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Screening of variables for extrusion of rice flour employing a Plackett–Burman design
Journal of Food Engineering 57 (2003) 135–144 www.elsevier.com/locate/jfoodeng
Screening of variables for extrusion of rice flour employing a Plackett–Burman design Manisha Guha, Syed Zakiuddin Ali, Suvendu Bhattacharya
*
Central Food Technological Research Institute, Mysore 570 013, India Received 31 March 2001; accepted 4 June 2002
Abstract A screening experiment with ten variables employing a Plackett–Burman experimental design was conducted on extrusion of rice flour. The variables include, hardware variables (mixing disk and reverse pitch screw elements), feed variables (moisture, sugar, salt and amylose contents, and particle size) and operating variables (barrel temperature, feed rate and screw speed). The response functions were extrusion characteristics (torque, specific mechanical energy and residence time), product attributes (water solubility index, water absorption index, and bulk density, peak viscosity, hot paste viscosity and cold paste viscosity). The response functions were highly affected by the hardware variables. A Plackett–Burman experimental design can serve as a useful tool for screening large numbers of variables and reducing the number of experiments. Ó 2002 Elsevier Science Ltd. All rights reserved.
1. Introduction The technology of extrusion cooking of foods has now been successfully applied to produce a large number of foods and speciality ingredients. However, a practical problem that a researcher faces in the beginning of the study is the existence of a large number of variables. This makes the situation complex if the researcher is interested in knowing the quantitative effect of these variables on the target parameters such as, expansion, density, etc. Hence, the researcher tries to reduce the number of extrusion trials, mostly based on previous experience, or by reducing the number of variables, usually by conducting some preliminary trials––basically screening experiments. Till now, it is still an art to select a particular variable among a number of variables. The basis of such an act is still experience, or sometimes, just a guess. Most of the development of extrusion process applications starts with empirical studies. The easiest and the most commonly used approach is by employing response surface methodology (RSM) (Bhattacharya & Prakash, 1994), though handling of more than 6–8 variables is difficult; this is true not only for extrusion of foods but *
Corresponding author. Tel.: +91-821-513910; fax: +91-821517233. E-mail address: [email protected] (S. Bhattacharya).
also for other areas of food processing. These results are product and machine specific, and the conclusion is limited within the scope of the investigation (Lue, Hsieh, & Huff, 1994). On the other hand, Meuser, Pfaller, and Van Lengerich (1987) proposed a system analytical model. This model distinguishes between process parameters such as screw speed, barrel temperature, feed rate, moisture content of the feed, etc. and the system parameters e.g., specific mechanical energy, die pressure, residence time, etc. as well as influenced target parameters like expansion ratio, water solubility index, water absorption index, bulk density, etc. The other approaches include the application of artificial neural networks (ANN), and dimensional analysis (Bhattacharya & Hanna, 1986). But the problem of a large number of variables consisting of extruder hardware variables, ingredient variables and extrusion operation variables is yet to be solved. It is thus logical to have a screening experiment that will yield some idea of the quantitative effects of the variables, usually large in number. Therefore, scope exists for a systematic processing of the large number of variables to reduce them to a sizeable number of variables such as four or five. The experimental design of Plackett–Burman can serve as an efficient tool though in food systems, its application is rather rare. However, Arnoldsson and Kaufman (1994), and Chan and Kavanagh (1992) have reported some applications though not in extrusion technology.
0260-8774/02/$ - see front matter Ó 2002 Elsevier Science Ltd. All rights reserved. PII: S 0 2 6 0 - 8 7 7 4 ( 0 2 ) 0 0 2 8 2 - 0
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Nomenclature b
colour value in CIELab system indicative of blueness with negative sign b0 constant in the first order polynomial b1 ; b2 ; . . . ; bk constants in the first order polynomial showing the linear effect of the variables x1 ; x2 ; . . . ; xk , respectively CPV cold paste viscosity (RVU) dg geometric average of two successive sieve openings (lm) dga geometric average particle diameter of rice flour (lm) F statistical F-value HPV hot paste viscosity (RVU) i integers (1; 2; 3; . . .) k number of variables Kf conductivity of the die (m3 ) MD mixing disk n screw speed (rpm) N number of filled channels p probability level PV peak viscosity (RVU) Q volumetric flow rate (m3 s1 ) r correlation coefficient RPSE reverse pitch screw element RT average residence time (s) RVU rapid visco-amylogram unit for apparent viscosity
A restriction or die is usually used during extrusion of foods for shaping the final product. But if the targeted product is a modified ingredient, such as, modified starch/cereal powder for developing other food products, e.g., baby food or weaning food, the use of a die becomes optional. Further, energy expenditure can be reduced if the die is omitted. The earlier studies by these authors (Guha, Ali, & Bhattacharya, 1997, 1998) has reported on twin-screw extrusion of rice flour without using a die. The objective of the present work is thus the application of the Plackett–Burman experimental design technique to screen 10 extruder and extrusion variables and the quantitative determination of the effect of these variables on the system parameters and target product parameters without using any die during extrusion processing of rice flour. The variables include extruder hardware variables such as MD and RPSE, feed variables e.g., moisture, sugar, salt and amylose contents of the feed, and particle size of the rice flour, and the extrusion operating variables like barrel temperature, feed rate and screw speed. The system parameters determined are torque ðT Þ, SME and RT, and the target product parameters are bulk density (qB ), WSI, WAI, PV, HPV and CPV.
SME T Wi WAI WSI xi y Z Zc Zp Zs Zw Zt
net specific mechanical energy (kJ kg1 ) torque at the screw shaft during extrusion (%) weight fraction of rice flour retained on ith sieve water absorption index (g g1 ) water solubility index (%) coded variable response function power for shearing within the channels (J s1 ) power for shearing between the flight tips and the barrels (J s1 ) power needed for pressure build up due to die (J s1 ) power for shearing between the flight tips and bottoms (J s1 ) power for shearing between the flanks of the flight in the intermeshing region (J s1 ) total power transmitted from the main motor to the screws (J s1 )
Greek letters e random error l apparent viscosity in the filled channels (Pa s) l average apparent viscosity in the filled channels (Pa s) qB bulk density of the dried extrudates (kg m3 )
2. Materials and methods 2.1. Rice A low amylose (Agoni Bora) and a high amylose (IR 64) rice varieties paddy (rough rice) were procured from rice growing farms. They were milled, and ground to flours in a hammer mill. The proximate composition of rice powders, as obtained by analysis (AOAC, 1984), is shown in Table 1. The feed powder was sieved by using an US standard 45 mesh sieve to categorise it into two fractions: (i) coarse that retained on the sieve and (ii) fine that passed through the same sieve. The geometric average diameter dga (Eq. (1)) of the particle in the rice flour, as determined by sieve analysis (Farrall, 1976), was 438 and 257 lm, respectively for coarse and fine fractions. P logðdga Þ ¼
½Wi logðdg Þ P Wi
ð1Þ
Here, Wi is the weight fraction of rice flour retained on ith sieve and dg is the geometric average of two successive sieve openings (lm).
M. Guha et al. / Journal of Food Engineering 57 (2003) 135–144 Table 1 Proximate composition of rice flour from IR 64 (high amylose) and Agoni Bora (low amylose) Parameter
IR 64
Agoni Bora
Moisture (%) Proteina (%) Fat (%) Ash (%) Carbohydrateb (%)
1.7 0.2 6.7 0.1 0.7 0.1 0.4 0.1 80.5
11.1 0.1 7.8 0.1 0.9 0.0 0.4 0.0 79.8
a b
Obtained by multiplying nitrogen content with 5.95. Calculated by difference.
2.2. Extruder and extrusion cooking A laboratory model, co-rotating, twin-screw extruder was employed without using a die. The details of the extruder have been reported earlier (Guha et al., 1997). The extruder screw consisted of forward pitch screw elements of varying pitches, and a RPSE near the outlet, and also, three kneading blocks (Table 2) for the screw configuration with MD and RPSE. For other configurations, these MD and RPSE was replaced with 20=20 forward pitch screw elements. According to the experimental design, the temperature of the extruder barrel was maintained at 100 or 140 °C throughout the barrel; the screw speed of the extruder was varied at 200 or 400 rpm while feed rate was maintained at 10 or 20 kg/h using a volumetric gravity feeder. Moisture content of the feed was either 12:0 0:1% or 20 0:1%. Extrusion trials were repeated twice. Sample preparation for determination of various quality characteristics was as reported earlier (Guha et al., 1997).
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Table 2 Screw profile used for extrusion trials with MD and RPSE Screw element details (pitch/ length of screw)
Total length (mm)
42/42 28/28 28/14 KB 45/5/14a 20/20 KB 45/5/14a 20/20 KB 45/5/14a 20/20 20=10b 20/20
268 336 14 14 80 14 80 14 100 10 20
a b
MD. RPSE (negative pitch).
