Evandro Bona

Validation of an Ultraviolet–visible (UV–Vis) technique for the quantitative determination of curcumin in poly(l-lactic acid) nanoparticles

Curcumin is a natural yellow-orange pigment extracted from turmeric and is a potential substitute of health-dangerous artificial dyes. Nanoencapsulation in biodegradable polymers is a promising alternative to improve curcumin stability and water solubility but curcumin concentration inside the nanoparticles must be precisely known. A reliable method to determine the actual curcumin concentration must be validated since the validation procedures warrant that the method is adequate and sufficient for the specific application involved. This work describes the validation parameters given by the International Conference on Harmonisation (ICH) guidelines to adopt an analytical method based on Ultraviolet-visible spectroscopy for the quantitative determination of curcumin encapsulated in poly(l-lactic acid) nanoparticles. This method was validated in respect to linearity, detection limit, quantification limit, accuracy and precision. Studies on the analytical procedure validation warranted safety in final results obtained for the curcumin concentration in the nanoparticles.

Partial least square with discriminant analysis and near infrared spectroscopy for evaluation of geographic and genotypic origin of arabica coffee

Display Omitted A fast and sample preparation free methodology was used to determine coffee origin.PLS-DA model is successful to predict geographic and genotype origin.NIR-PLS-DA is able to identify genotype that promotes better quality coffee. The agronomic practices and environmental conditions for coffee cultivation, such as climate, soil type and altitude, promote influence in the final chemical composition of the grain. Furthermore, the genotype directly influences the essential features of the beverage, increasing its aggregate price. Proof of geographic and genotypic origin of the coffee genotype must be done using reliable methods. Thus, near infrared spectroscopy (NIR) was used to analyze different coffee genotypes that were cultivated in Brazil. Due to complexity and quantity of information within the spectra, partial least square discriminant analysis (PLS-DA) were applied to analyze the NIR data. The multiplicative scatter correction (MSC) and the Savitzky-Golay second-derivative were tested as preprocessing techniques to find which one provides an appropriate identification model. The best model achieved correctly identified 94.4% of validation samples for both geographic and genotypic origin. The results demonstrate that NIR spectroscopy provides significant analytical data to be used in tandem with PLS-DA to distinguish green coffee samples geographically and genotypically.

Development of a freeze‐dried mixture of Nile tilapia (Oreochromis niloticus) croquette using a GA‐based multiobjective optimisation

BACKGROUND The mechanically separated meat (MSM) of Nile tilapia is an example of a by-product that can be used in the development of new foods. The aim of this study was to optimise the mixture of different flours in the development of a freeze-dried mixture of fish croquette using Nile tilapia MSM. Flavour, texture and overall acceptance of seven formulations were evaluated by an acceptance test. A genetic algorithm (GA) with desirability functions was combined with a multiobjective optimisation of the response surface models. RESULTS The combination of flours was chosen to minimise cost and maximise overall acceptance and fibre content. Overall acceptance showed a statistically significant correlation (P ≤ 0.05) with flavour (r = 0.67) and texture (r = 0.61). The GA-based approach indicated that the highest overall acceptance was obtained when using wheat and rye flours in equal parts. This formulation had an overall acceptance of 7.52, a fibre content of 11.50 g kg⁻¹ and a cost of US

Simulation of NaCl and KCl mass transfer during salting of Prato cheese in brine with agitation: a numerical solution

2.21/kg. After 24 h of freeze-drying, the water activity of the mixture was 0.11. CONCLUSION The GA-based approach was able to optimise the croquette formulation. The freeze-drying process contributed to the development of a value-added product with high quality and long shelf-life.

Optimized Neural Network for Instant Coffee Classification through an Electronic Nose

The association of dietary NaCl with arterial hypertension has led to a reduction in the levels of this salt in cheeses. For salting, KCl has been used as a partial substitute for NaCl, which cannot be completely substituted without affecting product acceptability. In this study a sensorially adequate saline solution (NaCl/KCl) was simultaneously diffused during salting of Prato cheese in brine with agitation. The simultaneous multicomponent diffusion during the process was modeled with Ficks second generalized law. The system of partial differential equations formed was solved by the finite element method (FEM). In the experimental data concentration the deviation for NaCl was of 7.3% and for KCl of 5.4%, both of which were considered acceptable. The simulation of salt diffusion will allow control and modulation of salt content in Prato cheese, permitting the prediction of final content from initial conditions.

