Rapid detection method of corn starch gelatinization degree based on principal component regression analysis
Corn starch gelatinization is a key physical change in feed processing,which affects the nutritional value and digestibility of feed.The objective of this study was to investigate the effects of different moisture content(30%,50%,100%,150%,200%,250%and 300%),water bath temperature(50,60,70,80,90℃),and time(1,3,5,7,10 min)on the gelatinization of corn starch by a single-factor design,and to evaluate the viscosity characteristics of samples with different gelatinization degrees by a rapid visco analyzer(RVA).The results showed that the degree of corn starch pasting increased highly significantly with the addition of moisture,water bath temperature and water bath time(P<0.01);with the increase of gelatinization degree,the peak viscosity,trough viscosity,final viscosity,setback and breakdown of corn starch decreased significantly(P<0.01),and the gelatinization temperature and peak time increased significantly(P<0.01).Using principal component regression analysis,the models of gelatinization degree and RVA parameters(peak viscosity,trough viscosity,final viscosity,setback,breakdown,gelatinization temperature and peak time)were established,the correlation coefficient R2 of the model was 0.915,and the regression correlation coefficient R2 between the predicted value and the true value of the regression model was 0.9175.The model could predict the gelatinization degree of corn starch rapidly according to its viscosity characteristics,it provide an effective method for quality control in feed processing.
principal component regressionstarchgelatinization degreerapid detection
万方数据
维普
