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Vieira H.P.,Federal University of Minas Gerais | Vieira H.P.,Instituto Mineiro Of Agropecuaria Ima | Nascentes C.C.,Federal University of Minas Gerais | Windmoller C.C.,Federal University of Minas Gerais
Journal of Food Composition and Analysis

The traditional method routinely used in laboratories to analyze mercury (Hg) in honey includes decomposition of samples, cold vapor generation and atomic absorption detection. Methods that avoid sample digestion could be applied in these laboratories and would represent an innovation relevant to the control of Hg in honey. In this paper, two methods were developed to determine Hg concentration in honey samples: one utilized cold vapor atomic absorption spectrometry (CVAAS), and the other used a direct mercury analyzer (DMA). The CVAAS method consisted of preparing solutions containing 5.0% (w/v) honey, 4.0% (v/v) H2O2 and 6.0% (v/v) HNO3. Hg determination was accomplished by treatment with 0.6% (w/v) NaBH4 in 0.5% (w/v) NaOH and 6.0mol/L HCl. In the DMA method, measurements were made using up to 100mg of honey sample without any prior treatment. The drying and decomposition times along with drying temperature were each optimized. After validation, the methods were used to quantify Hg in 35 honey samples collected from several cities in Minas Gerais, Brazil. All honey samples showed Hg concentrations below 2.5ng/g. The proposed methods were rapid, simple and did not require sample decomposition using concentrated acids at high temperatures, which is advantageous considering the high volatility of Hg. © 2014 Elsevier Inc. Source

Teixeira L.S.,Federal University of Minas Gerais | Vieira H.P.,Instituto Mineiro Of Agropecuaria Ima | Windmoller C.C.,Federal University of Minas Gerais | Nascentes C.C.,Federal University of Minas Gerais

A fast and accurate method based on ultrasound-assisted extraction in a cup-horn sonoreactor was developed to determine the total content of Cd, Co, Cr, Cu, Mn, Ni, Pb and Zn in organic fertilizers by fast sequential flame atomic absorption spectrometry (FS FAAS). Multivariate optimization was used to establish the optimal conditions for the extraction procedure. An aliquot containing approximately 120 mg of the sample was added to a 500 μL volume of an acid mixture (HNO3/HCl/HF, 5:3:3, v/v/v). After a few minutes, 500 μL of deionized water was added and eight samples were simultaneously sonicated for 10 min at 50% amplitude, allowing a sample throughput of 32 extractions per hour. The performance of the method was evaluated with a certified reference material of sewage sludge (CRM 029). The precision, expressed as the relative standard deviation, ranged from 0.58% to 5.6%. The recoveries of analytes were found to 100%, 109%, 96%, 92%, 101%, 104% and 102% for Cd, Cr, Cu, Mn, Ni, Pb and Zn, respectively. The linearity, limit of detection and limit of quantification were calculated and the values obtained were adequate for the quality control of organic fertilizers. The method was applied to the analysis of several commercial organic fertilizers and organic wastes used as fertilizers, and the results were compared with those obtained using the microwave digestion procedure. A good agreement was found between the results obtained by microwave and ultrasound procedures with recoveries ranging from 80.4% to 117%. Two organic waste samples were not in accordance with the Brazilian legislation regarding the acceptable levels of contaminants. © 2013 Elsevier B.V. Source

Fernandes H.C.,Federal University of Vicosa | Moreira R.F.,Instituto Mineiro Of Agropecuaria Ima | Longui F.C.,Federal University of Vicosa | Rinaldi P.C.,Federal University of Vicosa | Siqueira W.C.,Federal University of Vicosa
Revista Ceres

The environment of the intensive farming of pigs directly influences their comfort and welfare; a stressful environment leads to various responses, depending on the adaptability of the animal. The facility aims to minimize these problems. The objective of this study was to evaluate the physiological and production indices of lactating mothers and piglets with the use of cooling systems and floor heating, respectively. The experimental design was completely randomized in a split plot with five replicates for the following treatments: heated floor for piglets and cooled to the parent (HPiCPa), no floor heating for piglets and cooled for the parent (CPa) and floor without modification (FWM). We evaluated the thermal and physiological parameters of the arrays of treatments CPa and HPiCPa. In the room designated S2 without modification, we evaluated the parameters of the matrices FWM treatment. Treatment CPa showed the best result, providing greater thermal comfort for the animals, which reached an average gain 233grams per day. Source

Botelho B.G.,Federal University of Minas Gerais | Mendes B.A.P.,Instituto Mineiro Of Agropecuaria Ima | Sena M.M.,Federal University of Minas Gerais | Sena M.M.,Instituto Nacional Of Ciencia E Tecnologia Em Bioanalitica Inct Bio
Food Analytical Methods

This paper proposed and validated robust diffuse reflectance near-infrared methods for the direct determination of fat and moisture in cow mozzarella cheeses using partial least squares regression. They were developed under the realistic conditions of routine analysis in a state laboratory of quality inspection control and were used for analyzing a great variety of mozzarella samples manufactured by different manufacturing procedures and originating from the whole state of Minas Gerais, Brazil (more than 100 different producers). A robust methodology was implemented, including the detection of outliers and the harmonization of the multivariate concepts with the traditional univariate guidelines. The models were constructed in the ranges from 38. 7 to 58. 0 % w/w on dry basis for fat and from 41. 5 to 55. 1 % w/w for moisture, providing root mean square errors of prediction of 2. 1 and 0. 9 %, respectively. Both methods were validated through the estimation of figures of merit, such as linearity, trueness, precision, analytical sensitivity, ruggedness, bias, and residual prediction deviation. Once the methods were adopted, their performances were monitored for approximately 1 year through control charts and were considered satisfactorily stable with prediction errors within the established limits. Beyond these specific methods, it was also pursued to present a complete methodology for multivariate analytical validation, an important aspect for the implementation of near-infrared spectroscopy methods in the routine of food quality inspection. © 2012 Springer Science+Business Media, LLC. Source

De Figueiredo T.C.,Federal University of Minas Gerais | De Assis D.C.S.,Federal University of Minas Gerais | Menezes L.D.M.,Instituto Mineiro Of Agropecuaria Ima | Da Silva G.R.,Federal University of Minas Gerais | And 3 more authors.

A quantitative and confirmatory high-performance liquid chromatography with ultraviolet detection (HPLC-UV) method for the determination of bioactive amines in the albumen and yolk of commercial eggs was developed, optimized and validated by analyte extraction with trichloroacetic acid and pre-column derivatization with dansyl chloride. Phenylethylamine, putrescine, cadaverine, histamine, tyramine, spermidine and spermine standards were used to evaluate the following performance parameters: limit of detection (LoD), limit of quantification (LoQ), selectivity, linearity, precision, recovery and ruggedness. The LoD of the method was defined from 0.2 to 0.3 mg kg-1 for the yolk matrix and from 0.2 to 0.4 mg kg-1 for the albumen matrix; the LoQ was from 0.7 to 1.0 mg kg-1 for the yolk matrix and from 0.7 to 1.1 mg kg-1 for the albumen matrix. The validated method exhibited excellent selectivity and separation of all amines with coefficients of determination higher than 0.99. The obtained recovery values were from 90.5% to 108.3%, and the relative standard deviation (RSD) was lower than 10% under repeatability conditions for the studied analytes. The performance parameters show the validated method to be adequate for the determination of bioactive amines in egg albumen and yolk. © 2015 Elsevier B.V. All rights reserved. Source

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