fish feed production

1. Effect of Die Dimensions on Extrusion Processing Parameters
and Properties of DDGS-Based Aquaculture Feeds
Nehru Chevanan,' Kasiviswanathan Muthukumarappan,
2'3
Kurt A. Rosentrater, 4 and James L. Julson3
ABSTRACT
Cereal Chem. 84(4):389-398
The goal of this study was to investigate the effect of die nozzle
dimensions, barrel temperature profile, and moisture Content on DDGSbased extnidate properties and extruder processing parameters. An Ingredient blend containing 40 17'e. distillers dried grains with solubles
(DDGS), along with soy flour, corn flour, fish meal, whe y, mineral and
vitamin mix, with a net protein content adjusted to 28 0/c was extruded in a
single-screw laboratory extruder using seven different die nozzles. Increasing moisture content of the ingredient mix from 15 to 25% resulted
in a 2.0. 16.0, 16.3, 22.9. 18.5. 32.5. and 63.7% decrease, respectively, in
bulk density, water-solubility index, sinking velocity, L 5. 6*. mass flow
rate, and absolute pressure, as well as 11.6. 16.2, and 7% increases, respectively, in pellet durability, water-absorption index, and a. Increasing
the temperature from 101) to 140°C resulted in 17.0. 5.9. 35.4. 50.6. 28.8.
33.9, and 33.9% decreases, respectively, in unit density, pellet durability.
sinking velocity, absolute pressure. specific mechanical energy, torque, and
apparent viscosity, but a 49.1 and 16.9% increase, respectively, in dough
temperature and water-absorption index. Increasing the LID ratio of the
die nozzle resulted in an increase in bulk density. L* , o*, and torque, but a
decrease in unit density, pellet durability, water-absorption index, sinking
velocity, h, mass flow rate. dough temperature, and apparent viscosity.
As demonstrated in this study, the selection of an appropriate die geometry,
in addition to the selection of suitable temperature and moisture content
levels, are critical for producing DDGS-based extrudates with optimum
properties.
Distillers dried grains with solubles (DDGS) typically contain
high amounts of protein (23-29%) and low levels of' starch (l--2%)
and are thus a possible alternative protein source for aquaculture
feeds (Chin et al 1989; Lee et al 1991: Wu et al 1994. 1996). Depending on the species, aquaculture feeds generally require protein
contents of 26-50% (Lovell 1989). Consequently, these formulated
feeds can contain high quantities of both protein and starch.
Floatability of the extrudates is an important quality parameter for
aquaculture feeds (Bandyohadhyay and Ranjan 2001: RolI'e et al
2001). The unit density of extrudates, which affects the floatahility,
depends on the extent of expansion obtained during extrusion
cooking. Expansion can he controlled by changing the type and
nature of ingredients used, and by changing the processing conditions in the extruder. In the extrusion industry, starch-based ingredients are often used to obtain puffed products, while proteinbased ingredients are often used to obtain texturized products
(Kokini et al 1992). During extrusion processing of starch-based
products, the extent of gelatinization occurring inside the barrel
plays an important role in determining final extrudate properties.
Depending on the extent of gelatinization, the ingredient mix is
turned into an elastic melt inside the barrel (Case et al 1992; Sokhey
et al 1994; Ihanoglu et al 1996; Ilo et al 1996; Lin et al 2000). When
the elastic melt exits through the die, expansion occurs due to the
flashing of water vapor, which occurs due to the sudden drop in
pressure (Alves et al 1999; Lam and Flores 2003). During the
extrusion processing of protein-based products, on the other hand,
the ingredient mix becomes more of a plastic melt inside the
barrel. The protein can be denatured due to the heat, which results
in modifications in the peptide bonds and amino acid chains.
When the material exits through the die, it is in a plastic, homogenous state, and a more porous, fibrous textured product generally
results, often due to the voids formed by the steam generated during
sudden pressure drop (Gwiazda et al 1987; Singh et al 1991; Sandra
and Jose 1993). Operation of extruders depends on many factors,
including the pressure developed inside the die, slip at the barrel
wall, and the degree to which the screw is filled. The combination
of these variables, along with the type and composition of raw
ingredients used, will affect operational capabilities (Mercier et al
1989). The extruder die plays an important role in affecting the processing conditions as well. For circular dies, nozzle dimensions
(i.e., nozzle diameter and length) will affect process conditions and
performance (Chinnaswarny et al 1987). The how of dough inside
a circular shaped die (Q) is directly proportional to the pressure
developed inside the die (AP). and inversely proportional to the
apparent viscosity (id) of the dough inside the die. This can be
mathematically expressed as
2
Graduate research assistant, South Dakota State University, Brookings, SD 57007.
Professor, South Dakota State University, Brookings, SD 57007.
Corresponding author. Phone: 605-688-5661. Fax: 605-688-6764, E-mail address:
muthukum@sdstate.edu
Bioprocess Engineer, North Central Agricultural Research Laboratory, USDA, ARS,
Brookings, SD 57006. Mention of a trade name, propriety product or specific equipment does not Constitute a guarantee or warranty by the United States Department
of Agriculture and does not imply approval of a product to the exclusion of others
that may be suitable,
P rofessor, South Dakota State University, Brookings, SD 57007.
doi:1 0.1 094/CCHEM-84-4-0389
© 2007 AACC International, Inc.
Q =K ( AP/ ud )
(
I)
where K is a proportionality factor, which, for a circular die with
a nozzle radius of R and nozzle length of L, can be expressed as
(Sokhey et al 1997)
(2)
K=.irR4I8L
The rheological and thermodynamic processes occurring inside
the die during forming and stretching have decisive effects on the
final quality of extruded products (Mercier et al 1989). Apparent
viscosity is the most important rheological property that affects
final product properties. During extrusion of biologically based
l'eed materials, ingredients often transform into a pseudoplastic
melt. And the moisture content of the ingredients, as well as cooking temperature, often significantly affect the apparent viscosity
and thus the final extrudate properties (Harper 1981; Rosentrater
et al 2005; Shukla et al 2005).
Therefore, the objective of this study was to investigate the
effect of the die nozzle dimensions, barrel temperature profile,
and moisture content on the DDGS-based extrudate properties, and
extruder processing parameters.
MATERIALS AND METHODS
Sample Preparation
An ingredient blend containing 40% DDGS, along with appropriate quantities of soy flour, corn flour, Menhaden fish meal, whey,
vitamin and mineral mix, with the net protein adjusted to 28%
was prepared following Chevanan et al (2005a,b). DDGS was
provided by Dakota Ethanol LLC (Wentworth, SD) and was
Vol. 84, No. 4, 2007 389

2. ground to a particle size of 100 pm using a laboratory grinder
(S500 disc mill, Genmills, Clifton, NJ). Corn flour was provided
by Cargill Dry Ingredients (Paris, IL), and soy flour was provided
by Cargill Soy Protein Solutions (Cedar Rapids, IA). The ingredients were mixed in a laboratory-scale mixer (N50 mixer, Hobart
Corporation, Troy, OH) for 10 mm, and then stored overnight at
refrigerated conditions (10 ± 1°C) for moisture stabilization. The
moisture content of the ingredient mix was adjusted by adding
required quantities of water during mixing.
Experimental Design
The extrusion studies were conducted using a single-screw extruder (Brahender Plasti-Corder. model PL 2000. South Hackensack, NJ), which had a barrel of 317.5 mm. with a length to diameter
ratio of 20:1. The die assembly had an internal conical section
and a length of 101.6 mm. A screw with a uniform pitch of 9.05
rnni was used in the experiments. The screw had variable flute
depth, with the depth at the feed portion of 9.05 mm, and near the
die of 3.81 mm. The compression ratio achieved inside the barrel
was 3:1. The speed of the screw and the temperature inside the
barrel were controlled by a computer control system. The extruder
barrel's band heaters allowed the temperature of the feed lone.
transition zone in the barrel, and the die section to be controlled.
Compressed air cooling was provided in the barrel section as well,
but the die section was not cooled. The extruder had a 7.5 HP
motor, and the computer system could control the speed of the
screw at 0-2 10 rpm (0-22 rad/sec).
