SlideShare una empresa de Scribd logo
1 de 6
Descargar para leer sin conexión
IOSR Journal of Agriculture and Veterinary Science (IOSR-JAVS)
e-ISSN: 2319-2380, p-ISSN: 2319-2372. Volume 5, Issue 2 (Sep. - Oct. 2013), PP 77-82
www.iosrjournals.org

Behaviour of laying curve in Babcock-380 brown commercial
layers in Kelantan, Malaysia
1

M R Amin*1 and S A Nawawi2

Faculty of Agro Based Industry 2Faculty of Earth Science
University Malaysia Kelantan (Campus Jeli), 17600 Jeli, Kelantan, Malaysia
ruhulaminbau1961@gmail.com or ruhulamin@umk.edu.my

Abstract: Commercial layers start laying at 18-20 weeks of age and continues until 72 weeks under cost-effective
operation. Age of the hens, mortality rate, feed and environmental conditions determine the persistancy of production as
reflected in the laying curve. In this experiment laying performance of 10000 hen-housed Babcock-380 brown commercial
layers housed in Kelantan, Malaysia was assessed in mathematical model using hen-house and hen-day measurements. It
revealed that hens reached at peak lay at 21 weeks of age and maintained a stability until 44 weeks. Birds egg laying
performance gradually declined with progress in age till 80 weeks. Y= 35176.99 – 397.374 A + 5.065 F gave the best fitted
regression line (adj R2 = 0.905) for hen-housed egg production per week (A=age of hens in week and F= Kg feed
consumed/day). A 87.5% of the total variation in hen-housed egg production could be explained only by age of hens but
when feed consumption was added in the model age and feed consumption together explained 90.5% variabilty. For every
week advancement in hen’s age (week) a decrease of 0.039 eggs/hen/day was predicted (adj R2 = 83.8%). In this 10000 henhoused flock mortality/culling averaged at 14.82/week.
Key words: Babcock-380, hen-house egg production, hen-day egg production,mathematical model, laying curve

I.

Introduction

Commercial egg production with hybrid chicken is a very delicate bioentrepreneurship all over the
world. There are currently only few number of poultry breeding companies in the world owned pure lines to
make available grand parent and parent stocks to the breeder farm. Modern strains of hybrid layers are produced
by the local breeder farm/hatcheries using parent stocks. Lohman (white and brown), H&N white [Singh et al.,
2009, Silverside et al., 2012], Hy-Line (white and brown), Shaver (Anonym1, 2013), Starcross, Babcock
(Chowdhury et al., 2002, Durraniet al., 2012), Hisex (durrani, 2012) are the commonest hybrid strains of layer
chicken. According to Verma and Singh (1997) 87.33% contribution to gross return in layer enterprize comes
from eggs alone. Egg production by the hens in the laying cycle is influenced by manifold factors such as strain,
feed, survival rate and health of hens, management practices, age at point-of-lay, age at peak-of-lay (Durrani et
al., 2012). In a given flock egg production in a particular day of laying cycle depends on number of hens in the
cohort, stage of laying phase, hen health, feed, environmental condition such as temperature, humidity, light,
molting etc. Modern hybrid layers start laying at 18-20 weeks of age and continue until 72 weeks or little longer
cost-effectively (Amin and Hamidi, 2013). Determination of laying performance on individual hen basis
involves huge labour and cost. Therefore, flock efficiency is the most preferential approach for measuring laying
efficiency. ‘Hen house egg production’ and ‘hen day egg production’are the two widely used method of
measuring flock laying efficiency (Singh and Kumar, 1994). Stage of laying is a great determinant of number of
eggs laid in a given day in the laying cycle and therefore, it contributes greatly in the shape of laying curve. In
ideal condition, standard laying curve can predict the number of eggs to be laid out of a given flock size. Amin
(2012) demonstrated an incipient hen-day part laying curve with fitted quadraic equation (Y = 0.0483t 2 – 3.904,
t= age of hen in day; R2 = 0.807, p<0.001) for Babcock brown 380 layers in Kelantan, Malaysia. Zattar and
Nofal (2009) showed that relationship between egg number and variable age of hens in weeks can be best
represented in polynomial curve for Memourah (0.868≤ adj R2≤1.0) and Montazah (0.992≤adj R2≤1.0), the
two locally developed layer strain of chicken in Egypt. Atta et al. (2010) concluded that Wood equation (1967)
can be used with sufficient precision to predict whole cycle laying performance based on part egg production
record in Hyline W98 and Lohman SLS hybrid layers.Nevertheless, standard fitted regression line on laying
performance for common commercial hybrid layersis still inadequately available in literature. The present
investigation, therefore, aims at developing a standard mathematical model for Babcock brown 380 layer hens
in Kelantan, Malaysia along with some other related measurements.

II.

Materials and Methods

Data for this study were extracted from Taklimat Project Ternakan Ayam Penelor Tertutup – a
government private ownership layer farm in Kuala Balah, Kelantan, Malaysia. The flock of Babcock- 380
brown layers consisted of 10,000 pullets placed in the laying house at the age of 17 weeks in 2010.The pullets
started laying in the following week and continued until 80 weeks of age. From 17-20 weeks of age daily egg
www.iosrjournals.org

77 | Page
Behaviour of laying curve in Babcock-380 brown commercial layers in Kelantan, Malaysia
production quickly rose from 60 to 6300 and then became almost stable and took a regular shape of trend.That’s
why 21 weeks of age was considered as the begining for analysis of data.Furthermore, eggs laid until 20 weeks
were of smaller size and showed higher frequency of abnormality. Daily records were kept on number of hens
died/culled, number of eggs laid, amount of feed consumed on flock basis.Birds were provided with commercial
layer mash diet at the rate of 400 kg to 850 kg/day during first week of the placement in the laying house and
thereafter 900 kg to 1100 kg/day until last day. Variation in the amount of feed provided was independent of the
number of hens in the house rather was depended on voluntary intake by the hens. In order for quantifying the
efficiency of the layers, the following measurements were made (Amin, 2012)
𝑁𝑜 𝑜𝑓 𝑒𝑔𝑔𝑠 𝑙𝑎𝑖𝑑 𝑖𝑛 𝑎 𝑔𝑖𝑣𝑒𝑛 𝑤𝑒𝑒𝑘

i.

Hen house egg production per week (HHEPPW)= 𝑁𝑜

ii.

Hen housed egg production per cent per day (HHEPPD) =

𝑜𝑓 𝑕𝑒𝑛𝑠 𝑎𝑡 𝑡𝑕𝑒 𝑏𝑒𝑔𝑖𝑛𝑖𝑛𝑔 𝑜𝑓 𝑡𝑕𝑒 𝑤𝑒𝑒𝑘
𝑁𝑜 𝑜𝑓 𝑒𝑔𝑔𝑠 𝑙𝑎𝑖𝑑 𝑖𝑛 𝑎 𝑔𝑖𝑣𝑒𝑛 𝑑𝑎𝑦
𝑁𝑜 𝑜𝑓 𝑕𝑒𝑛𝑠 𝑜𝑛 𝑡𝑕𝑎𝑡 𝑑𝑎𝑦

× 100

Hen housed egg production per week indicates number of eggs laid per bird in a given week calculated based
on the number of hens placed at the begining of the week. So mortality/culling of hens within the period affects
HHEPPW. On the contrary, hen housed egg production per cent per day (HHEPPD) expresses average laying
performance of a hen in the flock in a particular day based on the exact number of hens exists on the particular
day. So mortality or culling does not affect HHEPPD but it includes birds that did not lay for any reason.
Statistical analyses were accomplished with the help of SPSS 11.5 statistical software. HHEPPW was compared
between a duration of every 3 months using one way ANOVA and then Tukeys test was performed for multiple
comparison (Kaps and Lamberson, 2009). So each 3 months laying duration (from 6 month to 20 month) was
splitted into equal 5 periods. The HHEPPW and HHEPPD were regressed against age of hens in week to see the
pattern of changes of egg production with progress of age. Age of hens and feed consumption were incorporated
in the mathematical model to estimate their contribution in egg production.

