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WILLIAM G. GALETTO and A. ALLEN BEDNARCZYKResearch & Development Labs, McCormick & Co., Hunt Valley, MD 21031

RELATIVE FLAVOR COMTRIBUTION OF INDIVIDUAL VOLATILE COMPONENTSOF THE OIL OF ONION (Allium cepa)

INTRODUCTIONCHARACTERISTIC FLAVOR of the onion has been the

of chemical investigations for over 80 yr . Semmlerprepared an oi l by steam distillation of fresh bulbs and

that a major component of the oi l ha d an empiricalof C6 H12 S2 . Carson an d Wong (1961) identified didisulfide, methyl propyl disulfide and dipropyl dias well as th e corresponding trisulfides in the steam

essence of onion. The onion flavor literature up tohas been reviewed and documented by Carson (1967).recently Brodnitz et al. ( 1969) and Brodnitz and Pollock

have reported th e results of their extensive analyses off onion. They identified a total of l 7 components-all ditrisulfides except for a single dimethyl thiophene. Boelens. (1971 ), using th e latest in GLC column technology, re

th e isolation an d identification of 45 volatile constituof steam distilled onion oil, primarily polysulfides and

compounds.is th e case with numerous other natural products, manycomponents have been identified in th e flavorful distilof onions, bu t little information exists on th e relative con

of the various individual components to overallflavor. Some general comments correlating flavor

an d composition can be found in th e literature.et al. (1971) stated that th e propyl and propenyl ditrisulfides have boiled onion flavor notes, th e dimethylfried onion flavor characteristics and that

thiosulfonates have fresh onion flavor. Th e fresh onionof alkyl thiosulfonates has also been demonstrated

et al. (1973). These compounds would no t beto be present in th e steam distilled oil of onionet al., 1971) due to their thermal instability.

order to correlate more accurately onion oi l flavor withcomposition, we have undertaken a study using mul

regression analysis techniques to correlate quantitativedata with organoleptic evaluation.EXPERIMENTAL

preparat ion and sensory panel evaluationsof onion oils to be evaluated by the sensory panel includedcommercial oils, blends of these oils, and oils fortified with fracobtained by fractionally distilling a commercially purchased onion

by blending O.Sg of each oil with O.Sg of Tween 80 and dilutingof 50g with 95% ethanol. Each base was then dilutedwere equivalent to O.lg of base in l,OOOg of water (IX), O.lg ofof water (3.33x) and O.Sg of base in 1OOg of water (SOX).of the blending operation and the use of oils at the threeof the individualof panel responses for overall onionintensity. of seven trained judges, graded 18at three different concentrations (54 total judgements). Be-of the lingering aftertaste of the flavorful oils, only one oil could

at each concentration was graded foronion intensity on a scale of I-3 with I being threshold, 1 ==moderate and 3 = high.

Gas chromatographic analysisGas chromatographic analysis was used to quantitate the individualcomponents of each oil sample. The areas of each peak were measuredby u ~ g a Hewlett-Packard 3370-A electronic integrator. The peakquantities were calculated by comparing the individual peak areas tothat of an internal standard of known weight, n-decane. The responsefactor of all of the peaks relative to n-decane was assumed to be 1.Using a Hewlett-Packard 5750 gas chromatograph equipped with aflame ionization detector, 1 1-11 of each oil was analyzed on an 8 ft X1/4 in. o.d. glass column packed with 10% Carbowax 20M on 80-100mesh Chromosorb WAW. The oven temperature was programmed from90-2300C at a rate of 4C/min and held at the maximum temperature

for 20 min.Statistical analysisStandardized peak areas, per 1-11 of oil, were multiplied by the appropriate factors (1 x, 3.33x and SOX) to give a relative quantitation ofeach peak evaluated by the sensory panel at the three concentrationstested for each oil. I t was not necessary to determine the absolutequantity of each peak in the oils evaluated by the sensory panel so longas the quantities were in the ratio of 1:3.33:50 for each base. Quantitative peak data were treated as independent variables and sensory panelscores for overall onion oil flavor intensity were treated as dependentvariables. The data were analyzed by using the University of CaliforniaBMD 02 R step-wise regression analysis program on a Univac HOBshared processor system at the University of Maryland's Computer Sci-ence Center.Regression equations may be used to predict specific values of onevariable in terms of another variable. Thus, in the regression equationfor a line

