Optimization Of Hot Air Drying Process Of Shiitakes And Drying Stage Detection Based On Electronic Nose

Shiitake mushroom(Lentinula edodes)is the second largest edible mushroom in the world.It is popular at the table because of its pleasant aroma,delicious taste and rich nutrients.However,the fresh shiitake is highly perishable as it contains moisture up to 90%that quality deterioration caused by microbial and enzyme activities would quickly take place if not preserved in time.Drying is the most commonly used method for shiitakes preservation.In this paper,hot air combined microwave heating was used to dry shiitakes.The response surface method was used to optimize the drying process parameters.Aroma is one of the most important marketable characteristics of dried shiitakes,and the changes in aroma are closely related to product quality,it is necessary to analyze and monitor the aroma of shiitakes during drying process.So this paper aimed to investigate the potential of electronic nose(PEN3 E-nose)to differentiate volatile organic compounds(VOCs)of shiitakes produced at different drying stages and screened out the sensitive sensors.Then,based on the metal oxide sensor(MOS)array,a convenient E-nose system for the non-destructive detection of drying stages of shiitakes was developed.Finally,an online E-nose system was designed to realize the moisture content prediction during hot air drying process of shiitakes based on the hot air oven.This study provides a theoretical basis for monitoring the quality of shiitakes during drying process,and also useful information for on-line or off-line detection of shiitakes during drying.The contents and results of the thesis are as follows:1.Optimization of microwave-assisted hot air drying process for shiitakes using response surface methodologyHot air combined microwave heating was used to dry shiitakes in this chapter.Effects of switching point(dry basis moisture content of 2.00～5.00 g/g),hot air temperature(50.0～70.0℃)and microwave power density(6.67～33.33 W/g)on the drying characteristics and quality of shiitakes were investigated through the single factor experiment.Box-Behnken design was used to optimize the process parameters of hot air-microwave drying process.Hot air temperature of 60.6℃,dry basis moisture content at switching point of 4.20 g/g and microwave power density of 30.00 W/g were determined as the optimal parameters for this combined drying process for shiitakes,and the corresponding drying time was 178.33 min(the hot air was dried for 170 min and the microwave was dried for 8.33 min),total color difference was 11.21,shrinkage was 65.28%,lentinan retention was 66.98%,and the overall rating is 0.145.This study suggests that the hot air-microwave combination can be an effective drying method to obtain dehydrated shiitakes with high quality.2.Study on drying stages of shiitakes based on PEN3 electronic noseThis chapter aimed to investigate the potential of PEN3 E-nose system to differentiate volatiles of shiitakes produced at different drying stages and screened out the sensitive sensors.Shiitakes at different drying time slots were categorized into four groups by sensory evaluation.E-nose was used to analyze the volatiles and compared with those data obtained by HS/GC-MS.The principal component analysis(PCA)results showed that shiitakes at each stage could be successfully discriminated by E-nose and HS/GC-MS.The differences in VOCs produced at each stage leading to apparent changes of sensors sensitive to sulfur and aromatic compounds.The discriminant models were established by partial least squares discriminant analysis(PLS-DA)and support vector machine classification(SVM-C),with accuracy rates of 91.25%and 95.83%,respectively.The results demonstrated the potential use of E-nose in classifying and monitoring shiitakes during drying process.3.Development of dedicated electronic nose for shiitakes during dryingA special E-nose system for the detection of different drying stages of shiitakes was independently developed.The system consisted of two parts:hardware and software.This system can meet the basic needs for detection the smell of shiitakes at different drying stages.The PCA results showed that the samples at different drying stages could be successfully distinguished.Then,load analysis and Successive projections algorithm(SPA)were used to optimize the array of sensors,and it is determined as S1,S2,S3,and S5.The discriminant models were established by PLS-DA and SVM-C,with accuracy rates of 93.75%and 96.75%,respectively.The SVM-C model with higher accuracy was introduced into the software system for independent verification.The final verification accuracy rate was 95%,which proves that the model performance was good.4.Preliminary development of online electronic nose for shiitakes during dryingAn online electronic nose device based on hot air drying oven was independently developed,including sensor array,data acquisition control module and software system.It was used to collect the odor response values of shiitakes during hot air drying.PCA and radar analysis showed that the VOCs of shiitakes were keep changing during drying.Samples with different drying times showed different odors.But with the end of drying,the change in odor was getting smaller and smaller.It was basically determined that the drying end can be reached when the shiitakes was dried for 450～480 min.Then,a prediction model of the electronic nose response values and moisture content was established based on the partial least squares,principal component regression and support vector machine algorithms.Finally,the optimal prediction model of moisture content was SVM.The R2P is 0.951,which proves that the model works well and can be used for moisture prediction during the drying process of mushrooms.