Effects of fertilizers and pesticides on the mineral elements used for the geographical origin traceability of rice

2019 ◽  
Vol 83 ◽  
pp. 103276 ◽  
Author(s):  
Lili Qian ◽  
Caidong Zhang ◽  
Feng Zuo ◽  
Lina Zheng ◽  
Dan Li ◽  
...  
2019 ◽  
Vol 99 (15) ◽  
pp. 6937-6943 ◽  
Author(s):  
Shimao Fang ◽  
Wen‐Jing Huang ◽  
Yuming Wei ◽  
Meng Tao ◽  
Xin Hu ◽  
...  

Food Control ◽  
2020 ◽  
Vol 107 ◽  
pp. 106780
Author(s):  
Shima Behkami ◽  
Rima Gholami ◽  
Mehrdad Gholami ◽  
Rasool Roohparvar

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11928
Author(s):  
Shanjia Li ◽  
Hui Wang ◽  
Ling Jin ◽  
James F. White ◽  
Kathryn L. Kingsley ◽  
...  

Background Place of origin is an important factor when determining the quality and authenticity of Angelica sinensis for medicinal use. It is important to trace the origin and confirm the regional characteristics of medicinal products for sustainable industrial development. Effectively tracing and confirming the material’s origin may be accomplished by detecting stable isotopes and mineral elements. Methods We studied 25 A. sinensis samples collected from three main producing areas (Linxia, Gannan, and Dingxi) in southeastern Gansu Province, China, to better identify its origin. We used inductively coupled plasma mass spectrometry (ICP-MS) and stable isotope ratio mass spectrometry (IRMS) to determine eight mineral elements (K, Mg, Ca, Zn, Cu, Mn, Cr, Al) and three stable isotopes (δ13C, δ15N, δ18O). Principal component analysis (PCA), partial least square discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) were used to verify the validity of its geographical origin. Results K, Ca/Al, δ13C, δ15N and δ18O are important elements to distinguish A. sinensis sampled from Linxia, Gannan and Dingxi. We used an unsupervised PCA model to determine the dimensionality reduction of mineral elements and stable isotopes, which could distinguish the A. sinensis from Linxia. However, it could not easily distinguish A. sinensis sampled from Gannan and Dingxi. The supervised PLS-DA and LDA models could effectively distinguish samples taken from all three regions and perform cross-validation. The cross-validation accuracy of PLS-DA using mineral elements and stable isotopes was 84%, which was higher than LDA using mineral elements and stable isotopes. Conclusions The PLS-DA and LDA models provide a theoretical basis for tracing the origin of A. sinensis in three regions (Linxia, Gannan and Dingxi). This is significant for protecting consumers’ health, rights and interests.


Molecules ◽  
2018 ◽  
Vol 23 (11) ◽  
pp. 3013 ◽  
Author(s):  
Jian Zhang ◽  
Ruidong Yang ◽  
Rong Chen ◽  
Yuncong Li ◽  
Yishu Peng ◽  
...  

This study aimed to construct objective and accurate geographical discriminant models for tea leaves based on multielement concentrations in combination with chemometrics tools. Forty mineral elements in 87 tea samples from three growing regions in Guizhou Province (China), namely Meitan and Fenggang (MTFG), Anshun (AS) and Leishan (LS) were analyzed. Chemometrics evaluations were conducted using a one-way analysis of variance (ANOVA), principal component analysis (PCA), linear discriminant analysis (LDA), and orthogonal partial least squares discriminant analysis (OPLS-DA). The results showed that the concentrations of the 28 elements were significantly different among the three regions (p < 0.05). The correct classification rates for the 87 tea samples were 98.9% for LDA and 100% for OPLS-DA. The variable importance in the projection (VIP) values ranged between 1.01–1.73 for 11 elements (Sb, Pb, K, As, S, Bi, U, P, Ca, Na, and Cr), which can be used as important indicators for geographical origin identification of tea samples. In conclusion, multielement analysis coupled with chemometrics can be useful for geographical origin identification of tea leaves.


2020 ◽  
Vol 12 (1) ◽  
pp. 9-20
Author(s):  
Na Wang ◽  
◽  
Dongjie Zhang* ◽  
Jinming Liu ◽  
◽  
...  

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