Y =bx +awhere a is the y intercept and b the slope of the line (the simplecorrelation coefficient), any value of y can be predicted for a corresponding value of x. In the case of multiple regression analysis, agiven value for a dependent variable is defined in terms of several in-dependent variables. Kramer and Twigg (1970) have suggested that inthe evaluation of flavor, gas chromatographic peaks that contribute toan explanation of flavor acceptability can be statistically selected bysubmitting the gas chromatographic data as independent variables, andtaste panel scores as dependent variables to a step-wise multiple re-gression analysis. Those peaks which significantly increase the multiplecorrelation coefficient (R) are considered as having significant flavorcontribution and are included in the regression equation. By defmition,the coefficient of determination (R2 ) for the various combinations of-independent variables (GC peaks) explains a given percentage (expressed as a decimal equivalent) of the dependent variable (in this case,flavor scores). Thus, i f the inclusion of three gas chromatographic peaksin an equation yields a multiple correlation coefficient (R) of 0.8, thecoefficient of determination (R 2 ) is equal to 0.64, meaning that 64% ofthe panel's response is explained by the three variables.

RESULTS & DISCUSSIONIN OU R ORIGINAL computer analysis of the data, th e computer was presented all of the data and given the option ofincluding or excluding an y of th e variables, in any order, ingenerating the regression equation. Although the computerdeveloped an equation using most of th e independent variables, the most significant contributors to a high multiple correlation coefficient were peaks l , 18 an d 6 (R 2 =0.8764). ThisVolume 40 (1975)-JOURNAL OF FOOD SC/ENCE-1165

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1166-JOURNAL OF FOOD SCIENCE-Volume 40 (1975)equation excluded the major onion oil components which weknew from previous experience (Galetto an d Pace, 1973) to bemajor contributors of onion flavor. An examination of thecompute r print-out allowed us to conclude that the nature ofthe data was preventing an efficient regression analysis. Th edata had to o many colinear variables as evidenced by th e largenumber of high correlation coefficients among the independen t variables (peaks) listed in the correlation matrix. Table 1lists th e mean correlation coefficient for each independentvariable with aU other independent variables. Th e large numberof high correlation coefficients implied a lack of orthogonalit y , i.e., th e effect of one variable is not independent of th eother variables. This is a common occunence with naturalproducts which we tried to eliminate by our blending andfortification methods, which apparently failed (Bender, 1974) .An alternate and effective way of handling such data is torequire that specific indepen dent variables (peaks) be includedin generated regression equations. This is accomplished bylimiting the number of variables available for use as possible

Tabla 1- M un COI',...tlon coefficients for eHh inclesMndent vert-eble with all other independent - ieb le lIndependent Ccwnlation Independent Correlation

variable - ' f i c i en t variebla eoafficient1 0.79 11 0.902 0.81 12 0.853 0.90 13 0.894 0.90 14 0.545 0.87 15 0.906 0.91 16 0.917 0.84 17 0.798 0.88 18 0.909 0.87 19 0.9010 0.88 20 0.9021 0.90

2

1

1840 44 48

Mlnwt..F ig. t - Ga chrof'fllltogram of th oil of onion. Carbo-x 20Mcolumn.

regression equation components. In this manner, the analystcan be assured of evaluating specific variables and specificcombinations which otherwise might no t be tested in equa-tions because of some accidenta l limitations in the mathematical calculations. The ultimate analysis is to develop regres-sion equations using all possible com binations of variables(on ion o il flavor compounds as represented by gas chromatographic peaks), adding and deleting variables from equationsand noting the ef fect of such additions or deletions upon thecoefficient of determination ( R2 ) . The coefficient of determination, by definition, tells how much of the panel's flavorresponse is explained by th e variables included in th e regres-sion equation . Since we have 21 variables from the chromatogram, this would require 21! or 5.1 X 10 1 9 equations. Rathertha n running that many regression analyses , we relied on theinformation already known about onion oil flavor (i.e., some ;of the major polysulfides are significant flavor contributors) an d developed a series of equations based on these compoundsan d combinations thereof. A total of 47 regression analyseswere ru n using the gas chromatographic data versus th e overallonion flavor panel scores. Ta ble 2 summarizes th e variables(gas chromatografhic peaks) included in th e equations andth ei r respective R 's.