Experiments were conducted with a full-factorial design using
three levels of moisture content (MC) (IS, 20. and 25%, wh);
three levels of temperature gradient in the barrel (90-100-100°C,
90-120-120, and 90-140-140'C) hereafter referred to as temperatures of 100, 120, and 140°C. respectively: and seven levels of
die geometry with various nozzle length to diameter ratios. The dimensions of the seven different dies used in the experiments are
given in Table I.
Measurement of Extrudate Properties
Unit density (UD). Extrudates were cut with a razor blade into
20-mm lengths. UD was determined as the ratio of mass to the calculated volume of each piece by assuming cylindrical shapes for
each extrudate according to Jamin and Flores (1998).
Bulk density (BD) was measured using a standard bushel tester
(Seedburo Equipment Co., Chicago. IL) following the method prescribed by the USDA (1999).
Pellet durability (PD) was determined following ASAE standard
method S269.4 DEC01 (1996); 200 g of the extrudates was tumbled inside a pellet durahilty tester (Seedhuro) for 10 min and then
hand-sieved through a No. 6 screen. PD was calculated as
where Q is the net torque exerted on the extruder drive (N-rn), w
is the angular velocity of the screw (rad/sec), and ,n,,.,.,, is the mass
flow rate (g/min).
Apparent viscosit y (ii) of the dough in the extruder (Pa-see) was
calculated by approximating the barrel and screw as a concentric
cylinder viscometer. and then incorporating corrections for tapered
screw geometry (Rogers 1970; Lo and Moreira 1996; Konkoly
1997; Lam and Flores 2003; Rosentrater et al 2005). The apparent
viscosity was determined as the ratio of shear stress (t,) at screw
(N/ni 2 ) to the shear rate (y,) at the screw (I /sec) calculated from
Equations 5 and 6
(3)
Water absorption index (WAI) was determined according to Jones
et a! (2000). To determine WAI, 2.5 g of finely ground sample
was suspended in 30 mL of distilled water at 30°C in a 50-mi,
tarred centrifuge tube. The content was stirred intermittently over
TABLE 1
Dimensions of Dies Used in Study
Diameter of
Nozzle (mm)
Length of
Nozzle (mm)
LID Ratio
3.0
6.0
4.0
2.7
3.0
2.0
3.0
10.0
20.0
13.7
13.0
17,5
14.5
30.0
3.3
3.3
3.4
4.8
5.8
7.3
10.0
390 CEREAL CHEMISTRY
Extrusion Processing Parameters
The temperature of the ingredient melt at the end of the barrel
(TB) was measured with a Type J thermocouple with a range of
0-400°C. The absolute pressure (P) inside the die was recorded
with pressure transducer that had it of 0-68.9 MR The teriiperature of the melt in the die (TD) was recorded with a therriiocouple that was integral to the pressure transducer. The net torque
() was measured with a torque transducer that had a range of 040,000 m-g. During experimentation, the extrudate samples were
collected for 30-sec intervals, and the mass flow rate (MFR) was
then calculated (g!nirn). Based on the torque and the mass how
rate data, the various processing variables were then determined.
Specific mechanical energ y ( SME) (J/g) was calculated accordin- to Harper (1981) and Martelli (1983) as
SME = (* W *60)/ fl7(4)
7.
PD = ( Mass of pellet after tumbling/Mass of pellet before
rumbling) x too
Die No.
30 min and then centrifuged at 3,000 x g for 10 mm. The supernatant water was transferred into tarred aluminum dishes. The mass
of the remaining gel was weighed, and WA! was calculated as the
ratio of gel mass to the sample mass.
Water-solubility index (WSJ) was determined as the water-soluble fraction in the supernatant, expressed as percent of dry sample
(Jones et al 2000). The WSI was determined from the amount of
dried solids recovered by evaporating the resulting supernatant in
an oven at 135°C for 2 hr; it was determined as the mass of solids
in the extract to the original sample mass (%).
Sinking velocit y (SV) was measured following the method adopted by Hiinadri et a! (1993). SV was measured by recording the
time takeii for an extrudate 20 mm long to travel from the surface
of water to a depth of 425 min a 2,000-mL graduated cylinder.
Color of the extrudates was determined using a spectrophotometer (portable model CM 2500d, Minolta Corporation, Ramsey,
NJ) using the L-a-b opposable color space. where L* quantifies
the brightness, a quantifies redness/greenness, and h* quantifies
yellowness/blueness.
=)/(2*)r*(cor)2 */) =C5 Q
= (2o)
wherer, -,rr i s
*r2)/(,.2
(r
2
)=
w
(5)
(ôa)
the radius correction due to frustum value
re, +T.ffJ ? JJ2
+r(, 2 )/3 ,(m)
(6b)
where r is the effective radius including the screw root radius
and half of flight height (in), L is the screw length in the axial
direction (,n), C,, is a correction factor for shear stress (5675.4 for
the screw used), 'y, is the shear rate at the screw (]/see), r5 is the
barrel radius (m), and C., is the correction factor for shear rate
(6.31 for the screw used).
Statistical Analysis
The measurements were completed in triplicate for all extrudate properties and extrusion processing parameters, except for
pellet durability, which was measured in duplicate. The data were

3. then analyzed with Proc GLM to determine the main and interaction effects and LSD using a = 0.05 for comparison, with SAS v.8
software (SAS Institute, Cary, NC). To determine the effect of
nozzle length (L), nozzle diameter (D), and length to diameter
ratio (L/D) on individual response variables, multiple linear
regression analysis was conducted with linear quadratic models
Response =Ii + a * D + 02 MC + a 1 * T+a4 * I) * T+ a D *
MC+a (, * 1 * MC+a 7 */)2+a5 MCI +a972
(7)
Response = 12 + b, * L + h 2 MC + h 3 * T + b4 * L * T+ b 5 * L
,MC+h6iMC+b7L2+b5 MCI +h911
(8)
Response =/+c 1 *(lJD)+c 2 *MC+csT+c 4* (lJD)*/+cs'
(liD) MC+c 5* T * MC+c 7 *(IJD)2+c5
MCI +
(9)
The Proc Reg procedure in SAS was used to determine the
coefficients for each of the terms, and only statistically significant
terms were included in the final model using a step-wise selection
method. In Equations 7, 8. and 9. J, '2, and 13 are the intercept
values; Oi - a. b 1 - h9 , and c 1 - c9 are the regression coefficients
for respective terms; D. L. LID. MC . and T represent the diameter
(mm), length (mm). length-to-diameter ratio of the die nozzle (-),
moisture content (%, wb) of the blend, and temperature (°C),
respectively.
RESULTS AND DISCUSSION
Changing the levels of temperature, moisture content, and die
dimensions were each found to have significant effects on all the
extrudate properties studied, except for UD, where the effect of
moisture content was not significant (Table II). Temperature,
moisture content, and die dimensions also significantly affected
all extrusion processing parameters as well (Table Ill). Additionally, the interaction effects were also significant (P < 0.05) for all
the extrudate properties. except for die*rnoisture content and die*
moisture content*temperature for UD, and temperature* moisture
content for WSI. The interaction effect of temperature, moisture
content, and die dimensions were also significant for all the extrusion processing variables studied.
With regression, it was determined that LID, moisture content,
and temperature (using Equation 9) predicted all extrudate properties and the extrusion processing parameters with high R2 values
compared with L or D alone as the primary geometric parameters
(Equations 7 and 8). Hence, regression modeling using L/D as the
die geometry parameter was pursued for all subsequent analysis.
Extrudate Properties
Unit density (UD), which affects floatahility of extrudates, is a
very important quality parameter for aquaculturc feed materials.
