利用 pXRF 测定普通豆类中的锌:一种应用于生物强化研究的简便且多用途的校准策略

IF 4 2区 农林科学 Q2 CHEMISTRY, APPLIED
Shayani Kimberly Benedito , Mikaela Martins de Bem , Luiz Roberto Guimarães Guilherme , Marco Aurélio Carbone Carneiro , Marcelo Braga Bueno Guerra
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引用次数: 0

摘要

数百万人缺锌(尤其是在欠发达国家)。因此,人们实施了一些农艺策略来缓解这一公共卫生问题,主要是对主食作物进行生物强化,例如世界上消耗量最大的豆类谷物之一--普通豆类。用分析方法准确测定锌是这些措施中最重要的步骤之一。本研究评估了通过便携式 X 射线荧光光谱仪(pXRF)测定粒状普通豆类样品中锌含量的三种校准方法。选择钛/铝初级过滤器和 10 秒照射时间作为优化操作条件。用稀释的 HCl 和 HNO3 对锌含量最高的样品进行酸提取,以获得合成空白样。将原始样品与获得的空白混合,以制备校准曲线标准。此外,还评估了另一种基于植物的有证标准物质的校准模型。使用 HCl 萃取和混合样品的校准模型计算出的锌质量分数与参考数据在 95% 的置信水平下通过学生 t 检验显示出统计学上的一致性。线性相关系数 (r) 大于 0.99,检测限低至 2.23 mg kg-1。所获得的校准模型也显示出较高的预测能力,其 RMSEP(预测均方根误差)较低,即 2.16 mg kg-1。我们的结论是,pXRF 是一种具有吸引力且经济有效的方法,可用于直接、快速、环保地测定普通豆类中的锌含量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Zinc determination in common beans by pXRF: An easy and versatile calibration strategy applied to biofortification studies
Zinc deficiency is observed in millions of individuals, especially in underdeveloped countries. Therefore, agronomical strategies have been implemented to mitigate this public health issue, mainly by the biofortification of staple food crops, e.g., common beans, one of the most consumed leguminous grains worldwide. Accurate Zn determination by an analytical method is one of the most relevant steps in these initiatives. This study evaluated three calibration methods for Zn determination by portable X-ray Fluorescence Spectrometry (pXRF) in pelletized common bean samples. A Ti/Al primary filter and a 10-second irradiation time were selected as optimized operating conditions. The sample with the highest Zn content was submitted to acid extraction with diluted HCl and HNO3 to obtain synthetic blanks. Increasing amounts of the original sample were mixed with the obtained blanks to prepare the calibration curves standards. An additional calibration model with plant-based CRMs was also evaluated. Zinc mass fractions calculated using the calibration model of HCl-extracted and mixed samples showed statistical agreement with the reference data as demonstrated by the Student t-test at a 95 % confidence level. The linear correlation factor (r) was greater than 0.99, with a detection limit as low as 2.23 mg kg−1. The obtained calibration model also exhibited high prediction capability, as revealed by the low RMSEP (Root Mean Square Error of Prediction), i.e., 2.16 mg kg−1. We concluded that pXRF is an attractive and cost-effective method for direct, quick, and environmentally friendly Zn determination in common beans.
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来源期刊
Journal of Food Composition and Analysis
Journal of Food Composition and Analysis 工程技术-食品科技
CiteScore
6.20
自引率
11.60%
发文量
601
审稿时长
53 days
期刊介绍: The Journal of Food Composition and Analysis publishes manuscripts on scientific aspects of data on the chemical composition of human foods, with particular emphasis on actual data on composition of foods; analytical methods; studies on the manipulation, storage, distribution and use of food composition data; and studies on the statistics, use and distribution of such data and data systems. The Journal''s basis is nutrient composition, with increasing emphasis on bioactive non-nutrient and anti-nutrient components. Papers must provide sufficient description of the food samples, analytical methods, quality control procedures and statistical treatments of the data to permit the end users of the food composition data to evaluate the appropriateness of such data in their projects. The Journal does not publish papers on: microbiological compounds; sensory quality; aromatics/volatiles in food and wine; essential oils; organoleptic characteristics of food; physical properties; or clinical papers and pharmacology-related papers.
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