u n i ve r s i t y o f co pe n h ag e n

Headspace solid-phase microextraction analysis of the volatile flavour compounds ofroasted chickpea (Cicer arietinum L.)

Lasekan, Ola; Juhari, Nurul Hanisah Binti; Pattiram, Parveen

Published in:Journal of Food Processing and Technology

DOI:10.4172/21577110.1000112

Publication date:2011

Document versionPublisher's PDF, also known as Version of record

Citation for published version (APA):Lasekan, O., Juhari, N. H. B., & Pattiram, P. (2011). Headspace solid-phase microextraction analysis of thevolatile flavour compounds of roasted chickpea (Cicer arietinum L.). Journal of Food Processing andTechnology, 2(3), 1000112. [2(3)]. https://doi.org/10.4172/21577110.1000112

Download date: 27. aug.. 2020

JFPT

http://www.omicsonline.org/jfpthome.php

Rogers E. Harry-OKuru, National Center for

Agricultural Utilization Research, USA

Xuetong Fan, Eastern Regional Research

Center, PA

Silvia M. Albillos National Center for Food Safety and Technology, Summit-Argo

Tony Jin,Eastern Regional

Research Center, USA

C J Boushey, Purdue University,

USA

Maria Gullo, University of

Modena and Reggio Emilia, Italy

Chalat Santivarangkna, Technical University of

Munich, Germany

Yin Li,North Dakota State University, Fargo

Ghufran bin redzwan, Universiti Malaya,

Kuala Lumpur

Jozef Kokini, Director, Illinois

Agricultural Experiment Station, USA

Noureddine Benkeblia, UWI Mona Campus,

JAMAICA

Fabio Mencarelli, University of Viterbo, Italy

Steven Pao,Virginia State

University, Petersburg

Toru Matsui, Univ. of the Ryukyus,

Japan

Mohamed Fawzy Ramadan Hassanien,

Zagazig university, Egypt

Daniel St-Gelais, Food Research and

Development Centre, Canada

Federico Harte, The University of Tennessee, USA

Anet Režek JambrakUniversity of Zagreb,

Zagreb Croatia

Thaddeus Ezeji, The Ohio State University

& OARDC, Wooster Ohio

Chris Sommers, Eastern Regional

Research Center, USA

Shiowshuh Sheen, Microbial Food Safety Research Unit, USA

Marie Yeung, California Polytechnic State University, USA

Kathiravan Krishnamurthy,

Illinois Institute of Technology, IL

Dike O. Ukuku, Philadelphia

Food Processing and Technology includes set of physical,

chemical or microbiological methods and techniques used to transmute raw ingredients into food and its transformation into other forms in food processing industry.

It is an international journal designed to publish original research on various disciplines encompassing the processing and technology of food. It features the significant interest to researchers and scholars for the progress of food science, scope of the journal to provide a complete source of authentic information about the current developments in the field of food processing and technology.

Journal of Food Processing & Technology – Open Access using online manuscript submission.

Submit your manuscript athttp://www.omicsonline.org/submission

ISSN: 2157-7110

OMICS Publishing Group5716 Corsa Ave., Suite 110, Westlake, Los Angeles, CA 91362-7354, USA, Phone: +1- 650-268-9744, Fax: +1-650-618-1414, Toll free: +1-800-216-6499

Volume 2 • Issue 3 • 1000112J Food Process TechnolISSN:2157-7110 JFPT, an open access journal

Open AccessResearch Article

FoodProcessing & Technology

Lasekan et al., J Food Process Technol 2011, 2:3http://dx.doi.org/10.4172/2157-7110.1000112

Keywords: HS-SPME; Chickpea; Roasted; Volatiles; RSM

Abbreviations: cm: centimetre; min-minute; g: gram; µm: micro-meter; mm: milimiter; ml: mililiter

IntroductionChickpea (Cicer arietinum) belongs to the class of food called

legumes or pulses. They have a delicious nut like taste and buttery texture after cooking. It is a staple food crop in some tropical and subtropical countries [1]. Chickpea was first domesticated in the Middle East and it’s an important crop in India, the Mediterranean area, and most recently, Mexico, Argentina, Chile and Peru [2]. It thrives in cool, dry climates on sunny sites with well-drained soils. Chickpea is reported to tolerate annual precipitation of 2.8 – 15.0 cm. There are many uses for chickpea. Sprouted seeds are eaten as a vegetable or salad. Dried seeds can be cooked in stews, ground into flour called ‘gram’ and shaped in balls and fried, or roasted and eaten as a snack called ‘leblebi’.

