Identification Of Mildew Grade And Mildew Regularity Of Soybean Under Simulated Different Transportation Conditions

Affected by factors such as planting area and yield,the supply and demand of soybean in the north and south regions of China are quite different.In order to maintain the supply stability of the soybean market,it is necessary to transport soybeans from the main northern producing areas across regions to the southern sales area—“North grain transportation to the south”.Container transportation is widely used as an economical and efficient multimodal transport mode.However,due to the obvious climate difference between north and south,the environmental conditions in the transportation process are complex and difficult to control,so there is a risk of mildew in the container,which is easy to cause soybean quality loss and cause economic disputes.Therefore,it is of great significance to explore the mildew law and the main influencing factors of soybean mildew under different transportation conditions for rapid detection and early warning of soybean mildew.In this study,soybean in Northeast China was taken as the research object to explore the mildew law of soybean in containers under different transport conditions and the main factors affecting soybean mildew,and the dominant fungal strains causing soybean mildew were isolated and purified.E-nose and GC-IMS techniques were used to analyze the composition and content changes of volatile substances during soybean mildew,and the characteristic volatile substances used for mildew identification were screened out to distinguish and identify the mildew grades of soybean.The specific research conclusions are as follows :1.The main factors affecting soybean mildew under different transport conditions were moisture content of soybean,environmental temperature and humidity,transport time and condensation.In the absence of dew,when the moisture content of soybean is below the safety value,the total number of molds in soybean is less affected by environmental temperature and humidity and transportation time,and it is not easy to mildew.When the moisture content of soybean is higher than the safety value,the total number of molds in soybean is greatly affected by environmental temperature and humidity and transportation time,which may cause mildew.In the case of dew,the total number of molds in soybean is significantly related to the moisture content of soybean,which is prone to mildew;the soybeans with moisture contents of 12%,13%and 14% had mildew on 4,12 and 24 d,respectively.Aspergillus,Penicillium and Rhizopus were the main pathogens causing soybean mildew in containers during transportation.The dominant fungal strains screened were Aspergillus niger,Penicillium rubens,Rhizopus microsporus,Penicillium oxalicum and Aspergillus versicolor,respectively.2.Five dominant mold inoculation and natural mildew of soybean were detected by E-nose technology.The analysis results of the contribution rate of Loadings algorithm to the E-nose sensor showed that the sensor W2W(sensitive to organic sulfur substances)played a major role,followed by W1W(sensitive to inorganic sulfur substances),W5S(sensitive to small molecule nitrogen oxides),W1S(sensitive to short-chain alkanes such as methane)and W2S(sensitive to alcohols,ethers,aldehydes and ketones),indicating that the differences in volatile substances in various moulded soybean samples were mainly reflected in organic sulfur substances.Secondly,there are significant differences in inorganic sulfur,nitrogen oxides,methane and other short-chain alkanes,as well as alcohol ether aldehydes and ketones.The PCA and LDA analysis results of E-nose response values showed that PCA and LDA had a general effect on distinguishing different dominant mold inoculations and natural moldy soybeans,but had a good effect on distinguishing different moldy soybeans,and the discriminant accuracy of LDA was82.72%.The results showed that E-nose detection technology was feasible in the identification of soybean mildew grade.3.The m VOCs of five dominant fungi and volatile organic compounds in mildewed soybean were analyzed by GC-IMS.16 characteristic m VOCs were screened from dominant molds;a total of 54 volatile organic compounds were detected in moulded soybean,including 24 aldehydes,15 ketones,10 alcohols,2 esters,1 pyrazine and 1 aromatic compound,among which aldehydes,ketones and alcohols accounted for a large proportion.With the deepening of moldy degree,the contents of nonanal,octanal,decanal,heptanal,glutaraldehyde,methyl-5-heptan-2-one,(E)-2-hexenal and(E)-2-pentenal gradually decreased,while the contents of phenylacetaldehyde,3-methyl-2-butenal,3-methylbutanal,3-methylthiopropanal,3-octanone,1-octene-3-ol,2-methyl-1-propanol,2-methyl-1-butanol and2-ethyl-3,5-dimethylpyrazine gradually increased.Combined with the analysis of characteristic m VOCs of dominant mold,it can be used as the characteristic volatile organic compounds for the identification of moldy degree of soybean.PCA and clustering results showed that volatile organic compounds in soybean samples with different mildew degrees were easily distinguished,and the mildew degree had a significant impact on the content change of volatile organic compounds,which was consistent with the results of E-nose detection.The experimental results showed that GC-IMS combined with chemometrics method could effectively distinguish soybean samples with different mildew degrees and was feasible in the identification of soybean mildew degrees.