Initial growth and development of southern sandbur based on thermal units

Availability of basic information on weed biology is an essential tool for designing integrated management programs for agricultural systems. Thus, this study was carried out in order to calculate the base temperature (Tb) of southern sandbur (Cenchrus echinatus), as well as fit the initial growth and development of the species to accumulated thermal units (growing degree days - GDD). For that purpose, experimental populations were sown six times in summer/autumn conditions (decreasing photoperiod) and six times in winter/spring condition (increasing photoperiod). Southern sandbur phenological evaluations were carried out, on alternate days, and total dry matter was measured when plants reached the flowering stage. All the growth and development fits were performed based on thermal units by assessing five base temperatures, as well as the absence of it. Southern sandbur development was best fit with Tb = 12 ºC, with equation y = 0,0993x, where y is the scale of phenological stage and x is the GDD. On average, flowering was reached at 518 GDD. Southern sandbur phenology may be predicted by using mathematical models based on accumulated thermal units, adopting Tb = 12 ºC. However, other environmental variables may also interfere with species development, particularly photoperiod.

Growth and Development of Purple Nutsedge Based on Days or Thermal Units

This work was carried out with the objective of elaborating mathematical models to predict growth and development of purple nutsedge (Cyperus rotundus) based on days or accumulated thermal units (growing degree days). Thus, two independent trials were developed, the first with a decreasing photoperiod (March to July) and the second with an increasing photoperiod (August to November). In each trial, ten assessments of plant growth and development were performed, quantifying total dry matter and the species phenology. After that, phenology was fit to first degree equations, considering individual trials or their grouping. In the same way, the total dry matter was fit to logistic-type models. In all regressions four temporal scales possibilities were assessed for the x axis: accumulated days or growing degree days (GDD) with base temperatures (Tb) of 10, 12 and 15 oC. For both photoperiod conditions, growth and development of purple nutsedge were adequately fit to prediction mathematical models based on accumulated thermal units, highlighting Tb = 12 oC. Considering GDD calculated with Tb = 12 oC, purple nutsedge phenology may be predicted by y = 0.113x, while species growth may be predicted by y = 37.678/(1+(x/509.353)-7.047).

Modeling temporal variations of Gracilaria Greville and Hypnea J.V. Lamouroux (Rhodophyta) assemblages on a midlittoral reef platform at Piedade Beach, Pernambuco State, Brazil

The diversity of algal banks composed of species out the genera Gracilaria Greville and Hypnea J.V. Lamouroux have been impacted by commercial exploitation and coastal eutrophication. The present study sought to construct dynamic models based on algal physiology to simulate seasonal variations in the biomasses of Gracilaria and Hypnea an intertidal reef at Piedade Beach in Jaboatão dos Guararapes, Pernambuco State, Brazil. Five 20 × 20 cm plots in a reef pool on a midlittoral reef platform were randomly sampled during April, June, August, October, and December/2009 and in January and March/2010. Water temperature, pH, irradiance, oxygen and salinity levels as well as the concentrations of ammonia, nitrate and phosphate were measured at the sampling site. Forcing functions were employed in the model to represent abiotic factors, and algal decay was simulated with a dispersal function. Algal growth was modeled using a logistic function and was found to be sensitive to temperature and salinity. Maximum absorption rates of ammonia and phosphate were higher in Hypnea than in Gracilaria, indicating that the former takes up nutrients more efficiently at higher concentrations. Gracilaria biomass peaked at approximately 120 g (dry weight m-2) in March/2010 and was significantly lower in August/2009; Hypnea biomasses, on the other hand, did not show any significant variations among the different months, indicating that resource competition may influence the productivity of these algae.

Thermodynamic evaluation and modeling of proton and water exchange associated with benzamidine and berenil binding to ß-trypsin

Serine-proteases are involved in vital processes in virtually all species. They are important targets for researchers studying the relationships between protein structure and activity, for the rational design of new pharmaceuticals. Trypsin was used as a model to assess a possible differential contribution of hydration water to the binding of two synthetic inhibitors. Thermodynamic parameters for the association of bovine ß-trypsin (homogeneous material, observed 23,294.4 ± 0.2 Da, theoretical 23,292.5 Da) with the inhibitors benzamidine and berenil at pH 8.0, 25ºC and with 25 mM CaCl2, were determined using isothermal titration calorimetry and the osmotic stress method. The association constant for berenil was about 12 times higher compared to the one for benzamidine (binding constants are K = 596,599 ± 25,057 and 49,513 ± 2,732 M-1, respectively; the number of binding sites is the same for both ligands, N = 0.99 ± 0.05). Apparently the driving force responsible for this large difference of affinity is not due to hydrophobic interactions because the variation in heat capacity (DCp), a characteristic signature of these interactions, was similar in both systems tested (-464.7 ± 23.9 and -477.1 ± 86.8 J K-1 mol-1 for berenil and benzamidine, respectively). The results also indicated that the enzyme has a net gain of about 21 water molecules regardless of the inhibitor tested. It was shown that the difference in affinity could be due to a larger number of interactions between berenil and the enzyme based on computational modeling. The data support the view that pharmaceuticals derived from benzamidine that enable hydrogen bond formation outside the catalytic binding pocket of ß-trypsin may result in more effective inhibitors.