Chickpeas are a helpful source of zinc, foliate and protein [3]. They are also very high in dietary fibre and hence a healthy source of carbohydrates for persons with insulin sensitivity or diabetes [4]. Chickpeas are low in fat and most of this is polyunsaturated [5]. Some studies on the attractiveness of chickpea’s volatile components to insect larvae have been reported [6,7], but, so far, very few published studies on the aroma constituents of the processed chickpeas have been reported. Rembold et al. [7], reported on the volatile components of chickpea seed.

Traditionally, pulses and seeds can be consumed raw or after different thermal processes. A substantial part of these foods is roasted to enhance their sensorial properties and nutritional value [8]. Solid-phase microextraction (SPME) is a simple, sensitive, robust, reliable, low cost sampling technique based on analyte diffusion that combines the advantages of both static and dynamic headspace for qualitative volatile analysis [9]. It has been widely adopted for use in food flavour analysis and most especially in legumes [10,11]. The amount of an analyte sorbed on the SPME fibre and the resulting sensitivity are determined both by sorption kinetics and by the distribution coefficient of the compound between the fibre surface and the sample. Unlike conventional solid phase extraction and purge- and trap- sampling techniques, in which a practically quantitative recovery is often

achieved. SPME is more sensitive to experimental conditions [12]. The partition equilibrium of the flavour compounds between the head-space of the sample and the SPME coating depends on the exposure time, temperature, sample volume and concentration, and type and uniformity of the matrix [12,13,14]. Application of this technique to the flavour analysis of roasted food still requires knowledge of the fibre affinity for the specific aroma compounds as well as selective studies to improve the reproducibility and the sensitivity of the method.

In the present study, HS-SPME was applied with GC-MS analysis, to provide the volatile profile of roasted chickpea as a means of unravelling and elucidating roasted chickpea as a prerequisite in developing a snack item for the health and functional food sectors. To optimize the extraction conditions, a response surface experimental design was set up to analyze the effect of three factors; extraction temperature, equilibrium time and extraction time.

Materials and Methods

Samples

Chickpea (C. arietinum) was obtained from a local supplier in Serdang, Malaysia. The chickpea was stored in a dry room (23oC, 15 –20% relative humidity) prior to roasting. Chickpeas (approximately 250 g for each treatment) were roasted at 150oC for 10, 30 and 60 min in a roaster (Model Duetl-M, Probat and Emmerich, Germany). Roasted samples were allowed to cool to room temperature (28±2oC) before milling in a household food processor (Kenwood Model FP 730) [15].

*Corresponding author: Ola Lasekan, Department of Food Technology, Faculty of Food Science and Technology, Universiti Putra Malaysia, 43400 Serdang, Malaysia, Tel: +603 8946 8535; Fax: +603 8942 3552; E-mail: Lasekan@food.upm.edu.my

Received December 20, 2010; Accepted May 01, 2011; Published May 03, 2011

Citation: Lasekan O, Juhari NH, Pattiram PD (2011) Headspace Solid-phase Microextraction Analysis of the Volatile Flavour Compounds of Roasted Chickpea (Cicer arietinum L). J Food Process Technol 2:112. doi:10.4172/2157-7110.1000112

Copyright: © 2011 Lasekan O, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

AbstractHeadspace-solid phase microextraction coupled with gas chromatography-mass spectrometry analysis were used to provide the volatile profile of roasted chickpea as a means of unravelling and elucidating roasted chickpea as a prerequisite in developing chickpea snack item for the health and functional food sectors. The results of the HS-SPME and optimization analysis using response surface methodology showed that DVB/CAR/PDMS was the most effective fibre and further results revealed the extraction temperature to be the dominant factor. A total of 61 volatile compounds were identified in the roasted chickpea. The best response within the range studied was established at 60oC extraction temperature, 30 min of equilibrium time and 15 min of extraction time. The volatile compounds iden-tified comprised of aldehydes (25%), hydrocarbons (25%), terpenoids (20%), esters (8%), ketones (8%), alcohols (8%) and heterocyclic (8%). The results further indicated that the final model was significantly (P < 0.05) fitted for the response variable (total flavour peak area) studied with a relatively high R 2 (0.9658).