(Table 3) to determine the effect of a total of 10 variables each at two levels on nine response functions. The variables included: (i) MD, (ii) RPSE, (iii) moisture, (iv) sugar, (v) salt, (vi) amylose content, (vii) average particle size of the feed, (viii) barrel temperature, (ix) feed rate and (x) screw speed. The discrete variables, MD and RPSE, were assigned a code of þ1 when they were used in the screw profile, or 1 when they were absent. The experimental design with the actual level of variables, is shown in Table 4. The response functions were the extrusion characteristics, such as, (i) torque ðT Þ, (ii) SME, (iii) RT, (iv) WSI, (v) WAI, (vi) bulk density (qB ), (vii) PV, (viii) HPV and (ix) CPV. 2.4. Torque (T) and net specific mechanical energy
2.3. Plackett–Burman experimental design for extrusion variables An experimental design, based on Plackett–Burman theory (Akhnazarova & Kafarov, 1982), was employed
The torque (T%) during extrusion was obtained from the digital display of the control panel of the extruder cooker, and the SME input during extrusion was determined (Bhattacharya & Choudhury, 1994; Guha
Table 3 Plackett–Burman experimental design using coded variables Expt. no. 1 2 3 4 5 6 7 8 9 10 11 12
x1
x2
x3
x4
x5
x6
x7
x8
x9
x10
Temp.
SS
FR
MC
Amy
Par. size
Salt
Sugar
RPSE
MD
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
Symbols: Temp.: Barrel temperature; SS: screw speed; FR: feed rate; MC: moisture content; Amy: amylose content; Par. size: particle size; Salt: salt content in feed; Sugar: sugar content in feed; RPSE: reverse pitch screw element; MD: mixing disk.
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Table 4 Experimental design employed for extrusion trials using actual level of variables Expt. no. 1 2 3 4 5 6 7 8 9 10 11 12
X1
X2
X3
Temp.
SS
FR
140 140 100 140 140 140 100 100 100 140 100 100
200 400 400 200 400 400 400 200 200 200 400 200
20 10 20 20 10 20 20 20 10 10 10 10
X4
X5
X6
X7
X8
X9
X10
MC
Amy
Par. size
Salt
Sugar
RPSE
MD
12 20 12 20 20 12 20 20 20 12 12 12
5 5 28.6 5 28.6 28.6 5 28.6 28.6 28.6 5 5
257 257 257 438 257 438 438 257 438 438 438 257
2 0 0 0 2 0 2 2 0 2 2 0
10 10 0 0 0 10 0 10 10 0 10 0
YES YES YES NO NO NO YES NO YES YES NO NO
NO YES YES YES NO NO NO YES NO YES YES NO
Symbols: Temp.: Barrel temperature; SS: screw speed; FR: feed rate; MC: moisture content; Amy: amylose content; Par. size: particle size; Salt: salt content in feed; Sugar: sugar content in feed; RPSE: reverse pitch screw element; MD: mixing disk.
et al., 1997). The energy for rotating the screws without feed was subtracted from the total SME to obtain net SME values for extrusion. 2.5. Average residence time The RT of the feed in the extruder was determined using phycocyanin, a natural blue dye, produced by algae. The extrudates were collected at regular intervals of 3 s, and the samples colour, after immediate cooling, were determined using a colour meter (UV–visible spectrophotometer, model # 2100, Shimadzu Corporation, Japan) with a reflectance attachment. As the dye comes out over a considerable period of time, a plot of time versus colour content was constructed from which RT was determined. The b -values, indicating the blueness of the sample with negative values, were used to determine the content of the blue dye in the extrudates. The reported values are the mean of five determinations. 2.6. Bulk density (qB ), water absorption index and water solubility index The method for determining bulk density, WAI and WSI were reported earlier (Guha et al., 1997). The mean of three replicates was reported. 2.7. Viscosity The visco-amylographic profile of the extruded and unextruded samples was determined (Guha et al., 1998) using a rapid visco analyser (RVA) (Newport Scientific, Narabeen, Australia). All viscosity values reported are the average of triplicate measurements and are reported in RVU.
2.8. Statistical analysis The experimental results (response function, y) were fitted to first order multiple regression equations (Eq. (2)) using coded level (1 or þ1) of the variables (xi ). y ¼ b0 þ
k X
bi x i þ e
ð2Þ
i¼1
The coefficients of the polynomial are represented by b0 (constant term), b1 ; b2 ; . . . ; bk (linear effect) and e (random error). The coefficients of the polynomial were obtained by using the Gauss–Jordan method (Jain, Iyengar, & Jain, 1995). The multiple correlation coefficient ðrÞ was determined and was judged at a probability ðpÞ level of 0.01. These developed regression equations were used to develop the plots for the response functions.
3. Results The experimental results for all the response functions are presented in Table 5. The coefficients of the first order multiple regression equations (in coded level of variables) are shown in Table 6. Sample response surfaces (Figs. 1–5), based on the effects of important variables (in actual level of variables) are cited to aid in visualisation of their effects. The magnitude of the multiple correlation coefficients (usually above 0.93, p 6 0:01) of the first order equations (Eq. (2)) show that these equations can adequately predict the response functions in relation to the variables. In addition, based on the sign (þ or ) of the coefficients in coded variables (Table 6), the effect of the individual variables can be categorised as a positive or negative effect. Furthermore, the magnitude of these
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Table 5 Results of the extrusion trials showing experimental values of the response functions Expt. no.
T (%)
SME (kJ kg1 )
RT (s)
qB (kg m3 )
WSI (%)
WAI (g g1 )
PV (RVU)
HPV (RVU)
CPV (RVU)
1 2 3 4 5 6 7 8 9 10 11 12 IR64 Agoni Bora
53.4 48.2 51.9 74.5 16.5 16.6 39.0 65.9 29.3 59.0 18.8 11.4 – –
328.2 1083.5 599.7 495.0 79.2 41.2 396.0 426.8 274.0 744.5 153.0 9.1 – –
28.5 29.3 25.2 21.0 17.8 15.4 24.6 19.6 24.8 32.9 21.7 16.6 – –
302.3 395.7 230.3 288.3 730.0 709.5 618.7 489.3 710.7 170.0 594.0 720.3 – –
55.6 65.0 15.2 55.6 3.4 8.2 32.4 20.2 13.7 20.8 14.4 12.2 2.3 7.6
1.8 2.0 6.7 2.5 2.5 2.5 5.1 5.0 4.9 5.7 2.4 2.6 2.6 2.7
9 5 38 10 182 174 18 42 74 30 150 158 211 196
10 4 22 9 90 96 12 12 19 16 90 95 102 86
13 5 28 12 216 192 18 29 44 22 146 158 227 124
Symbols: CPV: cold paste viscosity (RVU); HPV: hot paste viscosity (RVU); MD: mixing disk; PV: peak viscosity (RVU); RPSE: reverse pitch screw element; RT: average residence time (s); SME: net specific mechanical energy (kJ kg1 ); T : torque at the screw shaft during extrusion (%); WAI: water absorption index (g g1 ); WSI: water solubility index (%); qB : bulk density of the dried extrudates (kg m3 ).
Table 6 Coefficients of the first order multiple regression equations for response functions in coded level of variables Expt. no.
T (%)
SME (kJ kg1 )
b0 b1 b2 b3 b4 b5 b6 b7 b8 b9 b10 ra
38.07 2.10 10.88 10.14 4.71 2.79 0.33 1.52 1.29 8.84 15.18 0.982
236.20 67.56 147.91 76.50 127.36 171.39 85.38 51.30 65.90 347.15 371.88 0.721
RT (s) 21.29 0.68 2.58 0.74 0.46 2.30 0.51 1.09 0.15 6.36 3.79 0.918
qB (kg m3 )
WSI (%)
WAI (g g1 )
PV (RVU)
HPV (RVU)
CPV (RVU)
475.67 41.67 29.17 77.50 19.83 32.33 2.00 34.67 59.17 114.33 114.67 0.938
26.28 8.48 3.38 4.73 5.23 12.72 2.32 2.02 3.20 7.30 5.57 0.979
3.43 0.63 0.30 0.10 0.13 1.10 0.02 0.08 0.38 0.55 0.60 0.932
77.17 8.83 23.33 22.67 16.00 12.83 4.83 0.68 1.50 42.17 31.33 0.989
40.00 2.50 13.17 12.33 14.83 2.50 1.17 0.83 1.50 25.33 14.50 0.983
98.74 27.41 52.94 20.99 21.16 39.58 0.22 4.85 0.85 78.62 61.59 0.953
Variables associated with: b1 : barrel temperature; b2 : screw speed; b3 : feed rate; b4 : moisture content; b5 : amylose content; b6 : average particle size; b7 : salt content in feed; b8 : sugar content in the feed; b9 : RPSE; b10 : MD. Symbols: CPV: cold paste viscosity (RVU); HPV: hot paste viscosity (RVU); MD: mixing disk; PV: peak viscosity (RVU); RPSE: reverse pitch screw element; RT: average residence time (s); SME: net specific mechanical energy (kJ kg1 ); T : torque during extrusion (%); WAI: water absorption index (g g1 ); WSI: water solubility index (%); qB : bulk density of the dried extrudates (kg m3 ). a Significant at p 6 0:01.
