Deoxynivalenol (DON), a cosmopolitan mycotoxin found in agricultural commodities causes serious health maladies to human and animals when accidently consumed even at a low quantity. It necessitates selective and sensitive devices to analyse DON as the conventional methods are complex and time-consuming. This study is focused on developing a selective biosensing system using iron nanoflorets graphene nickel (INFGN) as the transducer and a specific aptamer as the biorecognition element. 3D-graphene is incorporated using a low-pressure chemical vapour deposition followed by the decoration of iron nanoflorets using electrochemical deposition. INFGN enables a feasible bio-capturing due to its large surface area. The X-ray photoelectron spectroscopy analysis confirms the presence of the hydroxyl groups on the INFGN surface, which acts as the linker. Clear Fourier-transform infrared peak shifts affirm the changes with surface chemical modification and biomolecular assembly. The limit of detection attained is 2.11 pg mL-1 and displays high stability whereby it retains 30.65% of activity after 48 h. The designed INFGN demonstrates remarkable discrimination of DON against similar mycotoxins (zearalenone and ochratoxin A). Overall, the high-performance biosensor shown here is an excellent, simple and cost-effective alternative for detecting DON in food and feed samples.
Adsorption plays an important role in the removal of mycotoxins from feedstuffs. The main objective of this study was to investigate the efficacy of using magnetic graphene oxide nanocomposites (MGO) as an adsorbent for the reduction of Fusarium mycotoxins in naturally contaminated palm kernel cake (PKC). Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to assess the mycotoxins in animal feed. Target mycotoxins included the zearalenone (ZEA), the fumonisins (FB1 and FB2) and trichothecenes (deoxynivalenol (DON), HT-2 and T-2 toxin). Response surface methodology (RSM) was applied to investigate the effects of time (3-7 h), temperature (30-50 °C) and pH (3-7) on the reduction. The response surface models with (R2 = 0.94-0.99) were significantly fitted to predict mycotoxins in contaminated PKC. Furthermore, the method ensured a satisfactory adjustment of the polynomial regression models with the experimental data except for fumonisin B1 and B2, which decrease the adsorption of magnetic graphene oxide (MGO). The optimum reduction was performed at pH 6.2 for 5.2 h at of 40.6 °C. Under these optimum conditions, reduced levels of 69.57, 67.28, 57.40 and 37.17%, were achieved for DON, ZEA, HT-2, and T-2, respectively.