III.

Results and Discussion

Egg Production: HHEPPW was compared between periods of every 3 month from 6 to 20 months of age (2180 weeks) of the hens. Age group (month) differed significantly (p<0.05) in HHEPPW (Table 1). HHEPPD was
compared between same periods but expressed in weeks and periods differed significantly (p<0.05) (Table 2).
Ten thousands hen-housed layers laid 60341.66 eggs per week during 6-8 months of age and upon gradual
declination in the number of eggs per week HHEPPW averaged at 50165.83 at the age of 18-20 months.
HHEPPW was found to be significantly decreased with the progress of age in months of the hens giving a
pattern of 6-8 months = 9-11 months>12-14 months = 15-17 months>18-20 months (Table 1).
Table 1 : Mean HHEPPW in varying ages of hens
hens
Age of hens
(month)
6-8
9-11
12-14
15-17
18-20
Overall
HHEPPW

Table 2 : Mean HHEPPD in varying ages of

Mean HHEPPW

Age of hens
(week)
21-32
33-44
45-56
57-68
69-80
Overall HHEPPD

60341.66a
58312.50a
48000.00b
44450.00b
39725.00c
50165.83

Mean HHEPPD
6.0743a
5.9352a
5.0166b
4.7153c
4.3094d
5.2102

Table 3 : Mean difference (Tukey’s test) of HHEPPW between months
Age of hens (month)
I, J
I
6-8

9-11

12-14

Mean difference
(I-J)
J
9-11
12-14
15-17
18-20
6-8
12-14
15-17
18-20
6-8
9-11

2029.16
12341.66(*)
15891.66(*)
20616.66(*)
-2029.16
10312.50(*)
13862.50(*)
18587.50(*)
-12341.66(*)
-10312.50(*)

www.iosrjournals.org

Sig
.482
.000
.000
.000
.482
.000
.000
.000
.000
.000

78 | Page
Behaviour of laying curve in Babcock-380 brown commercial layers in Kelantan, Malaysia
15-17
18-20
6-8
9-11
12-14
18-20
6-8
9-11
12-14
15-17

15-17

18-20

3550.00(*)
8275.00(*)
-15891.67(*)
-13862.50(*)
-3550.00(*)
4725.00(*)
-20616.67(*)
-18587.50(*)
-8275.00(*)
-4725.00(*)

.045
.000
.000
.000
.045
.003
.000
.000
.000
.003

(*), significant
Table 2 and Table 4 show that HHEPPD during 21-32 weeks did not differ (p>0.05) from that in 33-44 weeks
means that HHEPPD was almost stable in these two periods.It shows that during 21-32 weeks average egg
production per hen per week figured at 6.0743 which is point of peak lay and then steadily declined until 80
weeks. The flock kept hold peak production until 44 weeks started from 21st week. HHEPPW and HHEPPD
behaved similarly ( Fig 1 and Fig 2) during these periods which means that mortality/culling of hens did not
affect egg production during early phase of laying since they are very few in number (Fig 5).The HHEPPD of
45 - 56 weeks and 57- 68 weeks also did not vary significanty (p>0.05). The regression lines in Fig 1 and Fig 2
represent HHEPPW and HHEPPD of the hens respectively from 21 to 80 weeks. Fig 1 explains that an increase
of 1 week in layer’s age will decrease 457.4 eggs/week in a hen-housed flock of 10000 hens. A 87.5% of the
total variation of the HHEPPW can be explained by the variation in the age (week). The value of Pearson
Correlation, -0.935 shows that there is exist strong negative relationship between HHEPPW with age (Table 5).
It is also supported by value of Pearson Correlation. Fig 2 suggests that for every week advancement in hen’s
age a decrease of 0.039 egg/hen/day does happen.The coefficient of determination ( R2 ) indicates that 83.8% of
the total variation of the HHEPPD is explained by the variation in the age (week). Not many literature are
available to compare present results. However, Zatter and Nofal (2009) demonstrated that polynomial regression
line suits best to predict the relationship between age of hens in week and the number of eggs laid in Mamourah
layers which is Y = -2.743 + 3.248x – 0.545x2 + 0.048x3 – 0.002x4 + 5.81266 E-05 x5 – 5.84542E-07x
6
(p<0.001). Hen-day percentage of the same strain was predicted by the same authors with the equation Y = 101.468 +133.369x – 36.033x2 + 3.997 x 3– 0.1604x4 (p<0.001).
Durrani (2012) reported age of point-of-lay and age of peak-of-lay of Hisex and Babcock strains of
layers in Pakistan to be 116.81, 136.80 and195.26, 204.40 days respectively (strain difference significant,
p<0.05) which are in line with the present findings. Current study reveals that peak production did exist between
148 and 308 days (21-44 weeks) and birds started laying at 17 weeks. Peak egg production percent (calculated
from Table 2) obtained in this investigation was 86.78 where as Durrani (2012) showed 91.85 and92.72 percent
peak egg production in Hisex and Babcock layers. This discrepancy might be because peak egg production in
terms of HHEPPD was reported in this case by a mean for a period of 3 months in which HHEPPD was in
decreasing trend. Zatter and Nofal (2009) showed that egg number and hen day percentage were significantly
(p<0.001) increased with the advancement of age to reach peak at the 5th week of laying and reached at peak at
14th week of production in Mamourah and Silver Montazah local strain in Egypt. In the current study laying
was started at 17th week and reached peak at 21st week which is in good agreement with the results of Zatter
and Nofal (2009) although strains are different. Age at point-of-lay, age at peak-of-lay and persistency of egg
production determine mostly the shape of the laying curve.
Table 4. Mean difference (Tukey’s test) of HHEPPD between weeks
Age of hens (weeks)
I, J

Mean
difference (I-J)

Sig

I

J

21-32

33-44
45-56

.1392

.791

1.0577(*)

.000

57-68

1.3591(*)

.000

69-80

.000

-.1392

.791

.9186(*)

.000

57-68
69-80
45-56

1.7649(*)

21-32
45-56

33-44

1.2199(*)
1.6258(*)

.000
.000

21-32

-1.0577(*)

.000

www.iosrjournals.org

79 | Page
Behaviour of laying curve in Babcock-380 brown commercial layers in Kelantan, Malaysia
33-44

.3013

.119

.7072(*)

.000

21-32
33-44

-1.3591(*)
-1.2199(*)

.000
.000

45-56

-.3013

.119

69-80

.4058(*)

.014

21-32

-1.7649(*)

.000

33-44

-1.6258(*)

.000

45-56
57-68

69-80

.000

69-80
57-68

-.9186(*)

57-68

-.7072(*)

.000

-.4058(*)

.014

HHEPPW

80000
60000

40000

y = -457.4x + 73268
R² = 0.875

20000
0
0

10

20

30

40

50

60

70

80

90

AGE (WEEK)

HHEPPD

Fig 1. HHEPPW against age of hens in week

7
6
5
4
3
2
1
0

y = -0.039x + 7.203
R² = 0.838

0

20

40

60

80

100

AGE (WEEK)