coefficients indicates the relative effects of the variables on the response functions. Hence, variables that impart strong effects, as judged by comparing the magnitudes, can be identified for inclusion in the second stage of the experiments; thus, the number of variables can be reduced. These indicate that the Plackett–Burman design can be employed for screening of a large number of variables to reduce the number of experiments. The effect of variables studied on individual response functions is discussed in the subsequent sections. 3.1. Torque (T) The torque during extrusion ranged between 11.4% and 74.5%, of which low values ( 6 25%) were obtained
when both RPSE and MD were absent (Table 5). Among the individual variables, the effect of MD was maximum followed by screw speed, feed rate and RPSE (Table 6). The presence of MD and RPSE markedly increased the torque. On the other hand, an increase in screw speed reduced the torque, but feed rate had an opposite effect. The sample response surface (Fig. 1) for torque was drawn as a function of feed rate and screw speed with or without a MD while keeping remaining variables constant at a coded level of zero except for RPSE which was equal to 1, i.e., without using RPSE. It shows that torque increases with an increase in feed rate when a MD in the screw profile is included but decreases with an increase in screw speed.
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Fig. 1. Sample response surfaces for torque during extrusion of rice flour as a function of feed rate and screw speed with or without a MD.
Fig. 2. Response surfaces for SME during extrusion of rice flour at different amylose contents of the feed and screw speeds in presence or absence of a MD.
Fig. 3. Average residence time of the feed inside the extruder as a function of amylose content and screw speed when a RPSE was employed.
Fig. 4. WSI of the product obtained by extrusion at different barrel temperatures and amylose contents with or without a RPSE.
3.3. Average residence time 3.2. Net specific mechanical energy The high values (>300 kJ kg1 ) for SME during extrusion of rice flour were observed when the screw profile included RPSE and/or MD. Table 6 shows that both MD and RPSE exerted the maximum effect on SME; amylose content and screw speed imparted a marked negative effect. The response surface (Fig. 2) shows high SME values in the presence of MD. Increase in screw speed or amylose content reduced the SME.
The average residence time of material in the barrel varied between 15.4 and 32.9 s (Table 5). The presence of RPSE and MD had a maximum influence on the RT; screw speed, amylose content and feed rate also exerted a marked effect on RT (Table 6) in that order. The use of RPSE and/or MD markedly increased RT (Fig. 3) which confirms the findings of Yam, Gogoi, Karwe, and Wang (1994), Gogoi, Oswalt, and Choudhury (1996) and Altomare and Ghossi (1986).
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3.6. Viscosity indices The different viscosity indices, viz., PV, HPV and CPV of the extruded products as read from the RVA viscograms are shown in Table 5 along with those of non-extruded rice samples. The variables that affected these viscosity parameters most were RPSE, MD (both have negative effect), and screw speed (positive effect) (Table 6). Further, the PV and HPV were affected negatively by feed rate and moisture content of the feed, while CPV was affected (positively) by amylose content. Fig. 5 shows the response surfaces HPV with or without the use of RPSE. Incorporation of RPSE in the screw profile markedly reduced these viscosity parameters.
4. Discussion Fig. 5. HPV of the extruded product obtained by extrusion at different screw speed and feed moisture contents with or without a RPSE.
3.4. Bulk density (qB ) Lowest qB values were obtained when the screw profile incorporated RPSE and/or MD (Table 6). The negative effect of RPSE/MD indicated that their presence markedly decreased bulk density; feed rate also had a negative effect, whereas sugar exerted a positive effect. The variables that ranked next in exerting an effect on qB were salt (ve effect), amylose (þve effect) and screw speed (þve effect). 3.5. Water solubility index and water absorption index The raw rice (non-extruded) from a high amylose variety (IR 64) had a low WSI (about 2%), whereas, that from the low amylose variety (Agoni Bora) was 7.5%. Extruded rice products (Table 5) from the high amylose variety showed a low range of WSI (between 3.4% and 20.8%) whereas that from a low amylose variety showed a higher range (between 12.2% and 65.0%). The coefficients of the regression equations (Table 6) shows the temperature of extrusion had the highest (positive) effect on WSI whereas amylose content of the feed exerted a negative effect which indicated that the use of high amylose variety yields low WSI. Incorporation of RPSE in the screw profile enhanced WSI of the extruded products (Fig. 4). Similar results were also been observed for rice-fish mince blend (Gogoi et al., 1996). Amylose content exerted maximum (positive) effect on WAI (Table 6). The effect of amylose content on WAI was reported to be positive for rice flour extrudates (De Mosqueda, Perez, Juliano, Del Rosario, & Bechtel, 1986). The effect of temperature, MD and RPSE also showed positive effects. An increase in sugar content reduced WAI.
4.1. Torque (T) The use of RPSE/MD increases the residence time and also the shearing forces. Hence, the food material inside the extruder offers more resistance leading to an increase in torque. An increase in screw speed or a decrease in feed rate reduces the degree of fill in the extruder causing torque to be at a low level. The torque during extrusion usually decides the capacity of the extruder. The torque ðT Þ applied to the screwsÕ shaft is given by Martelli (1983): T ¼ Zt =n
ð3Þ
where n is the screw speed, and the total power (Zt ) is given by: Zt ¼ N ðZ þ Zc þ Zs þ Zw Þ þ Zp
ð4Þ
Here, N is the number of filled channels, Z is the power for shearing within the channels, Zc is power for shearing between the flight tips and barrels or bottom of the channels of the other screw, Zs is power for shearing between the flight tips and bottoms (J s1 ), Zw is power for shearing between the flanks of the flight in the intermeshing region, and Zp is power needed for pressure build up due to die. As no die was used during extrusion, Zp is zero due to the absence of pressure build-up at die. Now, an increase in screw speed ðnÞ reduces torque (Eq. (3)) provided Zt remains constant. Increasing screw speed reduces the number of filled lengths ðN Þ of the screw but increases the power expenditure for shearing (Z, Zc , Zs and Zw ). Therefore, an increase in screw speed results in a significant decline in N =n values (due to an increase in n compounded by a fall in the length of the filled channels) which is possibly much higher than the effect of the power ðZÞ terms, and hence, the torque decreases. Incorporation of the RPSE in the screw profile reduces the conveying efficiency of the feed with
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simultaneous increase in N and torque (Kirby, Ollett, Parker, & Smith, 1988). Besides, MD is likely to increase other Z terms, particularly Zs The net result is an increase in torque values. An increase in feed rate increases the number of filled channels ðN Þ and consequently, torque increases. A low amylose feed is generally sticky in nature and usually tends to bind with the screw and barrel surfaces. As stickiness of a dough depends on the moisture content (Bhattacharya & Narasimha, 1997), it is expected that a minimum moisture level is necessary for the dough to show stickiness. At a low moisture content (12%), the feed cannot behave as a sticky one, and hence, the torque is low, whereas, with high moisture content (20%) torque values are high. 4.2. Net specific mechanical energy The variation of SME during extrusion can be explained by considering the effect of the variables (Eq. (5)) on power expenditure (Martelli, 1983). 2 Ql 2 Zt ¼ f ; l; N ; n ð5Þ Kf Here, Q is the volumetric flow rate, l is apparent viscosity in the filled channels, l is average apparent viscosity in the filled channels and Kf is conductivity of the die. In the present experiment, the effect of Kf is omitted as a die was absent and hence the equation reduces to Zt ¼ f ðQ2 l; l; N ; n2 Þ
ð6Þ
