Title: | Quantitative analysis of colony number in mouldy wheat based on near infrared spectroscopy combined with colorimetric sensor |
Author(s): | Lin H; Kang W; Han E; Chen Q; |
Address: | "School of Food and Biological Engineering, Jiangsu University, Jiangsu 212013, PR China. School of Food and Biological Engineering, Jiangsu University, Jiangsu 212013, PR China. Electronic address: qschen@ujs.edu.cn" |
DOI: | 10.1016/j.foodchem.2021.129545 |
ISSN/ISBN: | 1873-7072 (Electronic) 0308-8146 (Linking) |
Abstract: | "Current work presented a novel method based on colorimetric sensor (CS) combined with visible/near-infrared spectroscopy (VNIRs) for the detection of volatile markers in wheat infected by Aspergillus glaucus. Wheat samples with different mouldy degree was cultivated for backup under temperature of 25-28 degrees C in incubator. The total colony number was determined by flat colony counting method. Through employing chemo-responsive dyes including 8-(4-nitrophenyl)-4, 4-difluoro-BODIPY (NO(2)BDP), 8-(4-bromophenyl)-4,4-difluoro-BODIPY(BrBDP) and 8-phenyl-4,4-difluoro- BODIPY(HBDP) as capture probes of colorimetric sensor for volatile organic compounds (VOCs). The spectral data of CS-VNIRs were scanned and used to build synergic interval partial least squares (Si-PLS) models. The optimized Si-PLS model based on HBDP sensor gave a better detection performance, and the correlation coefficient of the prediction set Rp = 0.9387. The achieved high correlation rates imply that the technique may be deployed as a panacea to identify and quantify the colony number of different mouldy wheat" |
Keywords: | "Aspergillus/*isolation & purification/*physiology *Colorimetry Least-Squares Analysis *Spectroscopy, Near-Infrared Triticum/chemistry/*microbiology Volatile Organic Compounds/analysis Colony number Colorimetric sensor VNIRs VOCs;" |
Notes: | "MedlineLin, Hao Kang, Wencui Han, En Chen, Quansheng eng England 2021/03/24 Food Chem. 2021 Aug 30; 354:129545. doi: 10.1016/j.foodchem.2021.129545. Epub 2021 Mar 12" |