Abstract
The differences in nutrition and health benefit between genetically modified (GM) and non-genetically modified (NG) foods have been attracting many concerns from the public and scientific fields. The combination of nuclear magnetic resonance (NMR) and gas chromatographic (GC) techniques provides feasible strategy for understanding and identifying the alterations in food composition. In this study, it has been applied to compare the nutritional composition of the GM and NG soybean and soybean oils to fully understand whether they should be treated equally without discrimination in the daily consumption. Eight kinds of GM and 8 kinds of NG soybeans and 28 kinds of GM and 30 kinds of NG soybean oils were detected by NMR and GC-FID techniques, respectively, and comparatively analyzed by the univariate and multivariate statistical analyses. The overall compositions of the NG and GM soybeans and soybean oils are quite similar; however, some minor component differences were also observed between the NG and GM ones. The NG soybeans bear the richer isoflavones and saccharides than the GM ones while the GM soybeans have the richer unsaturated fatty acids than the NG ones. The results derived from the two techniques could be mutually validated, and thus their combination will become an effective and accurate approach for evaluating the composition of the soybeans and edible oils. Our results will help to establish the quality parameters of the soybeans and soybean oils, and further serve to quality identification and quality control of foods.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data Availability
The data used in the current study are available from the corresponding author on reasonable request.
References
Adam O, Wolfram G, Zollner N (1988) Effect of alpha-linolenic acid in the human diet on linoleic acid metabolism and prostaglandin biosynthesis. J Lipid Res 27(4):421–426. https://doi.org/10.1016/S0022-2275(20)38815-5
Álvarez G, Montero L, Llorens L, Mı C-P, Cifuentes A (2018) Recent advances in the application of capillary electromigration methods for food analysis and Foodomics. Electrophoresis 39:136–159. https://doi.org/10.1002/elps.201700321
Bachleda N, Pham A, Li Z (2016) Identifying FATB1a deletion that causes reduced palmitic acid content in soybean N87–2122-4 to develop a functional marker for marker-assisted selection. Mol Breeding 36(4):45. https://doi.org/10.1007/s11032-016-0468-9
Bakshi A (2003) Potential adverse health effects of genetically modified crops. J Toxicol Environ Health Part B 6:211–225. https://doi.org/10.1080/10937400306469
Balkir P, Kemahlioglu K, Yucel U (2020) Foodomics: a new approach in food quality and safety. Trends Food Sci Technol 108(3):49–57. https://doi.org/10.1016/j.tifs.2020.11.028
Cai S, Zhang Y, Xia F, Shen G, Feng J (2019) An expert system based on 1H NMR spectroscopy for quality evaluation and adulteration identification of edible oils. J Food Compos Anal 84:103316. https://doi.org/10.1016/j.jfca.2019.103316
Cao S, Xu W, Luo Y, He X, Yuan Y, Ran W, Liang L, Huang K (2011) Metabonomics study of transgenic Bacillus thuringiensis rice (T2A–1) meal in a 90-day dietary toxicity study in rats. Mol BioSyst 7(7):2304–2310. https://doi.org/10.1039/c1mb05076a
Chang WC-W, Wu H-Y, Yeh Y, Liao P-C (2020) Untargeted foodomics strategy using high-resolution mass spectrometry reveals potential indicators for fish freshness. Anal Chim Acta 1127:98–105. https://doi.org/10.1016/j.aca.2020.06.016
