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Meri-Rastilantie 3 B, FI-00980 Journal of Food, Agriculture & Environment Vol.9 (1): 501-504. 2011 www.world-food.net Helsinki, Finland e-mail: [email protected]

Study on model of aroma quality evaluation for flue-cured tobacco based on principal component analysis

Xiefeng Ye 1, 2, Guoshun Liu 2, Hongen Liu 3 and Shiqing Li 1, 4* 1 College of Resources and Environment, Northwest AF University, Yangling 712100, . 2 Tobacco College of Agricultural University, National Tobacco Cultivation and Physiology and Biochemistry Research Centre, Wenhua Road No. 95, Jinshui , 450002, China. 3 Resources and Environment College of Henan Agricultural University, Zhengzhou 450002, China. 4 State Key Laboratory of Soil Erosion and Dryland Farming on Loess Plateau, Yangling 712100, China. *e-mail: [email protected], [email protected], [email protected]

Received 4 November 2010, accepted 20 January 2011.

Abstract To establish a new method for quality evaluation of flue-cured tobacco, aroma components in thirteen flue-cured tobacco samples were identified and determined by the simultaneous distillation extraction-gas chromatography-mass spectrometry (SDE-GC-MS), and an evaluation model of aroma quality was established based on principal component analysis. Results indicated that the highest integrated score occurred in the sample T10, followed by T13, T1, T8, T12, T5, T3, T4, T9, T7, T11, T2 and T6, which were grossly consistent with the results of the traditional sensory smoking evaluation. Therefore, this model established in our study was feasible. Compared with the appearance, sensory, and traditional chemical components quality evaluation methods, our evaluation model based on aroma quality and principal component analysis can reflect the aroma quality of flue-cured tobacco more objectively, directly and accurately, and clear the position of flue-cured tobacco leaves in the cigarette blend.

Key words: Flue-cured tobacco, aroma components, quality evaluation, SDE-GC-MS, principal component analysis.

Introduction Enough and pure aroma, clear aroma type and mellow flavor are Therefore, to research and establish an objective evaluation considered as the characteristics of high quality flue-cured method and system of tobacco leaves aroma quality is extremely tobacco leaves 1. Aroma components of tobacco leaves can be important. Recently, mathematical statistical tools have been classified into several kinds by functional groups which cause widely applied in tobacco quality evaluation, such as SPSS aroma, such as acids, alcohols, ketenes, aldehydes, esters, software 10, gray relative analysis method 11, artificial neural lactones, phenols, dicarboximides, furans, amides, ethers and network classified model 12, cluster analysis and fuzzy alkanes 2. Many studies have focused on the aroma components mathematics 13. Principal component analysis is a statistical analysis of tobacco leaves. Stedman 3 discussed more than 100 method that can as much as possible reflect the original variables kinds of tobacco acidic ingredients found at that time. Raloyd 4 information by dividing multiple indicators into a few irrelated separated and identified essential oils extracted from flue-cured composite indicators 14. Principal component analysis has been tobacco, and 323 chemicals were found, of which 275 were first applied in many fields, such as food quality evaluation 15, soil found in flue-cured tobacco. Xian et al. 5 systematically studied exploit 16 and water conservation 17. The main objective of this the neutral aroma components in Yunnan flue-cured tobacco and study was to establish a model of flue-cured tobacco aroma quality 129 chemicals were identified. evaluation through the analysis of aroma components based on Currently the methods of quality evaluation of tobacco are principal component analysis and obtain a more objective method mainly appearance quality evaluation (GB2635-92) 6, 7, of tobacco quality evaluation. conventional chemical composition evaluation 8, sensory evaluation (GB5606.4-2005) 9 and so on. Commonly, the results Materials and Methods from appearance quality evaluation and sensory evaluation are Sampling: Thirteen flue-cured tobacco leaf samples (8 to 12 leaf inaccurate and greatly affected by appraisers’ subjective factors. position from top to bottom) were collected from different districts Conventional chemical composition which is the inner basis of in Henan Province, in 2004. Each sample weight was 5.0 kg and tobacco quality includes total sugar, reducing sugar, nicotine, was represented by T1 ( County), T2 (Yexian County), total nitrogen, starch, potassium, chlorine, etc., and its results T3 (Huaiyang County), T4 (Suiyang County), T5 (Xiangcheng reflect the tobacco leaves quality better but cannot reflect the County), T6 (), T7 (Yanling County), T8 (Mianchi aroma quality exactly. Aroma quality is an important index to County), T9 (), T10 (Jia County), T11 (Neixiang assess the quality of tobacco leaves and cigarettes, and also is County), T12 (), T13 (Lushan County). the material base to distinguish the tobacco leaves type 1.

