Long-Term Agricultural Effects on the Authentication Accuracy of Organic, Green, and Conventional Rice Using Isotopic and Elemental Chemometric Analyses

Organically farmed rice is believed to be healthier, safer, and eco-friendlier than its conventionally farmed counterparts and sells for a premium price in global markets. Deliberate mislabeling of organic rice has become a critical consumer concern in China and elsewhere, and there is an increased...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of agricultural and food chemistry 2020-02, Vol.68 (5), p.1213-1225
Hauptverfasser: Liu, Zhi, Yuan, Yuwei, Xie, Tongzhou, Zhang, Yongzhi, Shao, Shengzhi, Nie, Jing, Xia, Wei, Rogers, Karyne M, Zhang, Weixing
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 1225
container_issue 5
container_start_page 1213
container_title Journal of agricultural and food chemistry
container_volume 68
creator Liu, Zhi
Yuan, Yuwei
Xie, Tongzhou
Zhang, Yongzhi
Shao, Shengzhi
Nie, Jing
Xia, Wei
Rogers, Karyne M
Zhang, Weixing
description Organically farmed rice is believed to be healthier, safer, and eco-friendlier than its conventionally farmed counterparts and sells for a premium price in global markets. Deliberate mislabeling of organic rice has become a critical consumer concern in China and elsewhere, and there is an increased risk of buying fraudulent organic rice in the market place. In this study, stable isotopic and multielemental analysis combined with chemometrics was used to differentiate organically farmed rice from green and conventional rice in a 4-year experimental field trial from 2014 to 2017. A total of 108 rice samples and their associated soils were collected during the study from three farming (fertilization) systems to investigate whether there are long-term changes in the rice farming classification accuracy from climate effects. Stable carbon and nitrogen isotopic ratios (i.e., δ13C and δ15N) and 27 elemental contents (e.g., Na, K, Ca, Fe, and Zn) of rice and soil samples were determined and then evaluated using statistical analysis [i.e., one-way analysis of variance, multivariable correlation analysis, and modeling of partial least-squares discriminant analysis]. Although δ15N values can be an effective indicator for organic rice authentication during one crop rotation, both δ13C and δ15N values of rice were easily affected by rice cultivar and interannual soil fertilization and localized agroclimatic variations. These two isotopes were not able to separate organic rice from green and conventional rice accurately. Elemental contents of green and conventional rice (especially K and Ca) were found at higher levels due to the abundant application of synthetic fertilizers (e.g., KNO3, KH2PO4, and CaHPO4), unlike organically farmed rice, which primarily used animal manure and composts. Partial least-squares discriminant analysis modeling combined isotopic and elemental signatures to correctly differentiate organic rice from green and conventional counterparts, with an accuracy up to 100% over the 4-year study. Therefore, this multi-isotope and -element strategy proposes a more rigorous, alternative tool to combat fraudulent mislabeling of organic rice, increasing the trust of organically labeled rice products and supporting the integrity of the organic sector worldwide.