TABLE II
Main Treatment Effects on the Ph ysical Properties of Extrudates'
Parameter
Unit
Density
(g/cm3)
Bulk
Density
(g/cm3)
Water
Pellet
Durability Absorption
Index
(%)
Water
Solubility
Index (%)
Sinking
Velocity
(m/sec)
Color
L
Temp profile ("C)
40,92h
0.l0a
17.71 it
2.63c
95.75a
1.03a
0.45h
90-100-I 00
41.39a
17.70a
0.09b
2.90h
0.45a
94.6Ib
l.00b
90-120-120
0.07c
39.65c
16.95a
3.13a
87.19c
0.42c
0.88c
90-140-140
Moisture content ('T)
4-4.41a
0.09a
18.33a
2,73c
0.44a
86,95c
0.96a
15
42.39h
0.08b
17.57b
2.88b
92.40h
0.44h
0,96a
20
36.1 3c
0.08c
I6,66c
101a
97.04a
0.44b
0.99a
25
D (mm)
L/D (-)
39.28c
0.08d
17.03c
2.99a
94.55c
0.43d
0.98ah
3.33
3.0
41,30b
0.12a
17.45h
2.85h
0,48a
85.06e
0.95b
6.0
3.33
40,78h
16.44d
0. lOb
2.96a
87.17d
0.45b
4.0
0.99c
3.43
41.27b
0.07e
17,61h
2.86h
95.06h
0.43d
0.97ab
2.7
4.81
0.08c
41,32h
18.30a
2.95a
95.21h
0.42f
0.98ah
3.0
5.83
38.09d
0.07f
17,34hc
2.84h
97.99a
0.42e
101a
7.25
2.0
0.08d
42,l3a
17.99a
2.78c
94.23c
0.44c
1.02a
3.0
10.00
a'
b'
4.30c
4,37h
4.51a
I 3.98th
14,06a
13.91b
4.26c
4.32b
4.56a
15.12a
14.33h
12,76c
4.35cd
4.38bcd
4.46b
4.15e
4.31d
4.67a
4.4lbc
13.36e
l4,62a
14.13b
13.7 Id
l3.90c
I 3.76cd
l4,17h
Values with the same letter in a column for a given factor are not significantly different (P < 0.05).
TABLE III
Main Treatment Effects on Extrusion Processing Parameters-'
Parameter
Temp profile (°C)
90-100-100
90-120-120
90-140-140
Moisture content (%)
IS
20
25
D (mm)
UD (-)
3.0
3.33
3.33
6.0
4.0
3.43
2.7
4.81
3.0
5.83
2.0
7.25
10.00
3.0
Mass Flow
Rate (g/min) Torque (N-m)
Absolute
Apparent
SME (Jig) Viscosity (Pa-sec) Pressure (MPa)
Dough Temp
(Barrel) (°C)
Dough Temp
(Die) (°C)
139.3c
141.6b
144.8a
74.04a
62.89b
55.24c
430.52a
360.34b
306.66c
4894.37a
4157.66h
3651.55c
10.91a
7.71b
5.38c
102.85c
1l6.82h
127.12a
104.09c
131.14b
155.19a
165.Ia
153.4b
11 1.5c
62.07b
89.12a
41.03c
307.24b
476.70a
305.24b
4103.00b
5890.98a
2712.31c
12.82a
8.02b
4.65c
116.31a
I l5.64h
1t4.43c
126.44c
129.25b
132.84a
126.2g
149.2a
145.6b
140.6e
138.5f
144.1c
143.Od
59.05d
54.67e
56.41de
65.06c
57,26de
80.06a
74.47b
364.65c
301.91e
312.73e
367.66c
330.83d
467.51a
471.89b
3903.20d
3614.00e
3728.80de
4300.80c
3784.90de
5292.00a
4922.40b
4.01f
3.94f
5.05c
9.32c
7.91d
11.88b
13.87a
117.05b
105.25d
I l7.58ab
118.l5a
114.89c
1t7.55ab
t17.84a
136.60a
126.88e
130.77c
132.05b
126.82e
128.82d
12805d
Values with the same letter in a column for a given factor are not significantly different (P < 0.05).
Vol. 84, No. 4, 2007 391
II

4. Increasing the moisture content of the ingredient mix had no
significant effect (P > 0.05) on the UD of the extrudates. However, increasing the temperature from 100 to 140°C resulted in a
significant decrease (17%) in UD of extrudates. Many researchers
have observed that temperature has an inverse relationship with
the apparent viscosity of the ingredient melt inside the barrel and
die (Harper et al 1981; Bhattacharya and Hanna 1986), and that
higher temperatures typically result in lower apparent viscosity of
the melt. When the ingredient melt (at lower viscosities) exits
through the die, extrudates tend to expand more and, thus, have
reduced UD. Regression analysis for UD resulted in an R2 value
0.65 using LID as the geometric parameter. Model equation 10
predicts the UD of extrudates with L/D. MC, and T (Table V). The
negative value for the term containing L/D, within the bounds of
the experiment, indicated that there was a general trend of decrease in UD as the LID ratio was increased.
Bulk density (BD) is another key property, as it influences storage
space required at the processing plant, during shipping, and at
animal production facilities. BD depends on the size, shape, and
the extent of expansion during extrusion. Increasing temperature
had a significant effect on the BD (P < 0.05). The lowest BD
(0.319 g/cm 3 ) was recorded at a Tof 140°C, MC of 25%, and L/D
of 7.25. The highest RD (0.509 g/cm) was recorded at a T of
120°C, MC of 20%, and L/D of 3.33 (Table IV). Changing the
MC of ingredient mix also had a significant effect on the BD (P <
0.05): increasing MC from 15 to 25% resulted in a 2% decrease in
BD. The R2 value of the linear quadratic model with L/D as the
geometric parameter was 0.62. Model equation 11 predicts BD using
L/D, MC, and T (Table V). A positive coefficient for the L/D and
(LID ) 2 terms in the model indicate that there was general increasing trend in BD as the L/D ratio was increased.
Pellet durability (PD), which is an important quality parameter
of feed materials (Rosentrater et al 2005), can indirectly assess the
mechanical strength of extrudates. Increasing T resulted in a significant decrease in the PD (P <0.05). The PD at Tof 100°C was
9.8% higher compared with the PD at T 140°C (Table II). Changing the MC of the ingredient mix also had a significant effect on
the PD of the extrudates; and PD at 25% MC was 11.9% higher
compared with the PD at 15% MC. At higher MC, the temperature of dough at the die was significantly higher as well (Table
III). The mechanical strength of extrudates depends on the extent
of heat treatment and the relative degree of starch gelatinization
that occurs during processing (Colonna et al 1989). Increasing the
MC and T synergistically resulted in a higher extent of heat treatment and gelatinization, which resulted in higher PD. The R2 value
of the linear quadratic model using liD as the geometric parameter
was 0.69. Model equation 12 predicts PD with L/D, MC, and T
(Table V). A negative coefficient for the L/D, LID * MC, and (LID)2
terms in the model indicated that there was, in general, a decreasing trend in PD as the LID ratio was increased. The higher PD at
lower T is indicated by the negative coefficient of (1.11 - 0.04*
MC) for the T term, while the higher PD at higher MC is summarized by the positive coefficient of (0.04 * 7' - 2.31) for the MC
term.
Water-absorption index (WAI) is related to the extent of starch
that has maintained integrity during extrusion processing, and to
the molecular breakdown of starch and protein components. WAI
is also indirectly related to water-holding capacity, which thus
affects product storage stability. T had a significant effect on the
WAI (P <0.05); the WAI was 16.9% higher at a T of 140°C compared with the WAI at a Tof 100°C (Table 11). A similar trend was
observed by Anderson et al (1969) with extruded corn grits.
TABLE IV
Treatment Combination Effects on the Extrudate Properties'
Property
Die Diameter
(mm)
Unit density (glcm3)
3.0
6.0
4.0
2.7
3.0
2.0
3.0
Bulk density (g/cm3)
3.0
6.0
4.0
2.7
3.0
2.0
3.0
Pellet durability (%)
3.0
6.0
4.0
2.7
3.0
2.0
3.0
Water absorption index (-)
3.0
6.0
4.0
2.7
3.0
2.0
3.0
90-100-1001C
LID (.)
