DOI: 10.1021/acs.jafc.9b06847
论文题名: Long-Term Agricultural Effects on the Authentication Accuracy of Organic, Green, and Conventional Rice Using Isotopic and Elemental Chemometric Analyses
作者: Liu Z. ; Yuan Y. ; Xie T. ; Zhang Y. ; Shao S. ; Nie J. ; Xia W. ; Rogers K.M. ; Zhang W.
刊名: Journal of Agricultural and Food Chemistry
ISSN: 218561
出版年: 2020
卷: 68, 期: 5 语种: 英语
英文关键词: climate effects
; organic authentication
; organic rice
; PLS-DA modeling
; stable isotope
; trace element
Scopus关键词: Agriculture
; Authentication
; Composting
; Discriminant analysis
; Fertilizers
; International trade
; Least squares approximations
; Potash
; Potassium Nitrate
; Soils
; Trace elements
; Classification accuracy
; Climate effects
; Multi-elemental analysis
; Multi-variable correlations
; Organic rice
; Partial least squares - discriminant analysis
; Stable isotopes
; Synthetic fertilizers
; Isotopes
英文摘要: 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. © 2020 American Chemical Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/159370
Appears in Collections: 气候变化与战略
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作者单位: State Key Lab. for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-Products, Hangzhou, 310021, China; China National Rice Research Institute, Hangzhou, 310006, China; Jiaxian Rice Product Limited Company, Province, Danyang, Jiangsu, 212341, China; Institute of Quality and Standards for Agricultural Products, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, China; Key Laboratory of Information Traceability for Agricultural Products, Ministry of Agriculture, Hangzhou, 310021, China; National Isotope Centre, GNS Science, 30 Gracefield Road, Lower Hutt, 5040, New Zealand
Recommended Citation:
Liu Z.,Yuan Y.,Xie T.,et al. Long-Term Agricultural Effects on the Authentication Accuracy of Organic, Green, and Conventional Rice Using Isotopic and Elemental Chemometric Analyses[J]. Journal of Agricultural and Food Chemistry,2020-01-01,68(5)