Chemical Profile and Chemometric Analysis of Genetically Modified Soybeans Produced in the Triângulo Mineiro Region (MG), Brazil

Marco Aurélio Borba Moreira, Amilton Diniz Souza, Fernanda Barbosa Borges Jardim, Luís Carlos Scalon Cunha, Mário Machado Martins, Luiz Ricardo Goulart, Sérgio Antônio Lemos de Morais, Francisco José Torres de Aquino, Welington de Oliveira Cruz, Lucas Gustavo da Costa, Waldomiro Borges Neto


Soy production in Brazil is an important factor for the agro-industrial, economic, and social development of the country. The expansion of soy in the Brazilian territory is mainly due to the incorporation of new genetic characteristics into cultivars that granted resistance to the Cerrado conditions and to herbicides. Currently, Brazilian soy production is the result of genetically modified cultivars. Studies regarding the chemical composition of soybeans show that qualitative and quantitative variations can occur, depending on the region of production. This work aimed to investigate the chemical composition of soybeans produced in different cities of the Triângulo Mineiro region/MG, Brazil (Harvest 2017/2018) and stored in three warehouses located in the city of Uberaba/MG. The grain analysis was made by liquid chromatography coupled to electrospray ionization mass spectrometry (LC-MS-ESI). The classes of metabolites identified from methanolic extraction were organic acids, phenolic compounds, flavonoids, sugars, amino acids, dipeptides, nitrogenous bases, nucleosides, sphingolipids, and fatty acids. The isoflavones genistein, daidzein, glycitein, genistin, acetyldaidzin, and acetylgenistin were identified in soybeans from the three warehouses. The flavonoid eriodictyol-O-hexoside was also found. The Principal Component Analysis (PCA) from the mass spectrum data obtained by direct injection in the negative and positive modes evidenced the well-defined separation of three groups, indicating that there was variance among the soy samples from each warehouse. The samples from warehouses 1 and 3 showed greater similarity in the Hierarchical Cluster Analysis (HCA) in negative mode, while in positive mode, the samples from warehouses 2 and 3 presented greater similarity.

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Journal of Agricultural Studies   ISSN 2166-0379


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