15%
20%
90-120.120°C
25%
20%
3.3
3.3
3.4
4.8
5.8
7.3
10.0
0.97612
na
0.95614
0.958- 14
0.8911-17
087 12.17
1.00 1 '
l.02''
0.994 ( 20.95 7.13
1.1116
1.03 31,05
1.09'
3,3
3.3
3.4
4.8
5.8
7.3
10.0
na
na
0.49
0.47460466.8
0.49
04219.21
0.41 21-22
0.48
0.42 1 6.2 00.493
0.43 15- 17
0.4226.2(
0.42 16-20
0.465-7
0459.12
0,467.10
0.402324
0431315
0.451'
0.49
no
na
0.511
0.51 1.2
0.47'
0.44 11130467.8
0.431518
na
0.4580.459-12
045112
0.46
3.3
3,3
3.4
4.8
5.8
7.3
10.0
93.601516 98.00
na
83 . 352397.96
99.06"
87 .982292.1316.79 9364'516
9601 9.129665510
96.56611
94 7313.15 96 ,098.1298.42'
9974(2
9942 1.299.411.2
9545(0(4 97.80
99.09
3.3
3.3
3.4
4.8
5.8
7.3
10.0
2.642226
na
2 .6926.242 . 6926.24
2 . 6826.2.7916.22
24927.29
2. 1229
2.6223.27
2 . 82 15.20
2.4627.29
2 .51 2529
2.6521.25
2.5026.29
1.1912
1.1115
0811417
119'
1.12'
1.17 1-4
1.17'
15%
2.761823
2.5175-29
2.92016
2.642327
2.891218
2.572429
2.7319.23
90-140.140°C
25%
0929.16
no
1.0I1'
0994.12
l.02''
1.01"'
0.96` 30.99412
1.001'
0,9480
1.00 1 '
0.948(5
0.9942
1.00 1 '
0.9812
1.08 1-8I.03'°
1.014-11
1.03 3-101.0431()
15%
25%
20%
0.92
no
O. 80 00.79 16-17
0929.16
0.75 17
0.939 6o.8911 17
na
0.89
0.99'
0.929- 16
098 5120.91'
0.8512
0939.15
0.99101'
0.83 13-1
0.948
0.75'
0.85''
0.412(23
0.5023
0.4590
0.4315'
0.431520
0.441214
04316.20
0.421821
no
0466.80457(0
0.43 [4-16
04411'
0.44 1214
0.402223
0.3923
na
0.4313-14
042 1620
0.412223
0.42°°
0.4022.23
0.46
046°
03726
0.3823
0.3227
03924.25
93.0016.18
no
88 . 162290.772021
91 .70 18.20 92 .68 16.18
95.2411-1493.3617
na
91.36 19-20
97494.7
99.771
95 .989292.05 17-20
96.90
96.5l6
97.10
97743.6
95.27'°'
97.6l
95.0712(4
88.3822
na
40.372675.8024
44042587.3022
9263 161991.1320.21
na
91.61 19-20
96 . 56&1935415.16
89 . 882188,3822
97444.8
93.66°'
98.01
96.24712
99.00'
98.3624
9439(4.15
2801621
na
2 . 6323.27
2.8912-18
2.86 14-19
3.13
2.6726.2430'J8-13
2.9111-17
2 .731923
3.02713
2.76 17-23
2.40282.65 22-26
3.093.10
2.9990
3.2025
3.02'
3.312
3.16
2.8116.20
3143.8
na
2 . 93 I63.12
3.02 7-13
3.05''
2.91 1.83.2923
3.2824
na
3 .085102,9610.15
2 .88 1 3. 19
3.1536
3.491
3192.6
3.03713
3.62'
3046.12
3.027-11
3.29
(continued on next page)
Values with the same superscript numbers for a given property are not significantly different (P <0.05); na, data not available.
392 CEREAL CHEMISTRY

5. Changing the MC of the ingredient mix also had a significant
effect on the WAI (P < 0.05). Increasing the MC from 15 to 25%
resulted in a 16.2% increase in the WAI. Anderson (1982)
observed that higher temperatures and higher moisture contents
could result in greater starch breakdown and thus increased formation of an expansible matrix, resulting in higher water-holding
capacity, which could lead to an increased extrudate WAI. In this
study also, higher T and higher MC resulted in higher WAI of the
extrudates. The R2 value for the linear quadratic model with L/D
as the geometric parameter was 0.65. Regression equation 13 predicts WAI with L/D, MC, and T (Table V). The negative coefficient for the L/D term in the model indicated that there was a
general decreasing trend in WAI as L/D ratio increased. Higher
WAI at higher MC and higher T are indicated by the positive
coefficients for MC and T terms in the model.
Water-solubilitv index (WSJ) is directly related to the extent of
starch gelatinization that occurs inside the extruder (Harper 1981).
Generally, WSJ increases as the temperature increases, due to starch
depolymerization, which leads to reduced length of amylose and
aniylopectin chains (Anderson et a! 1982). In our experiments
using DDGS. changing T did not result in significant changes in
the WSJ of the extrudates. But changing MC did have a signilicant effect. William et al (1977) observed drier conditions of the
ingredients affected the extent of dextrinization of starch, which
resulted in higher extrudate WSJ. Similarly, in this study the WSJ
at 15% MC was 16.0% higher compared with the WSI at 25% MC.
The R2 value with LID as the geometric parameter in the linear
quadratic model was 0.41. Model equation 14 predicts WSI with
L/D, MC, and T (Table V). The very low R 2 value for the resulting
model indicated that WSI may be controlled by various other
factors such as residence time, extent of shear, etc., in addition to
die dimensions, MC, and Tduring processing.
Sinking velocity (SV) depends on the extent of expansion and,
thus, the biochemical changes occurring inside the barrel. Extrudate expansion affects density of extrudates as well. Moreover,
the extent of biochemical changes affect the water-absorption
capacity and structural integrity of extrudates, which also affect
the SV. The SV of the extrudates significantly (P < 0.05) decreased
(35.4%) at higher T, indicating that the extrudates had a decreased
UD and better buoyancy. Even though changing the MC of the
ingredient mix had no significant effect on the UD of the extrudates, the SV of the extrudates obtained at 25% MC was significantly lower (16.3%) compared with the extrudates at 15% MC
(Table II). The R2 value using L/D as the geometric parameter in the
linear quadratic model was 0.84. Model equation IS predicts SV
with L/D, MC, and T (Table V). The negative value for terms containing liD, within experimental boundaries, indicated that there
was, in general, a decreasing trend in SV as the L/D ratio increased.
Lower SV at higher MC and higher T is indicated by the negative
coefficient for the MC and T terms in the model equation.
