Optimization Of Lentinus Edodes Heat Pump And Vacuum Drying And Study On Classification

Lentinus edodes(Berk.)sing,also known as mushroom,shiitake,agaric,snake butter,champignon,are the fruiting body of Pleurotaceae,with the folk name of "Mountain delicacy" in China.The fresh letinus edodes are unsuitable to storage for a long time because the moisture content reaches above 80%.To reduce the cost of processing,and obtain high quality dried Lentinus edodes.So,in this article,the drying characteristics of letinus edodes can be studied,the process of heat pump-vacuum drying can be optimized,the optimal parameters were obtained,and the multi-variable multinomial regression model can be derivated.In order to realize the automatic precise classification of dry lentinus edodes,the grading standards will be determined.(1)The effects of the heat pump temperature A,vacuum degree B and moisture content conversion point C on unit energy consumption,sense judgment,rehydration ratio and hardness are studied by using the single factor test.The zero level of heat pump temperature,vacuum degree and moisture content conversion point are 50℃,100Pa and 55%,respectively.(2)On the basis of the zero level that obtained by single factor test,the optimization tests can go on.By using the Box-Behnken Design(BBD),the response surface method of three-factor and three-level can be designed.The respective regression equations of unit energy consumption,sense judgment,rehydration ratio and hardness are proposed by regression analysis method.Comparing the absolute values of correlation coefficient regression equations,primary and secondary sequence of three factors is moisture content conversion point,heat pump temperature,vacuum degree.The optimal parameters were obtained as follows:the heat pump temperature is 49℃,vacuum degree is 1 10 Pa and moisture content conversion point is 56%.Under this conditions,the unit energy consumption is 345.01 kJ/g,the sense judgment is 8.3,the rehydration ratio is 2.72 and the hardness is 3.61N.These data is close to the predicted value.And the errors are only 0.19%,3.61%,1.47%and 1.66%.The comparison results are as follows:the unit energy consumption of combined drying is 37.69%less than vacuum drying,but higher than heat pump drying;the sense judgment and rehydration ratio of combined drying are close to single vacuum drying,and higher than single heat pump drying;the hardness is slightly larger than vacuum drying,and less than heat pump drying.(3)Using the moist that calculated from three drying process to fit with 12 kinds of drying models.The fitting precision is compared by decisive coefficients R2 and sum square variation χ2 as evaluation criterion.Then,solving the selected model.The results are as follows.For heat pump drying,Midilli has better fitting precision,and the formula is MR=((-7.5e-6A2+0.0007A+0.9836)exp(-(0.0003A2-0.0175A+0.4065)t^(-0.0010A2+0.0977A-1.3310))+(-2.9e-5A2+0.0028A-0.0689)t.For vacuum drying,Two term exponential has better fitting precision,and the formula is MR=(-0.0004B2+0.0646B-1.673)exp(-(0.0007B2-0.1023B+4.1010)t)+(1-(-0.0004B2+0.0646B-1.673))exp(-(0.0007B2-0.1023B+4.1010)t).For combined drying,Two term has better fitting precision,and the formula is MR=-24.02exp(-0.4275t)+25.01exp(-0.4181t).(4)In order to realize the automatic precise classification of dry lentinus edodes,extracting the shape feature,color characteristics of the cap and calculating the proportion of defects sections using Matlab to process the images of dry lentinus edodes.Judging the grade according to the circularity P,the Mahalanobis distance between test sample and the central point of each sample,the ratio of defection to cap.And determining the lowest level of the 3 classification results as the final degree of dry lentinus edodes.Then comparing the consequence with manual grading results.The recognition rates of four grades dry lentinus edodes are higher than that of manual grading,reaching 92.0%,96.0%,96.0%,94.0%respectively.The method in this article can classify dry lentinus edodes accurately and provide convincing reference to the automatic classification of dry lentinus edodes.