doi_str_mv 10.1021/acs.jafc.9b06847
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2333927307</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2333927307</sourcerecordid><originalsourceid>FETCH-LOGICAL-a336t-8b01a4d689768450a1c8b65c50a51915f6cccb2334423765b9a8bc36b22a24213</originalsourceid><addsrcrecordid>eNp1kU9r2zAYh8XYWLNu952GjjvEmf5Ytnw0IesKgcJoz0Z-I6cqtpRJ8iDfpB93b5qst14kIZ7f70V6CPnK2YozwX8YSKsnM8Cq6Vmly_odWXAlWKE41-_JgiFTaFXxK_IppSfGmFY1-0iuJG-YrEu9IM_b4PfFvY0TbffRwTzmOZqRbobBQk40eJofLW1nXH12YLLDqxYAKTjSMNC7uDfewZLeRGv9khq_o-vg_57w4LHqtwNLH5Lze3qbQg4HBy_QZrQTQkisH-0UJptxPm0xckw2fSYfBjMm--WyX5OHn5v79a9ie3dzu263hZGyyoXuGTflrtJNjR-gmOGg-0oBnhRvuBoqAOiFlGUpZF2pvjG6B1n1QhhRCi6vyfdz7yGGP7NNuZtcAjuOxtswpw6jshG1ZDWi7IxCDClFO3SH6CYTjx1n3clHhz66k4_u4gMj3y7tcz_Z3WvgvwAElmfgJRrmiM9Pb_f9AxEcl6c</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2333927307</pqid></control><display><type>article</type><title>Long-Term Agricultural Effects on the Authentication Accuracy of Organic, Green, and Conventional Rice Using Isotopic and Elemental Chemometric Analyses</title><source>MEDLINE</source><source>American Chemical Society Journals</source><creator>Liu, Zhi ; Yuan, Yuwei ; Xie, Tongzhou ; Zhang, Yongzhi ; Shao, Shengzhi ; Nie, Jing ; Xia, Wei ; Rogers, Karyne M ; Zhang, Weixing</creator><creatorcontrib>Liu, Zhi ; Yuan, Yuwei ; Xie, Tongzhou ; Zhang, Yongzhi ; Shao, Shengzhi ; Nie, Jing ; Xia, Wei ; Rogers, Karyne M ; Zhang, Weixing</creatorcontrib><description>Organically farmed rice is believed to be healthier, safer, and eco-friendlier than its conventionally farmed counterparts and sells for a premium price in global markets. Deliberate mislabeling of organic rice has become a critical consumer concern in China and elsewhere, and there is an increased risk of buying fraudulent organic rice in the market place. In this study, stable isotopic and multielemental analysis combined with chemometrics was used to differentiate organically farmed rice from green and conventional rice in a 4-year experimental field trial from 2014 to 2017. A total of 108 rice samples and their associated soils were collected during the study from three farming (fertilization) systems to investigate whether there are long-term changes in the rice farming classification accuracy from climate effects. Stable carbon and nitrogen isotopic ratios (i.e., δ13C and δ15N) and 27 elemental contents (e.g., Na, K, Ca, Fe, and Zn) of rice and soil samples were determined and then evaluated using statistical analysis [i.e., one-way analysis of variance, multivariable correlation analysis, and modeling of partial least-squares discriminant analysis]. Although δ15N values can be an effective indicator for organic rice authentication during one crop rotation, both δ13C and δ15N values of rice were easily affected by rice cultivar and interannual soil fertilization and localized agroclimatic variations. These two isotopes were not able to separate organic rice from green and conventional rice accurately. Elemental contents of green and conventional rice (especially K and Ca) were found at higher levels due to the abundant application of synthetic fertilizers (e.g., KNO3, KH2PO4, and CaHPO4), unlike organically farmed rice, which primarily used animal manure and composts. Partial least-squares discriminant analysis modeling combined isotopic and elemental signatures to correctly differentiate organic rice from green and conventional counterparts, with an accuracy up to 100% over the 4-year study. Therefore, this multi-isotope and -element strategy proposes a more rigorous, alternative tool to combat fraudulent mislabeling of organic rice, increasing the trust of organically labeled rice products and supporting the integrity of the organic sector worldwide.