It appears from Eq. (6) that when screw speed ðnÞ is increased (by keeping the feed rate constant), Zt / n2 and Zt / N . It follows that an increase in screw speed quadratically increases Zt but at the same time the number of filled channels ðN Þ decreases; a decrease in N proportionately reduces Zt and possibly they compensate each other. On the other hand, l and l are also proportional to Zt (Eq. (6)). As the extrusion feeds are pseudoplastic dough (Bhattacharya, Das, & Bose, 1992), an increase in screw speed increases shear rate and subsequently decreases l and l. The net result is a decrease in Zt and SME values. 4.3. Average residence time The presence of RPSE/MD markedly affects RT values as these screw elements restrict or even oppose the flow of the material. These elements enhance efficient transfer of thermal energy causing product transformation (Colonna, Melcion, Vergnes, & Mercier, 1983) and expansion (Lee & McCarthy, 1996). Increasing the screw speed or feed rate reduces the RT values of which the former had more effect. Yeh, Hwang, and Guo (1992) found similar results and reported a greater effect for feed rate than screw speed for extrusion of wheat
flour, and indicated that it was due to a shift towards a plug flow condition. An increase in the amylose content of the feed decreases stickiness (Bhattacharya, Sowbhagya, & Indudhara Swamy, 1982), and hence, improves its flowability inside the extruder which in turn reduces RT values. 4.4. Water solubility index and water absorption index The extrusion of non-waxy high amylose rice flour results in low WSI (Pan, Kong, & Chew, 1992) as highamylose rice takes long time for gelatinisation. A high value of WSI is desirable in cooked extruded products, such as, ready-to-eat snacks, breakfast cereal and porridges. A combination of high levels of barrel temperature (140 °C), moisture content of the feed (20%) in the presence of RPSE and MD using a feed with low amylose (5%) is found suitable for achieving high WSI values. Use of RPSE and MD increases the severity of the mechanical degradation (Yam et al., 1994). Hence, in a shear field, aided by enhanced mixing, large starch molecules degrade to a number of small units. This process is further aided by the thermal energy input caused by an elevated barrel temperature leading to an increase in solubility. The negative effect of sugar on WAI of extruded rice samples can be explained by lipid–sugar complex formation and by a decrease of available water for starch to gelatinise as sugar readily absorbs water. The formation of such a complex is a temperature dependent phenomenon, and therefore, an elevation in the same reduces WAI. 4.5. Bulk density (qB ) The use of RPSE and MD in the screw profile increases the RT (Table 5), and consequently, the shearing forces. An increase in mechanical and thermal energy (when screw speed and barrel temperature are increased) inputs thus leads to lowering of the product density due to enhancement of gelatinisation. Gogoi et al. (1996) have mentioned that extrudates for a screw configuration without RPSE always had higher bulk densities compared to those produced with it; as severity of the screw configuration was enhanced, the product density decreased. During extrusion of rice meal and wheat starch, Lee and McCarthy (1996) and Hoseney, Mason, Lai, and Guetzlaff (1992), respectively found that an increase in screw speed increases product expansion. Increasing feed rate increase the degree of fill in the extruder (Altomare & Ghossi, 1986) and the tendency towards plug flow increases (Yeh et al., 1992). Hence, heat transfer from the barrel to the material becomes efficient leading to enhanced gelatinisation and consequently bulk density decreases. The use of salt possibly also improves gelatinisation as it increases the thermal
M. Guha et al. / Journal of Food Engineering 57 (2003) 135–144
conductivity of the feed and aids in efficient heat transfer. Sugar in the feed enhances caramelisation and form complexes with lipids leading to a decrease in gelatinisation, and therefore, qB increases. 4.6. Viscosity indices The high values for PV in the viscogram of extrudates indicate the presence of a high proportion of ungelatinised (uncooked) starch. On the other hand, a low PV is associated with a high extent of cooking obtained with high moisture content (20%) in the feed with a screw profile consisting of RPSE and MD. The effect of screw speed and feed rate are opposing each other and the effect of the former is the more pronounced. This means that a proper combination of screw speed in relation to feed rate is necessary to obtain the desirable low PV values. Structural breakdown with a sufficient loss of integrity and disintegration of the starch granules occurs when thermal gelatinisation and mechanical damage occur (El-Dash, Gonzales, & Ciol, 1981). Hence, pregelatinised starch granules lose their ability to swell upon heating in water during viscographic studies which results in low HPV values. Similarly, as the intensity and degree of cooking (gelatinisation) increases, the HPV also decreases (Tipples, 1980). Extrusion operation for cereal flour is a typical example of a low moisture gelatinisation process because the moisture content in the feed hardly ever exceeds 20%. As moisture content was increased from 12% to 20% in the present study, gelatinisation was expected to increase with subsequent decrease in HPV values. The presence of RPSE and/or MD increases residence time, and the extent of shearing (discussed earlier) aids the process of gelatinisation, and hence, HPV decreases. CPV reflects the extent of starch retrogradation that occurs during the cooling phase. CPV values, apart from depending on the presence of RPSE and MD, and on screw speed and moisture content, increase with an increase in amylose content and barrel temperature. Starch with a low moisture content, extruded at a high temperature, results in extrudates characterised by a low degree of retrogradation (El-Dash et al., 1981). As high amylose can produce more retrograded starch (Cruzy Celis, Rooney, & McDonough, 1996), CPV increases.
5. Conclusions The existence of a large number of variables is a limitation for product development and process optimisation in a number of food processing technologies including extrusion technology. An experimental design
143
based on the Plackett–Burman theory can be applied efficiently to screen a large number of extrusion variables including discrete variables. The present work shows that the screw configuration, particularly the presence of RPSE and MD, imparts maximum effect on the extrusion and extrudate characteristics though marked effects are also obtained for amylose and moisture content, feed rate, screw speed and barrel temperature. Variables like particle size, salt and sugar contents had least effect. As high values of WSI are desirable in cooked extruded products, such as, ready-to-eat snacks, breakfast cereal and porridges, a combination of high barrel temperature (140 °C) in the presence of RPSE and MD using a low amylose (5%) variety is desirable to achieve high WSI. The experimental results relating the variables and response functions can be fitted well (0:72 6 r 6 0:99, p 6 0:01) by first order polynomials which indicate the suitability of the Plackett–Burman model for evaluating the effect of the individual extrusion variables.
References Akhnazarova, S., & Kafarov, V. (1982). Experiment optimization in chemistry and chemical engineering. Moscow: MIR Publishers. Altomare, R. E., & Ghossi, P. (1986). An analysis of residence time distribution patterns in a twin screw extruder. Biotechnol. Progr., 2, 157–163. AOAC. (1984). Official methods of analysis (14th ed.). Arlington, VA: Association of Official Analytical Chemists. Arnoldsson, K. C., & Kaufman, P. (1994). Lipid class analysis by normal phase high performance liquid chromatography, development and optimisation using multivariate method. Chromatographia, 38, 317–324. Bhattacharya, K. R., Sowbhagya, C. M., & Indudhara Swamy, Y. M. (1982). Quality profile of rice: a tentative scheme for clarification. J. Food Sci., 47, 564–569. Bhattacharya, M., & Hanna, M. A. (1986). Mathematical modelling of food extruder. Lebensmittal Wissenschaft und Technologie, 19, 34– 38. Bhattacharya, S., & Choudhury, G. S. (1994). Twin-screw extrusion of rice flour: effect of extruder length-to-diameter ratio and barrel temperature on extrusion parameters and product characteristics. J. Food Process. Pres., 18, 389–406. Bhattacharya, S., Das, H., & Bose, A. N. (1992). Rheological behaviour during extrusion of blends of minced fish and wheat flour. J. Food Eng., 15, 123–137. Bhattacharya, S., & Narasimha, H. V. (1997). Puncture and stress relaxation behaviour of blackgram (Phaseolus mungo) flour-based papad dough. J. Food Process Eng., 20, 301–316. Bhattacharya, S., & Prakash, M. (1994). Extrusion cooking of blends of rice and chickpea flour: A response surface analysis. J. Food Eng., 21, 315–330. Chan, K. Y., & Kavanagh, P. E. (1992). Application of Plakett– Burman design and linear programming to light-duty liquid detergent formulation. J. Am. Oil Chem. Soc., 69, 690–694. Colonna, P., Melcion, J. P., Vergnes, B., & Mercier, C. (1983). Flow mixing and residence time distribution of maize starch within a twin-screw extruder with a longitudinally-split barrel. J. Cereal Sci., 1, 115–125.