TABLE IV (con:inuedfro,n previous page)
Treatment Combination Effects on the Extrudate Propertiesa
Property
90-100-100°C
Die Diameter
(mm)
Water solubility index (%)
3.0
6.0
4.0
2.7
3.0
2.0
3.0
Sinking velocity (mis)
3.0
6.0
4.0
2.7
3.0
2.0
3.0
L8(-)
3.0
6.0
4.0
2.7
3.0
2.0
3.0
15%
3.3
3.3
3.4
4.8
5.8
7.3
10.0
3.3
3.3
3.4
4.8
5.8
7.3
10.0
3.3
3.3
3,4
4.8
5.8
7.3
10.0
3.0
6.0
4.0
2.7
3.0
2.0
3.0
3.3
3.3
3.4
4.8
5.8
7.3
10.0
3.0
6.0
4.0
2.7
3.0
2.0
3.0
3.3
3.3
3.4
4.8
5.8
7.3
10.0
b*()
20%
20%
25%
16.431322
17.16'° 0
na
17.1690
19 . 51 2418.37-57
1749 71416.6713 20
16.541422
18.3330
17.50'
I9.07
17.99610
19 . 63 2417,16ho118
17.387-1117.9860
18.21
14.0523
17 . 8461!19,662.4
0.091113
nit
0 . 12 20,121.2
0 , 106.90.1
0 . 09 000.0911'
0 . 09 1200.091316
0.081822
008 19.22
0.092 13
0 . 09 100
na
45.29
4495 4.7
43.31712
42658.14
43357.11
44 . 615 84404610
46. 08 s
4348710
43,357.11
38.94 18-22
47.22'
90-140-140°C
90-120-120°C
46.38
4Q719.25
na
4.19 16-22
4.29''
4.1417.22
4.18 16-22
4 . 01 2126
3.86 25-27
4.0220.26
422 15.21
5.23 2377'
3.962227
3 . 902327
0.111-1
0.113-1'
0.1
0.0169
0.1069
0.0719.23
0,109.12
35.622527
399016.19
36.9622.23
33.7027.28
36.4023.26
33.0428.29
31.6129
15%
17.96 6-10
na
17.4470
17 . 946 II)
17 . 02 1019
16261622
17121019
18.25
2016 1217.676'
18 . 03 31017131018
19.9323
21.14'
na
0.13'
0.10'
009 13.18
0.0913-15
0 . 08 19.22
0.09 1.1 '
na
4.28 13-1
4.29 13 '
389 24.27
4. 1017-24
4.6311
5Q92.4
4914.6
3 . 8026.27
14.4911.15
12.45 22-27
na
13.82'
15.541-314.822
12 o927-28
14.501 1-15
l5.09
12.11 25-28
14.15 14-18
14.961'
14.4711-1.512.25 25-28
15.5114
11.8328
14.50-15
15.05
12 o927-28
l4.94"
15.4215
na
15.80'
15.65'
14,885.12
15.25
15.29'
15.40'
16741220
16.65 13-21
15.6221 22
17.23"
16.72°°
16.321622
18644.6
0.0914-19
0.0720.24
0022.3
0.1224
0.108-11
00913.16
0.08 17-21 0.062932
0.0810.22
0.08 14-19
0.062529
0.07 21-25
0062630
0091'
43.856)0
na
46 . 162544435.9
46 . 292543996.10
45 . 523641.841 1-16
42700.13
45.62'
40.5915 8
40.65 14-18
42.8 1 8-13
48.70'
4.66"
4.0220.26
4091825
47369
43312.17
25%
4.25 15-20
4.0021.27
4.141 7.22
43113.18
43312.18
4431115
37.052225
40.51'"
390618.71
347926.28
35.822426
32.8628.29
34.562(28
4.27''
4.1018-25
4.1317-23
4.4600
4.65"
5.272
13.91 16-19
14.67
14.0611- 16
140415.18
13.90169
l4.18'
15,331.6
15%
25%
20%
17.61613
na
17 , 308.1616.51 14-22
16 . 75 12211
15.5822
18 , 05 5.1016.8011.10
19.45 3 5
na
17636.13
17.37°
17 . 786 1117.05")
16.261622
16141922
16.07 19-22
16.21 17-22
17636.13
16.0719.22
15.85 20-22
0.0723.27
na
0 . 12 240,116.9
0 . 109200815'
0.053032
0.08"
0.07 22-26
cia
0.06 27-30
0.06 29-31
0.0816-20 0.0631.32
na
38.721 8-22
39.31 17-20
46.88'
na
42.25 10-15
47,771.2
41391216
38.721822
36.052326
42.15'°°
41.15 13-17
41.1 1317
42.449- 15
4.15 17-22
na
4.80
4.63''
4 , 85 5.85.521
4 00 1 "
4.27''
4.25)520
na
4 . 28 14.19
4 50'° 13
3 . 8022743912.16
12.6122.27
na
13.7717-1914.3812- 16
14699.13
12.862224
11.8827-28
147383
12.34 13-28
na
12.4 123-28
14.751- 13
14.62912.95 21-23
14.0615-18
14.5210-15
14.3812-16
13.4719-21
14.5210-1.5
14.27130
14.0415-18
0.04
0.l0'°
0.072025
0.09
00624.28
0.06
0
344526.28
35372527
37.0921 .24
37.9219.22
39171720
35.2825.27
37.65 20-23
4.7069
5152.3
4.76
4.3212.18
4,539.11
4.50 10-14
4,519.12
12652226
14.24''
13.8916-19
13.1420-22
13.6218.20
12.2724-28
127122.25
with the same superscript numbers for a given property are not significantly different (P < 0.05); na, data not available.
Vol. 84, No. 4, 2007 393

6. Color change in extrusion processing is mostly due to Maillard
reactions (Mercier et al 1989). In fact, significant losses of lysine
(an important ammo acid required for fish growth) during"
sion processing (Bjorck and Asp 1983) have been observed due to
Maillard reactions. Extrudates obtained at a T of 140°C had lower
brightness (L) and yellowness (b) values, but had a higher redness (a) value (Table II). A similar trend was observed by Shukla
et al (2005) during extrusion experiments with raw materials that
also contained DDGS. This may have been due to Maillard
reactions, which resulted in the browning of extrudates at higher
temperatures. Increasing the MC from 15 to 25% resulted in a
22.9 and 18.5% decrease, respectively, in brightness and yellowness, hut a 7.0% increase in the redness of the extrudates. In
general. extrudates obtained with higher MC had lower brightness
and yellowness values and higher redness values. This might have
been due to the higher resulting temperature of the ingredient
melt at the die (Table Ill), which may have contributed to the
browning. Changing the die dimensions also had a significant
effect on resulting color values: model equations 16, 17. and 18
(Table V) predict the color of the extrudates with L/D. MC, and T
(R 2 for I. = 0.70, R 2 for a = 0.29, and R 2 for b* = 0.76). Within
the scope of the experiment, the positive value for the term containing L/D in the model indicated that there was a general increasing
(rend in L as the L/D ratio was increased. Similarly, a positive
value for the term containing L/D in the model indicated that
there was an increase in a as the LID ratio was increased. On the
other hand, the negative coefficient for the L/D term in the model
for b* indicated that there was a decrease in h as the L/D ratio
was increased.
Extrusion Processing Parameters
Mass flow rate (MFR) in a single-screw extruder depends on
the drag flow developed by screw rotation and the pressure flow
developed due to the restriction of the die (Mercier et al 1989). In
this study. increasing T from 100 to 140°C resulted in a significant increase (3.9%) in the MFR (P < 0.05). On the other hand,
increasing the MC from 15 to 25% resulted in a 32.5% decrease
in the MFR. The R 2 value using LID as the geometric parameter
in the linear quadratic model was 0.87. Regression equation 19
predicts MFR using L/D, T, and MC (Table V). A negative coefficient for LID in the model indicated that there was a decreasing
trend in MFR as the L/D ratio was increased. The decrease in
MFR with higher MC is explained by the coefficient (18.42_O.6*
MC) for MC term in the model. The higher MFR at higher Tcan
he explained by the positive coefficient for Tin the resulting model.
Dough Temperature
The temperature development inside the barrel depends on
thermal gradients, thermal conductivity, thermal diffusivity, degree
of mixing, velocity of flow, etc., and ultimately affects the extrusion process as well as the resulting extrudate properties. Increasing
T from 100 to 140°C resulted in a 23.60% increase in TB, which
compared with a 49.1% increase in TD. In the extruder used, the
die section did not have a compressed air cooling system, which
contributed to the increase in TD. The pressure and shear developed inside the die may also have contributed to the higher TD.
Increasing MC of the ingredient mix resulted in a significant (P <
0.05) decrease in TB, while the reverse was observed for ID
(Table LII). The R 2 value of the Linear quadratic model with L/D as
the geometric parameter in the TB prediction model was 0.73.
The R 2 value to predict TD was 0.97. The resulting TB prediction
equation 20 uses L/D, MC. and T (Table V). The negative value
for the L/D terms indicated that there was, in general, a decreasing
trend in TB as the L/D increased. A negative coefficient for MC in
the model indicated that the TB decreased as the MC was increased, whereas a positive coefficient for the T term indicated that
the TB increased as Tincreased.
Regression equation 21 predicts ID with LID. MC , and T(Tahle
V). A negative coefficient for the IJD term in the model indicated
that there was a general decreasing trend in TD as the LID ratio
was increased. On the other hand, a positive coefficient for the
MC and T terms in the model indicated that there were general
increasing trends in TD as the MC and T were increased. In our
experiment, we observed that increasing the temperature profile in
the barrel resulted in increased TD and TB (Table IL!) leading to a
reduction in UD, BD. PD, SV. L, and an increase in WAI and a*
of the extrudates (Table II). However, increasing the moisture
content of the ingredient mix resulted in reduced TD but increased
TB of the molten dough.
