| Fresh jujube with its own characteristics such as nourishing and medicinal value has been favored by the people.However, Fresh jujube would be causing subtle bruise when it on picking, storage, packaging, transportation, sales and many other sectors of the industry chain. Some of those subtle bruise was difficult to identify with the eyes. If the subtle bruise in jujube is not removed timely,it would cause great waste and directly affect the utilization value of the fresh jujube. Therefore, It had vital meaning to detect the subtle bruise of jujube by using the fast and effective method.Huping jujube was selected as the object in this study.Based on the set up fresh jujube subtle bruise on-line nondestructive detection device, near infrared analysis technology and chemometrics method, subtle bruise jujube and intact jujube were classified in 3 kinds of speed. Meanwhile, this research not only conducts an analysis and measurement of the physical and chemical properties about SSC of intact Huping jujubes, but also establishes a quantitative and analysis model for SSC online non-destructive testing.This study mainly focus on the following aspects:(1) Aiming at the existing deficiency of online nondestructive detection technology of fresh jujube subtle bruise, an online nondestructive testing device for fresh jujube subtle bruise had been preliminary designed by using NIR spectroscopy static nondestructive testing technology as the theoretical basis and combining with computer science, mechanics, electricity and chemometrics. The device was composed by mechanical transportation system, rotating friction system and spectral acquisition system. The device provided hardware support for online non-destructive detection of the fresh jujube subtle bruise.(2) Aiming at the characteristics of subtle bruise jujube was not easy to detected, the set up online nondestructive testing device collected NIR spectrum data of subtle bruise and intact Huping jujube in 3 kinds of rotational speed(1.5r/min、2.0r/min、2.5r/min).(3) In the range of full spectral(400-2450nm), the influence on classification accuracy of subtle bruise jujube and intact jujube in 3 kinds of rotational speed(1.5r/min、2.0 r/min、2.5 r/min)were analysed and compared. By using different spectra pretreatment methods, the models of Partial least squares discriminant analysis(PLS-DA) had been established, Extreme learning machine(ELM)and Least squares support vector machine(LS-SVM) were analysed. The result indicated that the speed of 2.0 r/min had higher classification accuracy by comparing with the other two speed. The classification rate for 4 kinds of unknown sample of ELM model established by using the full spectrum data(FS-ELM) were 100%,85.71%,83.33% and 100%, the identification rate were 92.26% in total. Therefore, The best model was FS-ELM in speed of 2.0 r/min in this situation.(4)In the range of full spectral(400-2450nm), the characteristic wavelength had been extraction by using RC regression coefficient method and SPA algorithm.The PLS-DA, ELM and LS-SVM classification models had been established by using the characteristic wavelength as the input, The 3 kinds of rotational speed(1.5r/min、.2.0 r/min、2.5 r/min)of each corresponding 6 discriminant analysis model had been got.The result indicated that the speed of 1.5 r/min had higher classification accuracy by comparing with the other two speed. And The characteristic wavelength extracted by using RC regression coefficient method were 687nm,773nm,829nm,963nm,1065nm,1119nm,1294nm,1333nm,1379nm,1417nm,1658nm,1814nm,1908n m and 2134nm,respectively. The classification rate for 4 kinds of unknown sample of RC-LS-SVM model were 83.33%,85.71%,100% and 83.33%, the classification rate were 88.09% in total. The 3 different rotational speed would all had impact to the classification rate and the system still had some problems need to be improved in the further.(5)In the range of full spectral(400-2450nm),the influence on classification accuracy of SSC of intact jujube in 3 kinds of rotational speed(1.5r/min,2.0 r/min、2.5 r/min) were analysed and compared.The PLS model had been established by using the spectral data with different pretreatment methods. The result indicated that the speed of 1.5 r/min with OSC pretreatment method had higher classification accuracy by comparing with the other two speed.The coefficients of the established FS-PLS model were as follows:Rc=0.876, RMSEC=1.846,Rp=0.763 and RMSEP=1.792. Therefore, The best model was FS-PLS in speed of 1.5 r/min in this situation.(6)In the range of full spectral(400-2450nm),the characteristic wavelength had been extraction by using RC regression coefficient method and SPA algorithm.The RC-PLS and SPA-PLS classification models had been established by using the characteristic wavelength as the input. The result indicated that the speed of 1.5 r/min with RC regression coefficient method had higher classification accuracy by comparing with the other two speed.And The characteristic wavelength extracted by using RC regression coefficient method were 796nm,915nm,993nm,1362nm,1463nm,1662nm,1816nm,1953nm,1984 nm,2134nm,2198nm,2255nm and 2415nm,respectively.The coefficients of the established RC-PLS model were as follows:Rc=0.846, RMSEC=1.962,Rp=0.782 and RMSEP=2.247.The study provided theoretical basis for online non-destructive detection of the SSC of intact jujube. |
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