Resíduos de agrotóxicos em alimentos: uma preocupação ambiental global - um enfoque às maçãs.

This paper describes the use of pesticides in agriculture. Research has shown that signifcant quantities of pesticide residues have been found in many types of foods. Thus, an overview is given of pesticide residue determinations in fruits and vegetables, with special attention to apples. The toxicity and the adverse effects possibly caused by the exposure of these compounds are alerting the scientifc community to develop studies about the validation of analytical methods for multiresidue pesticide determination in these samples. This review shows that pesticide-residue determination in apples is becoming a very important and challenging issue.

Desenvolvimento e validação de métodos para a determinação de agrotóxicos em água e solo das áreas de recarga de Aquífero Guarani, na região das nascentes do Rio Araguaia, MT/GO.

Abstract: The area near the Araguaia River, between Goiás and Mato Grosso States, is the location of a portion of the recharging of the Guarani Aquifer, which is one of the world¿s largest aquifer systems and an important source of drinking water. This reservoir could be threatened by the widespread use of pesticides in maize and soybean cultivation in this area. Thus, this work developed analytical methods for the determination of imazethapyr, nicosulfuron, imazaquin, carbofuran, atrazine, linuron, clorimuronethyl and diflubenzuron, pesticides used in maize and soybean cultivation. Pesticide separation, identification and quantification were performed using High-Performance Liquid Chromatography with Diode Array Detection (HPLC-DAD) and Liquid Chromatography-Electrospray Ionization Tandem Mass Spectrometry (LC-ESI-MS/MS). Solid Phase Extraction (SPE) with C18 sorbents was optimized for sample extraction from water. Soil samples were extracted by mechanical shaking, sonication or microwave-assisted extraction with industrial and home microwave ovens. Methods were validated resulting in limits of quantification (LOQ) for the pesticides in water in the range of 0.015-0.1 ng mL, using SPE-HPLC-DAD, and 0.01 ng mL using LC-ESI-MS/MS. LOQ of 1 ng mL for all pesticides in soil were achieved using the home microwave oven and LC-ESI-MS/MS. Recoveries for pesticides with all methods were in the range 70-120 %. Relative standard deviations for repeatability and intermediate precision were less than 15 %. SPEHPLC- DAD and LC-ESI-MS/MS were employed for the analysis of samples of water from the recharge area and most of the pesticides were detected at concentrations below the minimum residue limit (MRL) of 0.1 ng mL established by the European Community. The home microwave oven and LC-ESI-MS/MS were used for the analysis of soil samples from two other regions of Brazil and the pesticides were not detected in these samples. Adsorption and desorption parameters were determined for imazethapyr, imazaquin, nicosulfuron and chlorimuron-ethyl, indicating that these pesticides have little affinity for the soil of the region of the Guarani Aquifer recharge, and show significant leaching potential, according to the ground water ubiquity score (GUS index) for these pesticides.

Phosphorus quantification in fertilizers using laser induced breakdown spectroscopy (LIBS): a methodology of analysis to correct physical matrix effcts.

2016

Sequential factorial designs for method development of the determination of Cd and Pb in fish and shrimp by GF AAS after sample freezedrying and tetramethylammonium hydroxide solubilization.

2016

Uso da espectroscopia de reflectância do infravermelho próximo (NIRS) para previsão da composição bromatológica de vagens de algaroba e palma forrageira.