HHEPPW

Fig 2. HHEPPD against age of hen in week

60000
50000
40000
30000
20000
10000
0

y = 6.243x + 2662.
R² = 0.132

0

2000

4000
FEED (KG)

6000

8000

Fig 3. Relationship of feed consumed with HHEPPW
www.iosrjournals.org

80 | Page
Behaviour of laying curve in Babcock-380 brown commercial layers in Kelantan, Malaysia
Table 5. Pearson correlation matrix of HHEPPW with age of hen (week) and feed consumed (kg)
Pearson

HHEPPW
1

Age of hen (week)
-0.935**

Feed consumed (kg)
0.674**

Sig. (2-tailed)
N

HHEPPW
correlation

60

0.000
60

0.000
60

-0.935**

1

-0.560

0.000
60
0.674**

60
-0.560**

0.000
60
1

0.000
60

0.000
60

60

Age of hen

Pearson
correlation
Sig. (2-tailed)
N
Feed consumed
Pearson
Correlation
Sig. (2-tailed)
N

**p<0.01

HHEPPD

Feed consumption: Some 900 to 1100 kg feed was provided daily to the hen after first week of placement
although birds had access of 400-850 kg feed/day during first week. Fig. 4 shows that relationship between feed
intake and HHEPPD is positive but week. Variation in the feed intake might be due to some variation in the
house temperature and humidity ( Atta, 2010). However, feed intake positively and significantly (p<0.001)
affected HHEPPW (Table 5) and HHEPPD (Fig 4).
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0

y = 0.001x - 0.249
R² = 0.260
0

200

400

600

800

1000

1200

FEED (KG)
Fig 4. Relationship of feed consumed with HHEPPD
Coefficients of multiple determination and estimated value of β: When amount of feed consumed and age of
the hens were considered as contributing factors of HHEPPW in the regression model it was able to explain
about 91% of the variability (Table 6 ). The regression equation appears to be very useful for making prediction
since the value of R2 is close to 1.
Table 7 shows the estimated value of β, t and level of significance of the contributors in HHEPPW. Both the
independent variables such as amount of feed provided daily and age of the hens (month) contributed
significantly (p<0.001) in HHEPPW. The standard fitted multiple regression equation becomes 𝐻𝐻𝐸𝑃𝑃𝑊 =
35176.99 − 397.374𝐴 + 5.065𝐹where A and F stands for age of the hens in month and daily feed
conssumption in kg.It tells us that age in month linearly and negatively influenced HHEPPW but daily feed
intake positively influenced egg production measured in terms of HHEPPW and the t values for both the
independent factors are highly significant (p<0.001).
Table 6. Coefficient of multiple determination
Model
1

R
0.953a

R square
0.908

www.iosrjournals.org

Adj R square
0.905

81 | Page
Behaviour of laying curve in Babcock-380 brown commercial layers in Kelantan, Malaysia
Table 7. Estimated value of β
Unstandardized Coefficients

1 (constant)
Age (month)
Feed (kg)

B
35176.990
-397.374
5.065

CUMULATIVE
DEATH

Model

Standardized
Coefficients
Beta

SE
8464.270
23.684
1.117

1000
900
800
700
600
500
400
300
200
100
0

t

4.156
-16.778
4.535

-0.813
0.220

Sig.

0.000
0.000
0.000

y = 14.82x - 344.5
R² = 0.979

0

20

40

60

80

100

AGE (WEEK)
Fig 5. Cumulative mortality/culling of hens
Cumulative death/culling: Fig 5 denotes the cumulative death/culling of hens plotted against age of hens in
week. It interpretes that in a 10000 hen-housed flock 14.82 dead/culled birds are added in each week with
number of birds died/culled until previous week. The reason of death/culling was not available in the records. In
an infectious-disease-free flock cannibalism and vent pecking might be the major cause of death/culling.No
literature was found to compare this finding. However, in a large flock under normal condition death/culling rate
could be guessed from this curve.

References
[1].
[2].
[3].
[4].
[5].
[6].
[7].
[8].
[9].
[10].
[11].

Amin, M.R. 2012. Incipient production efficiency of Babcock-380 layers in a control house in Kelantan. J bioentrepreneurship 2:
22-27.
Amin, M.R. and Hamidi, E.N. 2013. Effect of phytase supplementation on the performance of Babcock-380 layers. J tropical
resource and sustainable science 1(1):36-41.
Anonym1 2013. Strain responses of laying hens to varying energy level. www2.ju.edu.jo....accessed on 2013.
Atta, M., Eljack, B.H. and El Obied, A.A. 2010. Use of mathematical modeling to evaluate production performance of some
commercial layer strains under Khartoum State conditions (Sudan) Animal science Journal 1(1): 19-22.
Chowdhury, S.R., Chowdhury, S.D. and Smith, T.K. 2002. Effect of dietary garlic on cholesterol metabolism in laying hens.
Poultry Science 81 (12):1856-1862.
Durrani, M.F. 2012. Egg production performance of commercial layers in Chakwal, Pakistan. Eprints.hec.gov.pk/460/1/347.html.htm. accessed on 12/12/2012.
Kaps, M. and Lamberson, W. 2009. Fixed effect one-way analysis of variance. In: Biostatistics for animal science. Cabi. pp 231271.
Singh, R, Cheng, K. M. and Silversides, F.G 2009. Production performance and egg quality of four strains of laying hens kept in
conventional cages and floor pens. Poultry science 88:256-264.
Singh, R.P. and Kumar, J. 1994. Biometrical methods in poultry breeding (First edi.). Kalyani publishers, India. pp
Silversides, F.G., Singh, R., Cheng, K.M. and Korver, D.R. 2012. Comparison of bones of 4 strains of laying hens kept in
conventional cages and floor pens. Poultry Science 91(1):1-7.
Verma, I.C. and Singh, K.S. 1997. Cost and return structure in layer farming. Indian J. Poultry science 32 (2):152-158.

www.iosrjournals.org

82 | Page

Más contenido relacionado

La actualidad más candente

Complex adaptation in Zea
Complex adaptation in ZeaComplex adaptation in Zea
Complex adaptation in Zeajrossibarra
 
New Tools for Genomic Selection of Livestock
New Tools for Genomic Selection of LivestockNew Tools for Genomic Selection of Livestock
New Tools for Genomic Selection of LivestockJohn B. Cole, Ph.D.
 
Introgression and the origin of maize in Mexico and the Southwest US
Introgression and the origin of maize in Mexico and the Southwest USIntrogression and the origin of maize in Mexico and the Southwest US
Introgression and the origin of maize in Mexico and the Southwest USjrossibarra
 
Genomic selection in small holder systems: Challenges and opportunities
Genomic selection in small holder systems: Challenges and opportunitiesGenomic selection in small holder systems: Challenges and opportunities
Genomic selection in small holder systems: Challenges and opportunitiesILRI
 
Genomic selection and systems biology – lessons from dairy cattle breeding
Genomic selection and systems biology – lessons from dairy cattle breedingGenomic selection and systems biology – lessons from dairy cattle breeding
Genomic selection and systems biology – lessons from dairy cattle breedingJohn B. Cole, Ph.D.
 