Journal of Food, Agriculture & Environment, Vol.9 (1), January 2011 501 Sample treatment and analysis: Aroma components were variables, respectively, expressed as: determined by internal standard method using GC-MS (HP 5890- 5972), with nitrobenzene as internal standard. Firstly, the sample ⎧ F =a X +a X +…+a X ⎨ 1 11 1 21 2 p1 p was ground into powder and distilled by water vapor, and then ⎩ F2=a12X1+a22X2+…+ap2Xp extracted with dichloromethane (10 g tobacco samples, 1 g citric … acid, 350 ml distilled water and 0.5 ml internal standard were added Fm=a1mX1+a2mX2+…+apmXp into a 500 ml round flask, and 60 ml dichloromethane was added °C α into the other 250 ml round flask which was heated with 60 2. Taking the weight i (i = 1,2, ..., m) of each factors variables waterbath, extracting with simultaneous distillation extraction calculated by variance contribution rate of different factor instrument). Secondly, drying organic phase by adding variables as the weighting coefficient. Then a sequence of aroma anhydrous sodium sulfate into organic phase and then quality of each samples was given according to the scores °C α concentrating organic phase to 1 ml with 60 waterbath will get caculated by using an integrated determine formula F = 1F1 + α α tobacco essential oils. Thirdly, the samples after pre-processing 2F2 + ... + mFm. were identified using GC/MS and qualitative analyzed using NIST library search. Results and Discussion The conditions of GC-MS analysis were: chromatographic Aroma components of different flue-cured tobacco samples: column HP-5 (60 m × 0.25 mm. i.d. × 0.25 µm d.f.), carrier gas and Aroma quality is an important index to evaluate the quality of current speed of helium gas and 0.8 ml/min, injection port flue-cured tobacco. It has been reported that 31 kinds of aroma temperature 250°C, transmission line temperature 280°C, ion components had a great influence on flue-cured tobacco aroma source temperature 177°C. Heating-up procedure: beginning quality. The concentrations of these aroma components of 13 temperature 50°C (keeping 2 min), then heating-up to 120°C with tobacco samples are listed in Table 1. In terms of the total aroma the rates of 2°C/min (then keeping 5 min), then heating-up to concentration, samples T13, T1 and T10 were top three and 240°C with the rates of 2°C/min (then keeping 30 min); split ratio samples T2, T11 and T6 were last three. of 1:15, sample size: 1:15, injection volume 2 µl, ionization energy 70 eV, mass number range of 50-500 amu, and MS spectra library Results of principal component analysis: Thirty-one kinds aroma of NIST02 18. components of 13 samples were statistically analyzed with Thirty-one aroma components were all detected, including principal component analysis procedure using SPSS 11.5 benzaldehyde (x1), benzyl alcohol (x2), phenylacetaldehyde (x3), software. Eigenvalues of correlation matrix and component score phenylethanol (x4), furfural (x5), furfuralcohol (x6), acetyl furan coefficient matrix were calculated respectively (Tables 2 and 3). (x7), 5-methyl-2-furfural (x8), 2,5-dimethyl-2,4-2-hydroxy-3- Six principal components were extracted according to the principal dihydro-furanone (x9), 3,4-dimethyl-2,5-furan-dione (x10), 2-acetyl that eigenvalue was greater than 1, respectively 16.547, 4.631, pyrrole (x11), solanone (x12), 6-methyl-5-heptene-2–ketone (x13),- 3.016, 1.882, 1.190, 1.122, and the cumulative variance contribution damascenone (x14), geranylacetone (x15),-ionone (x16), rate of these 6 principal components was 91.578% (Table 2). dihydroactinidiolide (x17), megastignone1 (x18), megastignone2 Because the information of these 6 principal components (x19), megastignone3 (x20), megastignone4 (x21), 3-hydroxy-β- accounted for 91.578% of the total information, they can basically keto-dihydro-malaysia (x22), farnesyl acetone (x23), reflect the information of original variables.