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Cruzy Celis, L. P., Rooney, L. W., & McDonough, C. M. (1996). A ready to eat breakfast cereal from food-grade sorghum. Cereal Chem., 73, 108–114. De Mosqueda, M. B., Perez, C. M., Juliano, B. O., Del Rosario, R. R., & Bechtel, D. B. (1986). Varietal differences in properties of extrusion-cooked rice flour. Food Chem., 19, 173–187. El-Dash, A. A., Gonzales, R., & Ciol, M. (1981). Response surface methodology in the control of thermoplastic extrusion of starch. In R. Jowitt (Ed.), Extrusion Cooking Technology (pp. 51–74). New York: Elsevier Applied Science. Farrall, A. W. (1976). Food engineering system-operations. Westport, CT: AVI Publishing. Gogoi, B. K., Oswalt, A. J., & Choudhury, G. S. (1996). Reverse screw element(s) and feed composition effects during twin-screw extrusion of rice flour and fish muscle blends. J. Food Sci., 61, 590–595. Guha, M., Ali, S. Z., & Bhattacharya, S. (1997). Twin-screw extrusion of rice flour without a die: Effect of barrel temperature and screw speed on extrusion and extrudate characteristics. J. Food Eng., 32, 251–267. Guha, M., Ali, S. Z., & Bhattacharya, S. (1998). Effect of barrel temperature and screw speed on rapid viscoanalyser pasting behaviour of rice extrudates. Int. J. Food Sci. Technol., 33, 259– 266. Hoseney, R. C., Mason, W. R., Lai, C. S., & Guetzlaff, J. (1992). Factors affecting the viscosity and structure of extrusion-cooked wheat starch. In J. L. Kokini, C. T. Ho, & M. V. Karwe (Eds.), Food Extrusion Science and Technology (pp. 277–305). New York: Marcel Dekker. Jain, M. K., Iyengar, S. R. K., & Jain, R. K. (1995). Numerical methods for scientific and engineering computation (third ed.). New Delhi, India: New Age International (P) Limited.
Kirby, A. R., Ollett, A.-L., Parker, R., & Smith, A. C. (1988). An experimental study of screw configuration effects in the twinscrew extrusion-cooking of maize grits. J. Food Eng., 8, 247– 272. Lee, S. Y., & McCarthy, K. L. (1996). Effect of screw configuration and speed on RTD and expansion of rice extrudate. J. Food Process Eng., 19, 153–170. Lue, S., Hsieh, F., & Huff, H. E. (1994). Modeling of twin-screw extrusion cooking of corn meal and sugar beet fiber mixtures. J. Food Eng., 21, 263–289. Martelli, F. G. (1983). Twin screw extruders: a basic understanding. New York: Van Nostrand Reinhold Company. Meuser, F., Pfaller, W., & Van Lengerich, B. (1987). Technological aspects regarding specific changes to the characteristic properties of extrudates by HTST-extrusion cooking. In C. O. Connor (Ed.), Extrusion Technology for the Food Industry. New York: Elsevier Applied Science. Pan, B. S., Kong, M. S., & Chew, H. H. (1992). Twin-screw extrusion for expanded rice products: processing parameters and formulation of extrudate properties. In J. L. Kokini, C. T. Ho, & M. V. Karwe (Eds.), Food Extrusion Science and Technology. New York: Marcel Dekker. Tipples, K. H. (1980). Uses and applications. In W. Shuey & K. Tipples (Eds.), The Amylograph Handbook (pp. 15–28). St. Paul, MN: American Association of Cereal Chemists. Yam, K. L., Gogoi, B. K., Karwe, M. V., & Wang, S. S. (1994). Shear conversion of corn meal by reverse screw elements during twin screw extrusion at low temperatures. J. Food Sci., 59, 113–114. Yeh, A. I., Hwang, S. J., & Guo, J. J. (1992). Effects of screw speed and feed rate on residence time distribution and axial mixing of wheat flour in a twin screw extruder. J. Food Eng., 17, 1–13.
Screening of variables for extrusion of rice flour employing a Plackett–Burman design Manisha Guha, Syed Zakiuddin Ali, Suvendu Bhattacharya
*
Central Food Technological Research Institute, Mysore 570 013, India Received 31 March 2001; accepted 4 June 2002
Abstract A screening experiment with ten variables employing a Plackett–Burman experimental design was conducted on extrusion of rice flour. The variables include, hardware variables (mixing disk and reverse pitch screw elements), feed variables (moisture, sugar, salt and amylose contents, and particle size) and operating variables (barrel temperature, feed rate and screw speed). The response functions were extrusion characteristics (torque, specific mechanical energy and residence time), product attributes (water solubility index, water absorption index, and bulk density, peak viscosity, hot paste viscosity and cold paste viscosity). The response functions were highly affected by the hardware variables. A Plackett–Burman experimental design can serve as a useful tool for screening large numbers of variables and reducing the number of experiments. Ó 2002 Elsevier Science Ltd. All rights reserved.
1. Introduction The technology of extrusion cooking of foods has now been successfully applied to produce a large number of foods and speciality ingredients. However, a practical problem that a researcher faces in the beginning of the study is the existence of a large number of variables. This makes the situation complex if the researcher is interested in knowing the quantitative effect of these variables on the target parameters such as, expansion, density, etc. Hence, the researcher tries to reduce the number of extrusion trials, mostly based on previous experience, or by reducing the number of variables, usually by conducting some preliminary trials––basically screening experiments. Till now, it is still an art to select a particular variable among a number of variables. The basis of such an act is still experience, or sometimes, just a guess. Most of the development of extrusion process applications starts with empirical studies. The easiest and the most commonly used approach is by employing response surface methodology (RSM) (Bhattacharya & Prakash, 1994), though handling of more than 6–8 variables is difficult; this is true not only for extrusion of foods but *
Corresponding author. Tel.: +91-821-513910; fax: +91-821517233. E-mail address: [email protected] (S. Bhattacharya).
also for other areas of food processing. These results are product and machine specific, and the conclusion is limited within the scope of the investigation (Lue, Hsieh, & Huff, 1994). On the other hand, Meuser, Pfaller, and Van Lengerich (1987) proposed a system analytical model. This model distinguishes between process parameters such as screw speed, barrel temperature, feed rate, moisture content of the feed, etc. and the system parameters e.g., specific mechanical energy, die pressure, residence time, etc. as well as influenced target parameters like expansion ratio, water solubility index, water absorption index, bulk density, etc. The other approaches include the application of artificial neural networks (ANN), and dimensional analysis (Bhattacharya & Hanna, 1986). But the problem of a large number of variables consisting of extruder hardware variables, ingredient variables and extrusion operation variables is yet to be solved. It is thus logical to have a screening experiment that will yield some idea of the quantitative effects of the variables, usually large in number. Therefore, scope exists for a systematic processing of the large number of variables to reduce them to a sizeable number of variables such as four or five. The experimental design of Plackett–Burman can serve as an efficient tool though in food systems, its application is rather rare. However, Arnoldsson and Kaufman (1994), and Chan and Kavanagh (1992) have reported some applications though not in extrusion technology.
0260-8774/02/$ - see front matter Ó 2002 Elsevier Science Ltd. All rights reserved. PII: S 0 2 6 0 - 8 7 7 4 ( 0 2 ) 0 0 2 8 2 - 0
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Nomenclature b
colour value in CIELab system indicative of blueness with negative sign b0 constant in the first order polynomial b1 ; b2 ; . . . ; bk constants in the first order polynomial showing the linear effect of the variables x1 ; x2 ; . . . ; xk , respectively CPV cold paste viscosity (RVU) dg geometric average of two successive sieve openings (lm) dga geometric average particle diameter of rice flour (lm) F statistical F-value HPV hot paste viscosity (RVU) i integers (1; 2; 3; . . .) k number of variables Kf conductivity of the die (m3 ) MD mixing disk n screw speed (rpm) N number of filled channels p probability level PV peak viscosity (RVU) Q volumetric flow rate (m3 s1 ) r correlation coefficient RPSE reverse pitch screw element RT average residence time (s) RVU rapid visco-amylogram unit for apparent viscosity
A restriction or die is usually used during extrusion of foods for shaping the final product. But if the targeted product is a modified ingredient, such as, modified starch/cereal powder for developing other food products, e.g., baby food or weaning food, the use of a die becomes optional. Further, energy expenditure can be reduced if the die is omitted. The earlier studies by these authors (Guha, Ali, & Bhattacharya, 1997, 1998) has reported on twin-screw extrusion of rice flour without using a die. The objective of the present work is thus the application of the Plackett–Burman experimental design technique to screen 10 extruder and extrusion variables and the quantitative determination of the effect of these variables on the system parameters and target product parameters without using any die during extrusion processing of rice flour. The variables include extruder hardware variables such as MD and RPSE, feed variables e.g., moisture, sugar, salt and amylose contents of the feed, and particle size of the rice flour, and the extrusion operating variables like barrel temperature, feed rate and screw speed. The system parameters determined are torque ðT Þ, SME and RT, and the target product parameters are bulk density (qB ), WSI, WAI, PV, HPV and CPV.