Headspace Solid-phase Microextraction Analysis of the Volatile Flavour Compounds of Roasted Chickpea (Cicer arietinum L)Ola Lasekan1*, Nurul Hanisah Juhari2 and Parveen Devi Pattiram1

1Department of Food Technology, Faculty of Food Science and Technology, Universiti Putra Malaysia, 43400 Serdang, Malaysia2Department of Food Service and Management, Faculty of Food Science and Technology, Universiti Putra Malaysia, 43400 Serdang, Malaysia

Citation: Lasekan O, Juhari NH, Pattiram PD (2011) Headspace Solid-phase Microextraction Analysis of the Volatile Flavour Compounds of Roasted Chickpea (Cicer arietinum L). J Food Process Technol 2:112. doi:10.4172/2157-7110.1000112

Page 2 of 6

Volume 2 • Issue 3 • 1000112J Food Process TechnolISSN:2157-7110 JFPT, an open access journal

Extraction by solid-phase microextraction (SPME)

Ground roasted chickpea (10g) each was transferred into a 125 ml pre-cleaned Erlenmeyer flask hermetically capped with PTFE/silicon septum (Supelco, Inc., Bellefonte, PA, USA). Each sample was allowed to equilibrate during the equilibrium time (depending on the experimental design) in a thermostatic bath (Heidolph MR 3002, Germany) at the desired temperature (depending on the experimental design). Then, the SPME device was inserted into the sealed vial by manually penetrating the septum and the fibre was exposed to the headspace during the extraction time (depending on the experimental design). Because of the solid nature of the samples, internal standard was not used. Volatiles were extracted by exposing a 1 cm – 50/30 µm divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) stable Flex SPME fibre (Supelco, Bellefonte, PA, USA) to the sample headspace. This SPME method was adopted based on the selection of the most effective fibre in adsorbing a wide range of polar and non-polar analytes and sampling conditions during preliminary investigations. Prior to each extraction, the fibre was conditioned in the injection port of the GC as recommended by the supplier. After sampling, the SPME was immediately inserted into the GC injector and the fibre was thermally desorbed. A desorption time of 2 min at 250oC was used in splitless mode. Before sampling, the fibre was reconditioned for 5 min in the GC injector port at 250oC.

GC-MS analysis

After extraction, the analytes were thermally desorbed at 250oC for 2 min in the injection port of an Agilent 6890/5973 GC-MS (Agilent

Technologies Wilmington, DE) and separated on a polar DB-5 column (30 m x 0.25 mm i.d., with a 0.25 µm film thickness; J & W Scientific Folsom, CA, USA). The injection port was operated in a splitless mode subjected to an initial flow rate of 1.7 ml/min of helium. The initial oven temperature of 40oC was raised at 1oC/min to 70oC, then 5oC/min increase rate up to 200oC, followed by 50oC/min to 250oC and held at that temperature for 15 min for a total run time of 74 min.

The quadrupole mass spectrometer was operated in the electron ionization mode at 70 eV, a source temperature of 230oC, quadrupole at 150oC, in the scan range of 35 to 350 m/z. Also, a mixture of aliphatic hydrocarbons (C7 – C22) in hexane was loaded onto the SPME fibre and injected under the above temperature program to calculate the retention index (as Kovats index) of each compound. Data were collected with Agilent enhanced Chemstation software (Standard MSD version) and searched against the National Institute of Standards and Technology (NIST, 2005) mass spectra library v 2.0 (Palisade Corp., Newfield, NY). Compounds were identified by preliminary library search, and identities were confirmed by comparison of their MS ion spectra and retention indices (as Kovats indices) with the literature data. The levels of flavour components were determined from the average of three replicate chromatograms calculated and expressed as the area units of their abundance (total area counts).

Experimental design

The optimization of the HS-SPME conditions was performed by the use of a central composite experimental design (CCD), which was based on a 23 factorial design plus six axial points plus six replicates in the centre of the design. For headspace- solid phase extraction optimization, the variables chosen were the extraction temperature (T, oC), equilibrium time (teq, min) and the extraction time (tex,

Experimental domainFactor —α — 1 0 1 αExtraction temperature (T, o C) 13.07 25.00 42.50 60.00 71.93Equilibrium time (teq, min) 3.18 10.00 20.00 30.00 36.82Extraction time (tex, min) 1.59 5.00 10.00 15.00 18.41

Table 1: Factor levels and experimental domain applied to optimize the HS-SPME experimental conditions.

Table 2: Central composite design and experimental results for the response func-tions for the total flavour peak area of roasted chickpea.

Run Block Independent variables Response variableExtractiontemp (°C) x1

Equilibriumtime (min) x2

Extractiontime (min) x3

Total flavour peak TIC x 104 Y1

1 1 25.00 30.00 15.00 3.582 1 25.00 30.00 5.00 3.233 1 42.50 20.00 10.00 4.414 1 60.00 30.00 15.00 4.665 1 42.50 20.00 10.00 4.416 1 25.00 10.00 5.00 3.237 1 60.00 10.00 5.00 4.518 1 42.50 20.00 10.00 4.419 1 25.00 10.00 15.00 3.5810 1 60.00 30.00 5.00 4.6111 1 42.50 20.00 10.00 4.4112 1 60.00 10.00 15.00 4.5713 2 42.50 36.82 10.00 4.4314 2 42.50 20.00 1.59 4.3715 2 42.50 20.00 10.00 4.4116 2 42.50 20.00 18.41 4.4917 2 42.50 20.00 10.00 4.4118 2 71.93 20.00 10.00 5.3619 2 13.07 20.00 10.00 2.5620 2 42.50 3.18 10.00 4.15

