G. J. B. B., Vol. 2 (3) 2013: 326-330 icon

G. J. B. B., Vol. 2 (3) 2013: 326-330



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G.J.B.B., VOL.2 (3) 2013: 326-330
  ISSN 2278 – 9103
EFFECT OF USING CUMIN OIL (Cuminum cyminum) AS FEED ADDITIVES
ON PROFILE ANALYSIS AND GROWTH CURVE OF BROILER
Eman H. Al- Anbari1, Ahmed A. Abbas2, Firas R. Al-Samarai3, Jenan  S. Al-Shamire4 & Falah H. Al-Zaidi5
1, 4Department of Animal Resources/College of Agriculture/University of Baghdad/Iraq
2Department of Animal Resources/College of Agriculture/University of Anbar/Iraq
3Department of Veterinary /Public Health/College of Veterinary Medicine/University of Baghdad/Iraq
5Department of Animal Resources / Directorate of Baghdad Agriculture /Ministry of Agriculture/ Iraq
ABSTRACT
An experiment was conducted to investigate the effect of adding different percentages of cumin oil in diet (0% (control),
15%, 30% and 45%) on weekly and final body weight of Ross 308 broiler.  Profile analysis was applied to detect the
parallelism between growth curves of all groups, whereas nonlinear regression and linear regression were used to fit
growth curves. The groups’ profiles were found not parallel in terms of cumulative weekly body weight. Two ways
analysis of variance with interaction (ANOVA) was performed and t-test was used to identify the differences between
studied traits. Results revealed that adding cumin oil to diet has increased significantly (P < 0.05) the weekly and final
weight in treated groups as compared with control. In order to describe the growth curve, four statistical methods were
used: simple linear regression and Gompertz, Verhulst, and Weighted Least Square (WLS) nonlinear regression. Results
obtained that WLS function was more powerful for fitting the data as compared with other functions. As there are
significant differences in weekly and final body weight in addition to that the growth curves were no parallel, the adding of
cumin oil (45%) to diet of broiler may play an important role in profitability by increasing the final body weight.
KEY WORDS: growth curve, nonlinear regression, cumin, broiler etc.
INTRODUCTION
Growth curve models provide a set of parameters that are
It was well known that using antibiotics as promoters had
using to describe growth pattern over time, and to estimate
a substantial role in poultry industry as the growth rate of
the expected weight of animals at a specific age (Tzeng
broiler chickens has been improved greatly. The World
and Becker, 1981; Yakupoglu and Atil, 2001). In addition,
Health Organization (WHO) has recently identified
the parameters obtained from growth curve functions are
antibiotic resistance as a major problem for public health.
highly heritable and have been used in selection studies
For this reason, several studies were conducted to looking
(Merrit, 1974; Mignon-Grasteau et al., 2000).There is a set
for and evaluate suitable alternatives for antibiotics.
of growth curve functions used to determine age-weight
Medicinal plants and their products including plant
relationship of poultry. The functions have different
extracts or essential oils are adopted as suitable candidates
properties and different mathematical limitations. The
for use in broiler diets due to their beneficial effects as
present study was conducted to determine the effect of
phytogenic feed additives (Bolukbasi & Erha, 2007;
adding different levels of cumin oil in broiler diets as feed
Soltan et al., 2008 and Dalkiliç et al., 2009). Such
additives on the shape of growth curve in addition to use
compounds influence poultry productivity and health
linear and some non-linear functions to fit the growth
mainly by stabilization of normal gut microflora,
curve.
prevention of pathogens colonization (Tekeli et al., 2006)
and digestive enzymes production and activities
MATERIALS & METHODS
improvement (Lee et al., 2004).  Many studies have been
An experiment was carried out at poultry farm in College
conducted to investigate the effect of using herbal plants
of Veterinary Medicine /University of Baghdad. A total of
as feed additives in broiler diets (Halle et al., 1999;
200day old (Ross 308) chicks were used. The experiment
Osman, 2002; Abbas and Ahmed, 2010; AL-Kassie et al.,
was lasted long for 35 days. Chicks were randomly
2011; Khan et al., 2012). Herbs contain some complicated
divided into four groups with 50 chicks each and located
mixtures of organic chemicals that may vary depending
as follows: (T0) chicks group freely access feed ad libitum
upon many factors related to the growth, production, and
as a control, the remaining treatments (T1, T2, and T3)
processing of the herbal product (Amal et al., 2013).
chicks were fed diet with adding cumin oil at 15, 30, and
Though herbs with antimicrobial properties are reported,
45%. Nipple drinker and round feeder were used to satisfy
their using in broiler diets has not been studied
the requirements of chickens. Birds were fed with starter
extensively. However, little or no work has been done on
diet between 0-3 weeks and with growth diet at 4th and
the effects of plant extracts on poultry growth curve in
5thweeks, Chemical composition of the basal diet is
Iraq.
presented in Table 1. It is formulated to meet nutrient
requirement of broiler chickens. Barn conditions
(temperature, humidity) were kept similar for each group.
326