</description><identifier>ISSN: 0021-8561</identifier><identifier>EISSN: 1520-5118</identifier><identifier>DOI: 10.1021/acs.jafc.9b06847</identifier><identifier>PMID: 31903748</identifier><language>eng</language><publisher>United States: American Chemical Society</publisher><subject>Carbon Isotopes - analysis ; China ; Discriminant Analysis ; Fertilizers - analysis ; Food Contamination - analysis ; Food, Organic - analysis ; Nitrogen Isotopes - analysis ; Oryza - chemistry ; Oryza - classification ; Soil - chemistry ; Trace Elements - analysis</subject><ispartof>Journal of agricultural and food chemistry, 2020-02, Vol.68 (5), p.1213-1225</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a336t-8b01a4d689768450a1c8b65c50a51915f6cccb2334423765b9a8bc36b22a24213</citedby><cites>FETCH-LOGICAL-a336t-8b01a4d689768450a1c8b65c50a51915f6cccb2334423765b9a8bc36b22a24213</cites><orcidid>0000-0001-8464-4337</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://pubs.acs.org/doi/pdf/10.1021/acs.jafc.9b06847$$EPDF$$P50$$Gacs$$H</linktopdf><linktohtml>$$Uhttps://pubs.acs.org/doi/10.1021/acs.jafc.9b06847$$EHTML$$P50$$Gacs$$H</linktohtml><link.rule.ids>314,780,784,2765,27076,27924,27925,56738,56788</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31903748$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Liu, Zhi</creatorcontrib><creatorcontrib>Yuan, Yuwei</creatorcontrib><creatorcontrib>Xie, Tongzhou</creatorcontrib><creatorcontrib>Zhang, Yongzhi</creatorcontrib><creatorcontrib>Shao, Shengzhi</creatorcontrib><creatorcontrib>Nie, Jing</creatorcontrib><creatorcontrib>Xia, Wei</creatorcontrib><creatorcontrib>Rogers, Karyne M</creatorcontrib><creatorcontrib>Zhang, Weixing</creatorcontrib><title>Long-Term Agricultural Effects on the Authentication Accuracy of Organic, Green, and Conventional Rice Using Isotopic and Elemental Chemometric Analyses</title><title>Journal of agricultural and food chemistry</title><addtitle>J. Agric. Food Chem</addtitle><description>Organically farmed rice is believed to be healthier, safer, and eco-friendlier than its conventionally farmed counterparts and sells for a premium price in global markets. Deliberate mislabeling of organic rice has become a critical consumer concern in China and elsewhere, and there is an increased risk of buying fraudulent organic rice in the market place. In this study, stable isotopic and multielemental analysis combined with chemometrics was used to differentiate organically farmed rice from green and conventional rice in a 4-year experimental field trial from 2014 to 2017. A total of 108 rice samples and their associated soils were collected during the study from three farming (fertilization) systems to investigate whether there are long-term changes in the rice farming classification accuracy from climate effects. Stable carbon and nitrogen isotopic ratios (i.e., δ13C and δ15N) and 27 elemental contents (e.g., Na, K, Ca, Fe, and Zn) of rice and soil samples were determined and then evaluated using statistical analysis [i.e., one-way analysis of variance, multivariable correlation analysis, and modeling of partial least-squares discriminant analysis]. Although δ15N values can be an effective indicator for organic rice authentication during one crop rotation, both δ13C and δ15N values of rice were easily affected by rice cultivar and interannual soil fertilization and localized agroclimatic variations. These two isotopes were not able to separate organic rice from green and conventional rice accurately. Elemental contents of green and conventional rice (especially K and Ca) were found at higher levels due to the abundant application of synthetic fertilizers (e.g., KNO3, KH2PO4, and CaHPO4), unlike organically farmed rice, which primarily used animal manure and composts. Partial least-squares discriminant analysis modeling combined isotopic and elemental signatures to correctly differentiate organic rice from green and conventional counterparts, with an accuracy up to 100% over the 4-year study. Therefore, this multi-isotope and -element strategy proposes a more rigorous, alternative tool to combat fraudulent mislabeling of organic rice, increasing the trust of organically labeled rice products and supporting the integrity of the organic sector worldwide.