| Auricularia auricula is a kind of precious and nutritious gum fungus and has the functions of beautifying,promoting digestion,promoting blood circulation,anticoagulation and other properties.A.auricular polysaccharide(AAP)has the functions of improving immunity,anti-tumor,anti-oxidation,reducing blood sugar and so on.When costumers choose A.auricula,they often only rely on sensory indicators such as color and shape for evaluation,this method usually lacks scientific basis.The key factor that determines the dual-use value of medicine and food is the biological functional nutrients in A.auricula which are not known by the senses.Therefore,in order to establish the relevant standards for the rapid detection and control of the effective ingredients of A.auricula,and promote the deep processing and technical improvement of the product.It is urgent to develop a rapid,simple,safe and reliable method for the detection of functional components and sensory substances in A.auricula to evaluate the quality of this product.Firstly,partial least-square method(PLS)was used to optimize the parameters and establish a quantitative model of total sugar in A.auricula.The content of total sugar in A.auricula from different regions was determined.Then NIR technology was used to collect the spectral information of the samples.The sample data were divided into calibration set and validation set.The best quantitative model of the total sugar content of A.auricula was established by selecting the parameters such as spectral range,pretreatment method and PLS main factor number of the calibration set data.The validation set data was used to verify the reliability of this model.In this model,the original spectrum was used to pre-process by standard normal variate(SNV)+ second derivative(SD)to eliminate the scattering effect caused by uneven particle distribution and the influence of noise on spectral data.The spectrum range was 4000-10000 cm-1,and the final choice of PLS main factor number was 11.Under this condition,the calibration set Rc2 of the model was 0.9092,the root mean square error of calibration(RMSEC)was 1.405,the root mean square error of prediction(RMSEP)was 1.507,and the residual predictive deviation(RPD)was 3.32.The validation samples were used to test the model,and the result showed that Rv2 = 0.9048 of the validation set.The result proved that the predicted value of the validation samples had a good linear relationship with the measured value.According to the T-test of the two sets of data in the validation set,the difference between the predicted value and the chemical value was not significant(P ≥ 0.05).The results were in line with the expected objectives.The NIR quantitative model established could be used to predict the total sugar content of unknown samples.Then,in order to explore the differences and characteristics of A.auricula from different producing areas in China,and provide some guidance for the selection of special flavor A.auricula,the volatile compounds of A.auricula from Heilongjiang,Jilin,Shanghai and Sichuan Provinces were analyzed by electronic nose combined with gas chromatography-mass spectrometry(GC-MS).The results showed that the electronic nose could obviously distinguish the samples from Jilin and Shanghai Provinces with a high degree of discrimination,while it is inappropriate to distinguish the samples from Heilongjiang and Sichuan Provinces.GC-MS was used to further analyze the volatile compounds in the samples qualitatively and quantitatively.The results showed that 98 volatile components were detected and 23 of them are common components,including alcohols,aldehydes,acids,esters and hydrocarbons.The relative content of Acetic acid and Diethyl azodicarboxylate in A.auricula from the four origins were relatively high.According to the relative odor activity value(ROAV),it was found that the key compounds caused the odor difference between different producing areas were 1-Octene-3-ol,Cis-3-nonene-1-ol,(E)-2-Octenal,(E)-2-Nonenal,(E,E)-2,4-Nonadienal and 3-Methyl butanal. |
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