Avaliação da influência da temperatura e do tratamento enzimático no comportamento reológico do suco de abacaxi pérola (Ananas Comosus L. merr.)

O objetivo deste trabalho foi determinar o comportamento reológico do suco de abacaxi- pérola natural e tratado com enzimas pectinolíticas. As condições de tratamento enzimático foram otimizadas através de um planejamento experimental do tipo fatorial completo 2^k, com três repetições do ponto central. Na avaliação do comportamento reológico foram utilizadas duas amostras submetidas a peneiramento (N e D), analisadas em quatro diferentes temperaturas (10; 25; 50 e 65 °C). As análises reológicas foram realizadas utilizando um viscosímetro de cilindros concêntricos Brookfield e os dados experimentais foram ajustados ao modelo de Mizrahi-Berk. A relação entre temperatura e viscosidade aparente foi descrita por uma equação tipo Arrhenius. A otimização da atividade enzimática indicou, através da análise de variância e da metodologia de superfície de resposta, que as variáveis temperatura e tempo de tratamento exerceram efeito estatisticamente significativo (p<0,05) sobre a concentração de pectina presente na amostra. O modelo utilizado mostrou-se adequado para descrever o comportamento reológico dos sucos de acordo com os parâmetros R², χ² e B_f. Os baixos valores obtidos para o índice de comportamento indicaram um comportamento pseudoplástico (n<1). A temperatura exerceu influência sobre a tensão de cisalhamento e a viscosidade aparente dos sucos analisados, sendo os menores valores observados nas amostras analisadas a 65 °C. A equação tipo Arrhenius descreveu de modo satisfatório o efeito da temperatura sobre a viscosidade aparente. Os valores da energia de ativação (E_at) foram de 4,54 Kcal.g.mol^-1 e 4,89 Kcal.g.mol^-1, respectivamente, para as amostras do suco de abacaxi natural e despectinizado, aumentando com o tratamento enzimático. A atividade enzimática proporcionou uma redução nos valores dos parâmetros de comportamento reológico das amostras, bem como na viscosidade aparente, em todas as temperaturas utilizadas, sendo o maior percentual de redução observado a 65 °C (41,66%).

Ajuste preciso do nível de energia na dieta de frangos de corte para controle do desempenho e da composição lipídica da carne

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Acurácia e precisão na formulação não linear de ração para frangos de corte: avanço e otimização de resultados

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Estudo do comportamento reológico de sucos combinados de frutas vermelhas

The aim of this work was to evaluate the rheological behavior of combined juices of strawberry, blackberry and raspberry in two different temperatures of interest in industrial processes in the food industry, using rheological analyses on non-oscillatory regime and the Response Surface Methodology (RSM). The rheological data were fitted by the Casson model. All samples of combined juices of ref fruits showed a Newtonian behavior and the rheological parameters yield stress (Kc) and plastic viscosity of Casson (Koc) had a decrease in its values with the temperature increase. By the analysis of the ternary diagrams it is evident that the raspberry juice effectively contributed to the higher values of yield stress and plastic viscosity of Casson in both temperatures studied.

Composição lipídica da carne de frango em função da densidade nutricional da ração

Pós-graduação em Ciência Animal - FMVA

Accurate adjustment of feed formulation for broiler chickens on performance and lipid composition of meat