Sequence Characterization of Coding Regions of the Myostatin Gene (GDF8) from...
Sequence Characterization of Coding Regions of the Myostatin Gene (GDF8) from...Sequence Characterization of Coding Regions of the Myostatin Gene (GDF8) from...
Sequence Characterization of Coding Regions of the Myostatin Gene (GDF8) from...Wani Ahad
 
Beyond GWAS QTL Identification and Strategies to Increase Yield
Beyond GWAS QTL Identification and Strategies to Increase YieldBeyond GWAS QTL Identification and Strategies to Increase Yield
Beyond GWAS QTL Identification and Strategies to Increase YieldKate Barlow
 
Heat tolerance, real-life genomics and GxE issues
Heat tolerance, real-life genomics and GxE issuesHeat tolerance, real-life genomics and GxE issues
Heat tolerance, real-life genomics and GxE issuesILRI
 
Population genetics of maize domestication, adaptation, and improvement
Population genetics of maize domestication, adaptation, and improvementPopulation genetics of maize domestication, adaptation, and improvement
Population genetics of maize domestication, adaptation, and improvementjrossibarra
 
From contemporary comparison to genomic selection: Trends in the principles f...
From contemporary comparison to genomic selection: Trends in the principles f...From contemporary comparison to genomic selection: Trends in the principles f...
From contemporary comparison to genomic selection: Trends in the principles f...ILRI
 
Genomic Selection in Dairy Cattle
Genomic Selection in Dairy CattleGenomic Selection in Dairy Cattle
Genomic Selection in Dairy CattleJohn B. Cole, Ph.D.
 
Finding More Value With Genomic Testing
Finding More Value With Genomic TestingFinding More Value With Genomic Testing
Finding More Value With Genomic TestingDAIReXNET
 
Heritability estimates of, genetic and phenotypic correlations among some sel...
Heritability estimates of, genetic and phenotypic correlations among some sel...Heritability estimates of, genetic and phenotypic correlations among some sel...
Heritability estimates of, genetic and phenotypic correlations among some sel...Alexander Decker
 
Effect of regulating mating system on sexing of Rahmani lambing
Effect of regulating mating system on sexing of Rahmani lambing Effect of regulating mating system on sexing of Rahmani lambing
Effect of regulating mating system on sexing of Rahmani lambing Faisal A. Alshamiry
 

La actualidad más candente (19)

Toronto 2015
Toronto 2015Toronto 2015
Toronto 2015
 
Complex adaptation in Zea
Complex adaptation in ZeaComplex adaptation in Zea
Complex adaptation in Zea
 
New Tools for Genomic Selection of Livestock
New Tools for Genomic Selection of LivestockNew Tools for Genomic Selection of Livestock
New Tools for Genomic Selection of Livestock
 
Introgression and the origin of maize in Mexico and the Southwest US
Introgression and the origin of maize in Mexico and the Southwest USIntrogression and the origin of maize in Mexico and the Southwest US
Introgression and the origin of maize in Mexico and the Southwest US
 
Genomic selection in small holder systems: Challenges and opportunities
Genomic selection in small holder systems: Challenges and opportunitiesGenomic selection in small holder systems: Challenges and opportunities
Genomic selection in small holder systems: Challenges and opportunities
 
Seminário temp bov
Seminário temp bovSeminário temp bov
Seminário temp bov
 
Genomic selection and systems biology – lessons from dairy cattle breeding
Genomic selection and systems biology – lessons from dairy cattle breedingGenomic selection and systems biology – lessons from dairy cattle breeding
Genomic selection and systems biology – lessons from dairy cattle breeding
 
Sequence Characterization of Coding Regions of the Myostatin Gene (GDF8) from...
Sequence Characterization of Coding Regions of the Myostatin Gene (GDF8) from...Sequence Characterization of Coding Regions of the Myostatin Gene (GDF8) from...
Sequence Characterization of Coding Regions of the Myostatin Gene (GDF8) from...
 
Buck development
Buck developmentBuck development
Buck development
 
Beyond GWAS QTL Identification and Strategies to Increase Yield
Beyond GWAS QTL Identification and Strategies to Increase YieldBeyond GWAS QTL Identification and Strategies to Increase Yield
Beyond GWAS QTL Identification and Strategies to Increase Yield
 
Heat tolerance, real-life genomics and GxE issues
Heat tolerance, real-life genomics and GxE issuesHeat tolerance, real-life genomics and GxE issues
Heat tolerance, real-life genomics and GxE issues
 
Population genetics of maize domestication, adaptation, and improvement
Population genetics of maize domestication, adaptation, and improvementPopulation genetics of maize domestication, adaptation, and improvement
Population genetics of maize domestication, adaptation, and improvement
 
From contemporary comparison to genomic selection: Trends in the principles f...
From contemporary comparison to genomic selection: Trends in the principles f...From contemporary comparison to genomic selection: Trends in the principles f...
From contemporary comparison to genomic selection: Trends in the principles f...
 
Genomic Selection in Dairy Cattle
Genomic Selection in Dairy CattleGenomic Selection in Dairy Cattle
Genomic Selection in Dairy Cattle
 
Finding More Value With Genomic Testing
Finding More Value With Genomic TestingFinding More Value With Genomic Testing
Finding More Value With Genomic Testing
 
Heritability estimates of, genetic and phenotypic correlations among some sel...
Heritability estimates of, genetic and phenotypic correlations among some sel...Heritability estimates of, genetic and phenotypic correlations among some sel...
Heritability estimates of, genetic and phenotypic correlations among some sel...
 
Effect of regulating mating system on sexing of Rahmani lambing
Effect of regulating mating system on sexing of Rahmani lambing Effect of regulating mating system on sexing of Rahmani lambing
Effect of regulating mating system on sexing of Rahmani lambing
 
Advanced genetics
Advanced geneticsAdvanced genetics
Advanced genetics
 
Growth and performance of lambs and kids on pasture
Growth and performance of lambs and kids on pastureGrowth and performance of lambs and kids on pasture
Growth and performance of lambs and kids on pasture
 

Destacado

Design of Gabor Filter for Noise Reduction in Betel Vine leaves Disease Segme...
Design of Gabor Filter for Noise Reduction in Betel Vine leaves Disease Segme...Design of Gabor Filter for Noise Reduction in Betel Vine leaves Disease Segme...
Design of Gabor Filter for Noise Reduction in Betel Vine leaves Disease Segme...IOSR Journals
 
Numerical Simulation and Design Optimization of Intake and Spiral Case for Lo...
Numerical Simulation and Design Optimization of Intake and Spiral Case for Lo...Numerical Simulation and Design Optimization of Intake and Spiral Case for Lo...
Numerical Simulation and Design Optimization of Intake and Spiral Case for Lo...IOSR Journals
 
Modeling Object Oriented Applications by Using Dynamic Information for the I...
Modeling Object Oriented Applications by Using Dynamic  Information for the I...Modeling Object Oriented Applications by Using Dynamic  Information for the I...
Modeling Object Oriented Applications by Using Dynamic Information for the I...IOSR Journals
 
Spectrophotometric Determination of Drugs and Pharmaceuticals by Cerium (IV) ...
Spectrophotometric Determination of Drugs and Pharmaceuticals by Cerium (IV) ...Spectrophotometric Determination of Drugs and Pharmaceuticals by Cerium (IV) ...
Spectrophotometric Determination of Drugs and Pharmaceuticals by Cerium (IV) ...IOSR Journals
 
Phytochemical, cytotoxic, in-vitro antioxidant and anti-microbial investigati...
Phytochemical, cytotoxic, in-vitro antioxidant and anti-microbial investigati...Phytochemical, cytotoxic, in-vitro antioxidant and anti-microbial investigati...
Phytochemical, cytotoxic, in-vitro antioxidant and anti-microbial investigati...IOSR Journals
 
(𝛕𝐢, 𝛕𝐣)− RGB Closed Sets in Bitopological Spaces
(𝛕𝐢, 𝛕𝐣)− RGB Closed Sets in Bitopological Spaces(𝛕𝐢, 𝛕𝐣)− RGB Closed Sets in Bitopological Spaces
(𝛕𝐢, 𝛕𝐣)− RGB Closed Sets in Bitopological SpacesIOSR Journals
 
