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- Rapid screening of fumonisins in maize using near-infrared spectroscopy (NIRS) and machine learning algorithmsPublication . Sampaio, Pedro; Barros, Sílvia Cruz; Freitas, Andreia; Silva, Ana Sanches; Brites, Carla; Carbas, BrunaFumonisins occurrence in maize represents a significant global challenge, impacting economic stability and food safety. This study evaluates the potential of near-infrared (NIR) spectroscopy combined with chemometric al- gorithms to detect fumonisins in maize. For fumonisin B1 (FB1) and B2 (FB2) levels were developed predictive NIR models using partial least squares (PLS) and artificial neural networks (ANN). PLS models demonstrated strong correlation coefficient (R2) values of 0.90 (FB1), 0.98 (FB2), and 0.91 (FB1 + FB2) for calibration, with ratio of prediction to deviation (RPD) values ranging 2.8–3.6. Similarly, ANN models showed good predictive performance, particularly for FB1 + FB2, with R = 0.99, and the root means square error (RMSE) of 131 μg/kg for calibration; and R = 0.95, RMSE = 656 μg/kg for validation. These findings underscore the efficacy of NIR spectroscopy as a rapid, non-destructive tool for fumonisin screening in maize, with chemometric algorithms enhancing model accuracy, offering a valuable method for ensuring food safety.
- Comparative Analysis of Maize Physico-Chemical Parameters and Mycotoxin Levels in Dual EnvironmentsPublication . Carbas, Bruna; Barros, Sílvia; Freitas, Andreia; Silva, Ana Sanches; Brites, Carla; Carbas, BrunaMaize (Zea mays L.) stands as a vital staple food globally, holding significant nutritional and economic value. However, its susceptibility to mycotoxin contamination under stressful environmental conditions poses a considerable concern. This study aimed to assess the quality and pasting characteristics of maize varieties across two distinct regions and examine the occurrence of mycotoxins influenced by climatic factors. Five maize varieties were cultivated in triplicate in the Goleg & atilde; and Coruche regions. The nutritional composition (protein, fat, fiber, ash, starch, and lutein), pasting properties, and mycotoxin levels were evaluated. A statistical analysis revealed notable differences in the nutritional profiles of the maize varieties between the two regions, particularly in the protein and lutein content. The peak viscosity ranged from 6430 to 8599 cP and from 4548 to 8178 cP in the maize varieties from the Coruche and Goleg & atilde; regions, respectively. Additionally, a significant correlation was observed between the climatic conditions and the grain nutritional quality components (p < 0.05). The M variety showed the highest ash content, protein content, final viscosity, and setback viscosity and the lowest peak viscosity. The Y variety revealed the lowest fat, fiber, and lutein content and the maximum peak viscosity. The incidence of mycotoxins was notably higher in the varieties from Coruche, which was potentially attributable to higher temperatures and lower precipitation levels leading to more frequent drought conditions. Fumonisin B1 was detected in 58% of the varieties from Coruche and 33% of the samples from Goleg & atilde;, while deoxynivalenol was found in 87% and 80% of the varieties from Coruche and Goleg & atilde;, respectively. The H variety, which was harvested in Coruche, exhibited the highest number of fumonisins and higher amounts of protein, lutein, and fat, while fumonisins were not detected in the Goleg & atilde; region, which was potentially influenced by the precipitation levels. The K variety revealed higher protein and lutein contents, a lower amount of fat, excellent pasting properties (a higher peak viscosity and holding strength and a lower peak time), and no fumonisins B1 or B2. This variety may be considered well adapted to higher temperatures and drier conditions, as verified in the Coruche region. In conclusion, our study underscored the profound impact of environmental factors on the quality and occurrence of mycotoxins in maize varieties.