Shayani Kimberly Benedito , Mikaela Martins de Bem , Luiz Roberto Guimarães Guilherme , Marco Aurélio Carbone Carneiro , Marcelo Braga Bueno Guerra
{"title":"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","authors":"Shayani Kimberly Benedito , Mikaela Martins de Bem , Luiz Roberto Guimarães Guilherme , Marco Aurélio Carbone Carneiro , Marcelo Braga Bueno Guerra","doi":"10.1016/j.jfca.2024.106851","DOIUrl":null,"url":null,"abstract":"<div><div>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, <em>e.g</em>., 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 HNO<sub>3</sub> 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<sup>−1</sup>. The obtained calibration model also exhibited high prediction capability, as revealed by the low RMSEP (Root Mean Square Error of Prediction), <em>i.e</em>., 2.16 mg kg<sup>−1</sup>. We concluded that pXRF is an attractive and cost-effective method for direct, quick, and environmentally friendly Zn determination in common beans.</div></div>","PeriodicalId":15867,"journal":{"name":"Journal of Food Composition and Analysis","volume":"137 ","pages":"Article 106851"},"PeriodicalIF":4.0000,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Zinc determination in common beans by pXRF: An easy and versatile calibration strategy applied to biofortification studies\",\"authors\":\"Shayani Kimberly Benedito , Mikaela Martins de Bem , Luiz Roberto Guimarães Guilherme , Marco Aurélio Carbone Carneiro , Marcelo Braga Bueno Guerra\",\"doi\":\"10.1016/j.jfca.2024.106851\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>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, <em>e.g</em>., 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 HNO<sub>3</sub> 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<sup>−1</sup>. The obtained calibration model also exhibited high prediction capability, as revealed by the low RMSEP (Root Mean Square Error of Prediction), <em>i.e</em>., 2.16 mg kg<sup>−1</sup>. We concluded that pXRF is an attractive and cost-effective method for direct, quick, and environmentally friendly Zn determination in common beans.</div></div>\",\"PeriodicalId\":15867,\"journal\":{\"name\":\"Journal of Food Composition and Analysis\",\"volume\":\"137 \",\"pages\":\"Article 106851\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2024-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Food Composition and Analysis\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0889157524008858\",\"RegionNum\":2,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CHEMISTRY, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Food Composition and Analysis","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0889157524008858","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, APPLIED","Score":null,"Total":0}
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.
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.