Sampling for Genetically Modified Organisms Content Analysisin Agricultural Products: From Analytical Sample to Test Portion
International Journal of Nutrition and Food Sciences
Volume 8, Issue 1, January 2019, Pages: 23-29
Received: Mar. 12, 2019;
Accepted: Apr. 27, 2019;
Published: May 23, 2019
Views 189 Downloads 47
Jing Xu, Inspection and Quarantine Technology Centre of China Customs, Dalian, China
Jiang Zheng, Inspection and Quarantine Technology Centre of China Customs, Dalian, China
Lu Gao, Inspection and Quarantine Technology Centre of China Customs, Dalian, China
Jijuan Cao, Inspection and Quarantine Technology Centre of China Customs, Dalian, China
Objective: At present, Sampling standards and regulations for genetically modified organisms (GMO) are commonly based on theoretical calculations or computer simulations, and there is a lack of field data to validate these simulations. In view of this situation, we sampled agricultural products for GMO content analysis, and investigated the influence of various factors on the accuracy of the results. We have prepared a three-part series and in this part focused on the process from analytical sample to test portions. Method: Using non-transgenic maize as matrix, 12 lines of transgenic maize were used to produce standard analytical samples. After systematic sampling, the GMO contents of these samples were randomly tested, and their single relative standard deviations (RSD) were calculated as a measure of total RSD (single analysis) per sample. Results: By comparing the RSDs of various sampling methods, it was found that the results of 12 strains were basically consistent, and the data of MON810 were listed as a representative. The parameters affecting the standard deviation included the content (aAS), particle size (dAS), test portion mass (MTP) and the number of increments (nIT). Total analytical RSD could be reduced by decreasing particle size, and increasing test portion mass or the number of increments. Based on current laboratory testing conditions and current used kits, for high content analytical sample(>0.01%), more than 2 duplicate test portions with at least -100mesh particle size and 200mg mass were recommended. Conclusion: Based on the results, the recommended values of particle size, test portion mass and the number of increments for the process from analytical sample to test portions were given. These factors were independent on species or strains of the product, so the results were suitable to all species and strains, provided that the solid particles could be crushed to required particle size.
Sampling for Genetically Modified Organisms Content Analysisin Agricultural Products: From Analytical Sample to Test Portion, International Journal of Nutrition and Food Sciences.
Vol. 8, No. 1,
2019, pp. 23-29.
Http: //www.isaaa.org, (cited 2015-08-20), ISAAA Brief 49-2014: “A record 181.5 million hectares of biotech crops were grown globally in 2014, at an annual growth rate of between 3 and 4%, up 6.3 million hectares from 175.2 million hectares in 2013. This year, 2014, was the 19th year of commercialization, 1996-2014, when growth continued after a remarkable 18 consecutive years of increases every single year; notably 12 of the 18 years were double-digit growth rates.”
Y. Sheng, W. T. Xu, and Y. B. Luo, “Commercialization of enetically modified organisms,” J. Agric Biotech, vol. 12, pp. 1479–1487, 2013.
P. L. Liu, N. Li, and Y. L. Zhou, “Safety administration system for transgenic organism in America and its enligh tenement for China,” J. Agric Sci Tech, vol.5, pp.49–53, 2009.
C. James, “The 2014 global biotech/gm crops commercialization development situation,” China Biotech, vol.1, pp.1–14, 2015.
E. Barbau-Piednoir, P. Stragier, N.Roosens et.al, “Inter-laboratory testing of GMO detection by combinatory SYBR® green PCR screening(Co SYPS),” Food Anal Methods, vol.8, pp. 1719–1728, 2014.
T. Twardowski and A. Malyska, “Uninformed and disinformed society and the GMO market,” Trends Biotechnol, vol.1, pp. 1–3, 2015.
Y. M. Han, G. Q. Zhai, and J. F. Xu, “The evolution of the eu regulation system of transgenic organisms and the enlightenment to our country,” J. Zhejiang Agric Sci, vol.11, pp. 1482–1485, 2013.
K. R. Emslie, L. Whaites, K. R. Griffiths et al, “Sampling plan and test protocol for the semiquantitative detection of genetically modified canola（Brassica napus）seed in bulk canola seed,” J. Agric Food Chem, vol.11, pp.4414–4421, 2007.
S. Kay and C. Paoletti, “Sampling Strategies for GMO detection andor Quantification,” EC Directorate General JRC, 2001.
ISO 542:1990, Oilseeds-Sampling.
ISO 13690:1999, Cereals, pulses and milled products-Sampling of static batches.
S. Kay and V. D. E. Guy, “The limit of GMO detection,” Nature Biotech, vol.19, pp. 405–409, 2001.
ISO 24333:2009, Cereals and cereal products-Sampling.
ISO DTR29263, Cereals and cereal products-Sampling studies.
GB/T 19495.7-2004, Detection of genetically modified organisms and derived products-Methods for sampling preparation.
J. Gilbert, “Sampling of raw materials and processed foods for the presence of GMOs,” Food Control, vol. 10, pp. 363-365, 1999.
G. S. Begg, D. W.Cullen, P. P. M. Iannetta, “Sources of uncertainty in the quantification of genetically modified oilseed rape contamination in seed lots,” Transgenic Research, vol. 16, No. 1, pp. 51-63, 2007.
C. Brera, E. Donnarumma, R. Onori, “Evaluation of sampling criteria for the detection of gm soybeans in bulk,” Italian Journal of Food Science, vol. 17, No. 2, pp. 177-185, 2005.
K. R. Emslie, L. Whaites, K. R. Griffiths, “Sampling plan and test protocol for the semiquantitative detection of genetically modified canola (Brassica napus) seed in bulk canola seed,” J of Agricultural and Food Chemistry, vol, 55, No. 11, pp. 4414-4421, 2007.
P. Minkkinen, K. H. Esbensen, and C. Paoletti, “Representative sampling of large kernel lots II. Application to soybean sampling for GMO control,” Trends in Analytical Chemistry, vol. 32, pp. 165–177, 2012.
R. Onori, R. Lopardo, M. D. Giacomo, B. D. Santis, E. Prantera, E. Palmaccio, C. Brera, “Traceability of genetically modiﬁed Roundup Ready soybean: A case study on sampling and analytical uncertainty along processing chain,” Food Control, vol. 34, pp. 494-501, 2013.
K. Yamamura, J. Mano, and H. Shibaike, “Optimal definition of the limit of detection (LOD) in detecting genetically modified grains from heterogeneous grain lots,” Quality Technology and Quantitative Management, vol. 16, No. 1, pp. 36-53, 2019.