Absolute Pressure (P)
The pressure developed inside the die depends on various
parameters such as rheological properties of the ingredient blend
and pumping characteristics, in addition to the die dimensions
used in the extruder. The biochemical conversions occurring inside
the barrel depend on the extent of pressure developed inside the
extruder, in addition to the extent of thermal and mechanical
energy available for chemical reactions, and ultimately affects the
extrudate properties. Increasing the T resulted in a significant decrease in the P developed in the die (P < 0.05). In foct, increasing
T from 100 to 140°C resulted in a 50.6% decrease. Moreover, at
TABLE V
Regression Models for Extrudate Properties and Extrusion Processing Parameters Using Moisture Content (MC),
Barrel Temperature (T), and Length-to. Diameter Ratio of I)ie (L/D)a
Eq
Property
to
UD
BD
PD
WAI
wsI
sv
L*
a*
Regre.ssion Model
R2
SE CV(%)
1.141+0003 *(IJD)-0.025 * MC +0.018 * T-O.003 *(LJD)*MC
0.65
0.098 10.0
-0.63 + 0.0104 * (UD) + 0.022 * MC + 0.01 6 * T+ 0.002 * (LID)2 - 0.003MC2
0.62
0.025
5.7
t2
t39.78- l4.93 *(UD)-2.3t *MC- lIT *T_0.33*(IJD)*MC+004*T*MC_054*(LID)2
0.69
6.87
7.4
13
0.99-0.02 * (LID) + 0.03 * MC + 0.01 * T
0.65
0.176
6.?
14
12.41 +0.57 *(IJD)-0.25 *MC+0.14 *T+0.002(1JD) T-0.017 *(UD)*
MC+0.002 * T*MC
0.4 I
t.to
6.3
l5
0.934-0.084 * (UD) - 0.005 * MC - 0.002 * T + 0.006 * (LID)2
0.84
0.044 15.4
16
16.62 + 1.77 *(UD)+ 3.21 * MC -0.03 * T- 0.09 *(LID) * MC -0.09 *(MC)2
0.70
2.36
5.7
17
2.42 + 0.14 * (LID)- 0.03 * MC + 0.02 * T- 0.003 * (LID) * T+ 0.0l * (L/D) * MC
0.29
0362
8.2
l8
27.86-0.03 * (LID) -0.67 * MC -0.07 T + 0.004 * T MC
0.76
0.520
3.7
19
MFR
3.95-0.20 *(tJD)+ 18.42 * MC + 0.17 * T-0.60 * MC2
0.87
9.33
6.6
20
TB
60.t4 - 0.710 * (L/D)- 0.229 * MC + 0.390 * T- 0.04 * (UD) * T- 0.259 * (L/D)2
0.73
6.43
5.6
21
TD
-30.38-0.41 *(LID)+ 0.48 * MC+ 1.27 * T
0.97
3.98
3.1
22
P
173.7- 0.64 * (LID)- 1.27 * MC - 14.0 * T- 0.03 *(L/D) * MC+0.09 * T* MC -3.0 * (JJTJ)2
0.86
1.58
19.2
23
SME
-2 t 90 + 58.3 * (LID) + 282.6 * MC - 3.16 * T - 3.03 * (LID)2 - 7.04 * MC2
0.56 tO 1.8
27.7
24
-447.9 + 3.26 * (L/D)+ 59.6 * MC -0.47 * T- 1.53 * MC2
0.71
15.3
23.8
25
-34049 + 1134.9 * (LID) +4049 * MC- 18.8*T_2 . 2 * (LID) * T- t53*(LJD) * MC-26.5 * (lJrJ)2_ 102.3 * MC2
0.71 101.7
23.8
UD, unit density, BD, bulk density; PD, pellet durability; WAL, waier-soluble index; WSI, water-soluble index; SV, sinking velocity; L* .
brightness. a*, redness,
b*, yellowness, MFR, mass flow rate; TB,
temperature of dough at the barrel; TD, temperature of dough at die; P, pressure developed in the die; SME, specific
mechanical energy; Q. torque; ii, viscosity of dough.
394 CEREAL CHEMISTRY

7. higher T, the apparent viscosity of the ingredient melt decreased
(Table 111). Thus the ingredient melt at lower viscosity might have
resulted in decreased P inside the die. Lam and Flores (2003) observed a similar trend during extrusion of fish feed. Increasing the
MC of the ingredient mix also had a significant effect on the P
developed in the die. The P at 15% MC was 63.7% higher compared with the P at 25% MC. The R 2 value using L/D as the geometric parameter in the linear quadratic model was 0.86. Model
equation 22 predicts P with L/D, MC, and T (Table V). Within the
bounds of the study, the coefficient for (LID ) 2 in the model was
significant indicating that P had a nonlinear relationship with
LID. The reduced P inside the die at higher T is indicated by the
negative value for the terms containing T in the model. Increasing
the temperature profile in the barrel as well as increasing the moisture content of the ingredient blend resulted in reduced P (Table
Ill) leading to decreasing trends in UD, BD, PD, SV, L*, and
increasing trends in WAI and a (Table 11).
Specific Mechanical Energy (SME)
In extrusion processing, the amount of biochemical reactions
occurring inside the barrel depends on the thermal and mechanical energy available. To induce optimum conversion of the ingredients to obtain extrudates of high quality, appropriate combinations
of shear and thermal energy are very important. The amount of
TABLE VI
Treatment Combination Effects on the Extrusion Parameters'
Property
Die
(mm)
LID (-)
15%
20%
25%
15%
20%
Mass flow rate (g/min)
940252s
na
157.45 11
na
1 48.9°
ia
3.3
3.0
55 7.14
152 4814
165.079
31.21"
158.8"
3.3
6.0
81.326
I56.3"°
I70,9''
I57.9'13
163.529
34
4.0
I
56.7'
99.62425
157.5' 1
173.71-4153,30.14
158.7''
4.8
2.7
553711
151.8814
109,52024
I50.9'''
158.0 °
5.8
3.0
146212.14
100.221156.0
163.4''°
0A'
2.0
144.01215
166.118
100,572.25
147,11114
154.4''°
0.0
3.0
Torque (N-rn)
3.0
6.0
4.0
2.7
3.0
2.0
3.0
3.3
3.3
34
4.8
5.8
73
10.0
SME (Jig)
3.3
3.0
3.3
6.0
3.4
4.0
4.8
2.7
5.8
3.0
7.3
2.0
10.0
3.0
Apparent viscosity (Pa-sec)
3.3
3.0
3.3
6.0
3.4
4.0
4.8
2.7
5.8
3.0
7.3
2.0
10.0
3.0
Absolute pressure (MPa)
3.3
3.0
3.3
6.0
3.4
4.0
4.8
2.7
5.8
3.0
7.3
2.0
10.0
3.0
Dough temp barrel (°C)
3.3
3.0
3.3
6.0
3.4
4.0
4.8
2.7
5.8
3.0
7.3
2.0
10.0
3.0
A,. i°C
Un.. 5
Ong
3.0
60
4.0
2.7
3.0
2.0
30
3.3
3.3
3.4
4.8
5.8
7.3
10.0
Ila
48.21922
58.415- 1 R
81.2811
68.212-14
74.9'0 11
91 90.7
102.7-1-429.6"°
30.12830
95 345
29.72830
100 745
41,322.27
107.214
104.22141,622.27
III 313
115.3'
107.6' 441 , 4 22.27
563.0"
na
247 . 8 2(25501.6'
520.868
291 , 8 18.22
381 . 7) 2.14570.9'
547.8'
352.5''''
576.3'
338.8'''
485 . 8 810596.9'
6788.0'
na
6298.9'
na
5367.5 11 7087.1 1-4
3862 . 3 1518 6658.7'
7623.9'
4948.5"
6888.324
4509.0°"
6073 . 4677l09.7"
na
492 2125
I3.07
l9.2
18.93
, 39479
27.68'
8.1014
5.16 20
6.67''
I
10,47)112
15.3556
17.14
102.82124
na
10172325
J01.6 23 25
103.121-24
104 . 9 19.2 )
108 . 1) 7 ( 8102.92)24
102.522-24
105.5 19-20
106 . 8 1819102.92124
108 . 8 .18103.2 21 23
na
101,223.27
102,422.27
l04.3223
101 923 .27
101,025.27
100.62627
90-140-140°C
90-120-120°C
90-100-100°C
no
50,818.21
53916.19
61,9117
34.12730
68.214
82,181
256.82024
no
187 , 5 27251,42(1.25
298 . 5( 20257.52024
318.4 1 ' °
338.8'' °'
194.6
310.5 15-1
626 . 2 2 .3
357.2''°
3359(512