Antimicrobial Screening of Vanga Vennai and Mathan Thailam for Diabetic Foot ...
Antimicrobial Screening of Vanga Vennai and Mathan Thailam for Diabetic Foot ...Antimicrobial Screening of Vanga Vennai and Mathan Thailam for Diabetic Foot ...
Antimicrobial Screening of Vanga Vennai and Mathan Thailam for Diabetic Foot ...IOSR Journals
 
Cellular digitized map on Google Earth
Cellular digitized map on Google EarthCellular digitized map on Google Earth
Cellular digitized map on Google EarthIOSR Journals
 
A comparison between M/M/1 and M/D/1 queuing models to vehicular traffic atKa...
A comparison between M/M/1 and M/D/1 queuing models to vehicular traffic atKa...A comparison between M/M/1 and M/D/1 queuing models to vehicular traffic atKa...
A comparison between M/M/1 and M/D/1 queuing models to vehicular traffic atKa...IOSR Journals
 
Comparison and Supply Chain Optimization of Poultry Firm Using Mixed Integer ...
Comparison and Supply Chain Optimization of Poultry Firm Using Mixed Integer ...Comparison and Supply Chain Optimization of Poultry Firm Using Mixed Integer ...
Comparison and Supply Chain Optimization of Poultry Firm Using Mixed Integer ...IOSR Journals
 
Investigation of Thermal Insulation on Ice Coolers
Investigation of Thermal Insulation on Ice CoolersInvestigation of Thermal Insulation on Ice Coolers
Investigation of Thermal Insulation on Ice CoolersIOSR Journals
 
Applying a Model Based Testing for a Controller Design in Fault Detection, I...
Applying a Model Based Testing for a Controller Design in Fault  Detection, I...Applying a Model Based Testing for a Controller Design in Fault  Detection, I...
Applying a Model Based Testing for a Controller Design in Fault Detection, I...IOSR Journals
 
The study of semiconductor layer effect on underground cables with Time Domai...
The study of semiconductor layer effect on underground cables with Time Domai...The study of semiconductor layer effect on underground cables with Time Domai...
The study of semiconductor layer effect on underground cables with Time Domai...IOSR Journals
 

Destacado (20)

Design of Gabor Filter for Noise Reduction in Betel Vine leaves Disease Segme...
Design of Gabor Filter for Noise Reduction in Betel Vine leaves Disease Segme...Design of Gabor Filter for Noise Reduction in Betel Vine leaves Disease Segme...
Design of Gabor Filter for Noise Reduction in Betel Vine leaves Disease Segme...
 
H010223640
H010223640H010223640
H010223640
 
G1303034650
G1303034650G1303034650
G1303034650
 
H013116878
H013116878H013116878
H013116878
 
Numerical Simulation and Design Optimization of Intake and Spiral Case for Lo...
Numerical Simulation and Design Optimization of Intake and Spiral Case for Lo...Numerical Simulation and Design Optimization of Intake and Spiral Case for Lo...
Numerical Simulation and Design Optimization of Intake and Spiral Case for Lo...
 
Modeling Object Oriented Applications by Using Dynamic Information for the I...
Modeling Object Oriented Applications by Using Dynamic  Information for the I...Modeling Object Oriented Applications by Using Dynamic  Information for the I...
Modeling Object Oriented Applications by Using Dynamic Information for the I...
 
Spectrophotometric Determination of Drugs and Pharmaceuticals by Cerium (IV) ...
Spectrophotometric Determination of Drugs and Pharmaceuticals by Cerium (IV) ...Spectrophotometric Determination of Drugs and Pharmaceuticals by Cerium (IV) ...
Spectrophotometric Determination of Drugs and Pharmaceuticals by Cerium (IV) ...
 
F0562732
F0562732F0562732
F0562732
 
Phytochemical, cytotoxic, in-vitro antioxidant and anti-microbial investigati...
Phytochemical, cytotoxic, in-vitro antioxidant and anti-microbial investigati...Phytochemical, cytotoxic, in-vitro antioxidant and anti-microbial investigati...
Phytochemical, cytotoxic, in-vitro antioxidant and anti-microbial investigati...
 
(𝛕𝐢, 𝛕𝐣)− RGB Closed Sets in Bitopological Spaces
(𝛕𝐢, 𝛕𝐣)− RGB Closed Sets in Bitopological Spaces(𝛕𝐢, 𝛕𝐣)− RGB Closed Sets in Bitopological Spaces
(𝛕𝐢, 𝛕𝐣)− RGB Closed Sets in Bitopological Spaces
 
L010218691
L010218691L010218691
L010218691
 
Antimicrobial Screening of Vanga Vennai and Mathan Thailam for Diabetic Foot ...
Antimicrobial Screening of Vanga Vennai and Mathan Thailam for Diabetic Foot ...Antimicrobial Screening of Vanga Vennai and Mathan Thailam for Diabetic Foot ...
Antimicrobial Screening of Vanga Vennai and Mathan Thailam for Diabetic Foot ...
 
Cellular digitized map on Google Earth
Cellular digitized map on Google EarthCellular digitized map on Google Earth
Cellular digitized map on Google Earth
 
E010232227
E010232227E010232227
E010232227
 
A comparison between M/M/1 and M/D/1 queuing models to vehicular traffic atKa...
A comparison between M/M/1 and M/D/1 queuing models to vehicular traffic atKa...A comparison between M/M/1 and M/D/1 queuing models to vehicular traffic atKa...
A comparison between M/M/1 and M/D/1 queuing models to vehicular traffic atKa...
 
Comparison and Supply Chain Optimization of Poultry Firm Using Mixed Integer ...
Comparison and Supply Chain Optimization of Poultry Firm Using Mixed Integer ...Comparison and Supply Chain Optimization of Poultry Firm Using Mixed Integer ...
Comparison and Supply Chain Optimization of Poultry Firm Using Mixed Integer ...
 
H01064759
H01064759H01064759
H01064759
 
Investigation of Thermal Insulation on Ice Coolers
Investigation of Thermal Insulation on Ice CoolersInvestigation of Thermal Insulation on Ice Coolers
Investigation of Thermal Insulation on Ice Coolers
 
Applying a Model Based Testing for a Controller Design in Fault Detection, I...
Applying a Model Based Testing for a Controller Design in Fault  Detection, I...Applying a Model Based Testing for a Controller Design in Fault  Detection, I...
Applying a Model Based Testing for a Controller Design in Fault Detection, I...
 
The study of semiconductor layer effect on underground cables with Time Domai...
The study of semiconductor layer effect on underground cables with Time Domai...The study of semiconductor layer effect on underground cables with Time Domai...
The study of semiconductor layer effect on underground cables with Time Domai...
 