Most consumers consider the fat of chicken meat undesirable for a healthy diet, due to the high levels of saturated fatty acids and cholesterol. The purpose of this experiment was to investigate the influence of changes in dietary metabolizable energy level, associated with a proportional nutrient density variation, on broiler chickens performance and on the lipid composition of meat. Males and females Cobb 500 broilers were evaluated separately. Performance evaluation followed a completely randomized design with factorial 6x3 arrangement - six energy levels (2,800, 2,900, 3,000, 3,100, 3,200 and 3,300 kcal/kg) and three slaughter ages (42, 49 and 56 days). Response surface methodology was used to establish a mathematical model to explain live weight, feed intake and feed conversion behavior. Total lipids and cholesterol were determined in skinned breast meat and in thigh meat, with and without skin. For lipid composition analysis, a 3x3x2 factorial arrangement in a completely randomized design - three ration’s metabolizable energy levels (2,800, 3,000 and 3,300 kcal/kg), three slaughter ages (42, 49 and 56 days) and two sexes - was used. The reduction in the diet metabolizable energy up to close to 3,000 kcal/kg did not affect live weight but, below this value, the live weight decreased. Feed intake was lower when the dietary energy level was higher. Feed conversion was favored in a direct proportion to the increase of the energy level of the diet. The performance of all birds was within the range considered appropriate for the lineage. Breast meat had less total lipids and cholesterol than thigh meat. Thigh with skin had more than the double of total lipids of skinned thigh, but the cholesterol content did not differ with the removal of the skin, suggesting that cholesterol content is not associated with the subcutaneous fat. Intramuscular fat content was lower in the meat from birds fed diets with lower energy level. These results may help to define the most appropriate nutritional management. Despite the decrease in bird’s productive performance, the restriction of energy in broiler chickens feed may be a viable alternative, if the consumers are willing to pay more for meat with less fat.

A biophysical model of Sugarcane growth

Scientists predict that global agricultural lands will expand over the next few decades due to increasing demands for food production and an exponential increase in crop-based biofuel production. These changes in land use will greatly impact biogeochemical and biogeophysical cycles across the globe. It is therefore important to develop models that can accurately simulate the interactions between the atmosphere and important crops. In this study, we develop and validate a new process-based sugarcane model (included as a module within the Agro-IBIS dynamic agro-ecosystem model) which can be applied at multiple spatial scales. At site level, the model systematically under/overestimated the daily sensible/latent heat flux (by -10.5% and 14.8%, H and E, respectively) when compared against the micrometeorological observations from southeast Brazil. The model underestimated ET (relative bias between -10.1% and 12.5%) when compared against an agro-meteorological field experiment from northeast Australia. At the regional level, the model accurately simulated average yield for the four largest mesoregions (clusters of municipalities) in the state of Sao Paulo, Brazil, over a period of 16 years, with a yield relative bias of -0.68% to 1.08%. Finally, the simulated annual average sugarcane yield over 31 years for the state of Louisiana (US) had a low relative bias (-2.67%), but exhibited a lower interannual variability than the observed yields.

Simultaneous use of urea and potassium nitrate for Arthrospira (Spirulina) platensis cultivation

Urea has been considered as a promising alternative nitrogen source for the cultivation of Arthrospira platensis if it is possible to avoid ammonia toxicity; however, this procedure can lead to periods of nitrogen shortage. This study shows that the addition of potassium nitrate, which acts as a nitrogen reservoir, to cultivations carried out with urea in a fed-batch process can increase the maximum cell concentration (Xm) and also cell productivity (PX). Using response surface methodology, the model indicates that the estimated optimum Xm can be achieved with 17.3 mM potassium nitrate and 8.9 mM urea. Under this condition an Xm of 6077 +/- 199 mg/L and a PX of 341.5 +/- 19.1 mg L1day1 were obtained.

Purification, characterization and structural determination of chitinases produced by Moniliophthora perniciosa

The enzyme chitinase from Moniliophthora perniciosa the causative agent of the witches' broom disease in Theobroma cacao, was partially purified with ammonium sulfate and filtration by Sephacryl S-200 using sodium phosphate as an extraction buffer. Response surface methodology (RSM) was used to determine the optimum pH and temperature conditions. Four different isoenzymes were obtained: ChitMp I, ChitMp II, ChitMp III and ChitMp IV. ChitMp I had an optimum temperature at 44-73ºC and an optimum pH at 7.0-8.4. ChitMp II had an optimum temperature at 45-73ºC and an optimum pH at 7.0-8.4. ChitMp III had an optimum temperature at 54-67ºC and an optimum pH at 7.3-8.8. ChitMp IV had an optimum temperature at 60ºC and an optimum pH at 7.0. For the computational biology, the primary sequence was determined in silico from the database of the Genome/Proteome Project of M. perniciosa, yielding a sequence with 564 bp and 188 amino acids that was used for the three-dimensional design in a comparative modeling methodology. The generated models were submitted to validation using Procheck 3.0 and ANOLEA. The model proposed for the chitinase was subjected to a dynamic analysis over a 1 ns interval, resulting in a model with 91.7% of the residues occupying favorable places on the Ramachandran plot and an RMS of 2.68.