</description><subject>Carbon Isotopes - analysis</subject><subject>China</subject><subject>Discriminant Analysis</subject><subject>Fertilizers - analysis</subject><subject>Food Contamination - analysis</subject><subject>Food, Organic - analysis</subject><subject>Nitrogen Isotopes - analysis</subject><subject>Oryza - chemistry</subject><subject>Oryza - classification</subject><subject>Soil - chemistry</subject><subject>Trace Elements - analysis</subject><issn>0021-8561</issn><issn>1520-5118</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kU9r2zAYh8XYWLNu952GjjvEmf5Ytnw0IesKgcJoz0Z-I6cqtpRJ8iDfpB93b5qst14kIZ7f70V6CPnK2YozwX8YSKsnM8Cq6Vmly_odWXAlWKE41-_JgiFTaFXxK_IppSfGmFY1-0iuJG-YrEu9IM_b4PfFvY0TbffRwTzmOZqRbobBQk40eJofLW1nXH12YLLDqxYAKTjSMNC7uDfewZLeRGv9khq_o-vg_57w4LHqtwNLH5Lze3qbQg4HBy_QZrQTQkisH-0UJptxPm0xckw2fSYfBjMm--WyX5OHn5v79a9ie3dzu263hZGyyoXuGTflrtJNjR-gmOGg-0oBnhRvuBoqAOiFlGUpZF2pvjG6B1n1QhhRCi6vyfdz7yGGP7NNuZtcAjuOxtswpw6jshG1ZDWi7IxCDClFO3SH6CYTjx1n3clHhz66k4_u4gMj3y7tcz_Z3WvgvwAElmfgJRrmiM9Pb_f9AxEcl6c</recordid><startdate>20200205</startdate><enddate>20200205</enddate><creator>Liu, Zhi</creator><creator>Yuan, Yuwei</creator><creator>Xie, Tongzhou</creator><creator>Zhang, Yongzhi</creator><creator>Shao, Shengzhi</creator><creator>Nie, Jing</creator><creator>Xia, Wei</creator><creator>Rogers, Karyne M</creator><creator>Zhang, Weixing</creator><general>American Chemical Society</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-8464-4337</orcidid></search><sort><creationdate>20200205</creationdate><title>Long-Term Agricultural Effects on the Authentication Accuracy of Organic, Green, and Conventional Rice Using Isotopic and Elemental Chemometric Analyses</title><author>Liu, Zhi ; Yuan, Yuwei ; Xie, Tongzhou ; Zhang, Yongzhi ; Shao, Shengzhi ; Nie, Jing ; Xia, Wei ; Rogers, Karyne M ; Zhang, Weixing</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a336t-8b01a4d689768450a1c8b65c50a51915f6cccb2334423765b9a8bc36b22a24213</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Carbon Isotopes - analysis</topic><topic>China</topic><topic>Discriminant Analysis</topic><topic>Fertilizers - analysis</topic><topic>Food Contamination - analysis</topic><topic>Food, Organic - analysis</topic><topic>Nitrogen Isotopes - analysis</topic><topic>Oryza - chemistry</topic><topic>Oryza - classification</topic><topic>Soil - chemistry</topic><topic>Trace Elements - analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Zhi</creatorcontrib><creatorcontrib>Yuan, Yuwei</creatorcontrib><creatorcontrib>Xie, Tongzhou</creatorcontrib><creatorcontrib>Zhang, Yongzhi</creatorcontrib><creatorcontrib>Shao, Shengzhi</creatorcontrib><creatorcontrib>Nie, Jing</creatorcontrib><creatorcontrib>Xia, Wei</creatorcontrib><creatorcontrib>Rogers, Karyne M</creatorcontrib><creatorcontrib>Zhang, Weixing</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of agricultural and food chemistry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Zhi</au><au>Yuan, Yuwei</au><au>Xie, Tongzhou</au><au>Zhang, Yongzhi</au><au>Shao, Shengzhi</au><au>Nie, Jing</au><au>Xia, Wei</au><au>Rogers, Karyne M</au><au>Zhang, Weixing</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Long-Term Agricultural Effects on the Authentication Accuracy of Organic, Green, and Conventional Rice Using Isotopic and Elemental Chemometric Analyses</atitle><jtitle>Journal of agricultural and food chemistry</jtitle><addtitle>J. Agric. Food Chem</addtitle><date>2020-02-05</date><risdate>2020</risdate><volume>68</volume><issue>5</issue><spage>1213</spage><epage>1225</epage><pages>1213-1225</pages><issn>0021-8561</issn><eissn>1520-5118</eissn><abstract>Organically