Figure 1: Response surface plot for: (A) total area versus equilibrium time (min) and extraction temperature (°C), with a constant extraction time equal to 10 min; (8) total area versus extraction time (min) and extraction temperature (°C), with a constant equilibrium time equal to 20 min; (C) total area versus extraction time (min) and equilibrium time (min), with a constant extraction temperature equal to 42.50°C

Citation: Lasekan O, Juhari NH, Pattiram PD (2011) Headspace Solid-phase Microextraction Analysis of the Volatile Flavour Compounds of Roasted Chickpea (Cicer arietinum L). J Food Process Technol 2:112. doi:10.4172/2157-7110.1000112

Page 3 of 6

Volume 2 • Issue 3 • 1000112J Food Process TechnolISSN:2157-7110 JFPT, an open access journal

min). The factor levels and experimental domain are shown in Table 1. Twenty experiments (Table 2) were performed in randomized order, to minimise the effects of unexplained variability in the actual responses due to extraneous factors. The centre point was repeated six times to calculate the repeatability of the method [16].

Statistical analyses

Regression analysis and analysis of variance (ANOVA) were conducted to (1) determine regression coefficients and statistical significance of the model terms; and (2) to fit the mathematical models to the experimental data, aiming at an overall optimal region for the response variable. Multiple regression coefficients were determined by employing the least-squares technique [17] to predict linear and quadratic polynomial models for the response variable. The behaviour of the response surface was investigated for the response function (Yi, the predicted response) using the regression polynomial equation. The generalized polynomial model proposed for predicting the response variables is given as:

Yi = β0 +β1x1 + β2x2 + β3x3 + β11x12 + β22x2

2 + β33x32 + β12x1x2 + β13x1x3 +

β23x2x3 (1)

The significance of the equation parameters for each response variable was also assessed by F-ratio at a probability (P) of 0.05. The adequacy of the models was determined using model analysis, lack-of-fit test and coefficient of determination (R2) analysis as outlined by previous studies [18,19]. Joglekar & May [20] suggested that for a good fit of a model, R2 should be at least 0.80. All results were expressed as the mean values of three independent trials. The experimental design matrix,

data and analysis and optimization procedure were performed using the Minitab v. 13.2 statistical packages (Minitab Inc., Pennsylvania, USA).

Optimization and verification procedures

Numerical and graphical optimization procedures were carried out for predicting the exact optimum level of independent variables leading to the desirable response goals. First, an optimal treatment was found via response surface plotting of the data, but there had to be a compromise between the optimum ranges for the response variable. For the graphical interpretation of the independent variable interactions, the use of 3D plots of the regression model was highly recommended [16]. Therefore, the 3D surface plots were drawn to illustrate the interactive effects of the independent variables with the response variable. A numerical optimization was also carried out by the response optimizer using the Minitab software to determine the exact optimum value of individual.

Results and Discussion

Fitting the response surface model

In this study, the estimated regression coefficients for the response variable along with the corresponding R2 and F- and P-values for lack of fit are given in Table 3. Each response (Yi) was assessed as a function of main, quadratic and interaction effects of the sample extraction temperature (x1), the equilibrium time (x2) and extraction time (x3). The individual significances (F- values and P- values) of the independent variables are shown in Table 3. The results showed that the

RegressionCoefficient

Total peakarea (TIC) Main effects P value Quadratic effects P value Interaction effects P value

(x 104) x1 x2 x3 x1 x2 x3 x1 x2 x3

b0 44373.22 <0.0001* (224.52)

b1 6911.56 0.3215ǂ

(1.10)

b2 483.93 0.1427ǂ (2.58)

b3 740.88 0.0012* (21.41)

b12 -2078.31 0.0730ǂ

(4.12)

b22 -911.59 0.3779ǂ

(0.86)

b32 -416.61 0.7027ǂ

(0.16)

b12 237.50 0.2521ǂ

(1.50)

b13 -737.50 0.9839ǂ

(0.00043)b23 -12.50R2 0.9658R2 (adj) 0.9315Regression P <0.0001*Lack of fit value 0.000*

biThe estimated regression coefficient for the main linear effects (bi, b2 & b3)biiThe estimated regression coefficient for the quadratic effects (b1

2, b22, b3

2)bijThe estimated regression coefficient for the interaction effects (b12, b13, b23)*Significant (P < 0.05)ǂNot significant (P > 0.05)( ) F ratio valuesX1Extraction temperature, X2Equilibrium time, X3Extraction timeTable 3: ANOVA, regression coefficients of the first- and second-order polynomial regression model, R2, adjusted R2, probability values and lack of fit for flavour total peak area (TIC) in coded form of process variables.