A novel polar-based human face recognition computational model

Motivated by a recently proposed biologically inspired face recognition approach, we investigated the relation between human behavior and a computational model based on Fourier-Bessel (FB) spatial patterns. We measured human recognition performance of FB filtered face images using an 8-alternative forced-choice method. Test stimuli were generated by converting the images from the spatial to the FB domain, filtering the resulting coefficients with a band-pass filter, and finally taking the inverse FB transformation of the filtered coefficients. The performance of the computational models was tested using a simulation of the psychophysical experiment. In the FB model, face images were first filtered by simulated V1- type neurons and later analyzed globally for their content of FB components. In general, there was a higher human contrast sensitivity to radially than to angularly filtered images, but both functions peaked at the 11.3-16 frequency interval. The FB-based model presented similar behavior with regard to peak position and relative sensitivity, but had a wider frequency band width and a narrower response range. The response pattern of two alternative models, based on local FB analysis and on raw luminance, strongly diverged from the human behavior patterns. These results suggest that human performance can be constrained by the type of information conveyed by polar patterns, and consequently that humans might use FB-like spatial patterns in face processing.

Pleiotropic effects of simvastatin in physically trained ovariectomized rats

This study tested the hypothesis that simvastatin treatment can improve cardiovascular and autonomic functions and membrane lipoperoxidation, with an increased effect when applied to physically trained ovariectomized rats. Ovariectomized rats were divided into sedentary, sedentary+simvastatin and trained+simvastatin groups (n = 8 each). Exercise training was performed on a treadmill for 8 weeks and simvastatin (5 mg/kg) was administered in the last 2 weeks. Blood pressure (BP) was recorded in conscious animals. Baroreflex sensitivity was evaluated by the tachycardic and bradycardic responses to BP changes. Cardiac vagal and sympathetic effects were determined using methylatropine and propranolol. Oxidative stress was evaluated based on heart and liver lipoperoxidation using the chemiluminescence method. The simvastatin-treated groups presented reduced body weight and mean BP (trained+simvastatin = 99 ± 2 and sedentary+simvastatin = 107 ± 2 mmHg) compared to the sedentary group (122 ± 1 mmHg). Furthermore, the trained group showed lower BP and heart rate compared to the other groups. Tachycardic and bradycardic responses were enhanced in both simvastatin-treated groups. The vagal effect was increased in the trained+simvastatin group and the sympathetic effect was decreased in the sedentary+simvastatin group. Hepatic lipoperoxidation was reduced in sedentary+simvastatin (≈21%) and trained+simvastatin groups (≈57%) compared to the sedentary group. Correlation analysis involving all animals demonstrated that cardiac lipoperoxidation was negatively related to the vagal effect (r = -0.7) and positively correlated to the sympathetic effect (r = 0.7). In conclusion, improvement in cardiovascular and autonomic functions associated with a reduction of lipoperoxidation with simvastatin treatment was increased in trained ovariectomized rats.

Mathematical modeling of dehydration of 'Fuji' and 'Gala' apples slices using infrared

The objective of this work was to determine and model the infrared dehydration curves of apple slices - Fuji and Gala varieties. The slices were dehydrated until constant mass, in a prototype dryer with infrared heating source. The applied temperatures ranged from 50 to 100 °C. Due to the physical characteristics of the product, the dehydration curve was divided in two periods, constant and falling, separated by the critical moisture content. A linear model was used to describe the constant dehydration period. Empirical models traditionally used to model the drying behavior of agricultural products were fitted to the experimental data of the falling dehydration period. Critical moisture contents of 2.811 and 3.103 kgw kgs-1 were observed for the Fuji and Gala varieties, respectively. Based on the results, it was concluded that the constant dehydration rates presented a direct relationship with the temperature; thus, it was possible to fit a model that describes the moisture content variation in function of time and temperature. Among the tested models, which describe the falling dehydration period, the model proposed by Midilli presented the best fit for all studied conditions.

Mathematical modeling of microbial growth in milk

A mathematical model to predict microbial growth in milk was developed and analyzed. The model consists of a system of two differential equations of first order. The equations are based on physical hypotheses of population growth. The model was applied to five different sets of data of microbial growth in dairy products selected from Combase, which is the most important database in the area with thousands of datasets from around the world, and the results showed a good fit. In addition, the model provides equations for the evaluation of the maximum specific growth rate and the duration of the lag phase which may provide useful information about microbial growth.

Mathematical modeling of microwave dried celery leaves and determination of the effective moisture diffusivities and activation energy

Celery (Apium graveolens L. var. secalinum Alef) leaves with 50±0.07 g weight and 91.75±0.15% humidity (~11.21 db) were dried using 8 different microwave power densities ranging between 1.8-20 W g-1, until the humidity fell down to 8.95±0.23% (~0.1 db). Microwave drying processes were completed between 5.5 and 77 min depending on the microwave power densities. In this study, measured values were compared with predicted values obtained from twenty thin layer drying theoretical, semi-empirical and empirical equations with a new thin layer drying equation. Within applied microwave power density; models whose coefficient and correlation (R²) values are highest were chosen as the best models. Weibull distribution model gave the most suitable predictions at all power density. At increasing microwave power densities, the effective moisture diffusivity values ranged from 1.595 10-10 to 6.377 10-12 m2 s-1. The activation energy was calculated using an exponential expression based on Arrhenius equation. The linear relationship between the drying rate constant and effective moisture diffusivity gave the best fit.

Modeling and kinetic study of bio-ethanol production from soy protein concentrate by-product

Abstract The aim of this work was to evaluate a non-agitated process of bioethanol production from soybean molasses and the kinetic parameters of fermentation using a strain of Saccharomyces cerevisiae (ATCC® 2345). Kinetic experiment was conducted in medium with 30% (w v-1) of soluble solids without supplementation or pH adjustment. The maximum ethanol concentration was in 44 hours, the ethanol productivity was 0.946 g L-1 h-1, the yield over total initial sugars (Y1) was 47.87%, over consumed sugars (Y2) was 88.08% and specific cells production rate was 0.006 h-1. The mathematical polynomial was adjusted to the experimental data and provided very similar parameters of yield and productivity. Based in this study, for one ton of soybean molasses can be produced 103 kg of anhydrous bioethanol.