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首页> 外文期刊>Journal of the Brazilian Chemical Society >Mineral composition of wheat flour consumed in Brazilian cities
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Mineral composition of wheat flour consumed in Brazilian cities

机译:巴西城市消费的小麦粉的矿物质成分

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摘要

In the present paper, the mineral composition of wheat flour consumed in Brazil was evaluated. In the sampling step 54 samples were collected in 15 cities, including principal Brazilian cities such as: S?o Paulo, Rio de Janeiro, Salvador, Porto Alegre, Recife and others. The elements determinate were: calcium, copper, magnesium, manganese, iron, phosphorus, potassium and zinc. The samples were digested using nitric acid and hydrogen peroxide in open system. The analytical technique employed was Inductively Coupled Plasma Optical Emission Spectrometry (ICP OES). The method validation (including digestion and determination) was performed using a certified reference material of wheat flour furnished by National Institute of Standards & Technology (NIST). Considering the 54 samples analyzed, the results demonstrated that the macronutrients: calcium, magnesium, potassium and phosphorus have average contents of 0.27, 0.35, 1.71 and 1.92 mg g-1, for concentration ranges of 0.11-1.96, 0.19-0.51, 0.76-3.16 and 0.81-7.15 mg g-1, respectively. The micronutrients: copper, iron, manganese and zinc have average contents of 1.84, 37.8, 8.2 and 9.4 μg g-1, for concentration ranges of 1.00-2.80, 10.5-146.6, 3.9-14.7 and 5.1-13.9 μg g-1, respectively. The results were also evaluated using the multivariate analysis techniques: principal component analysis (PCA) and hierarchical cluster analysis (HCA).
机译:本文对巴西消费的小麦粉的矿物质组成进行了评估。在抽样步骤中,在15个城市中收集了54个样本,包括巴西的主要城市,例如:圣保罗,里约热内卢,萨尔瓦多,阿雷格里港,累西腓等。确定的元素是:钙,铜,镁,锰,铁,磷,钾和锌。在开放系统中使用硝酸和过氧化氢消化样品。所采用的分析技术是电感耦合等离子体发射光谱(ICP OES)。方法验证(包括消化和测定)使用美国国家标准技术研究院(NIST)提供的认证小麦粉参考材料进行。考虑分析的54个样品,结果表明钙,镁,钾和磷等常量营养素的平均含量为0.27、0.35、1.71和1.92 mg g-1,浓度范围为0.11-1.96、0.19-0.51、0.76-分别为3.16和0.81-7.15 mg g-1。微量元素:铜,铁,锰和锌的平均含量为1.84、37.8、8.2和9.4μgg-1,浓度范围为1.00-2.80、10.5-146.6、3.9-14.7和5.1-13.9μgg-1,分别。还使用多元分析技术评估了结果:主成分分析(PCA)和层次聚类分析(HCA)。

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