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Multielement Principal Component Analysis and Origin Traceability of Rice Based on ICP-MS/MS
In this experiment, inductively coupled plasma tandem mass spectrometry (ICP-MS/MS) was used to determine the content of 30 elements in rice from six places of production and to explore the relationship between the multielement content in rice and the producing area. The contents of Ca, P, S, Zn, Cu...
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Published in: | Journal of food quality 2021, Vol.2021, p.1-12 |
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description | In this experiment, inductively coupled plasma tandem mass spectrometry (ICP-MS/MS) was used to determine the content of 30 elements in rice from six places of production and to explore the relationship between the multielement content in rice and the producing area. The contents of Ca, P, S, Zn, Cu, Fe, Mn, K, Mg, Na, Ge, Sb, Ba, Ti, V, Se, As, Sr, Mo, Ni, Co, Cr, Al, Li, Cs, Pb, Cd, B, In, and Sn in rice were determined by ICP-MS/MS in the SQ and MS/MS mode. By passing H2, O2, He, and NH3/He reaction gas into the ICP-MS/MS, respectively, the interference was eliminated by means of in situ mass spectrometry and mass transfer. The detection limit of each element was 0.0000662–0.144 mg/kg, and the limit of quantification was in the range of 0.000221–0.479 mg/kg, the linear correlation coefficient was greater or equal to 0.9987 (R2 ≥ 0.9987), and the detection results had low detection limit and great linear regression. Recovery of the method was in the range of 80.6% to 110.5% with spike levels of 0.10–100.00 mg/kg, and relative standard deviations were lower than 10%. For the multielement content of rice from different producing areas, the principal component factor analysis can get six principal component factors, 87.878% cumulative contribution rate, and the distribution of the principal component scores of each element and different producing areas. Based on the multielement content and cluster analysis, the samples were accurately divided into two major categories and six subcategories according to the places of production, which proved that there was a significant correlation between the multielement content in rice and the place of production, so that the place of rice origin can be traced. |
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The contents of Ca, P, S, Zn, Cu, Fe, Mn, K, Mg, Na, Ge, Sb, Ba, Ti, V, Se, As, Sr, Mo, Ni, Co, Cr, Al, Li, Cs, Pb, Cd, B, In, and Sn in rice were determined by ICP-MS/MS in the SQ and MS/MS mode. By passing H2, O2, He, and NH3/He reaction gas into the ICP-MS/MS, respectively, the interference was eliminated by means of in situ mass spectrometry and mass transfer. The detection limit of each element was 0.0000662–0.144 mg/kg, and the limit of quantification was in the range of 0.000221–0.479 mg/kg, the linear correlation coefficient was greater or equal to 0.9987 (R2 ≥ 0.9987), and the detection results had low detection limit and great linear regression. Recovery of the method was in the range of 80.6% to 110.5% with spike levels of 0.10–100.00 mg/kg, and relative standard deviations were lower than 10%. For the multielement content of rice from different producing areas, the principal component factor analysis can get six principal component factors, 87.878% cumulative contribution rate, and the distribution of the principal component scores of each element and different producing areas. Based on the multielement content and cluster analysis, the samples were accurately divided into two major categories and six subcategories according to the places of production, which proved that there was a significant correlation between the multielement content in rice and the place of production, so that the place of rice origin can be traced.</description><identifier>ISSN: 0146-9428</identifier><identifier>EISSN: 1745-4557</identifier><identifier>DOI: 10.1155/2021/5536241</identifier><language>eng</language><publisher>Cairo: Hindawi</publisher><subject>Analysis ; Correlation coefficient ; Factor analysis ; Food quality ; Gases ; Mass spectrometry ; Mass transfer ; Methods ; Plasma ; Principal components analysis ; Reagents ; Reference materials ; Scientific imaging</subject><ispartof>Journal of food quality, 2021, Vol.2021, p.1-12</ispartof><rights>Copyright © 2021 Yan Wang et al.</rights><rights>COPYRIGHT 2021 John Wiley & Sons, Inc.