Profile analysis and growth curve as feed additives of Cuminum cyminum on broiler
TABLE 1: Chemical composition of the basal diet in different periods of the experiment
Ingredients%
Starter  Finisher
1-21 
days  
22-35 
days
Yellow corn
51.0
 53.3
Wheat
13.8
 15.0
Soybean oil
1.0
 2.5
Premix*
2.5
 2.5
Methionine
0.1
 0.1
Salt
0.3
 0.3
Lysine
0.1
 0.1
Di-calcium phosphate
1.2
 1.2
Total
100
 100
Calculated chemical analysis
ME(Kcal/kg)
3000  3086
Crude protein
21.30  19.50
Calcium
0.69
 0.52
Available phosphate
0.74
 0.69
Methionine
0.33
 0.31
Lysine
1.19
 1.08
Premix (2.5%) Provided the following (Per Kg of complete diets). Vit A. 367500 IU,133500 IU Vit. D3,  1920 mg Vit.E,
84.42 Vit. K3, 50 mg Vit. B1, 150 mg Vit. B2, 500 mg Vit. B3, 177.5 mg Vit. B6, 0.8 mg Vit. B12, 600 mg Vit. PP, 24.5 mg
folic acid, 27 mg biotin, 5767.5 mg choline, 2667 mg Fe, 333.75 mg Cu, 3334.06 mg Mn , 203 mg Co , 2334.38 mg Zn ,
100.75 mg Ca , 10 mg Se,  65446.46 mg Ph, 36667.5 mg DLMithionine, 200.02mg, Ethoxyquin,50mg, Flavophospholipol,
30g Fish meal, 1800g wheat bran
Statistical Analysis
To fitting growth curves, three nonlinear functions
Profile analysis and four functions were used in analyzing
(Gompertz, Verhulst and WLS) and one linear function
data. Profile analysis was used to determine the magnitude
were used to investigate the effect of supplementation of
of both within-subjects (week) and between-subject
different levels of cumin oil in diet on the shapes of
(group) main effects and interactions. In this study, k-
growth curves of broiler.
sample profile analysis was adapted to compare body
Functions were defined as follows:
weight of Ross 308 broiler raised under four different
Gompertz growth function:
levels of feed additive. This allowed for the assignment of
W = A exp [-exp (-b (t-k))]
a level of statistical significant differences and the shapes
Verhulst growth function:
of the centroids of four groups. Profile analysis is a
W= A / (1 + k * exp (-b * t))
method of comparison of groups that are experimental
Weighted least square growth function:
units to the same set of p measurements by examining the
W = A/ (1+exp (-b-k*t))
p-1 slopes using multivariate analysis of variance
Where, W is the body weight (BW) at the day t; A is the
(MANOVA) between adjacent coordinate values for mean
maximum BW at maturity; b is the rate of growth; k is the
vectors of the groups. Profile analysis is an extension of
age (days) of the maximum daily BW gain. The analysis
the repeated measurement and special case of MANOVA.
was performed separately for each group.
The basic of profile analysis is a sequence comparison
Analysis of data was submitted by SAS program (2000).
method for finding and aligning distantly related
sequences.
RESULTS & DISCUSSION
There are some reasons for the superiority of profile
Test of parallel profiles obtained that the null hypothesis
analysis to other methods such as repeated measurements
of parallel profiles is rejected as F= 13.24, Wilk’s Lambda
and growth curve (Morrison, 1995; Mendes et al., 2005;
= 0.038 with p-value = 0.0001(Figure 1).
Ersoy et al., 2006).
3000
2500
2000