4035' 12
25%
1()1.821-21
121 I620
I l9.9'"°
104.02125
II
115.819-22
127.916 8
4941922
34 ITh'
730H
7331113
3592529
88.160
3532829
95.0156
83.97-938.32328
104.42-444.62125
46,120.24
105.524
256.3 20 21
392.8' 2-3
460.1 9 10
492.5' '°
45I.10'
624.62.3
597.831
273.41823
490.88)0
244322.25
277.4(7.23
264.51924
314.3 15-18
3266.0(9.22 2253.627.31)
no
1954.3 29 10
3357,91821
1991.52830
4846.4 14828.5'"°
"°
2336.020.29
6280.456
2728 , 42 2.224091.6°'
2371.425.29
1965 , 2 28303563.1 17.20
5822.6
6898 . 4 242946.5225
4511.112.14
7359.8 "
2533.42328
2255 . 8 27.305544.O'
2753. 122 21
2733 . 8 22275427 . 08 ( 06970 , 4243049.021.24
4 . 05 2326
flu
2 . 88 2629
6.9211- 18
3.37 24-29 8 l5''
3,7979
629)8.20
6 . 04 1821
10.34°
14.961-714.3968
20,572
8.02''
103 , 920.22
na
9932628
110.816
101 , 423.26
118.611-11
119.88.9
97 .928
99 . I 27118.38-11
119.38.10
101 , 623.27
120.0'
99.65 25-28
104.42123
109.3'
102 . 1 232799.82
105,220.22
103,12226
106,719.21
107.8'°
104.521.23
1039 21.24
102 . 62227103.62225
114.418
102 , 922.2)
3,942327
3.62 23-28
4752)25
8.97
7.72''
13.5589
12.8290
117.1(0.14
115.91214
I 17 . 3 (014
118.01°
I l6.7°'
117.410- 1
116.91
2.44283)
6.75 16-19
2.0929.32
4.08 23-26
4.31 22-25
7.07'
°
6,97(5(8
I l6.9°'
113.5°
11561315
117.79-11
115,314.15
I5.7°'°
1l5.515
136.811
143.4"
na
128.513(6
127.1(6
123.617
130.312-15141.410
129.8)1.16
138.01'
131.412'
I30.8°''
129.913.16
128.91-1-t6129.3'
127.715-16
127.2 16
128.414-16130.5(2.15
127.08
15%
20%
140.6 °
155.87 '
161.1312
153,9814
147.311-14
°
na
177 . 0( 2163.22 1 °
161.8 '
169.0"
172.2 1 '
176.1 5
flU
42.9212),
46.42024
112.6' 2
47.81922
n
694)2(4
67.1 ''
63.6 14-1
75.99 (2
53.6 17-20
9435.8
91.16-7
n
203.2 25- 27
215.2 24 27
289.5)7.21
n
319.915-18
324.3°' (8
653.6'
250.31' -25
322 5°'°
402.9' '-'
297.2(0.20
471 .8' '°
459.8' '°
25%
II47(9.21
130.4°'
123.616 1
110 19.24
l6.622
104,62025
11661722
25.9311
30.7 28-10
30 9281))
32.120.1))
34 12738
38.1 2 .29
37.4 24-29
184.6
191 . 926 27
203 .911-27
237.3 24-27
238.423 . 26
297.6 16-20
262.3''
1716.00
744l.1"
na
2026.82030
2832 . 921263157.1 19-22
2122.82830
5020.5''
3672.7"
2040.72830
3068 . 2 2023 4206.8'"'
2520.123.28
6234.4 5-6
4585.8° "
35444)7.20
2250.927.30
no
6023 , 60.72476.724.29
4438.0' -'
4332225
na
1.363072
2 . 6827.30
2.142932
3 . 91 2327
6.55'"
10.431 1-12
3.882327
na
12 . 799109.92i2
I0.15° "
15.92
136.8'
na
100 , 8 24.27
93.529
132. 1 2-5
133. 12-4
133 . 92l32.9
131.638
na
133 . 5 24131.63.6
131446
13372 3
na
151.58
156.1'
155.9
na
152.7
150.9
154. 947
152.078
155.7
155.2
l55.7'
152.468
150.30.9
1.18'
0.9432
1.3 131-32
2.902529
53032
4.922)'25
5491922
124.8
110.116.17
132.32.5
132.22.5
130. 11-6
129.66
13144.6
170.7'
156.1
153.05.8
158.523
160.22
159.32
147.49
Values with the same superscript numbers for a given property are not significantly different (P < 0.05); na. data not available.
Vol. 84, No. 4, 2007 395

8. TABLE VII
Correlation Coefficients for All Multivariate Extrusion Data,h
D
D
L
LD
T
MC
UD
WAI
wsI
BE)
PD
sv
MFR
SME
ii
a.
I,
TB
TI)
0.174
-0.541'
0.007
-0.028
-0.177
0.011
-0.090
0.509'
-0.405'
0.676'
3234'
0.117
0.270*
-0.193
0.116
-0.039
0.257
-0.43)'
-0.318'
-0.042
IM
0.716*
-0.001
-0.076
0.128
-0.164
0.226
0.105
-0.036
0.087
0.098
0.095
0.073
0.110
0.173
0.029
0.182
0.337*
-0.062
-0.087
LI)
-0003
-0.057
0.242*
-0.164
0.242'
-0.247'
0.255*
-0.380'
0.274'
0.021
(1.272*
0.243*
0.038
0.096
--0.0)0
0.60Y
0.150
-0.053
T
0.028
0.489*
0.693*
_0,223*
-0.368'
-0.332'
-0.499'
0.277*
0.089
-0.316'
-0.231 *
-0.112
0. 203 *
-0.022
-0.392'
0.813'
0,976*
MC
LSJJJ
WAL
wsI
0.074
0.383*
-0.492'
4)0887
0.380*
-0.221
-0.345'
-0.875'
-0.017
-0.294°
_0.76l*
0.298'
-0.839"
4)567*
-4)063
0.12)
4)414*
0.16)
0.372'
0.459*
1)162
0)77
-0.122
0.249'
0.141
-0.024
0.0)3
-0.062
0,314*
-0339'
-0.471'
473*
-0.334'
41.125
0.48l*
-0.387'
-0.287'
_0,299*
4)333*
-0.387'
0.211*
-4)384'
-0.566
0.552'
0.727*
0.007
0.02
0.099
0.307'
0,380*
0.186
0.283*
0.531*
-0.308'
11.480'
0.498'
-0.084
-0.282'
BD
-0.068
0.715'
-0.038
0.064
-0.078
-0.056
0.079
0.047
0.188
-0.048
-0.462'
-0.389'
PD
-0.255'
0.111
-0.384
0.210'
0.077
-0.096
-0.156
-4)272'
0.2)7
-0.033
-0.278*
(continued on next page)
D. diameter of die nozzle. 1.. length of (lie nozzle; liD. liD ratio of die nozzle;
T. temperature: MC, moisture content of ingredient mix; UD. twit density: WAI,
water-absorption index, WSI, water-solubility index: BD, hulk density: PD. pellet durability: SV, sinking velocity: Q. torque: MFR. mass flow rate; SME.
specific mechanical energy. t. apparent viscosity: I. e.
brightness; a. redness; 6'. yellowness; P. absolute pressure in the die; TB, temperature of ingredient nix
at the barrel; TD, temperature of the ingredient mix at die.
'. Significant at P <0.01.
mechanical energy applied to the ingredient mix is measured in
terms of SME. SME is the net amount of energy utilized by the
extruder to produce unit mass flow rate of the material. In singlescrew extrusion, it is very difficult to control the SME because the
material is transported by friction between the screw and barrel
surfaces and the material. At higher T, SME decreased; increasing
T from 100 to 140°C resulted in a 28.8% decrease in the SME.
The reduced SME consumption at higher temperature profile in
the barrel resulted in decreasing trends in UD, BD, PD, SV, L*,
and increasing trends in WAI and a' value. The MC also had
significant effect. The highest SME (653.6 JIg) was observed at
20% MC, while the lowest SME (184.6 JIg) was observed at 15
and 25% MC (Table VI). As expected, die dimensions also had a
significant effect. The R2 value with L/D as the geometric parameter in the linear quadratic model was 0.56. Model equation 23
predicts SME with LID, MC, and T (Table V). The (LID) 2 term in
the model indicated that there was a nonlinear trend between
SME consumption and LID ratio. A negative coefficient for T in
the model indicated that there was a decrease in SME as T was
increased. MC also exhibited a nonlinear relationship with SME,
as indicated by the MC 2 term in the model.