2cyclopentene1,4-dione (x24), linalool (x25), 1,2,3,4-tetrahydro- The first principal component F1= 0.166x1 - 0.034x2 + 0.146x3…- 1,1,6-trimethyl-1naphthalene (x26), 1,2,3,4-tetrahydro-1,1,6- 0.069x31, which could explain the 53.376% of original variables trimethyl-2-naphthalene (x27), indole (x28), 4-vinyle-2-methoxy- alone and its representative variables were x16 and x24 (Table 3). phenol (x29), 1,2-dihydro-2,5,8-trimethyl-naphthalene (x30) and The second principal component F2 = -0.043x1 + 0.080x2 + lo vetivone (x31). Sensory quality was evaluated by seven 0.101x3…0.042x31, which could explain the 14.940% of original appraisers of the smoking evaluation team of Henan Agricultural variables alone and its representative variables were x19, x20 and

University according to GB5606.4-2005. x21. The third principal component F3 = 0.030x1 + 0.084x2 + 0.002x4…0.157x31, which could explain the 9.730% of original Statistical analysis and aroma quality model evaluation: All variables alone and its representative variables were x23 and x26. data were statistically analyzed using SPSS 11.5 software and the The fourth principal component F4 = -0.086x1 - 0.027x2 - 0.135x3…- model of aroma quality evaluation was established according to 0.071x31, which could explain the 6.072% of original variables the methods of different researchers 10, 17, 19-20. alone and its representative variables were x18 and x27. The fifth

Correlation matrix of principal component analysis was principal component F5 = -0.024x1 - 0.061x2 - 0.149x3…- 0.044x31, constituted with aroma components of different flue-cured which could explain the 3.840% of original variables alone and tobacco samples. Then a sequence of tobacco aroma quality was its representative variables were x5, x7, x8, x9 and x12. The sixth obtained according to the sum of multiply between a linear principal component F6= -0.020x1 + 0.255x2 - 0.016x3…- 0.347x31, combination of the different principal components and its which could explain the 3.619% of original variables alone and its contribution rate. Concrete steps: 1. P index-variables of n samples representative variables were x2, x4, x22 and x31. built into data set, and the original variable Xi converted into factor variables which were linear combinations of the original Aroma quality evaluation of different flue-cured tobacco variable, that is X1, X2, …, Xp were integrated into irrelated m(m

502 Journal of Food, Agriculture & Environment, Vol.9 (1), January 2011 Table 1. Concentrations of the principal aroma components in different flue-cured tobacco samples.

