquid environments can be used for solid(like) systems.

Growth characteristics of selected thermophilic strains of cyanobacteria using crossed gradients of temperature and light

Growth requirements of 10 possibly thermophilic strains of cyanobacteria were compared under a wide spectrum of light and temperature conditions (7–80Wm−2, 12–40°C). The strains were isolated from different localities: six of thermal springs in Slovakia (4 from Piesťany, 2 from Sklene Teplice), one from thermal waters in Rupite, Bulgaria, 2 strains from a hypersaline lake Chott-el-Djerid, Tunisia, and one strain from the tropical island of Cebu, Philippines. Although the crossed gradient unit allowed only sub-optimal temperature range with respect to thermophile definition, i.e. optimum temperature above 45°C, there were difference among the strains. The most thermophilic and high-light tolerant strain was Synechococcus bigranulatus strain Lukavsky 2005/66, with a peak above 45°C; the second was Chroococcidiopsis thermalis strain Hindak 2008/9, and Isocystis sp. strain Hindak 2006/1. The temperature requirements of other strains were similar; the least thermophilic were both Slovakian strains of the genus Hapalosiphon. Growth was not limited below 80 W m−2, except for H. fontinalis strain Hindak 2008/3, which prefers lower irradiance. Hapalosiphon delicatulus strain Hindak 2007/20, isolated from a bark tree on the tropical island of Cebu was rather mesophilic than thermophilic and shade-preferring. The CCA revealed that the ecologically similar strains originated from the same or nearby localities. There were no significant correlations between temperature optima in culture and in nature. Bulgarian and Tunisian strains preferred higher irradiances.

Modeling growth rates as a function of temperature: Model performance evaluation with focus on the suboptimal temperature range

Secondary models, describing the microbial growth rate as a function of temperature, are evaluated with focus on model performance in the suboptimal temperature region. Escherichia coli K12 MG1655 is considered as the case study. A large set of μmax(T)-estimates is fitted with (1) the cardinal temperature model with inflection (CTMI, Rosso et al., 1993), (2) the square root model (SQRT, Ratkowsky et al., 1983), and (3) the CTMI adapted to describe the particular behavior of Listeria at suboptimal temperatures (aCTMI, Le Marc et al., 2002). Compared to the CTMI and the SQRT, a more accurate description of the μmax(T)-relation is obtained with the aCTMI, certainly at temperatures below 30°C. Also, the Tmin estimate is more realistic, i.e., ≈6°C, compared to 8–8.5°C for the CTMI and SQRT. Use of the aCTMI improved μmax(T)-data description which points at the existence of two phases in the suboptimal temperature region of E. coli K12. The alternation of the μmax(T) is most likely related to the cold shock response. These results reveal a possible shortcoming of the model structure of commonly used secondary models describing the temperature effect on the microbial growth rate.

Germination of Ocotea pulchella (Nees) Mez (Lauraceae) seeds in laboratory and natural restinga environment conditions

The germination response of Ocotea pulchella (Nees) Mez seeds to light, temperature, water level and pulp presence is introduced. The laboratory assays were carried out in germination chambers and thermal-gradient apparatus, whereas the field assays were performed in environments with distinct light, temperature and soil moisture conditions within a permanent parcel of Restinga forest of the Parque Estadual da Ilha do Cardoso, Cananéia, São Paulo. The seeds do not exhibit dormancy, they are non photoblastic, and a loss of viability in dry stored seeds can be related to a decrease in water content of the seed. The presence of the pulp and the flooded substratum influenced negatively the germination of O. pulchella seeds tested in the laboratory. Otherwise, light and temperature probably are not limiting factors of the germination of O. pulchella seeds in the natural environment of Restinga. The optimum temperature range for germination of Ocotea pulchella seeds was 20 to 32 degrees C, the minimum or base temperature estimated was 11 degrees C and the maximum ranged between 33 and 42 degrees C. The isotherms exhibited a sigmoidal pattern well described by the Weibull model in the sub-optimal temperature range. The germinability of O. pulchella seeds in the understorey, both in wet and dry soil, was higher than in gaps. Germination was not affected by fluctuations in soil moisture content in the understorey environment, whereas in gaps, germination was higher in wet soils. Thus, the germination of this species involves the interaction of two or more factors and it cannot be explained by a single factor.

Predicting germination response to temperature. I. Cardinal-temperature models and subpopulation-specific regression.

The purpose of this study was to compare the relative accuracy of different thermal-germination models in predicting germination-time under constant-temperature conditions. Of specific interest was the assessment of shape assumptions associated with the cardinal-temperature germination model and probit distribution often used to distribute thermal coefficients among seed subpopulations. The seeds of four rangeland grass species were germinated over the constant-temperature range of 3-38 degrees C and monitored for subpopulation variability in germination-rate response. Subpopulation-specific germination rate was estimated as a function of temperature and residual model error for three variations of the cardinal-temperature model, non-linear regression and piece-wise linear regression. The data were used to test relative model fit under alternative assumptions regarding model shape. In general, optimal model fit was obtained by limiting model-shape assumptions. All models were relatively accurate in the sub-optimal temperature range except in the 3 degrees C treatment where predicted germination times were in error by as much as 70 d for the cardinal-temperature models. Germination model selection should be driven by research objectives. Cardinal-temperature models yield coefficients that can be directly compared for purposes of screening germplasm. Other model formulations, however, may be more accurate in predicting germination-time, especially at low temperatures where small errors in predicted rate can result in relatively large errors in germination time.