Chun YJ, Kim DI, Park KW, Jeong S-C, Park S, Back K, Kim C-G (2013) Fitness cost and competitive ability of transgenic herbicide-tolerant rice expressing a protoporphyrinogen oxidase gene. J Ecol Environ 36(1):39–47. https://doi.org/10.1016/j.jhazmat.2008.07.058
EFSA European Food Safety Author (2021) Setting of an important tolerance for glyphosate in soyabens. EFSA J 19(10):6880. https://doi.org/10.2903/j.efsa.2021.6880
El SN, Simsek S (2011) Food technological applications for optimal nutrition: an overview of opportunities for the food industry. Compr Rev Food Sci Food Saf 11:2–12. https://doi.org/10.1111/j.1541-4337.2011.00167.x
Ferrer I, Thurman EM (2007) Multi-residue method for the analysis of 101 pesticides and their degradates in food and water samples by liquid chromatography/time-of-flight mass spectrometry. J Chromatogr A 1175:24–37. https://doi.org/10.1016/j.chroma.2007.09.092
Gao Y, Tao B, Qiu L, Jin L, Wu J (2014) Role of physiological mechanisms and EPSPS gene expression in glyphosate resistance in wild soybeans (Glycine soja). Pestic Biochem Physiol 109:6–11. https://doi.org/10.1016/j.pestbp.2013.12.005
García-Villalba R, León C, Dinelli G, Segura-Carretero A, Fernández-Gutiérrez A, Garcia-Cañas V, Cifuentes A (2008) Comparative metabolomic study of transgenic versus conventional soybean using capillary electrophoresis–time-of-flight mass spectrometry. J Chromatogr A 1195:164–173. https://doi.org/10.1016/j.chroma.2008.05.018
Golmakani M-T, Keramat M, Niakousari M, Khosravi H (2018) Changes in fatty acid profile and oxidation indices of soybean oil supplemented with Ocimum sanctum essential oil during accelerated storage. J Essent Oil Res 30(3):214–224. https://doi.org/10.1080/10412905.2018.1433084
Gruffat D, Bauchart D, Thomas A, Parafita E, Durand D (2021) Fatty acid composition and oxidation in beef muscles as affected by ageing times and cooking methods. Food Chem 343:128476. https://doi.org/10.1016/j.foodchem.2020.128476
Grunert KG (2005) Food quality and safety: consumer perception and demand. Eur Rev Agric Econ 32(3):369–391. https://doi.org/10.1093/eurrag/jbi011
Hutton WC, Garbow JR, Hayes TR (1999) Nondestructive NMR determination of oil composition in transformed canola seeds. Lipids 34(12):1339–1346. https://doi.org/10.1007/s11745-999-0487-0
Inaba Y, Brotherton JE, Ulanov A, Widholm JM (2007) Expression of a feedback insensitive anthranilate synthase gene from tobacco increases free tryptophan in soybean plants. Plant Cell Rep 26(10):1763–1771. https://doi.org/10.1007/s00299-007-0381-0
Ishigai M, Ishitani Y, Kumaki K (1997) Characteristics of mass spectrometric analyses coupled to gas chromatography and liquid chromatography for 22-oxacalcitriol, a vitamin D3 analog, and related compounds. J Chromatogr B 704:11–17. https://doi.org/10.1016/S0378-4347(97)00423-4
Kovak E, Blaustein-Rejto D, Qaim M (2022) Genetically modified crops support climate change mitigation. Trends Plant Sci 27(7):627–629. https://doi.org/10.1016/j.tplants.2022.01.004
Liang C, Prins TW, Wiel CCMvd, Kok EJ (2014) Safety aspects of genetically modified crops with abiotic stress tolerance. Trends Food Sci Technol 400:115–122. https://doi.org/10.1016/j.tifs.2014.08.005
Lin H-Y, Liao J-W, Chen R-S, Chang C-H, Chang H-W, Chang S-C, Chu W-S, Lin C-K, Lin H-T (2022) Food safety assessment of commercial genetically modified soybeans in rats. Foods 11(4):496. https://doi.org/10.3390/foods11040496
Loman AA, Ju L-K (2017) Enzyme-based processing of soybean carbohydrate: recent developments and future prospects. Enzyme Microb Technol 106:35–47. https://doi.org/10.1016/j.enzmictec.2017.06.013
