[Objective] This study was aimed to screen out the strong-aroma tobacco variety with good ecological adaptability as the best cultivar in Chizhou. [Method] Based on the ecological conditions that formed the strong ar...[Objective] This study was aimed to screen out the strong-aroma tobacco variety with good ecological adaptability as the best cultivar in Chizhou. [Method] Based on the ecological conditions that formed the strong aroma style of tobacco leaves in the tobacco-growing area, 6 varieties（K326, NC55, NC71, 0508, Yunyan99, Yan240） were selected and compared through combining the demand characteristics of industrial enterprise to the quality. [Results] The output value of 0508 was the highest and NC71 had a medium output value but with coordinated chemical composition. The system evaluation of this study on the quality and characteristic style further clarified the feature strength and utility value of various tobacco varieties with strong aroma. [Conclusion] NC71 is the best cultivar in Chizhou tobacco-growing area, and it is suggested using NC71 as the demonstrative variety of the next year. The study on the excavation and screening utilization of tobacco varieties with local features is of great significance to the tobacco production industry.展开更多
To objectively classify and evaluate the strong aroma base liquors(SABLs)of different grades,solid-phase microextraction-mass spectrometry(SPME-MS)combined with chemometrics were used.Results showed that SPME-MS combi...To objectively classify and evaluate the strong aroma base liquors(SABLs)of different grades,solid-phase microextraction-mass spectrometry(SPME-MS)combined with chemometrics were used.Results showed that SPME-MS combined with a back-propagation artificial neural network(BPANN)method yielded almost the same recognition performance compared to linear discriminant analysis(LDA)in distinguishing different grades of SABL,with 84%recognition rate for the test set.Partial least squares(PLS),successive projection algorithm partial least squares(SPA-PLS)model,and competitive adaptive reweighed samplingpartial least squares(CARS-PLS)were established for the prediction of the four esters in the SABL.CARS-PLS model showed a greater advantage in the quantitative analysis of ethyl acetate,ethyl butyrate,ethyl caproate,and ethyl lactate.These results corroborated the hypothesis that SPME-MS combined with chemometrics can effectively achieve an accurate determination of different grades of SABL and prediction performance of esters.展开更多
基金Supported by the Project of Anhui Tobacco Monopoly Administration(20110551011)~~
文摘[Objective] This study was aimed to screen out the strong-aroma tobacco variety with good ecological adaptability as the best cultivar in Chizhou. [Method] Based on the ecological conditions that formed the strong aroma style of tobacco leaves in the tobacco-growing area, 6 varieties（K326, NC55, NC71, 0508, Yunyan99, Yan240） were selected and compared through combining the demand characteristics of industrial enterprise to the quality. [Results] The output value of 0508 was the highest and NC71 had a medium output value but with coordinated chemical composition. The system evaluation of this study on the quality and characteristic style further clarified the feature strength and utility value of various tobacco varieties with strong aroma. [Conclusion] NC71 is the best cultivar in Chizhou tobacco-growing area, and it is suggested using NC71 as the demonstrative variety of the next year. The study on the excavation and screening utilization of tobacco varieties with local features is of great significance to the tobacco production industry.
基金The study was supported by the Key Research and Development Program of Jiangsu Province(BE2020312)National Natural Science Foundation of China(31671844)+2 种基金Open Project of National Engineering Laboratory for Agri-product Quality Traceability(AQT-2019-YB7)Science Foundation for Postdoctoral in Jiangsu Province(1501100C)Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD).
文摘To objectively classify and evaluate the strong aroma base liquors(SABLs)of different grades,solid-phase microextraction-mass spectrometry(SPME-MS)combined with chemometrics were used.Results showed that SPME-MS combined with a back-propagation artificial neural network(BPANN)method yielded almost the same recognition performance compared to linear discriminant analysis(LDA)in distinguishing different grades of SABL,with 84%recognition rate for the test set.Partial least squares(PLS),successive projection algorithm partial least squares(SPA-PLS)model,and competitive adaptive reweighed samplingpartial least squares(CARS-PLS)were established for the prediction of the four esters in the SABL.CARS-PLS model showed a greater advantage in the quantitative analysis of ethyl acetate,ethyl butyrate,ethyl caproate,and ethyl lactate.These results corroborated the hypothesis that SPME-MS combined with chemometrics can effectively achieve an accurate determination of different grades of SABL and prediction performance of esters.