When peaks I, 5 and 7 (methyl propyl disulfide, methylpropyl trisulfide and dipropyl trisulfide) (See Fig. 1) are ineluded in an equation (#1), an R2 value of 0.8699 is obtained;the addition of peak 2 (dipropyl disulfide} does no t increasethe R1 value. In this equ ation, the computer was given theoption of including peak 2 along with peaks 1, 5 an d 7, _but Iexcluded it because of its insignificant contribution. ThiS IS .somewhat sur prising since dipropyl disulfide is one of the ;major components of onion oil. We can see that the relative icontribution o f peale 1 is quite la rge by e xamining equation 9(peaks 21 : and 7, R2 =0.8066) and equation I (peaks I, 5an d 7, R - 0 .8699).

Another important flavor contributor appears to be ~ a k 18. Equation 8, including just peaks I , 5 an d 18 has an R o_0.8725 . Again there was an option t o include dipropyl dsulfide, peak 2, wh ich was not exercised. Upon comparison_ ofequation 10 (pe.ak s 2, 5, 7 an d 18, R2 =0 .8087) with equauon36 (peaks 2, 5, 7, 12, 15 an d 18, R2 = 0.8502) we see thatthere is a significant contribu tion to the overall flavor frompeaks 12 an d 1S. . 1The question frequently arises regarding how similar Rvalues can result from different combinations of peaks, ~ - equation 3 which includes only peaks 1 and S having an R 00.8497 and equation 36 (which includes peaks 2, 5, 7, 12, ISand 18) having an R2 of 0.8502. A valid explanation of tlliSsimilarity is that th e R1 values are predicting or explain ing acertain percent of the overall response of th e panel. This o v ~ r all response may be comprised of specific flavor r a c t e n s t ~such as sulfur , green or bite. One set of variables may explaJII85% of the response, but most of th e weight of the responstmay fall in th e sulfur category. Another se t of variables, alsoequaling 85%, may have their response explanations s p r ~ a d ove r several flavor characte'ristics such as green, bite or b o l e ~ with only a small contribution being attributed to that 0sulfur. One approach that is useful in the interpreta tion ofsuch data is to select th e fewest number of variables that pro-duce a significant increase in the R2 Using this type of ex.allltnation, it appears that th e major onion compounds of overallonion flavor signjfjcance are those represented by pea_Jcs l ,J 7, 12, I5 an d 18. Work is underway to isolate and ,dent Ycomponents 12, 15 and 18.

REFERENCESBender, F . 197. Personal eo mm unieatioru. 1971.Boeleru, M., de Va lo aa , P .J ., Wobben, H .J . and va n der Gen. A- 19.VolaUie O.vor compouoda f:rom onion. J . Aar . Food CberD-

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FLAVOR COMPONENTS OF OIL OF ONION-1161

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T.ble 2- Regnaion eque t i - devetoped from c:ombineticlfls of independent veriebles (GLC p lu ) vs fa- p.nel _ _.

1 2 3X 0X X XX 0X X XX XX 0X X XX 0

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R'0.86990.87680.84970.86080 .87 030 .87550.88670 .87250 .80660 .80870 .81560 .81560.81040 .82430.68220 .68230 .74850 .74850.66260.67360 .75820 .66740 .76610 .73910.60940.82540.81060 .82570.82240.82620.81490.78370.82750.82730 .83060 .85020 .83340.83180.82590 .83230 .86990.86830 .84970.86080.87320.87550.9021

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Data not Inc luded In cal c u la tio n; X Va riable Included in r egr - i on equation by t h e computer; 0 Ve rlable dele18d from regrel&ionutlon by th e computer.

t ~ . N.H ., Pucale , J . V. &J>d Van Denllce. L . 1$71 . FlaYOr co mpo-of &arlic extract. J . A&r. Fo od Cbem . 19 : 27 3 .M .H . Pao

Galetlo, W.G. an d Pace. C.A. 197 3. 8yntbeUe onion o il compoeiUoll.U.S . Patent 3 ,764 ,70 9 .Kramer. A. an d Twta. B.A . 1970. Flavor. 1n "Q..ality Conl.roiFor Tb eF o od IDduatry," Vo l1 , Jrd ed . Avl P:\lb. Co., Wel&port, Cono.SeiDIIller, F .W. 1892. Daa iuerUebo 01 de r Kiicbell1wiebel (ADiwncepa L.). Arc:b. Pbann. 23 0 : 443 .Ms received 4.{7[75 ; reviled 8/ tSnr.; accepted 6/ tan5.The au thon ac knowlec:l&e lb e Iliad Ultst&Dee of Prof. AmihudKramer, Dept. o f Horticulture, UDiv. of Mer)'land aod Prof. FilmoreBender, Acrlc:ultural Ec:onomlc:t Dept., UDiv. of Maryland Ill th e an.aJy.sla of tb o otaUatk:al data .