基于EDXRF法快速检测小麦中的Ca元素
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摘要
为建立基于能量色散X射线荧光光谱法(EDXRF)的小麦Ca含量快速检测方法,以7个产地157份小麦作为研究对象,分析粒径对小麦Ca检测精度的影响,同时对样本的一致性进行检测;建立Ca含量和全信息X射线荧光光谱的偏最小二乘法回归(PLSR)定量校正模型,并优选光谱预处理方法;对不同产地的小麦Ca含量进行方差分析。结果表明:60目粒径小麦满足检测要求,样本一致性较好;校正模型预测相关系数(R_p)和预测均方根误差(RMSEP)分别为0.977 2和4.737 9; 7个产地中,山西产小麦Ca含量最高,不同产地小麦Ca含量差异明显。可知,样本预处理方法、建立的校正模型提高了检测精度和可靠性,小麦Ca含量受地域影响,可为高钙小麦的优选以及小麦的产地识别提供参考。
A fast detection method of Ca content in wheat based on energy dispersive X-ray fluorescence spectrometry(EDXRF) was established. 157 samples of wheat from 7 origins were studied, the influence of particle size on the detection accuracy of wheat Ca was analyzed, and the consistency of the sample was tested. The partial least square regression(PLSR) quantitative correction model for Ca content and X-ray fluorescence spectra with entire imformation was established, and the method of spectral pretreatment was optimized. The variance of wheat Ca content in different producing areas was analyzed. The results showed that wheat of 60 mesh size meets the detection requirements, and samples had good consistency; The Rpand RMSEP were 0.977 2 and 4.737 9, respectively. Among the 7 producing areas, the Ca content of wheat in Shanxi Province was the highest and the content of wheat Ca was different in different geographical locations. Accordingly, the sample pretreatment method and the correction model could improved the detection accuracy and reliability, and Ca content of wheat was influenced by regional, which could provide the reference for the optimization of high calcium wheat and wheat origin recognition.
A fast detection method of Ca content in wheat based on energy dispersive X-ray fluorescence spectrometry(EDXRF) was established. 157 samples of wheat from 7 origins were studied, the influence of particle size on the detection accuracy of wheat Ca was analyzed, and the consistency of the sample was tested. The partial least square regression(PLSR) quantitative correction model for Ca content and X-ray fluorescence spectra with entire imformation was established, and the method of spectral pretreatment was optimized. The variance of wheat Ca content in different producing areas was analyzed. The results showed that wheat of 60 mesh size meets the detection requirements, and samples had good consistency; The Rpand RMSEP were 0.977 2 and 4.737 9, respectively. Among the 7 producing areas, the Ca content of wheat in Shanxi Province was the highest and the content of wheat Ca was different in different geographical locations. Accordingly, the sample pretreatment method and the correction model could improved the detection accuracy and reliability, and Ca content of wheat was influenced by regional, which could provide the reference for the optimization of high calcium wheat and wheat origin recognition.
引文
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[13]许艳霞,倪小英. X射线荧光光谱法测定稻米镉含量的影响因素[J].粮食与饲料工业, 2017, 12(6):60-64.
[14]陆金鑫,贾明哲,时超,等.基于无标样定量分析的X射线荧光光谱法快速测定谷物中多种营养元素[J].中国粮油学报, 2016, 31(7):138-141.
[15]倪子月,陈吉文.能量色散X射线荧光光谱法快速测定烟草中的镉和铅[J].中国烟草学报, 2016, 22(4):8-13.
[16] RIBEIRO R O, MáRSICO E T, DE JESUS E F, et al.Determination of trace elements in honey from different regions in Rio de Janeiro State(Brazil)by total reflection X-ray fluorescence.[J]. Journal of Food Science, 2014, 79(4):T738.
[17] PERRING L, ANDREY D. Multi-elemental ED-XRF determination in dehydrated bouillon and sauce base products[J].Food Analytical Methods, 2017(5):1-13.