</rights><rights>Copyright © 2021 Yan Wang et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c481t-484aa3b834f062d79818a69bdb4e5b6f1e1e3877956618ac3e21f45fb827be723</citedby><cites>FETCH-LOGICAL-c481t-484aa3b834f062d79818a69bdb4e5b6f1e1e3877956618ac3e21f45fb827be723</cites><orcidid>0000-0002-2947-1629 ; 0000-0002-5156-9251 ; 0000-0002-5568-0387 ; 0000-0003-2335-9078 ; 0000-0001-5744-1403 ; 0000-0001-8615-9917 ; 0000-0002-3126-5023</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2578641829/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2578641829?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,777,781,4010,25734,27904,27905,27906,36993,44571,74875</link.rule.ids></links><search><contributor>Signes-Pastor, Antonio J.</contributor><contributor>Antonio J Signes-Pastor</contributor><creatorcontrib>Wang, Yan</creatorcontrib><creatorcontrib>Yuan, Xiaoxuan</creatorcontrib><creatorcontrib>Liu, Linan</creatorcontrib><creatorcontrib>Ma, Junmei</creatorcontrib><creatorcontrib>Fan, Sufang</creatorcontrib><creatorcontrib>Zhang, Yan</creatorcontrib><creatorcontrib>Li, Qiang</creatorcontrib><title>Multielement Principal Component Analysis and Origin Traceability of Rice Based on ICP-MS/MS</title><title>Journal of food quality</title><description>In this experiment, inductively coupled plasma tandem mass spectrometry (ICP-MS/MS) was used to determine the content of 30 elements in rice from six places of production and to explore the relationship between the multielement content in rice and the producing area. The contents of Ca, P, S, Zn, Cu, Fe, Mn, K, Mg, Na, Ge, Sb, Ba, Ti, V, Se, As, Sr, Mo, Ni, Co, Cr, Al, Li, Cs, Pb, Cd, B, In, and Sn in rice were determined by ICP-MS/MS in the SQ and MS/MS mode. By passing H2, O2, He, and NH3/He reaction gas into the ICP-MS/MS, respectively, the interference was eliminated by means of in situ mass spectrometry and mass transfer. The detection limit of each element was 0.0000662–0.144 mg/kg, and the limit of quantification was in the range of 0.000221–0.479 mg/kg, the linear correlation coefficient was greater or equal to 0.9987 (R2 ≥ 0.9987), and the detection results had low detection limit and great linear regression. Recovery of the method was in the range of 80.6% to 110.5% with spike levels of 0.10–100.00 mg/kg, and relative standard deviations were lower than 10%. For the multielement content of rice from different producing areas, the principal component factor analysis can get six principal component factors, 87.878% cumulative contribution rate, and the distribution of the principal component scores of each element and different producing areas. 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The contents of Ca, P, S, Zn, Cu, Fe, Mn, K, Mg, Na, Ge, Sb, Ba, Ti, V, Se, As, Sr, Mo, Ni, Co, Cr, Al, Li, Cs, Pb, Cd, B, In, and Sn in rice were determined by ICP-MS/MS in the SQ and MS/MS mode. By passing H2, O2, He, and NH3/He reaction gas into the ICP-MS/MS, respectively, the interference was eliminated by means of in situ mass spectrometry and mass transfer. The detection limit of each element was 0.0000662–0.144 mg/kg, and the limit of quantification was in the range of 0.000221–0.479 mg/kg, the linear correlation coefficient was greater or equal to 0.9987 (R2 ≥ 0.9987), and the detection results had low detection limit and great linear regression. Recovery of the method was in the range of 80.6% to 110.5% with spike levels of 0.10–100.00 mg/kg, and relative standard deviations were lower than 10%. For the multielement content of rice from different producing areas, the principal component factor analysis can get six principal component factors, 87.878% cumulative contribution rate, and the distribution of the principal component scores of each element and different producing areas. Based on the multielement content and cluster analysis, the samples were accurately divided into two major categories and six subcategories according to the places of production, which proved that there was a significant correlation between the multielement content in rice and the place of production, so that the place of rice origin can be traced.</abstract><cop>Cairo</cop><pub>Hindawi</pub><doi>10.1155/2021/5536241</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-2947-1629</orcidid><orcidid>https://orcid.org/0000-0002-5156-9251</orcidid><orcidid>https://orcid.org/0000-0002-5568-0387</orcidid><orcidid>https://orcid.org/0000-0003-2335-9078</orcidid><orcidid>https://orcid.org/0000-0001-5744-1403</orcidid><orcidid>https://orcid.org/0000-0001-8615-9917</orcidid><orcidid>https://orcid.org/0000-0002-3126-5023</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Analysis Correlation coefficient Factor analysis Food quality Gases Mass spectrometry Mass transfer Methods Plasma Principal components analysis Reagents Reference materials Scientific imaging |
title | Multielement Principal Component Analysis and Origin Traceability of Rice Based on ICP-MS/MS |
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