[Effect of Characteristic Variable Extraction on Accuracy of Cu in Navel Orange Peel by LIBS].
Identifieur interne : 001E41 ( Ncbi/Checkpoint ); précédent : 001E40; suivant : 001E42[Effect of Characteristic Variable Extraction on Accuracy of Cu in Navel Orange Peel by LIBS].
Auteurs : Wen-Bing Li ; Ming-Yin Yao ; Lin Huang ; Tian-Bing Chen ; Jian-Hong Zheng ; Shi-Quan Fan ; Mu-Hua Liu Mu-Hua He ; Jin-Long Lin ; Jing-Yi OuyangSource :
- Guang pu xue yu guang pu fen xi = Guang pu [ 1000-0593 ] ; 2015.
English descriptors
- KwdEn :
- MESH :
- chemical , analysis : Copper.
- analysis : Food Contamination.
- chemistry : Citrus sinensis, Fruit.
- Calibration, Lasers, Spectrophotometry, Atomic.
Abstract
Heavy metals pollution in foodstuffs is more and more serious. It is impossible to satisfy the modern agricultural development by conventional chemical analysis. Laser induced breakdown spectroscopy (LIBS) is an emerging technology with the characteristic of rapid and nondestructive detection. But LIBS' s repeatability, sensitivity and accuracy has much room to improve. In this work, heavy metal Cu in Gannan Navel Orange which is the Jiangxi specialty fruit will be predicted by LIBS. Firstly, the navel orange samples were contaminated in our lab. The spectra of samples were collected by irradiating the peel by optimized LIBS parameters. The laser energy was set as 20 mJ, delay time of Spectral Data Gathering was set as 1.2 micros, the integration time of Spectral data gathering was set as 2 ms. The real concentration in samples was obtained by AAS (atom absorption spectroscopy). The characteristic variables Cu I 324.7 and Cu I 327.4 were extracted. And the calibration model was constructed between LIBS spectra and real concentration about Cu. The results show that relative error of the predicted concentrations of three relational model were 7.01% or less, reached a minimum of 0.02%, 0.01% and 0.02% respectively. The average relative errors were 2.33%, 3.10% and 26.3%. Tests showed that different characteristic variables decided different accuracy. It is very important to choose suitable characteristic variable. At the same time, this work is helpful to explore the distribution of heavy metals between pulp and peel.
PubMed: 26717771
Affiliations:
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<author><name sortKey="Li, Wen Bing" sort="Li, Wen Bing" uniqKey="Li W" first="Wen-Bing" last="Li">Wen-Bing Li</name>
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<author><name sortKey="Yao, Ming Yin" sort="Yao, Ming Yin" uniqKey="Yao M" first="Ming-Yin" last="Yao">Ming-Yin Yao</name>
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<author><name sortKey="Huang, Lin" sort="Huang, Lin" uniqKey="Huang L" first="Lin" last="Huang">Lin Huang</name>
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<author><name sortKey="Chen, Tian Bing" sort="Chen, Tian Bing" uniqKey="Chen T" first="Tian-Bing" last="Chen">Tian-Bing Chen</name>
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<author><name sortKey="Zheng, Jian Hong" sort="Zheng, Jian Hong" uniqKey="Zheng J" first="Jian-Hong" last="Zheng">Jian-Hong Zheng</name>
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<author><name sortKey="Fan, Shi Quan" sort="Fan, Shi Quan" uniqKey="Fan S" first="Shi-Quan" last="Fan">Shi-Quan Fan</name>
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<author><name sortKey="Liu Mu Hua He, Mu Hua" sort="Liu Mu Hua He, Mu Hua" uniqKey="Liu Mu Hua He M" first="Mu-Hua" last="Liu Mu-Hua He">Mu-Hua Liu Mu-Hua He</name>
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<author><name sortKey="Lin, Jin Long" sort="Lin, Jin Long" uniqKey="Lin J" first="Jin-Long" last="Lin">Jin-Long Lin</name>
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<author><name sortKey="Ouyang, Jing Yi" sort="Ouyang, Jing Yi" uniqKey="Ouyang J" first="Jing-Yi" last="Ouyang">Jing-Yi Ouyang</name>
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<author><name sortKey="Li, Wen Bing" sort="Li, Wen Bing" uniqKey="Li W" first="Wen-Bing" last="Li">Wen-Bing Li</name>
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<author><name sortKey="Yao, Ming Yin" sort="Yao, Ming Yin" uniqKey="Yao M" first="Ming-Yin" last="Yao">Ming-Yin Yao</name>
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<author><name sortKey="Huang, Lin" sort="Huang, Lin" uniqKey="Huang L" first="Lin" last="Huang">Lin Huang</name>
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<author><name sortKey="Chen, Tian Bing" sort="Chen, Tian Bing" uniqKey="Chen T" first="Tian-Bing" last="Chen">Tian-Bing Chen</name>
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<author><name sortKey="Zheng, Jian Hong" sort="Zheng, Jian Hong" uniqKey="Zheng J" first="Jian-Hong" last="Zheng">Jian-Hong Zheng</name>
