Detection of volatile marker in the wheat infected with Aspergillus flavus by porous silica nanospheres doped Bodipy dyes

• Published in: Sensors and actuators. B, Chemical Chemical, 2021-03, Vol.330, p.129407, Article 129407
• Main Authors: Duan, Yaxian, Lin, Hao, He, Peihuan, Chen, Quansheng
• Format: Article
• Language: English
• Subjects: A. flavusinfection; Boron; Colorimetry; Discriminant analysis; Factor analysis; Gas chromatography; Gas mixtures; Markers; Mass spectrometry; Nano-porous modified pigments; Nanospheres; Pigments; Principal components analysis; Sensors; Silicon dioxide; VOCs; Volatile maker; Volatile organic compounds; Wheat
• ISSN: 0925-4005; 1873-3077
• DOI: 10.1016/j.snb.2020.129407

•The compound of 1-Octen-3-ol was found greatly related to Aspergillus flavus colonies, so was considered to be volatile marker of infected wheat.•The nano-porous silica was synthetized to modify Bodipy pigment to fabricate colorimetric sensor for trace volatile compound detection.•The volatile marker of infected wheat could be detected by colorimetric sensor with high accuracy in low concentration (ppm).•The infection of Aspergillus flavus in wheat could be detected in a few minutes. Current work presented a new colorimetric sensor based on nano-porous modified NO2BDP pigment for the detection of volatile markers in wheat infected by Aspergillus flavus (A. flavus). Firstly, principal component analysis (PCA) load factor analysis was performed on each volatile organic compounds (VOCs) detected by gas chromatography-mass spectrometry (GC–MS) from the infected wheat samples. It was found that the content of 1-Octen-3-ol increased with the rise of the A. flavus number (Pearson Correlation of 0.983). The synthesized porous silica nanosphere was modified to fabricate the colorimetric sensor. The content of 1-Octen-3-ol could be accurately quantified within 6 ppm using nano-porous modified NO2BDP pigments in the gas mixture from the infected wheat, which was more sensitive than the conventional boron-dipyrromethene (Bodipy) pigment. Finally, the proposed colorimetric sensor was applied to analyze 108 wheat samples with different degrees of A. flavus infection. As a result, 98 % of infected wheat samples (with the concentration of A. flavus from 3.0–7.0 lgCFU/g) were correctly identified using linear discriminant analysis (LDA) model. Based on the achieved results, this work demonstrated that nano-porous modified NO2BDP pigment was an effective way for non-destructive detection of A. flavus infection in wheat.