Araça amarelo: atividade antioxidante, composição nutricional e aplicação em barra de cereais

Brazil has a great diversity of native fruits, which are not always widely consumed, being sold only in certain regions, due to their difficulty of post-harvest conservation. One such fruit is yellow guava, interesting source of nutrients. To promote the consumption and use of this fruit to the consumer public in different regions of the country, this study evaluated the incorporation of yellow Ya-cy araçá in formulating a cereal bar. Therefore, fruits were evaluated for their chemical, physical and chemical characteristics and bioactive compounds in different stages of maturation yellow guava (green, mature and dried forms). The behavior of guava yellow front of to UV-C radiation was also evaluated. After these reviews, there was obtained yellow ripe guava flour after previous tests, was added to the base formulation cereal bar. For the experimental planning and development of the formulations was used factorial design 22 with a central point. The developed formulations were subjected to sensory evaluation using for treatment of multivariate data analysis (Principal Component Analysis- ACP). The preferred formulation in sensory evaluation was evaluated in their physical characteristics (texture), physical-chemical (moisture, ash, lipids, proteins, carbohydrates, dietary fiber and calorie), mineral content and fatty acid profile. The results indicated that the added yellow guava cereal bar developed in this study is one way to application and use of guava, increasing the consumption of fruit to different regions of the country, and can be considered a functional product, not only to contain the fruit in its composition, but also to present many beneficial nutrients that contribute to the health of consumers.

Desenvolvimento e aplicação de modelo de calibração multivariada para determinação de açúcares e ácidos orgânicos em bebidas comerciais utilizando espectroscopia no infravermelho

The routine analysis for quantization of organic acids and sugars are generally slow methods that involve the use and preparation of several reagents, require trained professional, the availability of special equipment and is expensive. In this context, it has been increasing investment in research whose purpose is the development of substitutive methods to reference, which are faster, cheap and simple, and infrared spectroscopy have been highlighted in this regard. The present study developed multivariate calibration models for the simultaneous and quantitative determination of ascorbic acid, citric, malic and tartaric and sugars sucrose, glucose and fructose, and soluble solids in juices and fruit nectars and classification models for ACP. We used methods of spectroscopy in the near infrared (Near Infrared, NIR) in association with the method regression of partial least squares (PLS). Were used 42 samples between juices and fruit nectars commercially available in local shops. For the construction of the models were performed with reference analysis using high-performance liquid chromatography (HPLC) and refractometry for the analysis of soluble solids. Subsequently, the acquisition of the spectra was done in triplicate, in the spectral range 12500 to 4000 cm-1. The best models were applied to the quantification of analytes in study on natural juices and juice samples produced in the Paraná Southwest Region. The juices used in the application of the models also underwent physical and chemical analysis. Validation of chromatographic methodology has shown satisfactory results, since the external calibration curve obtained R-square value (R2) above 0.98 and coefficient of variation (%CV) for intermediate precision and repeatability below 8.83%. Through the Principal Component Analysis (PCA) was possible to separate samples of juices into two major groups, grape and apple and tangerine and orange, while for nectars groups separated guava and grape, and pineapple and apple. Different validation methods, and pre-processes that were used separately and in combination, were obtained with multivariate calibration models with average forecast square error (RMSEP) and cross validation (RMSECV) errors below 1.33 and 1.53 g.100 mL-1, respectively and R2 above 0.771, except for malic acid. The physicochemical analysis enabled the characterization of drinks, including the pH working range (variation of 2.83 to 5.79) and acidity within the parameters Regulation for each flavor. Regression models have demonstrated the possibility of determining both ascorbic acids, citric, malic and tartaric with successfully, besides sucrose, glucose and fructose by means of only a spectrum, suggesting that the models are economically viable for quality control and product standardization in the fruit juice and nectars processing industry.