Citation: Lasekan O, Juhari NH, Pattiram PD (2011) Headspace Solid-phase Microextraction Analysis of the Volatile Flavour Compounds of Roasted Chickpea (Cicer arietinum L). J Food Process Technol 2:112. doi:10.4172/2157-7110.1000112

Page 4 of 6

Volume 2 • Issue 3 • 1000112J Food Process TechnolISSN:2157-7110 JFPT, an open access journal

final model was significantly (P < 0.05) fitted for the response variable (total flavour peak area) studied with relatively high R2 (0.9658). Thus, more than 96 % of the response variation could be accurately explained by the response-surface model as function of three SPME variables (sample extraction temperature, equilibrium time and extraction time). The sign and magnitude of the coefficients indicate the effect of the variables on the response (Table 3). A negative coefficient means a decrease in response when the level of the variable is increased, whereas a positive coefficient indicates an increase in the response. A significant interaction suggests that the level of one of the interactive variables may increase while that of the other may decrease for a constant value of the response [16]. As shown in Table 3, the total flavour peak area (Y1) was significantly (P < 0.05) influenced by both the main and quadratic effects of the extraction temperature. The interaction effect of independent variables had no significant (P > 0.05) influence on the total flavour peak area. The response surface model (Equation 2) was fitted to the response variable (Yi) and three independent variables (x1, x2, and x3).

Y1 = 44373.2 + 6911.56x1 +483.93x2 +740.88x3 – 2078.31x12 – 911.59x2

2 – 416.61x3

2 + 237.50x1x2 – 737.50x1x3 – 12.50x2x3 (2)

To aid visualisation, the 3 D response surface plots for the total flavour peak area generated are shown in Figure 1. The individual optimum region led to a maximum total flavour peak area (Y1 = 4.859 x 104 TIC) which was predicted to be achieved at an extraction temperature of 60oC, equilibrium time of 30 min and extraction time of 15 min. Figure 1 shows the surface plots, were the total flavour peak area increased as the extraction temperature and extraction time were increased. It is well-known that an increase in sampling temperature increases the headspace concentration of the aroma compounds, favouring their extraction [21]. The observed increase in the experimental response studied at high temperature might be due to an increase in less volatile compounds in the headspace of the roasted chickpea. From the experimental results, the best response, within the range studied, was reached when the extraction temperature was 60oC, the equilibrium time near 30 min and extraction time of 15 min. These values were therefore selected to extract the volatile compounds from the roasted chickpea in all the subsequent analyses.

Identification of main roasted chickpea flavour compounds

A total of 61 aroma-active compounds were identified in roasted chickpea (Table 4). 30 compounds out of the 61 aroma compounds have been reported as major flavour constituents in red kidney beans [22], French beans [10,11,23,24] and chickpea [7]. Concurrent with previous reports, aldehydes (24.6 %) and hydrocarbons (24.6 %) constituted the main volatile constituents. These were closely followed by the terpenoids (20 %). Other volatile flavour compounds from different classes including esters (8.0 %), ketones (8.2 %), alcohols (8.2 %) and heterocyclic compounds (8.2 %) were also identified (Table 4). Three major aldehydes, (E)-hept-2-enal, (E)-hex-2-enal and furfural were identified as some of the principal compounds of the roasted chickpea. Additionally, the chickpea was also characterized by the presence of valeraldehyde, pent-2-enal, 3-methylbut-2-enal, hexanal, heptanal and but-2-enal respectively. Aldehydes are known to be derived from the thermal Strecker oxidative degradation of amino acids and fatty acids [25,26]. Most of these aliphatic unsaturated aldehydes, particularly, hexenal and heptenal are flavour compounds commonly identified in many fruits and vegetables.

Twelve terpenoids were present in the roasted chickpea with an abundance of β-pinene and α-phellandrene. The presences of some

aKovats indices for a DB-5 capillary columnbStandard deviation (3 replicates)cReliability of identification: MS, mass spectrum identification using Libraries; KI, Kovats index in agreement with literatures [Buttery et al., 1975; Lovegren et al., 1979; Del Rosario et al., 1984; Rembold et al., 1989; Oomah et al., 2007; Barra et al., 2007]

Table 4: Volatile flavour compounds of roasted (150oC) chickpea obtained by HS-SPME.