Variability in thermal response of primed and non-primed seeds of squirreltail [Elymus elymoides (Raf.) Swezey and Elymus multisetus (J. G. Smith) M. E. Jones

Bottlebrush squirreltail [Elymus elymoides (Raf.) Swezey = Sitanion hystrix (Nutt.) J. G. Smith] and big squirrel-tail [Elymus multisetus (J. G. Smith) M. E. Jones = Sitanion jubatum (J. G. Smith)] have a broad geographical distribution and have been identified as high priority species for restoration of degraded rangelands in the western United States. These rangelands exhibit high annual and seasonal variability in seedbed microclimate. The objective of this study was to examine variability in thermal response of both primed and non-primed seeds of these species in the context of field-variable temperature regimes. Seed priming treatments were selected to optimize germination rate in a low-temperature test environment. Primed and non-primed seeds were evaluated for laboratory germination response under 12 constant temperature treatments between 3 and 36 degrees C. Thermal time and base temperature were estimated by regression analysis of germination rate as a function of temperature in the sub-optimal temperature range. The thermal germination model and 6 years of field temperature data were used to simulate the potential germination response under different field planting scenarios. Seed priming reduced the total germination percentage of some seedlots, especially at higher germination temperatures. Seed priming increased the germination rate (reduced the number of days to 50 % germination) by 3.8-8.4 d at 6 degrees C with a mean germination advancement of 6.9 +/- 0.6 d. Maximum germination advancement in the model simulations was 5-10 d for planting dates between I March and 15 May. Model simulations can be used to expand germination analysis beyond simple treatment comparisons, to include a probabilistic description of potential germination response under historical or potential future conditions of seedbed microclimate.

Quantal Response of Fruit and Seed Germination Rate inQuercus roburL. andCastanea sativaMill, to Constant Temperatures and Photon Dose

A linear relationship between constant temperatures in the sub-optimal temperature range and germination rate is shown in both Quercus robur L and Castanea sativa Mill germinated under nominal dark conditions. The mean base temperature was interpolated for Q robur as 0 8 ° or 2-4 °, depending on seed lot provenance, and for C. sativa as 1 -4° The optimum temperature for germination in Q. robur was about 20° compared with around 28 ° in C. sativa Over the sub-optimal temperature range the distribution of thermal times was log-normal for each population studied their spread varying both between Q robur seed lots and between species However, in C. sativa germinated close to the mean base temperature, the distribution in thermal times was reduced Thermal times to germination were decreased in Q. robur and C sativa by approximately 0 3 and 0-5 log-units, respectively, when the pericarp was removed, i.e in the seeds, but the sensitivity of the response remained relatively unaltered In both species the germination rate was the same when nominal dark or safe green light conditions were employed during the germination test. However, at 21 ° Q robur exhibited the high irradiance reaction (HIR) at photon doses above 30mmol m−2 d−1. HIR first affected the germination rate by an inhibition of radicle extension The sensitivity of the response to thermal time was reduced as photon dose increased. This photo-inhibition was exacerbated at supra-optimal temperatures. In contrast, C. sativa germination rate at 26 ° was little influenced by light at a photon dose of 752 mmol m−2 d−1

Effects of temperature on microbial production IV. The influence of ethanol on the temperature‐profile curve of ethanol production

AbstractThe shape of the temperature profile curve of ethanol production changes in the presence of ethanol. So the characteristic points of the curve are shifted to lower values at increasing ethanol concentrations. As a reason for it the potentiation of thermal deactivation effects by ethanol already at lower temperatures is assumed. Compared to it, the activation energy of ethanol for mation in the suboptimal temperature range was found to be unaffected by alcohol.

The Influence of Temperature on Seed Germination Rate in Grain Legumes

Positive linear relationships were shown between constant temperatures and the rates of progress of germination to different percentiles, G, for single populations of each of five genotypes of chickpea (Cicer anetinum L.). The base temperature, Tb, at which the rate of germination is zero, was 0·0°C for all germination percentiles of all genotypes. The optimum temperature, To(G), at which rate of germination is most rapid, varied between the five genotypes and also between percentiles within at least one population. Over the sub-optimal temperature range, i.e. from Tb to To(G), the distribution of thermal times within each population was normal. Consequently a single equation was applied to describe the influence of sub-optimal temperatures on rate of germination of all seeds within each population of each genotype. The precision with which optimum temperature, Tb(G), could be defined varied between populations. In each of three genotypes there was a negative linear relationship between temperature above Tb(G) and rate of germination. For all seeds within any of these three populations thermal time at supra-optimal temperatures was constant. Variation in the time taken to germinate at supra-optimal temperatures was a consequence of normal variation in the ceiling temperature, To(G)—the temperature at or above which rate of progress to germination percentile G is zero. A new approach to defining the response of seed germination rate to temperature is proposed for use in germplasm screening programmes. In two populations final percentage germination was influenced by temperature. The optimum constant temperature for maximum final germination was between 10°C and 15°C in these populations; approximately 15°C cooler than the optimum temperature for rate of germination. It is suggested that laboratory tests of chickpea germination should be carried out at temperatures between 10°C and 15°C.