Aroma Components T1 T2 T3 T4 T5 T6 T7 T8 T9 T10 T11 T12 T13 µg g-1 x1 0.812 0.494 0.504 0.161 0.614 0.432 0.431 0.833 0.339 1.889 0.534 0.728 0.913 x2 10.103 3.397 4.031 5.851 8.520 3.130 5.105 6.143 5.376 6.834 3.205 6.613 6.733 x3 5.773 2.462 3.581 4.226 4.669 1.989 4.386 6.455 2.848 9.446 2.587 3.765 6.049 x4 4.781 2.532 2.016 3.323 4.792 2.110 2.804 2.707 3.702 4.501 3.173 4.680 3.310 x5 34.911 13.957 17.804 10.800 21.993 12.944 14.668 23.634 16.462 27.226 14.493 24.631 37.776 x6 4.420 3.458 3.107 3.468 2.887 2.344 2.445 3.019 3.587 10.057 2.735 2.748 5.820 x7 1.263 0.856 0.672 0.578 0.983 0.835 0.647 0.937 0.909 1.611 0.875 1.033 1.712 x8 3.699 2.779 2.642 1.734 1.904 1.589 2.229 2.811 3.275 3.167 2.735 3.663 3.424 x9 1.534 0.366 0.336 0.000 1.413 0.000 0.575 1.249 0.000 0.000 0.000 0.000 2.054 x10 2.977 0.741 1.428 1.336 3.010 2.134 1.798 1.562 2.278 5.501 1.422 2.645 1.712 x11 2.526 1.725 2.016 1.553 2.273 1.839 1.869 2.082 2.136 3.112 1.969 1.933 2.625 x12 66.304 21.861 42.831 18.746 23.099 14.134 43.212 0.000 16.639 52.064 11.587 20.949 66.993 x13 1.985 0.865 1.260 0.867 1.843 0.742 1.079 1.874 0.997 3.000 0.547 1.628 2.625 x14 33.558 14.451 21.415 20.552 22.853 11.181 26.531 27.590 18.855 34.839 12.812 32.762 35.493 x15 7.578 5.681 5.879 6.429 7.741 3.828 6.112 7.808 9.966 12.835 6.455 10.073 7.989 x16 2.706 1.667 1.848 1.625 2.457 1.714 2.013 2.811 2.902 1.778 1.847 2.747 2.625 x17 9.472 5.434 5.711 5.599 7.433 5.470 6.759 7.808 10.536 12.391 7.331 9.259 9.701 x18 3.338 2.408 3.023 2.167 2.457 2.594 2.732 3.436 5.553 5.445 3.829 3.256 3.538 x19 14.794 5.022 13.269 8.452 11.119 8.515 11.432 17.074 10.936 17.392 5.759 13.939 15.065 x20 2.977 1.227 3.107 1.517 2.457 1.759 2.373 3.123 2.671 3.278 1.152 2.544 2.967 x21 22.552 6.421 16.292 8.416 18.737 7.241 15.746 22.592 10.055 18.836 6.505 16.890 21.342 x22 0.000 1.853 2.771 2.131 0.000 1.529 3.020 3.019 3.153 4.945 2.149 2.951 4.451 x23 29.047 13.050 17.888 14.304 25.864 0.000 0.000 33.628 0.000 30.394 16.501 33.474 32.754 x24 1.173 1.050 0.756 0.578 0.922 0.710 0.719 1.145 1.139 4.112 0.766 1.730 1.826 x25 2.075 0.679 0.840 1.445 1.659 0.710 2.013 1.770 1.566 2.000 1.313 2.035 2.625 x26 3.879 1.544 1.680 1.517 2.826 0.815 2.588 2.395 1.770 3.000 0.719 7.936 5.022 x27 2.616 1.359 1.260 1.336 1.413 3.154 1.798 1.666 4.698 3.501 1.969 4.375 2.511 x28 2.526 0.803 1.764 1.047 1.536 0.972 1.869 1.562 0.000 2.278 0.000 0.000 2.283 x29 11.547 2.161 3.191 1.084 4.672 2.227 5.536 6.663 0.000 8.077 0.875 0.000 6.848 x30 21.019 6.813 14.697 10.728 15.420 8.862 15.602 16.970 11.363 14.502 6.306 15.160 19.858 x31 0.000 1.297 1.428 1.084 1.782 0.645 1.941 1.458 1.126 0.000 0.605 1.354 2.397 Total quantity 311.945 128.413 199.047 142.654 209.348 106.148 190.032 215.824 154.837 308.011 122.755 235.501 321.041