Peak Compound KIa % relative peak area ±SDb Reliabilityc

1 Ethyl acetate 589 0.12±0.01 MS; KI2 But-2-enal 610 0.89±0.06 MS; KI3 3-Methylbutanal 625 0.17±0.01 MS; KI4 2-Methylbutanal 635 0.34±0.02 MS; KI5 Butanol 639 0.71±0.05 MS; KI6 Pentane-2, 3-dione 660 0.834±0.06 MS; KI7 Valeraldehyde 665 1.240±0.10 MS; KI8 3-Hydroxybutan-2-one 673 15.130±2.10 MS; KI9 Isopentenylmetylether 676 0.714±0.05 MS; KI10 2-Ethylfuran 684 0.117±0.01 MS; KI11 n-Heptane 697 1.686±0.26 MS; KI12 Pentan-2-ol 704 1.513±0.05 MS; KI13 Pyridine 709 4.752±0.93 MS; KI14 Pent-2-enal 734 1.263±0.35 MS; KI15 Toluene 744 0.539±0.02 MS; KI16 3-Methylbut-2-enal 753 2.176±0.76 MS; KI17 Hexanal 772 2.188±0.81 MS; KI18 1-Octene 782 1.181±0.03 MS; KI19 3-Methylhep-3-ene 793 0.656±0.01 MS; KI20 n-octane 798 0.376±0.01 MS; KI21 Furfural 810 4.835±0.94 MS; KI22 (E)-Hex-2-enal 829 6.247±0.55 MS; KI23 3-Methylthiopropanal 863 0.329±0.01 MS; KI24 Heptanal 870 2.426±0.46 MS; KI25 3-Methyl octane 872 0.765±0.03 MS; KI26 2-Butylfuran 886 0.292±0.01 MS; KI27 Nonane 894 0.292±0.01 MS; KI28 Heptan-2-ol 904 0.726±0.34 MS; KI29 Y-Butyrolactone 908 1.240±0.05 MS; KI30 α-Pinene 920 0.730±0.03 MS; KI31 α-Thujene 923 0.304±0.01 MS; KI32 Benzaldehyde 929 0.357±0.01 MS; KI33 (E) Hept-2-enal 934 6.257±1.01 MS; KI34 Camphene 938 4.018±0.93 MS; KI35 Octan-3-one 959 0.577±0.01 MS; KI36 Oct-1-en-3-ol 964 0.159±0.01 MS; KI37 β-Pinene 968 21.826±3.45 MS; KI38 3-Octanol 974 0.146±0.01 MS; KI39 2-Pentylfuran 979 0.459±0.02 MS; KI40 Hept-2, 4-dienal 983 0.027±0.01 MS; KI41 1, 2, 4-Trimethylbenzene 984 0.136±0.01 MS; KI42 (Z) Hex-3-enylacetate 986 0.365±0.01 MS; KI43 Myrcene 989 0.569±0.02 MS; KI44 Hexylacetate 991 2.439±0.67 MS; KI45 α-Phellandrene 997 3.132±0.85 MS; KI46 n-Decane 1000 0.354±0.01 MS; KI47 α-Terpinene 1009 0.113±0.01 MS; KI48 P-Cymene 1019 0.349±0.01 MS; KI49 β-Phellandrene 1021 0.523±0.02 MS; KI50 Limonene 1022 0.545±0.03 MS; KI51 Butylcyclohexane 1025 0.798±0.55 MS; KI52 (E) Oct-3-enal 1033 0.105±0.01 MS; KI53 3-Octen-2-one 1035 0.133±0.01 MS; KI54 (E)-β-Ocimene 1037 0.060±0.01 MS; KI55 Decahydronaphthalene 1041 0.436±0.02 MS; KI56 Y-Terpinene 1055 0.278±0.01 MS; KI57 2-Methyldecane 1064 0.083±0.01 MS; KI58 α-Terpinolene 1082 0.100±0.01 MS; KI59 n-Undecane 1100 0.118±0.01 MS; KI60 Nonanal 1101 0.036±0.01 MS; KI61 Pentylcyclohexane 1128 0.722±0.01 MS; KI

Citation: Lasekan O, Juhari NH, Pattiram PD (2011) Headspace Solid-phase Microextraction Analysis of the Volatile Flavour Compounds of Roasted Chickpea (Cicer arietinum L). J Food Process Technol 2:112. doi:10.4172/2157-7110.1000112