Maedler K, Spinas GA, Dyntar D, Moritz W, Kaiser N, Donath MY (2001) Distinct effects of saturated and monounsaturated fatty acids on beta-cell turnover and function. Diabetes 50(1):69–76. https://doi.org/10.2337/diabetes.50.1.69
Mall T, Gupta M, Dhadialla TS, Rodrigo S (2019) Overview of biotechnology-derived herbicide tolerance and insect resistance traits in plant agriculture. Transgenic Plants 1864:313–342. https://doi.org/10.1007/978-1-4939-8778-8_21
Minami I, Nakamura Y, Todoriki S, Murata Y (2012) Effect of γ irradiation on the fatty acid composition of soybean and soybean oil. Biosci Biotechnol Biochem 76(5):900–905. https://doi.org/10.1271/bbb.110859
Moreno MRF, Sarantinopoulos P, Tsakalidou E, Vuyst LD (2006) The role and application of enterococci in food and health. Int J Food Microbiol 106(1):1–24. https://doi.org/10.1016/j.ijfoodmicro.2005.06.026
Muramoto N, Tanaka T, Shimamura T, Mitsukawa N, Hori E, Koda K, Otani M, Hirai M, Nakamura K, Imaeda T (2012) Transgenic sweet potato expressing thionin from barley gives resistance to black rot disease caused by Ceratocystis fimbriata in leaves and storage roots. Plant Cell Rep 31(6):987–997. https://doi.org/10.1007/s00299-011-1217-5
Ng MS, Ku YS, Yung WS, Cheng SS, Man CK, Yang L, Song SK, Chung G, Lam HM (2021) MATE-type proteins are responsible for isoflavone transportation and accumulation in soybean seeds. Int J Mol Sci 22(21):12017. https://doi.org/10.3390/ijms222112017
Oh SD, Jang YJ, Park SY, Lee K, Lee SK, Yun DW, Suh SJ, Chae JC (2021) Assessment of the effect on soil microbial communities of genetically modified soybean and a hybrid from crossing with wild soybean. Plant Biotechnol Rep 15:855–862. https://doi.org/10.1007/s11816-021-00710-4
Pal US, Patra RK, Sahoo NR, Bakhara CK, Panda MK (2015) Effect of refining on quality and composition of sunflower oil. J Food Sci Technol 52:4613–4618. https://doi.org/10.1007/s13197-014-1461-0
Peng D, Bi Y, Ren X, Yang G, Sun S, Wang X (2015) Detection and quantification of adulteration of sesame oils with vegetable oils using gas chromatography and multivariate data analysis - ScienceDirect. Food Chem 188:415–421. https://doi.org/10.1016/j.foodchem.2015.05.001
Qaim M (2020) Role of new plant breeding technologies for food security and sustainable agricultural development. Appl Econ Perspect Policy 42(2):129–150. https://doi.org/10.1002/aepp.13044
Qiao F, Hu R, Huang J (2020) Genetically modified (GM) rice versus non-GM rice: pesticide use and yield. Sci China Life Sci 63(5):785–787. https://doi.org/10.1007/s11427-019-9578-4
Ren Y, Wang T, Peng Y, Xia B, Qu L-J (2009) Distinguishing transgenic from non-transgenic Arabidopsis plants by 1H NMR-based metabolic fingerprinting. J Genet Genomics 36(10):621–628. https://doi.org/10.1016/S1673-8527(08)60154-X
Ren Q, Guo F, Teng F, Ma Y (2021) A novel approach for the reconstitution of bovine milk fat globules with different-melting-temperature triacylglycerol cores. Food Chem 345:128563. https://doi.org/10.1016/j.foodchem.2020.128563
Shi Z, Zou S, Lu C, Wu B, Huang K, Zhao C, He X (2019) Evaluation of the effects of feeding glyphosatetolerant soybeans (CP4 EPSPS) on the testis of male Sprague-Dawley rats. GM Crops Food 10:181–190. https://doi.org/10.1080/21645698.2019.1649565
Song I-B, Gu H, Han H-J, Lee N-Y, Cha J-Y, Son Y-K, Kwon J (2018) Omega-7 inhibits inflammation and promotes collagen synthesis through SIRT1 activation. Appl Biol Chem 61(4):433–439. https://doi.org/10.1007/s13765-018-0377-1