SME T Wi WAI WSI xi y Z Zc Zp Zs Zw Zt
net specific mechanical energy (kJ kg1 ) torque at the screw shaft during extrusion (%) weight fraction of rice flour retained on ith sieve water absorption index (g g1 ) water solubility index (%) coded variable response function power for shearing within the channels (J s1 ) power for shearing between the flight tips and the barrels (J s1 ) power needed for pressure build up due to die (J s1 ) power for shearing between the flight tips and bottoms (J s1 ) power for shearing between the flanks of the flight in the intermeshing region (J s1 ) total power transmitted from the main motor to the screws (J s1 )
Greek letters e random error l apparent viscosity in the filled channels (Pa s) l average apparent viscosity in the filled channels (Pa s) qB bulk density of the dried extrudates (kg m3 )
2. Materials and methods 2.1. Rice A low amylose (Agoni Bora) and a high amylose (IR 64) rice varieties paddy (rough rice) were procured from rice growing farms. They were milled, and ground to flours in a hammer mill. The proximate composition of rice powders, as obtained by analysis (AOAC, 1984), is shown in Table 1. The feed powder was sieved by using an US standard 45 mesh sieve to categorise it into two fractions: (i) coarse that retained on the sieve and (ii) fine that passed through the same sieve. The geometric average diameter dga (Eq. (1)) of the particle in the rice flour, as determined by sieve analysis (Farrall, 1976), was 438 and 257 lm, respectively for coarse and fine fractions. P logðdga Þ ¼
½Wi logðdg Þ P Wi
ð1Þ
Here, Wi is the weight fraction of rice flour retained on ith sieve and dg is the geometric average of two successive sieve openings (lm).
M. Guha et al. / Journal of Food Engineering 57 (2003) 135–144 Table 1 Proximate composition of rice flour from IR 64 (high amylose) and Agoni Bora (low amylose) Parameter
IR 64
Agoni Bora
Moisture (%) Proteina (%) Fat (%) Ash (%) Carbohydrateb (%)
1.7 0.2 6.7 0.1 0.7 0.1 0.4 0.1 80.5
11.1 0.1 7.8 0.1 0.9 0.0 0.4 0.0 79.8
a b
Obtained by multiplying nitrogen content with 5.95. Calculated by difference.
2.2. Extruder and extrusion cooking A laboratory model, co-rotating, twin-screw extruder was employed without using a die. The details of the extruder have been reported earlier (Guha et al., 1997). The extruder screw consisted of forward pitch screw elements of varying pitches, and a RPSE near the outlet, and also, three kneading blocks (Table 2) for the screw configuration with MD and RPSE. For other configurations, these MD and RPSE was replaced with 20=20 forward pitch screw elements. According to the experimental design, the temperature of the extruder barrel was maintained at 100 or 140 °C throughout the barrel; the screw speed of the extruder was varied at 200 or 400 rpm while feed rate was maintained at 10 or 20 kg/h using a volumetric gravity feeder. Moisture content of the feed was either 12:0 0:1% or 20 0:1%. Extrusion trials were repeated twice. Sample preparation for determination of various quality characteristics was as reported earlier (Guha et al., 1997).
137
Table 2 Screw profile used for extrusion trials with MD and RPSE Screw element details (pitch/ length of screw)
Total length (mm)
42/42 28/28 28/14 KB 45/5/14a 20/20 KB 45/5/14a 20/20 KB 45/5/14a 20/20 20=10b 20/20
268 336 14 14 80 14 80 14 100 10 20
a b
MD. RPSE (negative pitch).
(Table 3) to determine the effect of a total of 10 variables each at two levels on nine response functions. The variables included: (i) MD, (ii) RPSE, (iii) moisture, (iv) sugar, (v) salt, (vi) amylose content, (vii) average particle size of the feed, (viii) barrel temperature, (ix) feed rate and (x) screw speed. The discrete variables, MD and RPSE, were assigned a code of þ1 when they were used in the screw profile, or 1 when they were absent. The experimental design with the actual level of variables, is shown in Table 4. The response functions were the extrusion characteristics, such as, (i) torque ðT Þ, (ii) SME, (iii) RT, (iv) WSI, (v) WAI, (vi) bulk density (qB ), (vii) PV, (viii) HPV and (ix) CPV. 2.4. Torque (T) and net specific mechanical energy
2.3. Plackett–Burman experimental design for extrusion variables An experimental design, based on Plackett–Burman theory (Akhnazarova & Kafarov, 1982), was employed
The torque (T%) during extrusion was obtained from the digital display of the control panel of the extruder cooker, and the SME input during extrusion was determined (Bhattacharya & Choudhury, 1994; Guha
Table 3 Plackett–Burman experimental design using coded variables Expt. no. 1 2 3 4 5 6 7 8 9 10 11 12
x1
x2
x3
x4
x5
x6
x7
x8
x9
x10
Temp.
SS
FR
MC
Amy
Par. size
Salt
Sugar
RPSE
MD
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1
Symbols: Temp.: Barrel temperature; SS: screw speed; FR: feed rate; MC: moisture content; Amy: amylose content; Par. size: particle size; Salt: salt content in feed; Sugar: sugar content in feed; RPSE: reverse pitch screw element; MD: mixing disk.
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Table 4 Experimental design employed for extrusion trials using actual level of variables Expt. no. 1 2 3 4 5 6 7 8 9 10 11 12
X1
X2
X3
Temp.
SS
FR
140 140 100 140 140 140 100 100 100 140 100 100
200 400 400 200 400 400 400 200 200 200 400 200
20 10 20 20 10 20 20 20 10 10 10 10
X4
X5
X6
X7
X8
X9
X10
MC
Amy
Par. size
Salt
Sugar
RPSE
MD
12 20 12 20 20 12 20 20 20 12 12 12
5 5 28.6 5 28.6 28.6 5 28.6 28.6 28.6 5 5
257 257 257 438 257 438 438 257 438 438 438 257
2 0 0 0 2 0 2 2 0 2 2 0
10 10 0 0 0 10 0 10 10 0 10 0
YES YES YES NO NO NO YES NO YES YES NO NO
NO YES YES YES NO NO NO YES NO YES YES NO
Symbols: Temp.: Barrel temperature; SS: screw speed; FR: feed rate; MC: moisture content; Amy: amylose content; Par. size: particle size; Salt: salt content in feed; Sugar: sugar content in feed; RPSE: reverse pitch screw element; MD: mixing disk.
et al., 1997). The energy for rotating the screws without feed was subtracted from the total SME to obtain net SME values for extrusion. 2.5. Average residence time The RT of the feed in the extruder was determined using phycocyanin, a natural blue dye, produced by algae. The extrudates were collected at regular intervals of 3 s, and the samples colour, after immediate cooling, were determined using a colour meter (UV–visible spectrophotometer, model # 2100, Shimadzu Corporation, Japan) with a reflectance attachment. As the dye comes out over a considerable period of time, a plot of time versus colour content was constructed from which RT was determined. The b -values, indicating the blueness of the sample with negative values, were used to determine the content of the blue dye in the extrudates. The reported values are the mean of five determinations. 2.6. Bulk density (qB ), water absorption index and water solubility index The method for determining bulk density, WAI and WSI were reported earlier (Guha et al., 1997). The mean of three replicates was reported. 2.7. Viscosity The visco-amylographic profile of the extruded and unextruded samples was determined (Guha et al., 1998) using a rapid visco analyser (RVA) (Newport Scientific, Narabeen, Australia). All viscosity values reported are the average of triplicate measurements and are reported in RVU.
2.8. Statistical analysis The experimental results (response function, y) were fitted to first order multiple regression equations (Eq. (2)) using coded level (1 or þ1) of the variables (xi ). y ¼ b0 þ
k X
bi x i þ e
ð2Þ
i¼1
The coefficients of the polynomial are represented by b0 (constant term), b1 ; b2 ; . . . ; bk (linear effect) and e (random error). The coefficients of the polynomial were obtained by using the Gauss–Jordan method (Jain, Iyengar, & Jain, 1995). The multiple correlation coefficient ðrÞ was determined and was judged at a probability ðpÞ level of 0.01. These developed regression equations were used to develop the plots for the response functions.
3. Results The experimental results for all the response functions are presented in Table 5. The coefficients of the first order multiple regression equations (in coded level of variables) are shown in Table 6. Sample response surfaces (Figs. 1–5), based on the effects of important variables (in actual level of variables) are cited to aid in visualisation of their effects. The magnitude of the multiple correlation coefficients (usually above 0.93, p 6 0:01) of the first order equations (Eq. (2)) show that these equations can adequately predict the response functions in relation to the variables. In addition, based on the sign (þ or ) of the coefficients in coded variables (Table 6), the effect of the individual variables can be categorised as a positive or negative effect. Furthermore, the magnitude of these
M. Guha et al. / Journal of Food Engineering 57 (2003) 135–144
139
Table 5 Results of the extrusion trials showing experimental values of the response functions Expt. no.