Torque (U)
In general, most food and feed materials exhibit pseudoplastic
behavior. As the screw speed increases, viscosity decreases,
which affects the torque requirement. Reduced viscosity at higher
shear rates affects the mass flow rate as well. Mass flow rate also
affects the torque requirement. Hence, U is an important parameter in extrusion processing, and ultimately affects the quality of
extrudate properties. Increasing T resulted in a decrease (P <
005) in the U required to operate the extruder (Table Ill). In fact,
increasing T from 100 to 140°C resulted in a 33.9% decrease in
U. This behavior occurred, at least in part, because increasing T
resulted in a reduced apparent viscosity (Ti) of the dough, which
thus required less torque to rotate the screw. The decreased torque
requirement at higher temperature profile in the barrel resulted in
reduced UD, BD, PD, SV, L*, and increased WAI and a' values
(Table III). Changing the MC also had a significant effect on the
U required to operate the extruder. Maximum U was required at
396 CEREAL CHEMISTRY
20% MC, and increasing or decreasing the moisture content from
20% resulted in reduced U. Changing the die dimensions also had
a significant effect on U. The R2 value with L/D as the geometric
parameter in the linear quadratic model was 0.71. Model equation
24 predicts U with LID, MC, and T (Table V). A positive coefficient for the L/D term in the model indicated that there was, in
general, an increasing trend in U requirement as L/D increased. A
negative coefficient for T in the model indicated that the U requirement decreased as the temperature was increased.
Apparent Viscosity (i)
Viscosity development inside the barrel depends on ingredient
composition, constituent molecular weights, processing temperatures, pressures developed, and thermomechanjcal history, and
affects the final product properties (Gagos and Bhakuni 1992).
Apparent viscosity can reveal several of these parameters and thus
is often used to monitor product quality online. Increasing T from
100 to 140°C resulted in a 33.9% decrease in the r inside the
barrel. Due to this decreased r], there was a decreasing trend in
extrudate properties such as UD, BD, PD, SV, and an increasing
trend in WAI and a' value was observed (Table II). As expected,
changing the MC of the ingredient mix also had a significant effect
on i Maximum Ti was observed at 20% MC. Changin g the die
dimensions had significant effect on ii as well. The R2 value to
predict Ti with L/D was 0.71. Model equation 25 predicts Ti using
L/D, MC, and T (Table V). The negative coefficient for the T term
in the model indicated that there was a decrease in apparent
viscosity as Tincreased. The (LID) 2 and (MC) 2 terms in the model
were also significant, indicating that the LID of the die and MC
had a nonlinear relationship with Ti of the ingredient melt inside
the barrel.
Correlation Analysis
After examining individual treatment effects, as well as treatment combination effects, the multivariate data were subjected to
correlation analysis to further examine relationships between the
variables. The Pearson correlation coefficient r provides the strength
of linear relationship between two variables (Rao 1997). In this
study, high correlation coefficients occurred between some a priori

9. TABLE VII (continued from previous page)
Correlation Coefficients for All Multivariate Extrusion Dataa
sV
ri
MFR
-0006
0.143
-0.033
0.008
0.233*
-0.149
0.288*
-.1)027
-0.643*
-0.532'
0.468
0.890
0.956*
0,464
_0.284*
0.398*
0.575°
-0.095
.0350*
0.074
0.409*
0.721*
.0.205*
0.844*
0.414°
0.119
-0.018
0.9l6
0.186
.40236*
0.055
0.453°
-0.156
.0356*
TB
a
SME
TD
D
L
LD
T
MC
UD
WA!
Wsl
BD
PD
sv
MFR
SME
11
L5
a
b5
P
TB
TD
I
0.462k
_0.347*
0.354°
0.530*
4)070
.0299*
I
-.0,672*
0.832°
0.531
0.066
-.0.202*
-0.226°
.40323°
0.016
0.229°
I
0.454°
0.025
-0.132
I
-0.129
-0463°
0799°
LID ratio of die nozzle; T. temperature; MC, moisture content of ingredient mix; 1.JD, unit density; WA!,
D. diameter of die nozzle: L. length of die nozzle; LID.
torque: MFR. mass flow rate, SME, specific
water-absorption index; WSI. water-solubility index: BI). hulk density: PD. pellet durability; SV. sinking velocity; D,
h* . yellowness: P. absolute pressure in the die; TB. temperature of ingredient inix at the
r, apparent viscosity; l.°. brightness; a°, redness:
mechanical energy:
barrel: TD, temperature of the ingredient mix at die.
. Significant at P <0.01.
expected pairs of responses; some were not anticipated, however.
The temperature profile in the barrel was adjusted to control the
extent of heat treatment applied to the dough during processing.
The nature of thermo/cheinical/mechaflical changes occurring in
the ingredient mix affects the viscosity of the dough that develops,
which thus affects the extrusion processing parameters. Hence,
we expected strong correlations between barrel and dough temperature, between die and dough temperature, and between apparent
viscosity, torque, and SME. As anticipated, several of these correlation coefficients exhibited very strong relationships, with absolute
r values >0.90 (P < 0.01) (Table VII). The independent variables
controlled in our experiments will affect the extruder processing
conditions, which in turn will affect the extrudate properties.
Hence, we expected good correlations between the processing conditions and extrudate properties. As anticipated, mass flow rate and
moisture content, WAI, and dough temperature at the die, sinking
velocity, and dough temperature at the barrel, apparent viscosity,
and die pressure, sinking velocity, and dough temperature at the
die, and bulk density and die diameter had correlation coefficients
with an absolute value >0.70. It was also anticipated that correlations between extrudate properties such as bulk density, unit density, sinking velocity, and color would occur. As expected, the correlation between bulk density and sinking velocity, unit density,
and sinking velocity, L* and a* had correlation coefficients with
absolute values >0.70. Additionally, the color of the extrudates exhibited correlation with extrusion processing parameters: mass flow
L*,
rate and L*, mass flow rate and b*, water-solubility index and
L* all were significant, with correlation coeffidie pressure and
cients with absolute values > 0.6. These correlations may have the
potential for predicting extrusion processing conditions and extrudate properties and should be further investigated.
CONCLUSIONS
The goal of this study was to investigate the effect of die nozzle
dimensions, barrel temperature profile, and moisture content on
DDGS-based extrudate properties and extruder processing parameters. All of these factors had significant effects on extrudate
properties such as unit density, bulk density, pellet durability,
water absorption index, water solubility index, sinking velocity,
and color, and extrusion process ingparameterS such as the mass
flow rate, dough temperature, absolute pressure, specific mechanical energy, torque, and apparent viscosity. Increasing the moisture
content from 15 to 25% resulted in decreases of 2.0, 16.0, 16.3,
22.9, 18.5, 32.5, and 63.7%, respectively, in bulk density, water
solubility index, sinking velocity, L*, b*, mass flow rate, and absolute pressure, but an 11.6, 16.2, and 7.0% increase, respectively,
in pellet durability, water absorption index, and a* . On the other
hand, increasing temperature from 100 to 140°C resulted in decreases of 17.0, 5.9. 35.4, 50.6, 28.8, 33.9, and 33.9%, respectively,
in unit density, pellet durability, sinking velocity, absolute pressure,
specific mechanical energy, torque, and apparent viscosity, but a
49.1 and 16.9% increase, respectively, in dough temperature and
water absorption index. It was also determined that, using a linear
quadratic model, the L/D ratio of the die, along with moisture content and temperature of the transition and die sections, predicted
well most of the extrudate and extrusion properties studied. The
aim of this study was to investigate extrusion processing of a 40%
DDGS aquaculture feed blend on a laboratory scale, as a precursor
to scaling up to commercial equipment.
Ultimately, production of these types of feeds on a larger
extruder may change the interactions observed with this study, but
we have examined a wide range of parameter settings, which will
be useful for scale-up purposes. Future studies will examine other
levels of DDGS as well.
ACKNOWLEDGMENTS
We thankfully acknowledge the financial support provided by the
Agricultural Experiment Station, South Dakota State University, Brookings, SD, and the North Central Agricultural Research Laboratory, USDA,
ARS, Brookings, SD.
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