Similar a Evaluation of long-term vegetation trends for northeastern of Iraq: Mosul, Kirkuk and Salah al-Din

Effect of Age of Spawned Catfish (Clarias Gariepinus) Broodstock on Quantity ...
Effect of Age of Spawned Catfish (Clarias Gariepinus) Broodstock on Quantity ...Effect of Age of Spawned Catfish (Clarias Gariepinus) Broodstock on Quantity ...
Effect of Age of Spawned Catfish (Clarias Gariepinus) Broodstock on Quantity ...IOSR Journals
 
Assessment of productive and reproductive performances of cross
Assessment of productive and reproductive performances of crossAssessment of productive and reproductive performances of cross
Assessment of productive and reproductive performances of crossAlexander Decker
 
Assessment of productive and reproductive performances of cross
Assessment of productive and reproductive performances of crossAssessment of productive and reproductive performances of cross
Assessment of productive and reproductive performances of crossAlexander Decker
 
Proceeding of FAVA: Reproductive Efficiency of Brahman Cross Cattle Using ar...
Proceeding of FAVA:  Reproductive Efficiency of Brahman Cross Cattle Using ar...Proceeding of FAVA:  Reproductive Efficiency of Brahman Cross Cattle Using ar...
Proceeding of FAVA: Reproductive Efficiency of Brahman Cross Cattle Using ar...anbiocore
 
Evaluation of the Productive and Reproductive Performance of Pigeon in Select...
Evaluation of the Productive and Reproductive Performance of Pigeon in Select...Evaluation of the Productive and Reproductive Performance of Pigeon in Select...
Evaluation of the Productive and Reproductive Performance of Pigeon in Select...semualkaira
 
Evaluation of the Productive and Reproductive Performance of Pigeon in Select...
Evaluation of the Productive and Reproductive Performance of Pigeon in Select...Evaluation of the Productive and Reproductive Performance of Pigeon in Select...
Evaluation of the Productive and Reproductive Performance of Pigeon in Select...semualkaira
 
Evaluation of the Productive and Reproductive Performance of Pigeon in Select...
Evaluation of the Productive and Reproductive Performance of Pigeon in Select...Evaluation of the Productive and Reproductive Performance of Pigeon in Select...
Evaluation of the Productive and Reproductive Performance of Pigeon in Select...semualkaira
 
Egg quality characteristics and phenotypic correlations among egg quality tra...
Egg quality characteristics and phenotypic correlations among egg quality tra...Egg quality characteristics and phenotypic correlations among egg quality tra...
Egg quality characteristics and phenotypic correlations among egg quality tra...Agriculture Journal IJOEAR
 
Comparative Study on Productive and Reproductive Performances of Indigenous, ...
Comparative Study on Productive and Reproductive Performances of Indigenous, ...Comparative Study on Productive and Reproductive Performances of Indigenous, ...
Comparative Study on Productive and Reproductive Performances of Indigenous, ...Premier Publishers
 
Nutritive evaluation of different energy sources with Maxigrain® enzyme in br...
Nutritive evaluation of different energy sources with Maxigrain® enzyme in br...Nutritive evaluation of different energy sources with Maxigrain® enzyme in br...
Nutritive evaluation of different energy sources with Maxigrain® enzyme in br...Journal of Research in Biology
 
Nutritive evaluation of different energy sources with Maxigrain® enzyme in br...
Nutritive evaluation of different energy sources with Maxigrain® enzyme in br...Nutritive evaluation of different energy sources with Maxigrain® enzyme in br...
Nutritive evaluation of different energy sources with Maxigrain® enzyme in br...Journal of Research in Biology
 
Effect of Potato Meal on Broiler Production
Effect of Potato Meal on Broiler ProductionEffect of Potato Meal on Broiler Production
Effect of Potato Meal on Broiler ProductionNazmus Sakib
 
Effect of potato (Solanum tuberosum) meal on broiler production
Effect of potato (Solanum tuberosum) meal on broiler productionEffect of potato (Solanum tuberosum) meal on broiler production
Effect of potato (Solanum tuberosum) meal on broiler productionNazmus Sakib
 
Poultry Industry Kerala Scenario
Poultry Industry Kerala ScenarioPoultry Industry Kerala Scenario
Poultry Industry Kerala ScenarioDeepa Menon
 
Reproductive performance of different goat breeds in Malaysia
Reproductive performance of different goat breeds in MalaysiaReproductive performance of different goat breeds in Malaysia
Reproductive performance of different goat breeds in MalaysiaMohammed Muayad TA
 

Similar a Evaluation of long-term vegetation trends for northeastern of Iraq: Mosul, Kirkuk and Salah al-Din (20)

Effect of Age of Spawned Catfish (Clarias Gariepinus) Broodstock on Quantity ...
Effect of Age of Spawned Catfish (Clarias Gariepinus) Broodstock on Quantity ...Effect of Age of Spawned Catfish (Clarias Gariepinus) Broodstock on Quantity ...
Effect of Age of Spawned Catfish (Clarias Gariepinus) Broodstock on Quantity ...
 
Paper 5 (eleazar c. nwogu)
Paper 5 (eleazar c. nwogu)Paper 5 (eleazar c. nwogu)
Paper 5 (eleazar c. nwogu)
 
EFFECTS OF LAYING KADHAKNATH HEN SERUM AND ANTI-PROLACTIN MEDICATION [BROMOCR...
EFFECTS OF LAYING KADHAKNATH HEN SERUM AND ANTI-PROLACTIN MEDICATION [BROMOCR...EFFECTS OF LAYING KADHAKNATH HEN SERUM AND ANTI-PROLACTIN MEDICATION [BROMOCR...
EFFECTS OF LAYING KADHAKNATH HEN SERUM AND ANTI-PROLACTIN MEDICATION [BROMOCR...
 
Assessment of productive and reproductive performances of cross
Assessment of productive and reproductive performances of crossAssessment of productive and reproductive performances of cross
Assessment of productive and reproductive performances of cross
 
Assessment of productive and reproductive performances of cross
Assessment of productive and reproductive performances of crossAssessment of productive and reproductive performances of cross
Assessment of productive and reproductive performances of cross
 
Research on backyard poultry on the livelihood and nutritional security of BP...
Research on backyard poultry on the livelihood and nutritional security of BP...Research on backyard poultry on the livelihood and nutritional security of BP...
Research on backyard poultry on the livelihood and nutritional security of BP...
 
Duck n quail
Duck n quailDuck n quail
Duck n quail
 
Proceeding of FAVA: Reproductive Efficiency of Brahman Cross Cattle Using ar...
Proceeding of FAVA:  Reproductive Efficiency of Brahman Cross Cattle Using ar...Proceeding of FAVA:  Reproductive Efficiency of Brahman Cross Cattle Using ar...
Proceeding of FAVA: Reproductive Efficiency of Brahman Cross Cattle Using ar...
 
Evaluation of the Productive and Reproductive Performance of Pigeon in Select...
Evaluation of the Productive and Reproductive Performance of Pigeon in Select...Evaluation of the Productive and Reproductive Performance of Pigeon in Select...
Evaluation of the Productive and Reproductive Performance of Pigeon in Select...
 
Evaluation of the Productive and Reproductive Performance of Pigeon in Select...
Evaluation of the Productive and Reproductive Performance of Pigeon in Select...Evaluation of the Productive and Reproductive Performance of Pigeon in Select...
Evaluation of the Productive and Reproductive Performance of Pigeon in Select...
 
Evaluation of the Productive and Reproductive Performance of Pigeon in Select...
Evaluation of the Productive and Reproductive Performance of Pigeon in Select...Evaluation of the Productive and Reproductive Performance of Pigeon in Select...
Evaluation of the Productive and Reproductive Performance of Pigeon in Select...
 
Egg quality characteristics and phenotypic correlations among egg quality tra...
Egg quality characteristics and phenotypic correlations among egg quality tra...Egg quality characteristics and phenotypic correlations among egg quality tra...
Egg quality characteristics and phenotypic correlations among egg quality tra...
 
Comparative Study on Productive and Reproductive Performances of Indigenous, ...
Comparative Study on Productive and Reproductive Performances of Indigenous, ...Comparative Study on Productive and Reproductive Performances of Indigenous, ...
Comparative Study on Productive and Reproductive Performances of Indigenous, ...
 