Page 5 of 6

Volume 2 • Issue 3 • 1000112J Food Process TechnolISSN:2157-7110 JFPT, an open access journal

of these terpenes (β-pinene, α-pinene, β-cymene and limonene) have been reported in dry beans [10,11] and chickpea [7]. The presence of limonene in vacuum steam volatile oil of dry red beans has also been reported [24]. In general, all the main classes of compounds commonly listed as thermally generated flavours in pulses were identified in the roasted chickpea, with the most important from a flavour standpoint being 2-ethylfuran, 2-butylfuran, 2-pentylfuran, 3-hydroxybutan-2-one, Y-butyrolactone, 1-penten-2-ol, 1-octen-3-ol, 1, 2, 4-trimethyl-benzene, and decane. 2-Pentylfuran was recently reported in tropical almond nuts [27] and previously identified as a compound of the volatile decomposition products of slightly autooxidised soybean [28]. Furans are products of carbohydrate thermal degradation and rearrangement [29]. Although, three furans were identified in the volatile of the roasted chickpea, their contribution to the overall aroma note may be negligible. However, the aldehydes, ketones and alcohols identified in this study are expected to play major role in the aroma of the roasted chickpea.

ConclusionHS-SPME coupled with GC-MS is a rapid and simple method for

the extraction and identification of the volatile compounds in roasted chickpea. In this study, the most effective fibre for HS-SPME was the DVB/CAR/PDMS. Results revealed that extraction temperature is the dominant factor for the HS-SPME of the roasted volatile compounds of chickpea. Also, aldehydes (24.6 %) and hydrocarbons (24.6 %) constituted the main volatile constituents of the roasted chickpea. These were closely followed by the terpenoids (20 %). Individually, 3-hydroxybutan-2-one and β-pinene were the most abundant. In all, a total of 61 aroma-active compounds were identified in the roasted chickpea. The results further indicated that the final model was significantly (P < 0.05) fitted for the response variable (total flavour peak area) studied. Optimization revealed that the best response, within the range studied, was reached when the extraction temperature was 60oC, the equilibrium time, 30 min and extraction time, 15 min respectively. The results of the total antioxidant capacity of chickpea highlighted marked increase with the roasting temperature and a concomitant decrease in moisture level.

Acknowledgements

I would like to thank RUGS (Research University Grant Scheme), Universiti Putra Malaysia for providing grant.

References

1. Rembold H, Wallner P, Nitz S, Kollmannsberger H ,Drawert F (1989) Volatile components of chickpea seed. Agricultural and Food Chemistry 37: 659-662.

2. Angulo-Bejarano PI, Verdugo-Montoya NM, Cuevas-Rodriguez EO, Milan-Carrillo JM, Mora-Escobedo R, et al. (2008) Tempeh flour from chickpea; nutritional and physicochemical properties. Chemistry 106: 106-112.

3. Chavan JK, Kadam, SS, Salunkhe DK (1986) Biochemistry and technology of chickpea (Cicer arietinum) seeds. Crit Rev Food Sci Nutr 25: 107-158.

4. Pittaway JK, Robertson IK, Ball MJ (2008) Chickpeas may influence fatty acid and fibre intake in an ad libitum diet, leading to small improvements in serum lipid profile and glycemic control . American Diet Associate 108: 1009-1013.

5. Marconi E, Ruggeri S, Cappelloni M, Leonardi D, Carnovale E (2000) Physicochemical, nutritional, and microstructural characteristics of chickpeas and common beans following microwave cooking. Agriculture and Food Chemistry 48: 5986-5994.

6. Saxena KN, Rembold H (1984) Attraction of Heliothis armigera larvae by chickpea seed powder constituents. Zeitschrift fur Angewandte Ent 97: 145-153.

7. Rembold H, Wallner P, Singh AK (1989) Attractiveness of volatile chickpea seed Components to Heliothis armigera larvae. Zeitschrift Angewandte Ent 107: 65-70.

8. Lasekan O, Lasekan W, Idowu MA, Ojo OA (1996) Effect of extrusion cooking on the nutrition characteristics of indigenous maize based snack. Cereal Science 24: 78-85 .

9. Vas G, Vekey K (2004 )Solid-phase microextraction: a powerful sample preparation tool prior to mass spectrometric analysis. J Mass Spectrom 39: 233-254.

10. Barra A, Baldovini N, Loiseau AM, Albino L, Lesecq C et al. (2007) Chemical analysis of French beans (Phaseolus vulgaris L) by headspace solid-phase microextraction (HS-SPME) and simultaneous distillation/extraction(SDE) Food Chemistry 101: 1279-1284.

11. Oomah BD, Liang LSY ,Balasubramanian P (2007) Volatile compounds of dry beans (Phaseolus vulgaris L). Plant Foods for Human Nut 62: 177-183.