/gm 1500
Control
ght  1000
15%Cumin
Wei
500
30%Cumin
0
45%Cumin
1day week 1 week 2 week 3 week 4 week 5
Age
FIGURE 1: Profiles of weekly body weight of all groups
327

G.J.B.B., VOL.2 (3) 2013: 326-330
  ISSN 2278 – 9103
Two ways analysis of variance with interaction (ANOVA)
fifth week, the final body weight of group 4 only has been
was conducted to test the differences between means of
differed significantly (P < 0.05) compared with control.
treatments within each period. Results revealed that the
These results are in agreement with those results reported
differences between treatments were significant (P < 0.05).
by several researches who confirmed that the final body
As shown in table (2) the chicks in group 3 and 4 have
weight increased as a result of adding herbal plants to
higher body weight at first week as compared with control.
broiler diet (William & Losa, 2001; AL-Kassie et al.,
The dominance in body weight of group 3 and 4 was
2011; Khan et al., 2012).
continued through progress age till the fourth week as in
TABLE 2: Means of weekly and final body weight of groups (control, T1, T2, and T3)
Group 

day
1 weeks
2 weeks
3 weeks
4 weeks
5 weeks
Control
E38.50±0.61a
 E121.10±7.69b
 D378.50±24.03b
C712.90±25.77b  B1370.10±56.51b  A2102.00±72.36b
15% cumin
E38.20±0.07a
 E123.90±6.29ab D429.50±21.81a  C866.80±41.00a  B1503.30±0.01b
 A2149.40±102.20b
30% cumin
E39.60±0.49a
 E135.40±4.44a
 D454.00±14.62a  C876.10±22.40a  B1759.70±51.47a  A2315.90±59.58ab
45% cumin
E39.30±0.55a
 E128.00±3.05a
 D436.40±11.43a  C833.60±22.43a  B1835.30±43.07a
A2390.90±68.36a
Means with different subscript small letters in the same column differ significantly (P< 0.05)
Means with different subscript capital letters in the same row differ significantly (P< 0.05)
Concerning the fitting growth curves, three nonlinear
Results indicated that WLS function was the best function
functions and one linear function were used. In order to
for describing the shape of growth curves for all
determine goodness of fit for growth curves, the values of
treatments; on the other hand the corresponding values of
mean square error (MSE) were taken in our consideration.
MSE for linear function were58463.46, 56293.73,
The values of MSE of WLS function are 637.11, 1005.53,
66808.35, and 82387.68 respectively which mean that
926.40 and 802.68 for groups: control, 1, 2 and
linear regression was the worst function to fit growth
3respectively (Table 3, 4, 5, 6) which represent the lowest
curves as compared with nonlinear functions.
values as compared to those values of other functions.
TABLE 3: Parameter estimates and growth characteristics of broiler based on Gompertz, Verhulst and WLS functions and
linear regression in control group
Parameter Gompertz
Verhulst
WLS
Mean±SE
Mean±SE
Mean±SE
A
8872.96±3863.08  3253.86±396.91 2874.82±205.11
b
0.03±0.008
0.13±0.01
-4.17±0.10
K
44.39±9.71
54.80±8.15 0.14±0.007
MSE 15874.22
15952.41
637.11
Linear  =-278.12+60.30x
MSE 58463.46
TABLE 4: Parameter estimates and growth characteristics of broiler based on Gompertz, Verhulst and WLS functions and
linear regression in 15% cumin oil
Parameter Gompertz
Verhulst
WLS
Mean±SE
Mean±SE Mean±SE
A
4836.03±1285.00  2825.30±276.22 
2555.20±152.39
b
0.05±0.01
0.14±0.01 -4.05±0.13
K
31.02±5.14
44.38±9.45 0.16±0.009
MSE 26578.93
27179.98
1005.53
Linear 
 
