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JFAE(Food & Health-Parta) Vol3-1 (2005)

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JFAE(Food & Health-Parta) Vol3-1 (2005) WFL Publisher Science and Technology 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, China. 2 Tobacco College of Henan Agricultural University, National Tobacco Cultivation and Physiology and Biochemistry Research Centre, Wenhua Road No. 95, Jinshui District, Zhengzhou 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 (Xuchang 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 (Luoshan County), T7 (Yanling County), T8 (Mianchi aroma quality exactly. Aroma quality is an important index to County), T9 (Gushi County), T10 (Jia County), T11 (Neixiang assess the quality of tobacco leaves and cigarettes, and also is County), T12 (Pingqiao District), 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.
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