12. Yang X, Peppard T (1994) Solid phase microextraction for flavour analysis. Agric and Food Chem 42: 1925-1930.

13. Rocha S, Ramalheira V, Barros A, Delgadillo I, Coimbra M (2001) Headspace solid-phase microextraction (SPME) analysis of flavour compounds in wines. Effect of the matrix volatile composition in the relative response factors in a wine model. Agric and Food Chem 49: 5142-5151.

14. Garcia D, Reichenbacher M and Danzer K (1998) Analysis of wine bouquet using headspace solid-phase microextraction-capillary gas chromatography. High Resolution Chrom 21: 373-377.

15. Lasekan O (1991) Effect of malting energy, sedimentation rate and diastatic power measurement in sorghum selection. Food Chemistry 46: 415-417.

16. Montgomery DC, Runger GC, Hubele NF (2001) Engineering Statistics. Wiley, Hoboken, NJ Pp 51-117.

17. Myers RH (1971) Response Surface Methodology. Allayan and Bacon, Boston, MA, Pp. 10- 45.

18. Lee J, Ye L, Landen WO and Eitenmiller RR (2000 )Optimization of an extraction Procedure for the quantification of vitamin E in tomato and broccoli using response Surface 13- methodology. Food Comp and Anal 13: 45-57.

19. Weng W, Liu W, Lin W (2001) Studies on the optimum models of the dairy product ‘kou woan loa’ using response surface methodology. Asian-Australian J of Animal Science 14: 1470-1476.

20. Joglekar AM, May AT (1987) Product excellence through design of experiments.Cereal Food World 32: 857-868.

21. Pellati F, Benvenuti S, Yoshizaki F, Bertelli D, Rossi MC (2005) Headspace solid-phase microextraction-gas chromatography-mass spectrometry analysis of the volatile compounds of Evodia species fruits. Chromatography A 1087: 265-273.

22. Van Ruth S, Dings L, Buhr K, Posthumus MA (2004) In vitro and in vivo volatile flavour analysis of red kidney beans by proton transfer reaction-mass spectrometry. Food Res Int 37: 785-791.

23. Lovengren NV, Fisher GS, Legendre MG, Schuller WH (1979) Volatile constituents of dried legumes. Agriculture and Food Chemistry 27: 851-853.

24. Buttery RG, Steifert RM, Ling LC (1975) Characterization of some volatile constituents of dry beans. Agriculture and Food Chemistry 23: 516-519.

25. Tressl R, Ericka D (1999) Heat generated flavour and precursors. In R. Teranishi, E.L. WickI. Horstein (Eds.), Flavour Chemistry: 30 years of progress, Pp. 305-325 New York, Kluwer Academic/Plenum Publishers.

26. vernin G, Parkanyi C (1982) Mechanisms of formation of heterocyclic compounds in Maillard and pyrolysis reactions. In G. Vernin (Ed.), the chemistry of heterocyclic flavouring and aroma compounds PP. 151-161 Chichester: Ellis Howoord.

27. Lasekan O, Abbas K (2010) Analysis of volatile flavour compounds and acrylamide in roasted Malaysian tropical almond (Terminalia catappa L) nuts using supercritical fluid extraction. Food and Chemistry Texaco 48: 2212-2216.

Citation: Lasekan O, Juhari NH, Pattiram PD (2011) Headspace Solid-phase Microextraction Analysis of the Volatile Flavour Compounds of Roasted Chickpea (Cicer arietinum L). J Food Process Technol 2:112. doi:10.4172/2157-7110.1000112

Page 6 of 6

Volume 2 • Issue 3 • 1000112J Food Process TechnolISSN:2157-7110 JFPT, an open access journal

28. Krishnamurthy RG, Smouse TH, Mookherje BD, Reddy BR, Chang SS (1967) Identification of 2-pentylfuran in fats and oils and its relationship to the reversion flavour of soybean oil. Food Science 32: 372-374.

29. Morini G, Maga JA, (1995) Volatile compounds in roasted and boiled Chinese chestnuts (Castanea moussima). Lebensmittel-Wiss Und Tecnol 28: 638-640.

Submit your next manuscript and get advantages of OMICS Group submissionsUnique features:

• User friendly/feasible website-translation of your paper to 50 world’s lead-ing languages

• Audio Version of published paper• Digital articles to share and exploreSpecial features:

• 100 Open Access Journals• 10,000 editorial team• 21 days rapid review process• Quality and quick editorial, review and publication processing• Indexing at PubMed (partial), Scopus, DOAJ, EBSCO, Index Copernicus

and Google Scholar etc• Sharing Option: Social Networking Enabled• Authors, Reviewers and Editors rewarded with online Scientific Credits• Better discount for your subsequent articlesSubmit your manuscript at: www.omicsonline.org/submission