Difusão multicomponente durante a salga mista de queijo prato

Flavor is one of the most important features of food, especially of coffee. The evaluation of this sensory feature is complex yet indispensable in quality control of instant coffees. In this work, an artificial neural network (ANN) was developed for instant coffee classification based on an electronic nose (EN) aroma profile. To this purpose, a hybrid algorithm was developed, containing: bootstrap resample methodology; factorial design and sequential simplex optimization to tune network parameters; an ensemble multilayer perceptron (MLP) trained with backpropagation for coffee classification; and causal index procedure for knowledge extraction from the trained ANN. The produced neural network classifier correctly recognizes 100% of coffees studied. Furthermore, the causal index employment allowed inference of some rules on how the coffees were separated according to the sensors available in EN. The results indicate that the applied methodology is a promising tool for instant coffee quality control.

Modelagem e simulação da desidratação osmótica em pedaços de abacaxi utilizando o método de elementos finitos

A relacao entre o NaCl e a hipertensao arterial tem estimulado a sua substituicao parcial por KCl em queijos. Entretanto, para manter a qualidade final do produto, e de suma importância assegurar uma proporcao adequada de NaCl/KCl, bem como a distribuicao homogenea destes sais. Os modelos que estimam a concentracao salina, portanto, sao valiosas ferramentas para o controle de qualidade. Para simular a difusao multicomponente durante a salga em salmoura estatica, foi proposto um modelo unidimensional, baseado na solucao analitica da 2a lei de Fick generalizada para dois solutos. A solucao analitica, implementada atraves de um algoritmo computacional, permitiu o ajuste dos coeficientes de difusao e a avaliacao da resistencia externa. Os resultados da simulacao obtidos apresentaram boa concordância com os valores experimentais (desvio de 2,7% para o NaCl e 6,6% para o KCl), validando a capacidade preditiva do modelo proposto. Alem disso, a simulacao pode permitir um ajuste de ganhos de produtividade (reducao do tempo de salga) atraves da estimativa do tempo de salga para teores salinos desejados.

Preparation of curcumin-loaded nanoparticles and determination of the antioxidant potential of curcumin after encapsulation

Water loss and sugar gain were modelling during the osmotic dehydration process of pieces of pineaplle. The transfer of solute to the fruit and the water to the solution was based on Ficks 2nd law. The three dimensional model was solved by the finite element method with the usage of the software COMSOL Multiphysics 3.2. The main and cross diffusion coefficients and the Biot number were determined on the simulation and the deviation between the experimental and the simulated data were 4,28% to sucrose and 1,66 to the water.

Aplicação de redes neurais artificiais na identificação de gasolinas adulteradas comercializadas na região de Londrina - Paraná

Encapsulation of bioactive compounds has been carried out to improve bioavailability and to protect them against harm conditions. However, encapsulation processes are often aggressive and it is important that encapsulated substances keep their biological activity. In this work curcumin was nanoencapsulated using dichloromethane as solvent and ultrasound as dispersion device. Nanoparticles were obtained using different curcumin concentrations and encapsulants (PLLA and Eudragit S100) and the encapsulation efficiency was inferred using spectroscopic and calorimetric techniques as well as optical microscopy. Total phenolic contents and antioxidant activity tests were applied to the curcumin before and after encapsulation and also to blank polymer nanoparticles. Results demonstrated that the encapsulation process had no deleterious influence on its antioxidant activity.

Application of multi-block analysis and mixture design with process variable for development of chocolate cake containing yacon (Smallanthus sonchifolius) and maca (Lepidium meyenii): Chocolate cake development with yacon and maca

The multilayer perceptron network was used to classify the gasoline. The main parameters used in the classification were established by the Ordinance no 309 of the Agencia Nacional do Petroleo, but without informing the network the legal limits of these parameters. The network used had 10 neurons in a single hidden layer, learning rate of 0.04 and 250 training epochs. The application of artificial neural network served classify 100% of the commercialized gas in the region of Londrina-PR and to identify the tampered gasoline even those suspected of tampering.