Data_Sheet_2_Discrimination of Geographical Origin of Agricultural Products From Small-Scale Districts by Widely Targeted Metabolomics With a Case Study on Pinggu Peach.PDF

Geographical indications of agricultural products are characterized by high quality and regional attributes, while they are more likely to be counterfeited by similar products from nearby regions. Accurate discrimination of origin on small geographical scales is extremely important for geographical indications of agricultural products to avoid food fraud. In this study, a widely targeted metabolomics based on ultra-high-performance liquid chromatography–tandem mass spectrometry combined with multivariate statistical analysis was used to distinguish the geographical origin of Pinggu Peach of Beijing and its two surrounding areas in Heibei province (China). Orthogonal partial least squares-discriminant analysis (OPLS-DA) based on 159 identified metabolites showed significant separation from Pinggu and the other adjacent regions. The number of the most important discriminant variables (VIP value >1) was up to 62, which contributed to the differentiation model. The results demonstrated that the metabolic fingerprinting combined with OPLS-DA could be successfully implemented to differentiate the geographical origin of peach from small-scale origins, thus providing technical support to further ensure the authenticity of geographical indication products. The greenness of the developed method was assessed using the Analytical GREEnness Metric Approach and Software (ARGEE) tool. It was a relatively green analytical method with room for improvement.</p

Data_Sheet_1_Discrimination of Geographical Origin of Agricultural Products From Small-Scale Districts by Widely Targeted Metabolomics With a Case Study on Pinggu Peach.pdf

Geographical indications of agricultural products are characterized by high quality and regional attributes, while they are more likely to be counterfeited by similar products from nearby regions. Accurate discrimination of origin on small geographical scales is extremely important for geographical indications of agricultural products to avoid food fraud. In this study, a widely targeted metabolomics based on ultra-high-performance liquid chromatography–tandem mass spectrometry combined with multivariate statistical analysis was used to distinguish the geographical origin of Pinggu Peach of Beijing and its two surrounding areas in Heibei province (China). Orthogonal partial least squares-discriminant analysis (OPLS-DA) based on 159 identified metabolites showed significant separation from Pinggu and the other adjacent regions. The number of the most important discriminant variables (VIP value >1) was up to 62, which contributed to the differentiation model. The results demonstrated that the metabolic fingerprinting combined with OPLS-DA could be successfully implemented to differentiate the geographical origin of peach from small-scale origins, thus providing technical support to further ensure the authenticity of geographical indication products. The greenness of the developed method was assessed using the Analytical GREEnness Metric Approach and Software (ARGEE) tool. It was a relatively green analytical method with room for improvement.</p

Effect of land use type on metals accumulation and risk assessment in soil in the peri-urban area of Beijing, China

<p>Heavy metal concentrations of As, Cd, Cu, Hg, Ni, Pb, and Zn were investigated for 107 soil samples collected from crop land, orchard land, greenhouse land, and wood land in the peri-urban area of Beijing, China. The mean concentrations of As, Cd, Cu, Hg, Ni, Pb, and Zn in all soil samples were 8.40, 0.20, 24.7, 0.08, 25.0, 23.0, and 77.1 mg/kg, dw, respectively. Among the four land use types, the Cd concentration in greenhouse land was significantly higher than the other three kinds of land uses (<i>p</i> < .05), and Cu and Zn concentrations in greenhouse land were significantly higher than in crop land and wood land (<i>p</i> < .05). Based on principal component analysis, elevated Cu, Zn, and Cd concentrations in greenhouse land might have originated from high application rates of manure and fertilizer. According to an ecological risk analysis, the four land use types can be ranked in the following order: greenhouse land > orchard land > crop land > wood land. However, the degree of non-cancer risk for both adults and children in different land uses decreased in the order of greenhouse land > orchard land > wood land > crop land.</p

Aptamer-based fluorometric determination of <i>Salmonella Typhimurium</i> using Fe₃O₄ magnetic separation and CdTe quantum dots - Fig 3

TEM (a) and HRTEM (b) images of CdTe QDs.</p

Aptamer-based fluorometric determination of <i>Salmonella Typhimurium</i> using Fe₃O₄ magnetic separation and CdTe quantum dots - Fig 7

(a) Fluorescence spectra of aptasensors with different concentrations (from a to h: 1010, 107, 105, 104, 103, 102, 10, 0 cfu•mL-1) of S. Typhimurium; (b) calibration curve of the fluorescence intensity of the QDs@ssDNA2 at 612 nm for S. Typhimurium detection.</p

Specificity result for the detection of <i>S</i>. <i>enteritidis</i>, <i>S</i>. <i>aureus</i>, <i>E</i>. <i>coli O157</i>:<i>H7</i>, <i>L</i>. <i>monocytogenes</i>, <i>B</i>. <i>cereus</i>, <i>P</i>. <i>aeruginosa</i> and <i>S</i>. <i>Typhimurium</i>.

Specificity result for the detection of S. enteritidis, S. aureus, E. coli O157:H7, L. monocytogenes, B. cereus, P. aeruginosa and S. Typhimurium.</p

Aptamer-based fluorometric determination of <i>Salmonella Typhimurium</i> using Fe₃O₄ magnetic separation and CdTe quantum dots - Fig 1

The flow chart diagram of synthesis of QDs (a), QDs-ssDNA2 (b) and aptamer@MNPs (c).</p

Aptamer-based fluorometric determination of <i>Salmonella Typhimurium</i> using Fe₃O₄ magnetic separation and CdTe quantum dots - Fig 6

(a) UV-visible absorption spectrum of 10 μL of 1 mg•mL-1 streptavidin-coated MNPs decorated with 50 μL of 10 nM aptamer. (b) Fluorescence spectra of different concentrations (from 70 μL to 10 μL) of ssDNA2@CdTe QDs of 30 μg·mL-1 ssDNA2@CdTe QDs. (c) Fluorescence spectra of aptamer&QDs-ssDNA2@MNPs after different incubation times with S. Typhimurium. (d) Fluorescence spectra of aptamer&QDs-ssDNA2@MNPs incubated with S. Typhimurium at different incubation temperatures.</p

Aptamer-based fluorometric determination of <i>Salmonella Typhimurium</i> using Fe₃O₄ magnetic separation and CdTe quantum dots - Fig 5

UV-vis absorption spectrum of MNPs@aptamer (curve a) and aptamer (curve b).</p

Comparison of different methods for the detection of <i>S</i>. <i>Typhimurium</i>.

Comparison of different methods for the detection of S. Typhimurium.</p