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<author><name sortKey="Fan, Shi Quan" sort="Fan, Shi Quan" uniqKey="Fan S" first="Shi-Quan" last="Fan">Shi-Quan Fan</name>
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<author><name sortKey="Liu Mu Hua He, Mu Hua" sort="Liu Mu Hua He, Mu Hua" uniqKey="Liu Mu Hua He M" first="Mu-Hua" last="Liu Mu-Hua He">Mu-Hua Liu Mu-Hua He</name>
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<author><name sortKey="Lin, Jin Long" sort="Lin, Jin Long" uniqKey="Lin J" first="Jin-Long" last="Lin">Jin-Long Lin</name>
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<author><name sortKey="Ouyang, Jing Yi" sort="Ouyang, Jing Yi" uniqKey="Ouyang J" first="Jing-Yi" last="Ouyang">Jing-Yi Ouyang</name>
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<series><title level="j">Guang pu xue yu guang pu fen xi = Guang pu</title>
<idno type="ISSN">1000-0593</idno>
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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Calibration</term>
<term>Citrus sinensis (chemistry)</term>
<term>Copper (analysis)</term>
<term>Food Contamination (analysis)</term>
<term>Fruit (chemistry)</term>
<term>Lasers</term>
<term>Spectrophotometry, Atomic</term>
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<keywords scheme="MESH" type="chemical" qualifier="analysis" xml:lang="en"><term>Copper</term>
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<keywords scheme="MESH" qualifier="analysis" xml:lang="en"><term>Food Contamination</term>
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<keywords scheme="MESH" qualifier="chemistry" xml:lang="en"><term>Citrus sinensis</term>
<term>Fruit</term>
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<keywords scheme="MESH" xml:lang="en"><term>Calibration</term>
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<front><div type="abstract" xml:lang="en">Heavy metals pollution in foodstuffs is more and more serious. It is impossible to satisfy the modern agricultural development by conventional chemical analysis. Laser induced breakdown spectroscopy (LIBS) is an emerging technology with the characteristic of rapid and nondestructive detection. But LIBS' s repeatability, sensitivity and accuracy has much room to improve. In this work, heavy metal Cu in Gannan Navel Orange which is the Jiangxi specialty fruit will be predicted by LIBS. Firstly, the navel orange samples were contaminated in our lab. The spectra of samples were collected by irradiating the peel by optimized LIBS parameters. The laser energy was set as 20 mJ, delay time of Spectral Data Gathering was set as 1.2 micros, the integration time of Spectral data gathering was set as 2 ms. The real concentration in samples was obtained by AAS (atom absorption spectroscopy). The characteristic variables Cu I 324.7 and Cu I 327.4 were extracted. And the calibration model was constructed between LIBS spectra and real concentration about Cu. The results show that relative error of the predicted concentrations of three relational model were 7.01% or less, reached a minimum of 0.02%, 0.01% and 0.02% respectively. The average relative errors were 2.33%, 3.10% and 26.3%. Tests showed that different characteristic variables decided different accuracy. It is very important to choose suitable characteristic variable. At the same time, this work is helpful to explore the distribution of heavy metals between pulp and peel.</div>
</front>
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<affiliations><list></list>
<tree><noCountry><name sortKey="Chen, Tian Bing" sort="Chen, Tian Bing" uniqKey="Chen T" first="Tian-Bing" last="Chen">Tian-Bing Chen</name>
<name sortKey="Fan, Shi Quan" sort="Fan, Shi Quan" uniqKey="Fan S" first="Shi-Quan" last="Fan">Shi-Quan Fan</name>
<name sortKey="Huang, Lin" sort="Huang, Lin" uniqKey="Huang L" first="Lin" last="Huang">Lin Huang</name>
<name sortKey="Li, Wen Bing" sort="Li, Wen Bing" uniqKey="Li W" first="Wen-Bing" last="Li">Wen-Bing Li</name>
<name sortKey="Lin, Jin Long" sort="Lin, Jin Long" uniqKey="Lin J" first="Jin-Long" last="Lin">Jin-Long Lin</name>
<name sortKey="Liu Mu Hua He, Mu Hua" sort="Liu Mu Hua He, Mu Hua" uniqKey="Liu Mu Hua He M" first="Mu-Hua" last="Liu Mu-Hua He">Mu-Hua Liu Mu-Hua He</name>
<name sortKey="Ouyang, Jing Yi" sort="Ouyang, Jing Yi" uniqKey="Ouyang J" first="Jing-Yi" last="Ouyang">Jing-Yi Ouyang</name>
<name sortKey="Yao, Ming Yin" sort="Yao, Ming Yin" uniqKey="Yao M" first="Ming-Yin" last="Yao">Ming-Yin Yao</name>
<name sortKey="Zheng, Jian Hong" sort="Zheng, Jian Hong" uniqKey="Zheng J" first="Jian-Hong" last="Zheng">Jian-Hong Zheng</name>
</noCountry>
</tree>
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</record>
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