Nutritive evaluation of different energy sources with Maxigrain® enzyme in br...
Nutritive evaluation of different energy sources with Maxigrain® enzyme in br...Nutritive evaluation of different energy sources with Maxigrain® enzyme in br...
Nutritive evaluation of different energy sources with Maxigrain® enzyme in br...
 
Nutritive evaluation of different energy sources with Maxigrain® enzyme in br...
Nutritive evaluation of different energy sources with Maxigrain® enzyme in br...Nutritive evaluation of different energy sources with Maxigrain® enzyme in br...
Nutritive evaluation of different energy sources with Maxigrain® enzyme in br...
 
Reproductive performance
Reproductive  performanceReproductive  performance
Reproductive performance
 
Effect of Potato Meal on Broiler Production
Effect of Potato Meal on Broiler ProductionEffect of Potato Meal on Broiler Production
Effect of Potato Meal on Broiler Production
 
Effect of potato (Solanum tuberosum) meal on broiler production
Effect of potato (Solanum tuberosum) meal on broiler productionEffect of potato (Solanum tuberosum) meal on broiler production
Effect of potato (Solanum tuberosum) meal on broiler production
 
Poultry Industry Kerala Scenario
Poultry Industry Kerala ScenarioPoultry Industry Kerala Scenario
Poultry Industry Kerala Scenario
 
Reproductive performance of different goat breeds in Malaysia
Reproductive performance of different goat breeds in MalaysiaReproductive performance of different goat breeds in Malaysia
Reproductive performance of different goat breeds in Malaysia
 

Más de IOSR Journals (20)

A011140104
A011140104A011140104
A011140104
 
M0111397100
M0111397100M0111397100
M0111397100
 
L011138596
L011138596L011138596
L011138596
 
K011138084
K011138084K011138084
K011138084
 
J011137479
J011137479J011137479
J011137479
 
I011136673
I011136673I011136673
I011136673
 
G011134454
G011134454G011134454
G011134454
 
H011135565
H011135565H011135565
H011135565
 
F011134043
F011134043F011134043
F011134043
 
E011133639
E011133639E011133639
E011133639
 
D011132635
D011132635D011132635
D011132635
 
C011131925
C011131925C011131925
C011131925
 
B011130918
B011130918B011130918
B011130918
 
A011130108
A011130108A011130108
A011130108
 
I011125160
I011125160I011125160
I011125160
 
H011124050
H011124050H011124050
H011124050
 
G011123539
G011123539G011123539
G011123539
 
F011123134
F011123134F011123134
F011123134
 
E011122530
E011122530E011122530
E011122530
 
D011121524
D011121524D011121524
D011121524
 

Último

DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenHervé Boutemy
 
CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):comworks
 
Take control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteTake control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteDianaGray10
 
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsRizwan Syed
 
Artificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptxArtificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptxhariprasad279825
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii SoldatenkoFwdays
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningLars Bell
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfAddepto
 
How to write a Business Continuity Plan
How to write a Business Continuity PlanHow to write a Business Continuity Plan
How to write a Business Continuity PlanDatabarracks
 
Story boards and shot lists for my a level piece
Story boards and shot lists for my a level pieceStory boards and shot lists for my a level piece
Story boards and shot lists for my a level piececharlottematthew16
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebUiPathCommunity
 
From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .Alan Dix
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr BaganFwdays
 
Vertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsVertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsMiki Katsuragi
 
What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024Stephanie Beckett
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024Lorenzo Miniero
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfAlex Barbosa Coqueiro
 

Último (20)

DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache Maven
 
CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):
 
Take control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteTake control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test Suite
 
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL Certs
 
Artificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptxArtificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptx
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine Tuning
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdf
 
How to write a Business Continuity Plan
How to write a Business Continuity PlanHow to write a Business Continuity Plan
How to write a Business Continuity Plan
 
Story boards and shot lists for my a level piece
Story boards and shot lists for my a level pieceStory boards and shot lists for my a level piece
Story boards and shot lists for my a level piece
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio Web
 
From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan
 
Vertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsVertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering Tips
 
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptxE-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
 
What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdf
 

Evaluation of long-term vegetation trends for northeastern of Iraq: Mosul, Kirkuk and Salah al-Din