=-267.08+55.42x
MSE 56293.73
TABLE 5: Parameter estimates and growth characteristics of broiler based on Gompertz, Verhulst and WLS functions and
linear regression in 30% cumin oil
Parameter Gompertz
Verhulst
WLS
Mean±SE
Mean±SE Mean±SE
A
3925.41±650.36  2676.22±156.10 
2681.24±132.91
b
0.06±0.01
0.17±0.01 -4.22±0.13
K
26.00±2.70
68.26±17.93 0.17±0.008
MSE 24683.74
25008.37
926.40
Linear 
 
=-301.92+68.48x
MSE 66808.35
328

Profile analysis and growth curve as feed additives of Cuminum cyminum on broiler
TABLE 6: Parameter estimates and growth characteristics of broiler based on Gompertz, Verhulst and WLS functions and
linear regression in 45% cumin oil
Parameter Gompertz
Verhulst
WLS
Mean±SE
Mean±SE
Mean±SE
A
4175.40±625.40  2809.83±131.94 
2926.63±140.13
b
0.07±0.01
0.18±0.01
-4.44±0.13
K
26.54±2.31
106.12±27.64 0.17±0.008
MSE 24283.50
19711.90
802.68
Linear 
 
=-351.12+72.63x
MSE 82387.68
According to MSE values it’s obvious that Gompertz
Mignon-Grasteau, S., Piles, M., Varona, L., de
function has lower values as compared with Verhulst
Rochambeau, H., Poivey, J. P., Blasco, A., Beaumont, C.
function and linear regression. In other words it was more
(2000) Genetic analysis of growth curve parameters for
appropriate for describing growth carve in control, group 1
male and female chickens resulting from selection on
and 2 whereas the situation was in contrast for group 3 as
shape of growth curve. J. Anim. Sci. 78: 2515-2524.
Verhulst function has lower MSE value. These results are
in accordance with the results of no parallelism in growth
Merrit, E.S. (1974) Selection for growth rate of broilers
curves, that was noticed previously which means that the
with a minimum increase in adult size. pp 951-958 in
power of functions -except WLS- was not same when the
Proc. 1st World Congr. Genet. Appl. to Livest,. Madrid,
curves have different shapes also these results confirm
Spain.
other results reported by Narinc et al. (2010) who found
that Gompertz function was more fit for broiler growth
William, P., Losa, R. (2001) The use of essential oils and
curve in female and male as compared with Bertalanffy
their compounds in poultry nutrition. World Poultry, 17:
and logistic functions.
14–15.
REFERENCES
Khan, S.H., Ansari, J., Haq, A.U., Abbas, G. (2012) Black
Mendes, M., Karabayir, A., Ersoy, I.E., Atasoglu, C.
cumin seeds as phytogenic product in broiler diets and its
(2005) Effect of three different lighting programs on live
effects on performance, blood constituents, immunity and
weight change of bronze turkey under semi-
caecal microbial population. Italian Anim. Sci.11: 438-
intensivecondition. Arch. Tierz., Dummerstorf, 48:1, 86-
444.
93.
Osman, M. (2002) Beneficial effects of blackseed oil
Ersoy, I.E., Mendes, M., Aktan, S. (2006) Growth Curve
inclusion in broiler diet on performance and carcass
Establishment for American Bronze Turkeys. Arch. Tierz.,
characteristics.Egypt. Poult. Sci. 22:839-853.
Dummerstorf, 49:3, 293-299.