The impact of different surface parameterizations and vertical resolutions on the simulation of seabreeze episodes at the island of Fuerteventura

[EN] On 8-10 April 2007, several episodes of intense sea-breeze fronts were registered at the island of Fuerteventura (Canary Islands). The sea-breeze circulation was primary driven by daytime heating contrasts between land and the Atlantic Ocean during a period of weak trade winds. Numerical simulations of these events were carried out using the 3.1.1 version of the Weather Research and Forecasting (WRF) Model. Two different domains with 6.6-km and 2.2-km horizontal grid spacing and two sets with 27 and 51 vertical sigma levels were defined. The simulation was performed using two-way interactive nesting between the first and the second domain, using different land surface model parameterizations (Thermal diffusion, Noah LSM and RUC) for comparison. Initial conditions were provided by the NCAR Dataset analysis from April 2007, which were improved using surface and upper-air observations. The poster is focused on the 9 April episode.

A GIS based model for solving the planar Huff problem considering different demand distributions and forbidden regions

[EN] In this paper, we have used Geographical Information Systems (GIS) to solve the planar Huff problem considering different demand distributions and forbidden regions. Most of the papers connected with the competitive location problems consider that the demand is aggregated in a finite set of points. In other few cases, the models suppose that the demand is distributed along the feasible region according to a functional form, mainly a uniform distribution. In this case, in addition to the discrete and uniform demand distributions we have considered that the demand is represented by a population surface model, that is, a raster map where each pixel has associated a value corresponding to the population living in the area that it covers...

Single fluoroscopic image based 2D/3D reconstruction of a scaled, patient-specific vertebral model

Purpose Accurate three-dimensional (3D) models of lumbar vertebrae can enable image-based 3D kinematic analysis. The common approach to derive 3D models is by direct segmentation of CT or MRI datasets. However, these have the disadvantages that they are expensive, timeconsuming and/or induce high-radiation doses to the patient. In this study, we present a technique to automatically reconstruct a scaled 3D lumbar vertebral model from a single two-dimensional (2D) lateral fluoroscopic image. Methods Our technique is based on a hybrid 2D/3D deformable registration strategy combining a landmark-to-ray registration with a statistical shape model-based 2D/3D reconstruction scheme. Fig. 1 shows different stages of the reconstruction process. Four cadaveric lumbar spine segments (total twelve lumbar vertebrae) were used to validate the technique. To evaluate the reconstruction accuracy, the surface models reconstructed from the lateral fluoroscopic images were compared to the associated ground truth data derived from a 3D CT-scan reconstruction technique. For each case, a surface-based matching was first used to recover the scale and the rigid transformation between the reconstructed surface model Results Our technique could successfully reconstruct 3D surface models of all twelve vertebrae. After recovering the scale and the rigid transformation between the reconstructed surface models and the ground truth models, the average error of the 2D/3D surface model reconstruction over the twelve lumbar vertebrae was found to be 1.0 mm. The errors of reconstructing surface models of all twelve vertebrae are shown in Fig. 2. It was found that the mean errors of the reconstructed surface models in comparison to their associated ground truths after iterative scaled rigid registrations ranged from 0.7 mm to 1.3 mm and the rootmean squared (RMS) errors ranged from 1.0 mm to 1.7 mm. The average mean reconstruction error was found to be 1.0 mm. Conclusion An accurate, scaled 3D reconstruction of the lumbar vertebra can be obtained from a single lateral fluoroscopic image using a statistical shape model based 2D/3D reconstruction technique. Future work will focus on applying the reconstructed model for 3D kinematic analysis of lumbar vertebrae, an extension of our previously-reported imagebased kinematic analysis. The developed method also has potential applications in surgical planning and navigation.

