To scientifically and objectively monitor the fermentation quality of black tea,a computer vision system(CVS)and electronic nose(e-nose)were employed to analyze the black tea image and odor eigenvalues of Yinghong No....To scientifically and objectively monitor the fermentation quality of black tea,a computer vision system(CVS)and electronic nose(e-nose)were employed to analyze the black tea image and odor eigenvalues of Yinghong No.9 black tea.First,the variation trends of tea polyphenols,volatile substances,image eigenvalues and odor eigenvalues with the extension of fermentation time were analyzed,and the fermentation process was categorized into three stages for classification.Second,principal component analysis(PCA)was employed on the image and odor eigenvalues obtained by CVS and e-nose.Partial least squares discriminant analysis(PLS-DA)was performed on 117 volatile components,and 51 differential volatiles were screened out based on variable importance in projection(VIP≥1)and one-way analysis of variance(P<0.05),including geraniol,linalool,nerolidol,and α-ionone.Then,image features and odor features are fused by using a data fusion strategy.Finally,the image,smell and fusion information were combined with random forest(RF),K-nearest neighbor(KNN)and support vector machine(SVM)to establish the classification models of different fermentation stages and to compare them.The results show that the feature-level fusion strategy integrating the SVM was the most efficient approach,with classification accuracy rates of 100%for the training sets and 95.6%for the testing sets.The performance of Support Vector Regression(SVR)prediction models for tea polyphenol content based on feature-level fusion data outperformed data-level models(Rc,RMSEC,Rp and RMSEP of 0.96,0.48 mg/g,0.94,0.6 mg/g).展开更多
Rainbow refractometry is widely used to measure the radius and real part of refractive index of a cylinder. However, studies on the detection of imaginary part of the refractive index with rainbow technique were scarc...Rainbow refractometry is widely used to measure the radius and real part of refractive index of a cylinder. However, studies on the detection of imaginary part of the refractive index with rainbow technique were scarce. This paper presents a new method for simultaneously measuring the radius, real and imaginary part of the refractive index of a cylinder, on the basis of the Airy theory and the Bouguer theory. The rainbows produced by the illuminated cylinder at a capillary exit are captured by a CCD camera in a lab- scale system, and then processed by the proposed method. Experimental results showed that the radius, real and imaginary part of the refractive index can be accurately determined when the SNR （signal to noise ratio） of the ripple structure is sufficiently high. However, the SNR of the ripple structure gradually decreases with decreasing scattering intensity of the cylinder, leading to larger measurement errors of the radius and real part of the refractive index. The relative error of the imaginary part of the refractive index derived from the measurement errors of the radius and real part of the refractive index, is less than 3.4%.展开更多
An intelligent control system is designed in green tea fixation,which can automatically and continuously adjust the fixation parameters for quality improvement.Aroma is detected with PEN-3 electronic nose,and signals ...An intelligent control system is designed in green tea fixation,which can automatically and continuously adjust the fixation parameters for quality improvement.Aroma is detected with PEN-3 electronic nose,and signals are sent to the computer.With the aroma signals,the fixation process is separated into two stages:in the first stage,the key purpose is enzymatic reaction,which can be suppressed with high temperature;it is the oxidation re-action which should be concentrated on in the second stage,and a middle temperature is a good choice.With the designed fuzzy logic algorithm,the pot temperature is kept at a high level at the beginning,and the enzymatic reaction can be successfully reduced.In the second stage,the temperature is kept at a middle value to decrease oxidation.With the designed intelligent control,the green tea product quality is improved for aroma,taste,appearance,liquor color,and residues.展开更多
基金The authors gratefully acknowledge financial support from the Open Project of Guangdong Provincial Key Laboratory of Tea Plant Resources Innovation and Utilization(2020KF02)Guangzhou Science and Technology Program Project(202002020079)+1 种基金Guangdong Provincial Special Fund for Modern Agriculture Industry Technology Innovation Teams(2022KJ120)Qingyuan Science and Technology Program Project(2022KJJH065).
文摘To scientifically and objectively monitor the fermentation quality of black tea,a computer vision system(CVS)and electronic nose(e-nose)were employed to analyze the black tea image and odor eigenvalues of Yinghong No.9 black tea.First,the variation trends of tea polyphenols,volatile substances,image eigenvalues and odor eigenvalues with the extension of fermentation time were analyzed,and the fermentation process was categorized into three stages for classification.Second,principal component analysis(PCA)was employed on the image and odor eigenvalues obtained by CVS and e-nose.Partial least squares discriminant analysis(PLS-DA)was performed on 117 volatile components,and 51 differential volatiles were screened out based on variable importance in projection(VIP≥1)and one-way analysis of variance(P<0.05),including geraniol,linalool,nerolidol,and α-ionone.Then,image features and odor features are fused by using a data fusion strategy.Finally,the image,smell and fusion information were combined with random forest(RF),K-nearest neighbor(KNN)and support vector machine(SVM)to establish the classification models of different fermentation stages and to compare them.The results show that the feature-level fusion strategy integrating the SVM was the most efficient approach,with classification accuracy rates of 100%for the training sets and 95.6%for the testing sets.The performance of Support Vector Regression(SVR)prediction models for tea polyphenol content based on feature-level fusion data outperformed data-level models(Rc,RMSEC,Rp and RMSEP of 0.96,0.48 mg/g,0.94,0.6 mg/g).
基金the National Natural Science Foundation of China(No.50906012)Research Award Program for Outstanding Young Teachers in Southeast University,China(No.3203001202)+2 种基金QingLan Project(No.1103000126)Scientific Research Foundation of Graduate School of Southeast University(YBJJ1220)Research and Innovation Project for College Graduates of Jiangsu Province(CLCX-0106)
文摘Rainbow refractometry is widely used to measure the radius and real part of refractive index of a cylinder. However, studies on the detection of imaginary part of the refractive index with rainbow technique were scarce. This paper presents a new method for simultaneously measuring the radius, real and imaginary part of the refractive index of a cylinder, on the basis of the Airy theory and the Bouguer theory. The rainbows produced by the illuminated cylinder at a capillary exit are captured by a CCD camera in a lab- scale system, and then processed by the proposed method. Experimental results showed that the radius, real and imaginary part of the refractive index can be accurately determined when the SNR （signal to noise ratio） of the ripple structure is sufficiently high. However, the SNR of the ripple structure gradually decreases with decreasing scattering intensity of the cylinder, leading to larger measurement errors of the radius and real part of the refractive index. The relative error of the imaginary part of the refractive index derived from the measurement errors of the radius and real part of the refractive index, is less than 3.4%.
基金financial support from Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment&Technology(FMZ202002)the Open Fund of Yunnan Provincial Key Laboratory of Tea Science(2021YNCX004).
文摘An intelligent control system is designed in green tea fixation,which can automatically and continuously adjust the fixation parameters for quality improvement.Aroma is detected with PEN-3 electronic nose,and signals are sent to the computer.With the aroma signals,the fixation process is separated into two stages:in the first stage,the key purpose is enzymatic reaction,which can be suppressed with high temperature;it is the oxidation re-action which should be concentrated on in the second stage,and a middle temperature is a good choice.With the designed fuzzy logic algorithm,the pot temperature is kept at a high level at the beginning,and the enzymatic reaction can be successfully reduced.In the second stage,the temperature is kept at a middle value to decrease oxidation.With the designed intelligent control,the green tea product quality is improved for aroma,taste,appearance,liquor color,and residues.