Tan J, Baisakh N, Oliva N, Parkhi V, Rai M, Torrizo L, Datta K, Datta SK (2010) The screening of rice germplasm, including those transgenic rice lines which accumulate β-carotene in their polished seeds, for their carotenoid profile. Int J Food Sci Technol 40(5):563–569. https://doi.org/10.1111/j.1365-2621.2005.00971.x
Vahteristo LT, Ollilainen V, Koivistoinen PE, Varo P (1996) Improvements in the analysis of reduced folate monoglutamates and folic acid in food by high-performance liquid chromatography. J Agric Food Chem 44(2):477–482. https://doi.org/10.1021/jf9503467
Wang X, Komatsu S (2017) Improvement of soybean products through the response mechanism analysis using proteomic technique. Adv Food Nutr Res 82:117–148. https://doi.org/10.1016/bs.afnr.2016.12.006
Xu MY, Liu ZX, Qin HT, Qi HD, Wang ZY, Mao XR, Xin DW, Hu ZB, Wu XX, Jiang HW, Qi ZM, Chen QS (2018) Identification of novel soybean oil content-related genes using QTL-based collinearity analysis from the collective soybean genome. J Integr Agric 17(8):1727–1735. https://doi.org/10.1016/S2095-3119(17)61862-8
Zhang Y, Zhao Y, Shen G, Zhong S, Feng J (2018) NMR spectroscopy in conjugation with multivariate statistical analysis for distinguishing plant origin of edible oils. J Food Compos Anal 69:140–148. https://doi.org/10.1016/j.jfca.2018.03.006
Zhou J, Ma C, Xu H, Yuan K, Lu X, Zhu Z, Wu Y, Xu G (2009) Metabolic profiling of transgenic rice with cryIAc and sck genes: an evaluation of unintended effects at metabolic level by using GC-FID and GC-MS. J Chromatogr B 877:725–732. https://doi.org/10.1016/j.jchromb.2009.01.040
Zhou Y, Kim S-Y, Lee J-S, Shin B-K, Seo J-A, Kim Y-S, Lee D-Y, Choi H-K (2021) Discrimination of the geographical origin of soybeans using NMR-based metabolomics. Foods 10:435. https://doi.org/10.3390/foods10020435
Acknowledgements
The authors gratefully acknowledge Mr. Liubin Feng of High-Field NMR Research Center, Xiamen University, for technical supports.
Funding
This work was financially supported by the National Natural Science Foundation of China (No. 31671920) and the Natural Science Foundation of Fujian Province (2018Y0078).
Author information
Authors and Affiliations
Contributions
Quanquan Li: data curation, formal analysis, software, visualization, writing — original draft; Shihao Cai: investigation, software, formal analysis, writing — review and editing; Dunming Xu: resources, investigation, writing — review and editing; Jiangzhong Lin: conceptualization, writing — review and editing; Guiping Shen: methodology, funding acquisition, writing — review and editing; Jianghua Feng: conceptualization, methodology, funding acquisition, supervision, writing — review and editing.
Corresponding author
Ethics declarations
Conflict of Interest
Quanquan Li declares that she has no conflict of interest. Shihao Cai declares that he has no conflict of interest. Dunming Xu declares that he has no conflict of interest. Jianzhong Lin declares that he has no conflict of interest. Guiping Shen declares that he has no conflict of interest. Jianghua Feng declares that he has no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Li, Q., Cai, S., Xu, D. et al. Comparative Analysis of Nutritional Composition Between GM and Non-GM Soybeans and Soybean Oils by NMR and GC-FID Techniques. Food Anal. Methods 16, 478–490 (2023). https://doi.org/10.1007/s12161-022-02435-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12161-022-02435-8