T (%)
SME (kJ kg1 )
RT (s)
qB (kg m3 )
WSI (%)
WAI (g g1 )
PV (RVU)
HPV (RVU)
CPV (RVU)
1 2 3 4 5 6 7 8 9 10 11 12 IR64 Agoni Bora
53.4 48.2 51.9 74.5 16.5 16.6 39.0 65.9 29.3 59.0 18.8 11.4 – –
328.2 1083.5 599.7 495.0 79.2 41.2 396.0 426.8 274.0 744.5 153.0 9.1 – –
28.5 29.3 25.2 21.0 17.8 15.4 24.6 19.6 24.8 32.9 21.7 16.6 – –
302.3 395.7 230.3 288.3 730.0 709.5 618.7 489.3 710.7 170.0 594.0 720.3 – –
55.6 65.0 15.2 55.6 3.4 8.2 32.4 20.2 13.7 20.8 14.4 12.2 2.3 7.6
1.8 2.0 6.7 2.5 2.5 2.5 5.1 5.0 4.9 5.7 2.4 2.6 2.6 2.7
9 5 38 10 182 174 18 42 74 30 150 158 211 196
10 4 22 9 90 96 12 12 19 16 90 95 102 86
13 5 28 12 216 192 18 29 44 22 146 158 227 124
Symbols: CPV: cold paste viscosity (RVU); HPV: hot paste viscosity (RVU); MD: mixing disk; PV: peak viscosity (RVU); RPSE: reverse pitch screw element; RT: average residence time (s); SME: net specific mechanical energy (kJ kg1 ); T : torque at the screw shaft during extrusion (%); WAI: water absorption index (g g1 ); WSI: water solubility index (%); qB : bulk density of the dried extrudates (kg m3 ).
Table 6 Coefficients of the first order multiple regression equations for response functions in coded level of variables Expt. no.
T (%)
SME (kJ kg1 )
b0 b1 b2 b3 b4 b5 b6 b7 b8 b9 b10 ra
38.07 2.10 10.88 10.14 4.71 2.79 0.33 1.52 1.29 8.84 15.18 0.982
236.20 67.56 147.91 76.50 127.36 171.39 85.38 51.30 65.90 347.15 371.88 0.721
RT (s) 21.29 0.68 2.58 0.74 0.46 2.30 0.51 1.09 0.15 6.36 3.79 0.918
qB (kg m3 )
WSI (%)
WAI (g g1 )
PV (RVU)
HPV (RVU)
CPV (RVU)
475.67 41.67 29.17 77.50 19.83 32.33 2.00 34.67 59.17 114.33 114.67 0.938
26.28 8.48 3.38 4.73 5.23 12.72 2.32 2.02 3.20 7.30 5.57 0.979
3.43 0.63 0.30 0.10 0.13 1.10 0.02 0.08 0.38 0.55 0.60 0.932
77.17 8.83 23.33 22.67 16.00 12.83 4.83 0.68 1.50 42.17 31.33 0.989
40.00 2.50 13.17 12.33 14.83 2.50 1.17 0.83 1.50 25.33 14.50 0.983
98.74 27.41 52.94 20.99 21.16 39.58 0.22 4.85 0.85 78.62 61.59 0.953
Variables associated with: b1 : barrel temperature; b2 : screw speed; b3 : feed rate; b4 : moisture content; b5 : amylose content; b6 : average particle size; b7 : salt content in feed; b8 : sugar content in the feed; b9 : RPSE; b10 : MD. Symbols: CPV: cold paste viscosity (RVU); HPV: hot paste viscosity (RVU); MD: mixing disk; PV: peak viscosity (RVU); RPSE: reverse pitch screw element; RT: average residence time (s); SME: net specific mechanical energy (kJ kg1 ); T : torque during extrusion (%); WAI: water absorption index (g g1 ); WSI: water solubility index (%); qB : bulk density of the dried extrudates (kg m3 ). a Significant at p 6 0:01.
coefficients indicates the relative effects of the variables on the response functions. Hence, variables that impart strong effects, as judged by comparing the magnitudes, can be identified for inclusion in the second stage of the experiments; thus, the number of variables can be reduced. These indicate that the Plackett–Burman design can be employed for screening of a large number of variables to reduce the number of experiments. The effect of variables studied on individual response functions is discussed in the subsequent sections. 3.1. Torque (T) The torque during extrusion ranged between 11.4% and 74.5%, of which low values ( 6 25%) were obtained
when both RPSE and MD were absent (Table 5). Among the individual variables, the effect of MD was maximum followed by screw speed, feed rate and RPSE (Table 6). The presence of MD and RPSE markedly increased the torque. On the other hand, an increase in screw speed reduced the torque, but feed rate had an opposite effect. The sample response surface (Fig. 1) for torque was drawn as a function of feed rate and screw speed with or without a MD while keeping remaining variables constant at a coded level of zero except for RPSE which was equal to 1, i.e., without using RPSE. It shows that torque increases with an increase in feed rate when a MD in the screw profile is included but decreases with an increase in screw speed.
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Fig. 1. Sample response surfaces for torque during extrusion of rice flour as a function of feed rate and screw speed with or without a MD.
Fig. 2. Response surfaces for SME during extrusion of rice flour at different amylose contents of the feed and screw speeds in presence or absence of a MD.
Fig. 3. Average residence time of the feed inside the extruder as a function of amylose content and screw speed when a RPSE was employed.
Fig. 4. WSI of the product obtained by extrusion at different barrel temperatures and amylose contents with or without a RPSE.
3.3. Average residence time 3.2. Net specific mechanical energy The high values (>300 kJ kg1 ) for SME during extrusion of rice flour were observed when the screw profile included RPSE and/or MD. Table 6 shows that both MD and RPSE exerted the maximum effect on SME; amylose content and screw speed imparted a marked negative effect. The response surface (Fig. 2) shows high SME values in the presence of MD. Increase in screw speed or amylose content reduced the SME.
The average residence time of material in the barrel varied between 15.4 and 32.9 s (Table 5). The presence of RPSE and MD had a maximum influence on the RT; screw speed, amylose content and feed rate also exerted a marked effect on RT (Table 6) in that order. The use of RPSE and/or MD markedly increased RT (Fig. 3) which confirms the findings of Yam, Gogoi, Karwe, and Wang (1994), Gogoi, Oswalt, and Choudhury (1996) and Altomare and Ghossi (1986).
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3.6. Viscosity indices The different viscosity indices, viz., PV, HPV and CPV of the extruded products as read from the RVA viscograms are shown in Table 5 along with those of non-extruded rice samples. The variables that affected these viscosity parameters most were RPSE, MD (both have negative effect), and screw speed (positive effect) (Table 6). Further, the PV and HPV were affected negatively by feed rate and moisture content of the feed, while CPV was affected (positively) by amylose content. Fig. 5 shows the response surfaces HPV with or without the use of RPSE. Incorporation of RPSE in the screw profile markedly reduced these viscosity parameters.
4. Discussion Fig. 5. HPV of the extruded product obtained by extrusion at different screw speed and feed moisture contents with or without a RPSE.
3.4. Bulk density (qB ) Lowest qB values were obtained when the screw profile incorporated RPSE and/or MD (Table 6). The negative effect of RPSE/MD indicated that their presence markedly decreased bulk density; feed rate also had a negative effect, whereas sugar exerted a positive effect. The variables that ranked next in exerting an effect on qB were salt (ve effect), amylose (þve effect) and screw speed (þve effect). 3.5. Water solubility index and water absorption index The raw rice (non-extruded) from a high amylose variety (IR 64) had a low WSI (about 2%), whereas, that from the low amylose variety (Agoni Bora) was 7.5%. Extruded rice products (Table 5) from the high amylose variety showed a low range of WSI (between 3.4% and 20.8%) whereas that from a low amylose variety showed a higher range (between 12.2% and 65.0%). The coefficients of the regression equations (Table 6) shows the temperature of extrusion had the highest (positive) effect on WSI whereas amylose content of the feed exerted a negative effect which indicated that the use of high amylose variety yields low WSI. Incorporation of RPSE in the screw profile enhanced WSI of the extruded products (Fig. 4). Similar results were also been observed for rice-fish mince blend (Gogoi et al., 1996). Amylose content exerted maximum (positive) effect on WAI (Table 6). The effect of amylose content on WAI was reported to be positive for rice flour extrudates (De Mosqueda, Perez, Juliano, Del Rosario, & Bechtel, 1986). The effect of temperature, MD and RPSE also showed positive effects. An increase in sugar content reduced WAI.
