Detection of deoxynivalenol(DON)content in wheat grain using electronic nose technology
To explore the potential of electronic nose technology for quantifying deoxynivalenol(DON)content in wheat grains,the detection on the headspace gas of 80 wheat grain samples with different DON contents at equilibrium temperatures of 25℃ and 40℃ were conducted using electronic nose,and alongside the DON content of each wheat sample was measured by UPLC-MS/MS.The statistic analysis results showed that,except for sensors no.4 and no.5,the response values of the remaining eight sensors significantly correlated or extremely significantly correlated with the sample DON content.Notably,sensor no.1 exhibited the strongest correlation,indicating its potential as a principal gas sensor for detecting DON content in wheat grain samples.Regression models for sample DON content were established mainly based on sensor no.1 parameters at each equilibrium temperature.The analysis of the fitting effect of these models revealed that the univariate regression model based on X17(the sum of response values of sensor no.1 from 21 to 60 seconds)yielded the best fitting effect at equilibrium temperature of 40C.The bivariate regression model based on X1(the average response value of sensor no.1 from 20 to 40 seconds)and X12(the sum of response values of sensor no.8 from 1 to 5 seconds)yielded the best fitting effect at 25℃,the univariate regression model based on X1 also showed promising results.This study provides a theoretical basis and technical support for detecting DON content in wheat grains using electronic nose technology.
electronic nosewheat graindeoxynivalenol(DON)toxin detectionregression model
万方数据
维普