Espécies forrageiras adaptadas às condições semiáridas são uma alternativa para reduzir os impactos negativos na cadeia produtiva de ruminantes da região Nordeste brasileira devido à sazonalidade na oferta de forragem, além de reduzir custo com o fornecimento de alimentos concentrados. Dentre as espécies, a vagem de algaroba (Prosopis juliflora SW D.C.) e palma forrageira (Opuntia e Nopalea) ganham destaque por tolerarem o déficit hídrico e produzirem em períodos onde a oferta de forragem está reduzida, além de apresentam bom valor nutricional e serem bem aceitas pelos animais. Porém, devido à variação na sua composição, seu uso na alimentação animal exige o conhecimento profundo da sua composição para a elaboração de dietas balanceadas. No entanto, devido ao custo e tempo para análise, os produtores não fazem uso da prática de análise da composição químico-bromatológica dos alimentos. Por isto, a espectroscopia de reflectância no infravermelho próximo (NIRS) representa uma importante alternativa aos métodos tradicionais. Objetivou-se com este estudo desenvolver e validar modelos de predição da composição bromatológica de vagem de algaroba e palma forrageira baseados em espectroscopia NIRS, escaneadas em dois modelos de equipamentos e com diferentes processamentos da amostra. Foram coletadas amostras de vagem de algaroba nos estados do Ceará, Bahia, Paraíba e Pernambuco, e amostras de palma forrageira nos estados do Ceará, Paraíba e Pernambuco, frescas (in natura) ou pré-secas e moídas. Para obtenção dos espectros utilizaram-se dois equipamentos NIR, Perten DA 7250 e FOSS 5000. Inicialmente os alimentos foram escaneados in natura em aparelho do modelo Perten, e, com o auxílio do software The Unscrambler 10.2 foi selecionado um grupo de amostras para o banco de calibração. As amostras selecionadas foram secas e moídas, e escaneadas novamente em equipamentos Perten e FOSS. Os valores dos parâmetros de referência foram obtidos por meio de metodologias tradicionalmente aplicadas em laboratório de nutrição animal para matéria seca (MS), matéria mineral (MM), matéria orgânica (MO), proteína bruta (PB), estrato etéreo (EE), fibra solúvel em detergente neutro (FDN), fibra solúvel em detergente ácido (FDA), hemicelulose (HEM) e digestibilidade in vitro da matéria seca (DIVMS). O desempenho dos modelos foi avaliado de acordo com os erros médios de calibração (RMSEC) e validação (RMSECV), coeficiente de determinação (R2 ) e da relação de desempenho de desvio dos modelos (RPD). A análise exploratória dos dados, por meio de tratamentos espectrais e análise de componentes principais (PCA), demonstraram que os bancos de dados eram similares entre si, dando segurança de desenvolver os modelos com todas as amostras selecionadas em um único modelo para cada alimento, algaroba e palma. Na avaliação dos resultados de referência, observou-se que a variação dos resultados para cada parâmetro corroboraram com os descritos na literatura. No desempenho dos modelos, aqueles desenvolvidos com pré-processamento da amostra (pré-secagem e moagem) se mostraram mais robustos do que aqueles construídos com amostras in natura. O aparelho NIRS Perten apresentou desempenho semelhante ao equipamento FOSS, apesar desse último cobrir uma faixa espectral maior e com intervalos de leituras menores. A técnica NIR, associada ao método de calibração multivariada de regressão por meio de quadrados mínimos (PLS), mostrou-se confiável para prever a composição químico-bromatológica de vagem de algaroba e da palma forrageira. Abstract: Forage species adapted to semi-arid conditions are an alternative to reduce the negative impacts in the feed supply for ruminants in the Brazilian Northeast region, due to seasonality in forage availability, as well as in the reducing of cost by providing concentrated feedstuffs. Among the species, mesquite pods (Prosopis juliflora SW DC) and spineless cactus (Opuntia and Nopalea) are highlighted for tolerating the drought and producion in periods where the forage is scarce, and have high nutritional value and also are well accepted by the animals. However, its use in animal diets requires a knowledge about its composition to prepare balanced diets. However, farmers usually do not use feed composition analysis, because their high cost and time-consuming. Thus, the Near Infrared Reflectance Spectroscopy in the (NIRS) is an important alternative to traditional methods. The objective of this study to develop and validate predictive models of the chemical composition of mesquite pods and spineless cactus-based NIRS spectroscopy, scanned in two different spectrometers and sample processing. Mesquite pods samples were collected in the states of Ceará, Bahia, Paraiba and Pernambuco, and samples of forage cactus in the states of Ceará, Paraíba and Pernambuco. In order to obtain the spectra, it was used two NIR equipment: Perten DA 7250 and FOSS 5000. sSpectra of samples were initially obtained fresh (as received) using Perten instrument, and with The Unscrambler software 10.2, a group of subsamples was selected to model development, keeping out redundant ones. The selected samples were dried and ground, and scanned again in both Perten and FOSS instruments. The values of the reference analysis were obtained by methods traditionally applied in animal nutrition laboratory to dry matter (DM), mineral matter (MM), organic matter (OM), crude protein (CP), ether extract (EE), soluble neutral detergent fiber (NDF), soluble acid detergent fiber (ADF), hemicellulose ( HEM) and in vitro digestibility of dry matter (DIVDM). The performance of the models was evaluated according to the Root Mean Square Error of Calibration (RMSEC) and cross-validation (RMSECV), coefficient of determination (R2 ) and the deviation of Ratio of performance Deviation of the models (RPD). Exploratory data analysis through spectral treatments and principal component analysis (PCA), showed that the databases were similar to each other, and may be treated asa single model for each feed - mesquite pods and cactus. Evaluating the reference results, it was observed that the variation were similar to those reported in the literature. Comparing the preprocessing of samples, the performance ofthose developed with preprocessing (dried and ground) of the sample were more robust than those built with fresh samples. The NIRS Perten device performance similar to FOSS equipment, although the latter cover a larger spectral range and with lower readings intervals. NIR technology associate do multivariate techniques is reliable to predict the bromatological composition of mesquite pods and cactus.