4.1. Torque (T) The use of RPSE/MD increases the residence time and also the shearing forces. Hence, the food material inside the extruder offers more resistance leading to an increase in torque. An increase in screw speed or a decrease in feed rate reduces the degree of fill in the extruder causing torque to be at a low level. The torque during extrusion usually decides the capacity of the extruder. The torque ðT Þ applied to the screwsÕ shaft is given by Martelli (1983): T ¼ Zt =n
ð3Þ
where n is the screw speed, and the total power (Zt ) is given by: Zt ¼ N ðZ þ Zc þ Zs þ Zw Þ þ Zp
ð4Þ
Here, N is the number of filled channels, Z is the power for shearing within the channels, Zc is power for shearing between the flight tips and barrels or bottom of the channels of the other screw, Zs is power for shearing between the flight tips and bottoms (J s1 ), Zw is power for shearing between the flanks of the flight in the intermeshing region, and Zp is power needed for pressure build up due to die. As no die was used during extrusion, Zp is zero due to the absence of pressure build-up at die. Now, an increase in screw speed ðnÞ reduces torque (Eq. (3)) provided Zt remains constant. Increasing screw speed reduces the number of filled lengths ðN Þ of the screw but increases the power expenditure for shearing (Z, Zc , Zs and Zw ). Therefore, an increase in screw speed results in a significant decline in N =n values (due to an increase in n compounded by a fall in the length of the filled channels) which is possibly much higher than the effect of the power ðZÞ terms, and hence, the torque decreases. Incorporation of the RPSE in the screw profile reduces the conveying efficiency of the feed with
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simultaneous increase in N and torque (Kirby, Ollett, Parker, & Smith, 1988). Besides, MD is likely to increase other Z terms, particularly Zs The net result is an increase in torque values. An increase in feed rate increases the number of filled channels ðN Þ and consequently, torque increases. A low amylose feed is generally sticky in nature and usually tends to bind with the screw and barrel surfaces. As stickiness of a dough depends on the moisture content (Bhattacharya & Narasimha, 1997), it is expected that a minimum moisture level is necessary for the dough to show stickiness. At a low moisture content (12%), the feed cannot behave as a sticky one, and hence, the torque is low, whereas, with high moisture content (20%) torque values are high. 4.2. Net specific mechanical energy The variation of SME during extrusion can be explained by considering the effect of the variables (Eq. (5)) on power expenditure (Martelli, 1983). 2 Ql 2 Zt ¼ f ; l; N ; n ð5Þ Kf Here, Q is the volumetric flow rate, l is apparent viscosity in the filled channels, l is average apparent viscosity in the filled channels and Kf is conductivity of the die. In the present experiment, the effect of Kf is omitted as a die was absent and hence the equation reduces to Zt ¼ f ðQ2 l; l; N ; n2 Þ
ð6Þ
It appears from Eq. (6) that when screw speed ðnÞ is increased (by keeping the feed rate constant), Zt / n2 and Zt / N . It follows that an increase in screw speed quadratically increases Zt but at the same time the number of filled channels ðN Þ decreases; a decrease in N proportionately reduces Zt and possibly they compensate each other. On the other hand, l and l are also proportional to Zt (Eq. (6)). As the extrusion feeds are pseudoplastic dough (Bhattacharya, Das, & Bose, 1992), an increase in screw speed increases shear rate and subsequently decreases l and l. The net result is a decrease in Zt and SME values. 4.3. Average residence time The presence of RPSE/MD markedly affects RT values as these screw elements restrict or even oppose the flow of the material. These elements enhance efficient transfer of thermal energy causing product transformation (Colonna, Melcion, Vergnes, & Mercier, 1983) and expansion (Lee & McCarthy, 1996). Increasing the screw speed or feed rate reduces the RT values of which the former had more effect. Yeh, Hwang, and Guo (1992) found similar results and reported a greater effect for feed rate than screw speed for extrusion of wheat
flour, and indicated that it was due to a shift towards a plug flow condition. An increase in the amylose content of the feed decreases stickiness (Bhattacharya, Sowbhagya, & Indudhara Swamy, 1982), and hence, improves its flowability inside the extruder which in turn reduces RT values. 4.4. Water solubility index and water absorption index The extrusion of non-waxy high amylose rice flour results in low WSI (Pan, Kong, & Chew, 1992) as highamylose rice takes long time for gelatinisation. A high value of WSI is desirable in cooked extruded products, such as, ready-to-eat snacks, breakfast cereal and porridges. A combination of high levels of barrel temperature (140 °C), moisture content of the feed (20%) in the presence of RPSE and MD using a feed with low amylose (5%) is found suitable for achieving high WSI values. Use of RPSE and MD increases the severity of the mechanical degradation (Yam et al., 1994). Hence, in a shear field, aided by enhanced mixing, large starch molecules degrade to a number of small units. This process is further aided by the thermal energy input caused by an elevated barrel temperature leading to an increase in solubility. The negative effect of sugar on WAI of extruded rice samples can be explained by lipid–sugar complex formation and by a decrease of available water for starch to gelatinise as sugar readily absorbs water. The formation of such a complex is a temperature dependent phenomenon, and therefore, an elevation in the same reduces WAI. 4.5. Bulk density (qB ) The use of RPSE and MD in the screw profile increases the RT (Table 5), and consequently, the shearing forces. An increase in mechanical and thermal energy (when screw speed and barrel temperature are increased) inputs thus leads to lowering of the product density due to enhancement of gelatinisation. Gogoi et al. (1996) have mentioned that extrudates for a screw configuration without RPSE always had higher bulk densities compared to those produced with it; as severity of the screw configuration was enhanced, the product density decreased. During extrusion of rice meal and wheat starch, Lee and McCarthy (1996) and Hoseney, Mason, Lai, and Guetzlaff (1992), respectively found that an increase in screw speed increases product expansion. Increasing feed rate increase the degree of fill in the extruder (Altomare & Ghossi, 1986) and the tendency towards plug flow increases (Yeh et al., 1992). Hence, heat transfer from the barrel to the material becomes efficient leading to enhanced gelatinisation and consequently bulk density decreases. The use of salt possibly also improves gelatinisation as it increases the thermal
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conductivity of the feed and aids in efficient heat transfer. Sugar in the feed enhances caramelisation and form complexes with lipids leading to a decrease in gelatinisation, and therefore, qB increases. 4.6. Viscosity indices The high values for PV in the viscogram of extrudates indicate the presence of a high proportion of ungelatinised (uncooked) starch. On the other hand, a low PV is associated with a high extent of cooking obtained with high moisture content (20%) in the feed with a screw profile consisting of RPSE and MD. The effect of screw speed and feed rate are opposing each other and the effect of the former is the more pronounced. This means that a proper combination of screw speed in relation to feed rate is necessary to obtain the desirable low PV values. Structural breakdown with a sufficient loss of integrity and disintegration of the starch granules occurs when thermal gelatinisation and mechanical damage occur (El-Dash, Gonzales, & Ciol, 1981). Hence, pregelatinised starch granules lose their ability to swell upon heating in water during viscographic studies which results in low HPV values. Similarly, as the intensity and degree of cooking (gelatinisation) increases, the HPV also decreases (Tipples, 1980). Extrusion operation for cereal flour is a typical example of a low moisture gelatinisation process because the moisture content in the feed hardly ever exceeds 20%. As moisture content was increased from 12% to 20% in the present study, gelatinisation was expected to increase with subsequent decrease in HPV values. The presence of RPSE and/or MD increases residence time, and the extent of shearing (discussed earlier) aids the process of gelatinisation, and hence, HPV decreases. CPV reflects the extent of starch retrogradation that occurs during the cooling phase. CPV values, apart from depending on the presence of RPSE and MD, and on screw speed and moisture content, increase with an increase in amylose content and barrel temperature. Starch with a low moisture content, extruded at a high temperature, results in extrudates characterised by a low degree of retrogradation (El-Dash et al., 1981). As high amylose can produce more retrograded starch (Cruzy Celis, Rooney, & McDonough, 1996), CPV increases.
5. Conclusions The existence of a large number of variables is a limitation for product development and process optimisation in a number of food processing technologies including extrusion technology. An experimental design
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based on the Plackett–Burman theory can be applied efficiently to screen a large number of extrusion variables including discrete variables. The present work shows that the screw configuration, particularly the presence of RPSE and MD, imparts maximum effect on the extrusion and extrudate characteristics though marked effects are also obtained for amylose and moisture content, feed rate, screw speed and barrel temperature. Variables like particle size, salt and sugar contents had least effect. As high values of WSI are desirable in cooked extruded products, such as, ready-to-eat snacks, breakfast cereal and porridges, a combination of high barrel temperature (140 °C) in the presence of RPSE and MD using a low amylose (5%) variety is desirable to achieve high WSI. The experimental results relating the variables and response functions can be fitted well (0:72 6 r 6 0:99, p 6 0:01) by first order polynomials which indicate the suitability of the Plackett–Burman model for evaluating the effect of the individual extrusion variables.
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