RESUMEN
Corn is one of the most produced cereals in the world and plays a major role in poultry nutrition. As there is limited scientific information regarding the impact of transgenic technology on the quality and nutrient composition of the grains, this study investigated the effect of three major transgenic corn varieties-VT PRO3®, PowerCore® ULTRA, and Agrisure® Viptera 3-on the field traits, nutrient composition, and mycotoxin contamination of corn grains cultivated in southern Brazil during three consecutive harvests. VT PRO3®, while demonstrating superior crop yield, showed susceptibility to mycotoxins, particularly fumonisins. In contrast, PowerCore® ULTRA, with the lowest yield, consistently exhibited lower levels of fumonisins. VT PRO3® had higher AMEn than the other varieties, while PowerCore® ULTRA had the highest total and digestible amino acid contents over the three years. The study's comprehensive analysis reveals the distinct impact of transgenic corn technologies on both productivity and nutritional levels. Balancing the crops yield, mycotoxin resistance, and nutritional content of corn is crucial to meet the demands of the poultry feed industry. Such insights are essential for decision-making, ensuring sustainability and efficiency in agricultural production as well as meeting the demands of the poultry industry.
RESUMEN
Fumonisins (FBs) and zearalenone (ZEN) are mycotoxins which occur naturally in grains and cereals, especially maize, causing negative effects on animals and humans. Along with the need for constant monitoring, there is a growing demand for rapid, non-destructive methods. Among these, Near Infrared Spectroscopy (NIR) has made great headway for being an easy-to-use technology. NIR was applied in the present research to quantify the contamination level of total FBs, i.e., fumonisin B1+fumonisin B2 (FB1+FB2), and ZEN in Brazilian maize. From a total of six hundred and seventy-six samples, 236 were analyzed for FBs and 440 for ZEN. Three regression models were defined: one with 18 principal components (PCs) for FB1, one with 10 PCs for FB2, and one with 7 PCs for ZEN. Partial least square regression algorithm with full cross-validation was applied as internal validation. External validation was performed with 200 unknown samples (100 for FBs and 100 for ZEN). Correlation coefficient (R), determination coefficient (R2), root mean square error of prediction (RMSEP), standard error of prediction (SEP) and residual prediction deviation (RPD) for FBs and ZEN were, respectively: 0.809 and 0.991; 0.899 and 0.984; 659 and 69.4; 682 and 69.8; and 3.33 and 2.71. No significant difference was observed between predicted values using NIR and reference values obtained by Liquid Chromatography Coupled to Tandem Mass Spectrometry (LC-MS/MS), thus indicating the suitability of NIR to rapidly analyze a large numbers of maize samples for FBs and ZEN contamination. The external validation confirmed a fair potential of the model in predicting FB1+FB2 and ZEN concentration. This is the first study providing scientific knowledge on the determination of FBs and ZEN in Brazilian maize samples using NIR, which is confirmed as a reliable alternative methodology for the analysis of such toxins.