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

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

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

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 4

(a) Fluorescence spectra of QDs (curve a) and QDs@ssDNA2 (curve b); (b) UV-vis absorption spectrum of QDs and QDs@ssDNA2.</p

Determination of <i>S</i>. <i>Typhimurium</i> in real samples.

Determination of S. Typhimurium in real samples.</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 5

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