[18]程锋,谷懿,葛良全,等.原位能量色散X射线荧光分析中岩样基体效应及其修正研究[J].光谱学与光谱分析, 2017,37(3):919-923.
[19]张凤菊,刘晓娟,赵丽平,等.数据差异显著性检验[J].农机使用与维修, 2012(4):51-52.
[20]沈玉芳.不同土层水、氮、磷空间组合对冬小麦生理生态特征的影响[D].杨凌:西北农林科技大学, 2007.
[2]陈洁,吕真真,徐经杰,等.我国小麦主产区的小麦粉理化性质分析[J].粮食与饲料工业, 2013, 12(2):6-9.
[3]徐娟,郑志锋,刘祥义,等. ICP-AES法同时测6种薯类作物中无机元素[J].食品工业, 2016, 37(12):255-257.
[4]LICATAP,BELLAGD,POTORT?AG,etal.Determination of trace elements in goat and ovine milk from Calabria(Italy)by ICP-AES[J]. Food Additives&Contaminants Part B, 2012, 5(4):268-271.
[5]臧鹏雯,张岚.火焰原子吸收光谱法测定蛋粉中微量元素含量[J].农产品加工, 2017(1):72-73.
[6] WHEAL M S, DECOURCY-IRELAND E, BOGARD J R,et al. Measurement of haem and total iron in fish, shrimp and prawn using ICP-MS:Implications for dietary iron intake calculations[J]. Food Chemistry, 2016:201-222.
[7]彭雪梅,刘永文,富中华.微波消解-ICP-AES法测定大米和小麦粉中21种无机元素[J].山西大同大学学报(自然科学版), 2012, 28(2):40-42.
[8]乔秋菊,夏昊云,黄为红,等.微波消解-ICP-MS法测定小麦粉及其制品中17种元素[J].食品研究与开发, 2017,38(17):171-175.
[9]王秀敏,谢令琴,刘艳苏,等.原子吸收光谱法测定小麦品种子粒中钾钠钙镁的含量[J].河北农业大学学报, 2003,26(4):90-92.
[10]汪学荣,彭顺清,吴峰.钙代谢及生理功能研究进展[J].中国食品添加剂, 2005(2):20-22.
[11]魏艳敏.牛乳中钠、钾、钙、镁元素含量测定的研究[J].中国乳业, 2016(12):59-61.
[12]PERRINGL,NICOLASM,ANDREYD,etal.Development and validation of an ED-XRF method for the fast quantification of mineral elements in dry pet food samples[J].Food Analytical Methods, 2017, 10(5):1469-1478.
[13]许艳霞,倪小英. X射线荧光光谱法测定稻米镉含量的影响因素[J].粮食与饲料工业, 2017, 12(6):60-64.
[14]陆金鑫,贾明哲,时超,等.基于无标样定量分析的X射线荧光光谱法快速测定谷物中多种营养元素[J].中国粮油学报, 2016, 31(7):138-141.
[15]倪子月,陈吉文.能量色散X射线荧光光谱法快速测定烟草中的镉和铅[J].中国烟草学报, 2016, 22(4):8-13.
[16] RIBEIRO R O, MáRSICO E T, DE JESUS E F, et al.Determination of trace elements in honey from different regions in Rio de Janeiro State(Brazil)by total reflection X-ray fluorescence.[J]. Journal of Food Science, 2014, 79(4):T738.
[17] PERRING L, ANDREY D. Multi-elemental ED-XRF determination in dehydrated bouillon and sauce base products[J].Food Analytical Methods, 2017(5):1-13.
[18]程锋,谷懿,葛良全,等.原位能量色散X射线荧光分析中岩样基体效应及其修正研究[J].光谱学与光谱分析, 2017,37(3):919-923.
[19]张凤菊,刘晓娟,赵丽平,等.数据差异显著性检验[J].农机使用与维修, 2012(4):51-52.
[20]沈玉芳.不同土层水、氮、磷空间组合对冬小麦生理生态特征的影响[D].杨凌:西北农林科技大学, 2007.