Halle, I.R., Thomann, R., Flachowsky, G. (1999) Effect of
SAS (2001) SAS/STAT Users Guide for Personal
ethereal (essential) oil and oilseeds on the growth of
Computer. Release 6.18.SAS Institute, Inc., Cary, N.C.,
broilers. pp 469-472in Proc. 7th Symp. Vitam. Feed.
USA.
Addit.Human Anim., Jena, Germany.
Morrison, D.F. (1995) Multivariate statistical Methods.
Abbas, T. E. E., Ahmed, M. E. (2010) Effect of
Third edition. New York: McGraw-Hill Publ.
supplementation of Nigella sativa seeds to thebroiler
chicks diet on the performance andcarcass quality. Int. J.
Ersoy, I.E., Mendes, M., Aktan, S. (2006) Growth curve
Agric. Sci. 2:9-13.
establishment for American Bronze Turkeys. Arch. Tierz.,
Dummerstorf, 49:293-299.
AL-Kassie, G.A.M., Mohseen, A. M. and Abd-AL-Jaleel,
R. A. (2011) Modification of productive performance and
Narinc, D., Aksoy, T., Karaman, E.,  Curek, D. I. (2010)
physiological aspects of broilers on the addition of a
Analysis of fitting growth models in medium growing
mixture of cumin and turmeric to the diet. Research
chicken raised indoor system. Trends Anim. Vet. Sci. J.,
Opinions in Anim. Vet. Sci. 1: 31-34.
1:12-18.
Amal, O. A., Mukhtar, A. M., Mohamed, K. A. and A.H.
Tzeng, R.Y., Becker, W.A. (1981) Growth pattern of body
Ahlam, H.A. (2013) Use of Halfa Bar essential oil (HBO)
and abdominal fat weight in male broiler chickens. Poultry
as a natural growth promoter in broiler nutrition.
Sci. 60:1101-1106.
International Journal of Poultry Science 12: 15-18.
Yakupoglu, C., Atil, H. (2001) Comparison of growth
Bolukbasi, S., Erhan, M. (2007) Effect of dietary Thyme
curve models on broilers II: Comparison of models. J.
(Thymus vulgaris) on laying hens performance and
Bioscience 1:682-684.
Escherichia coli (E. coli) concentration in feces. Atatürk
University, the Faculty of Agriculture, Department of
Animal Science, 25240, Erzurum, Turkey.
329

G.J.B.B., VOL.2 (3) 2013: 326-330
  ISSN 2278 – 9103
Soltan, M.A., Shewita, R.S., El-Katcha, M.I. (2008) Effect
development, intestinal microflora and some blood
of dietary anise seeds supplementation on growth
parameters of broiler chicks. Abstract Book of 12th
performance, immune response, carcass traits and some
European Poultry Conference, Verona- Italy 10-14th Sept.
blood parameters of broiler chickens. Int. J. Poult. Sci., 7:
1078-1088.
 Lee K.W., Everts, H., Kappert, H.J., Frehner, M., Losa,
R., Beynen, A.C. (2004) Effects of dietary essential oil
Dalkiliç, B., Güler, T. (2009) The Effects of clove extract
components on growth performance, digestive enzymes
supplementation on performance and digestibility of
and lipid metabolism in female broiler chickens. Br. J.
nNutrients in broilers. F.Ü.Sa . Bil. Vet. Derg., 23: 161–
Poult. Sci., 3: 738-752.
166.
Tekeli, A., Çelik L., Kutlu, H.R., Gorgülü, M. (2006)
Effect of dietary supplemental plant extracts on
performance, carcass characteristics, digestive system
330





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