farmed rice is believed to be healthier, safer, and eco-friendlier than its conventionally farmed counterparts and sells for a premium price in global markets. Deliberate mislabeling of organic rice has become a critical consumer concern in China and elsewhere, and there is an increased risk of buying fraudulent organic rice in the market place. In this study, stable isotopic and multielemental analysis combined with chemometrics was used to differentiate organically farmed rice from green and conventional rice in a 4-year experimental field trial from 2014 to 2017. A total of 108 rice samples and their associated soils were collected during the study from three farming (fertilization) systems to investigate whether there are long-term changes in the rice farming classification accuracy from climate effects. Stable carbon and nitrogen isotopic ratios (i.e., δ13C and δ15N) and 27 elemental contents (e.g., Na, K, Ca, Fe, and Zn) of rice and soil samples were determined and then evaluated using statistical analysis [i.e., one-way analysis of variance, multivariable correlation analysis, and modeling of partial least-squares discriminant analysis]. Although δ15N values can be an effective indicator for organic rice authentication during one crop rotation, both δ13C and δ15N values of rice were easily affected by rice cultivar and interannual soil fertilization and localized agroclimatic variations. These two isotopes were not able to separate organic rice from green and conventional rice accurately. Elemental contents of green and conventional rice (especially K and Ca) were found at higher levels due to the abundant application of synthetic fertilizers (e.g., KNO3, KH2PO4, and CaHPO4), unlike organically farmed rice, which primarily used animal manure and composts. Partial least-squares discriminant analysis modeling combined isotopic and elemental signatures to correctly differentiate organic rice from green and conventional counterparts, with an accuracy up to 100% over the 4-year study. Therefore, this multi-isotope and -element strategy proposes a more rigorous, alternative tool to combat fraudulent mislabeling of organic rice, increasing the trust of organically labeled rice products and supporting the integrity of the organic sector worldwide.</abstract><cop>United States</cop><pub>American Chemical Society</pub><pmid>31903748</pmid><doi>10.1021/acs.jafc.9b06847</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0001-8464-4337</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 0021-8561
ispartof Journal of agricultural and food chemistry, 2020-02, Vol.68 (5), p.1213-1225
issn 0021-8561
1520-5118
language eng
recordid cdi_proquest_miscellaneous_2333927307
source MEDLINE; American Chemical Society Journals
subjects Carbon Isotopes - analysis
China
Discriminant Analysis
Fertilizers - analysis
Food Contamination - analysis
Food, Organic - analysis
Nitrogen Isotopes - analysis
Oryza - chemistry
Oryza - classification
Soil - chemistry
Trace Elements - analysis
title Long-Term Agricultural Effects on the Authentication Accuracy of Organic, Green, and Conventional Rice Using Isotopic and Elemental Chemometric Analyses
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-26T01%3A52%3A05IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Long-Term%20Agricultural%20Effects%20on%20the%20Authentication%20Accuracy%20of%20Organic,%20Green,%20and%20Conventional%20Rice%20Using%20Isotopic%20and%20Elemental%20Chemometric%20Analyses&rft.jtitle=Journal%20of%20agricultural%20and%20food%20chemistry&rft.au=Liu,%20Zhi&rft.date=2020-02-05&rft.volume=68&rft.issue=5&rft.spage=1213&rft.epage=1225&rft.pages=1213-1225&rft.issn=0021-8561&rft.eissn=1520-5118&rft_id=info:doi/10.1021/acs.jafc.9b06847&rft_dat=%3Cproquest_cross%3E2333927307%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2333927307&rft_id=info:pmid/31903748&rfr_iscdi=true