Table 2. Eigenvalues of the correlation matrix. Table 3. Principal component factor score coefficient matrix. Principal Variance Cumulative variance Aroma Eigenvalue F1 F2 F3 F4 F5 F6 components contribution rate contribution rate components 1 16.547 53.376 53.376 x1 0.166 -0.043 0.030 -0.086 -0.024 -0.020 2 4.631 14.940 68.316 x2 -0.034 0.080 0.084 -0.027 -0.061 0.255 3 3.016 9.730 78.046 x3 0.146 0.101 0.002 -0.135 -0.149 -0.016 4 1.882 6.072 84.118 x4 0.028 -0.088 0.227 -0.021 -0.086 0.285 x5 -0.054 -0.066 0.073 0.051 0.239 -0.004 5 1.190 3.840 87.959 x6 0.162 -0.102 -0.015 -0.048 0.096 -0.040 6 1.122 3.619 91.578 x7 0.034 -0.186 0.086 0.038 0.288 -0.049 x8 -0.092 -0.130 0.060 0.212 0.256 -0.056 x9 -0.116 0.028 0.026 -0.016 0.230 -0.011 six principal components were calculated as 0.5828, 0.1631, 0.1063, x10 0.134 0.057 -0.043 -0.017 -0.165 0.197 0.0663, 0.0419, 0.0395 respectively. The composite scores of x11 0.052 -0.007 -0.093 0.060 0.141 0.044 principal aroma components in 13 samples have been received x12 -0.038 -0.107 -0.066 0.051 0.407 -0.019 α α x13 0.089 0.019 0.069 -0.082 -0.016 -0.048 according to the integrated determine formula F = 1×F1 + 2×F2 +α ×F + α ×F + α ×F + α ×F . The highest integrated score of x14 0.027 0.042 0.119 -0.046 -0.044 -0.063 3 3 4 4 5 5 6 6 x15 0.096 0.013 0.086 0.042 -0.192 0.003 1.913 occurred in T10, followed by T13, T1, T8, T12, T5, T3, T4, x16 -0.188 0.160 -0.014 0.233 -0.042 0.035 T9, T7, T11, T2, and T6 (Table 4). x17 0.009 -0.007 -0.032 0.170 0.037 0.031 x18 -0.005 0.062 -0.228 0.282 0.034 -0.024 x19 0.023 0.258 -0.094 0.017 -0.211 -0.065 Testing of flue-cured tobacco aroma quality evaluation model: x20 -0.029 0.304 -0.202 0.101 -0.153 -0.055 In order to test the established model of flue-cured tobacco aroma x21 -0.021 0.204 -0.012 -0.035 -0.113 -0.007 evaluation was conducted according to the traditional method x22 0.106 -0.004 -0.015 0.029 -0.048 -0.418 (Table 5). The results between the model established in this paper x23 0.091 -0.088 0.314 -0.198 -0.086 -0.017 x24 0.179 -0.090 0.068 -0.058 -0.040 -0.060 and the traditional sensory smoking evaluation method indicated x25 -0.029 0.002 0.129 0.025 0.025 -0.062 better consistency with each other. In addition to the order x26 -0.015 -0.112 0.344 -0.037 -0.042 -0.076 precedence of T3, T4, T6, T7 were different, that of the others x27 -0.064 -0.017 -0.058 0.294 0.013 0.037 were same. The results showed that the evaluation model of flue- x28 0.034 0.126 -0.157 -0.106 0.118 0.011 x29 -0.007 0.102 -0.157 -0.023 0.162 0.121 cured tobacco aroma quality in this paper was feasible to a certain x30 -0.079 0.189 -0.043 0.026 -0.011 0.003 extent. x31 -0.069 0.042 0.157-0.071 -0.044 -0.347

Journal of Food, Agriculture & Environment, Vol.9 (1), January 2011 503 Table 4. Aroma evaluation of different flue-cured tobacco. References 1Shi, H. Z. and Liu, G. S. 1998. Tobacco Aroma. China Agriculture Press, Rank Sample F Rank Sample F Beijing. 1 T10 1.913 8 T4 -0.241 2Stedman, R. L. 1965. Turkish tobacco substitute. US Patent: 3180340. 2 T13 0.215 9 T9 -0.323 3Stedman, R. L. 1968. The chemical composition of tobacco and tobacco 3 T1 0.135 10 T7 -0.329 smoke. Chem. Rev. 68:153-207. 4 T8 0.089 11 T11 -0.360 4Lloyd, R. A., Miller, C. W., Robert, D. L. et al. 1976. Flue-cured tobacco 5 T12 0.080 12 T2 -0.458 6 T5 -0.013 13 T6 -0.467 flavor. I. Essence and essential oil components. Tob. Sci. 54:40-48. 5 7 T3 -0.240 Xian, K. F., Shen, C. Z. and Qi, W. M. 1992. Study on the neutral aroma constituents of Yunnan flue-cured tobacco. China J. Tob. 2:1-9 (in Table 5. Aroma quality evaluation of different flue-cured Chinese with English abstract). 6Yin, Q. S., Chen, J. H., Wang, X. 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504 Journal of Food, Agriculture & Environment, Vol.9 (1), January 2011