Validation of statistical shape model based reconstruction of the proximal femur - A morphology study

Seventeen bones (sixteen cadaveric bones and one plastic bone) were used to validate a method for reconstructing a surface model of the proximal femur from 2D X-ray radiographs and a statistical shape model that was constructed from thirty training surface models. Unlike previously introduced validation studies, where surface-based distance errors were used to evaluate the reconstruction accuracy, here we propose to use errors measured based on clinically relevant morphometric parameters. For this purpose, a program was developed to robustly extract those morphometric parameters from the thirty training surface models (training population), from the seventeen surface models reconstructed from X-ray radiographs, and from the seventeen ground truth surface models obtained either by a CT-scan reconstruction method or by a laser-scan reconstruction method. A statistical analysis was then performed to classify the seventeen test bones into two categories: normal cases and outliers. This classification step depends on the measured parameters of the particular test bone. In case all parameters of a test bone were covered by the training population's parameter ranges, this bone is classified as normal bone, otherwise as outlier bone. Our experimental results showed that statistically there was no significant difference between the morphometric parameters extracted from the reconstructed surface models of the normal cases and those extracted from the reconstructed surface models of the outliers. Therefore, our statistical shape model based reconstruction technique can be used to reconstruct not only the surface model of a normal bone but also that of an outlier bone.

Accurate and robust reconstruction of proximal femur from sparse intraoperative data and dense point distribution model for surgical navigation

Constructing a 3D surface model from sparse-point data is a nontrivial task. Here, we report an accurate and robust approach for reconstructing a surface model of the proximal femur from sparse-point data and a dense-point distribution model (DPDM). The problem is formulated as a three-stage optimal estimation process. The first stage, affine registration, is to iteratively estimate a scale and a rigid transformation between the mean surface model of the DPDM and the sparse input points. The estimation results of the first stage are used to establish point correspondences for the second stage, statistical instantiation, which stably instantiates a surface model from the DPDM using a statistical approach. This surface model is then fed to the third stage, kernel-based deformation, which further refines the surface model. Handling outliers is achieved by consistently employing the least trimmed squares (LTS) approach with a roughly estimated outlier rate in all three stages. If an optimal value of the outlier rate is preferred, we propose a hypothesis testing procedure to automatically estimate it. We present here our validations using four experiments, which include 1 leave-one-out experiment, 2 experiment on evaluating the present approach for handling pathology, 3 experiment on evaluating the present approach for handling outliers, and 4 experiment on reconstructing surface models of seven dry cadaver femurs using clinically relevant data without noise and with noise added. Our validation results demonstrate the robust performance of the present approach in handling outliers, pathology, and noise. An average 95-percentile error of 1.7-2.3 mm was found when the present approach was used to reconstruct surface models of the cadaver femurs from sparse-point data with noise added.

An integrated approach for reconstructing surface models of the proximal femur from sparse input data for surgical navigation

A patient-specific surface model of the proximal femur plays an important role in planning and supporting various computer-assisted surgical procedures including total hip replacement, hip resurfacing, and osteotomy of the proximal femur. The common approach to derive 3D models of the proximal femur is to use imaging techniques such as computed tomography (CT) or magnetic resonance imaging (MRI). However, the high logistic effort, the extra radiation (CT-imaging), and the large quantity of data to be acquired and processed make them less functional. In this paper, we present an integrated approach using a multi-level point distribution model (ML-PDM) to reconstruct a patient-specific model of the proximal femur from intra-operatively available sparse data. Results of experiments performed on dry cadaveric bones using dozens of 3D points are presented, as well as experiments using a limited number of 2D X-ray images, which demonstrate promising accuracy of the present approach.