  • 1. IOSR Journal of Agriculture and Veterinary Science (IOSR-JAVS) e-ISSN: 2319-2380, p-ISSN: 2319-2372. Volume 5, Issue 2 (Sep. - Oct. 2013), PP 77-82 www.iosrjournals.org Behaviour of laying curve in Babcock-380 brown commercial layers in Kelantan, Malaysia 1 M R Amin*1 and S A Nawawi2 Faculty of Agro Based Industry 2Faculty of Earth Science University Malaysia Kelantan (Campus Jeli), 17600 Jeli, Kelantan, Malaysia ruhulaminbau1961@gmail.com or ruhulamin@umk.edu.my Abstract: Commercial layers start laying at 18-20 weeks of age and continues until 72 weeks under cost-effective operation. Age of the hens, mortality rate, feed and environmental conditions determine the persistancy of production as reflected in the laying curve. In this experiment laying performance of 10000 hen-housed Babcock-380 brown commercial layers housed in Kelantan, Malaysia was assessed in mathematical model using hen-house and hen-day measurements. It revealed that hens reached at peak lay at 21 weeks of age and maintained a stability until 44 weeks. Birds egg laying performance gradually declined with progress in age till 80 weeks. Y= 35176.99 – 397.374 A + 5.065 F gave the best fitted regression line (adj R2 = 0.905) for hen-housed egg production per week (A=age of hens in week and F= Kg feed consumed/day). A 87.5% of the total variation in hen-housed egg production could be explained only by age of hens but when feed consumption was added in the model age and feed consumption together explained 90.5% variabilty. For every week advancement in hen’s age (week) a decrease of 0.039 eggs/hen/day was predicted (adj R2 = 83.8%). In this 10000 henhoused flock mortality/culling averaged at 14.82/week. Key words: Babcock-380, hen-house egg production, hen-day egg production,mathematical model, laying curve I. Introduction Commercial egg production with hybrid chicken is a very delicate bioentrepreneurship all over the world. There are currently only few number of poultry breeding companies in the world owned pure lines to make available grand parent and parent stocks to the breeder farm. Modern strains of hybrid layers are produced by the local breeder farm/hatcheries using parent stocks. Lohman (white and brown), H&N white [Singh et al., 2009, Silverside et al., 2012], Hy-Line (white and brown), Shaver (Anonym1, 2013), Starcross, Babcock (Chowdhury et al., 2002, Durraniet al., 2012), Hisex (durrani, 2012) are the commonest hybrid strains of layer chicken. According to Verma and Singh (1997) 87.33% contribution to gross return in layer enterprize comes from eggs alone. Egg production by the hens in the laying cycle is influenced by manifold factors such as strain, feed, survival rate and health of hens, management practices, age at point-of-lay, age at peak-of-lay (Durrani et al., 2012). In a given flock egg production in a particular day of laying cycle depends on number of hens in the cohort, stage of laying phase, hen health, feed, environmental condition such as temperature, humidity, light, molting etc. Modern hybrid layers start laying at 18-20 weeks of age and continue until 72 weeks or little longer cost-effectively (Amin and Hamidi, 2013). Determination of laying performance on individual hen basis involves huge labour and cost. Therefore, flock efficiency is the most preferential approach for measuring laying efficiency. ‘Hen house egg production’ and ‘hen day egg production’are the two widely used method of measuring flock laying efficiency (Singh and Kumar, 1994). Stage of laying is a great determinant of number of eggs laid in a given day in the laying cycle and therefore, it contributes greatly in the shape of laying curve. In ideal condition, standard laying curve can predict the number of eggs to be laid out of a given flock size. Amin (2012) demonstrated an incipient hen-day part laying curve with fitted quadraic equation (Y = 0.0483t 2 – 3.904, t= age of hen in day; R2 = 0.807, p<0.001) for Babcock brown 380 layers in Kelantan, Malaysia. Zattar and Nofal (2009) showed that relationship between egg number and variable age of hens in weeks can be best represented in polynomial curve for Memourah (0.868≤ adj R2≤1.0) and Montazah (0.992≤adj R2≤1.0), the two locally developed layer strain of chicken in Egypt. Atta et al. (2010) concluded that Wood equation (1967) can be used with sufficient precision to predict whole cycle laying performance based on part egg production record in Hyline W98 and Lohman SLS hybrid layers.Nevertheless, standard fitted regression line on laying performance for common commercial hybrid layersis still inadequately available in literature. The present investigation, therefore, aims at developing a standard mathematical model for Babcock brown 380 layer hens in Kelantan, Malaysia along with some other related measurements. II. Materials and Methods Data for this study were extracted from Taklimat Project Ternakan Ayam Penelor Tertutup – a government private ownership layer farm in Kuala Balah, Kelantan, Malaysia. The flock of Babcock- 380 brown layers consisted of 10,000 pullets placed in the laying house at the age of 17 weeks in 2010.The pullets started laying in the following week and continued until 80 weeks of age. From 17-20 weeks of age daily egg www.iosrjournals.org 77 | Page
  • 2. Behaviour of laying curve in Babcock-380 brown commercial layers in Kelantan, Malaysia production quickly rose from 60 to 6300 and then became almost stable and took a regular shape of trend.That’s why 21 weeks of age was considered as the begining for analysis of data.Furthermore, eggs laid until 20 weeks were of smaller size and showed higher frequency of abnormality. Daily records were kept on number of hens died/culled, number of eggs laid, amount of feed consumed on flock basis.Birds were provided with commercial layer mash diet at the rate of 400 kg to 850 kg/day during first week of the placement in the laying house and thereafter 900 kg to 1100 kg/day until last day. Variation in the amount of feed provided was independent of the number of hens in the house rather was depended on voluntary intake by the hens. In order for quantifying the efficiency of the layers, the following measurements were made (Amin, 2012) 𝑁𝑜 𝑜𝑓 𝑒𝑔𝑔𝑠 𝑙𝑎𝑖𝑑 𝑖𝑛 𝑎 𝑔𝑖𝑣𝑒𝑛 𝑤𝑒𝑒𝑘 i. Hen house egg production per week (HHEPPW)= 𝑁𝑜 ii. Hen housed egg production per cent per day (HHEPPD) = 𝑜𝑓 𝑕𝑒𝑛𝑠 𝑎𝑡 𝑡𝑕𝑒 𝑏𝑒𝑔𝑖𝑛𝑖𝑛𝑔 𝑜𝑓 𝑡𝑕𝑒 𝑤𝑒𝑒𝑘 𝑁𝑜 𝑜𝑓 𝑒𝑔𝑔𝑠 𝑙𝑎𝑖𝑑 𝑖𝑛 𝑎 𝑔𝑖𝑣𝑒𝑛 𝑑𝑎𝑦 𝑁𝑜 𝑜𝑓 𝑕𝑒𝑛𝑠 𝑜𝑛 𝑡𝑕𝑎𝑡 𝑑𝑎𝑦 × 100 Hen housed egg production per week indicates number of eggs laid per bird in a given week calculated based on the number of hens placed at the begining of the week. So mortality/culling of hens within the period affects HHEPPW. On the contrary, hen housed egg production per cent per day (HHEPPD) expresses average laying performance of a hen in the flock in a particular day based on the exact number of hens exists on the particular day. So mortality or culling does not affect HHEPPD but it includes birds that did not lay for any reason. Statistical analyses were accomplished with the help of SPSS 11.5 statistical software. HHEPPW was compared between a duration of every 3 months using one way ANOVA and then Tukeys test was performed for multiple comparison (Kaps and Lamberson, 2009). So each 3 months laying duration (from 6 month to 20 month) was splitted into equal 5 periods. The HHEPPW and HHEPPD were regressed against age of hens in week to see the pattern of changes of egg production with progress of age. Age of hens and feed consumption were incorporated in the mathematical model to estimate their contribution in egg production. III. Results and Discussion Egg Production: HHEPPW was compared between periods of every 3 month from 6 to 20 months of age (2180 weeks) of the hens. Age group (month) differed significantly (p<0.05) in HHEPPW (Table 1). HHEPPD was compared between same periods but expressed in weeks and periods differed significantly (p<0.05) (Table 2). Ten thousands hen-housed layers laid 60341.66 eggs per week during 6-8 months of age and upon gradual declination in the number of eggs per week HHEPPW averaged at 50165.83 at the age of 18-20 months. HHEPPW was found to be significantly decreased with the progress of age in months of the hens giving a pattern of 6-8 months = 9-11 months>12-14 months = 15-17 months>18-20 months (Table 1). Table 1 : Mean HHEPPW in varying ages of hens hens Age of hens (month) 6-8 9-11 12-14 15-17 18-20 Overall HHEPPW Table 2 : Mean HHEPPD in varying ages of Mean HHEPPW Age of hens (week) 21-32 33-44 45-56 57-68 69-80 Overall HHEPPD 60341.66a 58312.50a 48000.00b 44450.00b 39725.00c 50165.83 Mean HHEPPD 6.0743a 5.9352a 5.0166b 4.7153c 4.3094d 5.2102 Table 3 : Mean difference (Tukey’s test) of HHEPPW between months Age of hens (month) I, J I 6-8 9-11 12-14 Mean difference (I-J) J 9-11 12-14 15-17 18-20 6-8 12-14 15-17 18-20 6-8 9-11 2029.16 12341.66(*) 15891.66(*) 20616.66(*) -2029.16 10312.50(*) 13862.50(*) 18587.50(*) -12341.66(*) -10312.50(*) www.iosrjournals.org Sig .482 .000 .000 .000 .482 .000 .000 .000 .000 .000 78 | Page
  • 3. Behaviour of laying curve in Babcock-380 brown commercial layers in Kelantan, Malaysia 15-17 18-20 6-8 9-11 12-14 18-20 6-8 9-11 12-14 15-17 15-17 18-20 3550.00(*) 8275.00(*) -15891.67(*) -13862.50(*) -3550.00(*) 4725.00(*) -20616.67(*) -18587.50(*) -8275.00(*) -4725.00(*) .045 .000 .000 .000 .045 .003 .000 .000 .000 .003 (*), significant Table 2 and Table 4 show that HHEPPD during 21-32 weeks did not differ (p>0.05) from that in 33-44 weeks means that HHEPPD was almost stable in these two periods.It shows that during 21-32 weeks average egg production per hen per week figured at 6.0743 which is point of peak lay and then steadily declined until 80 weeks. The flock kept hold peak production until 44 weeks started from 21st week. HHEPPW and HHEPPD behaved similarly ( Fig 1 and Fig 2) during these periods which means that mortality/culling of hens did not affect egg production during early phase of laying since they are very few in number (Fig 5).The HHEPPD of 45 - 56 weeks and 57- 68 weeks also did not vary significanty (p>0.05). The regression lines in Fig 1 and Fig 2 represent HHEPPW and HHEPPD of the hens respectively from 21 to 80 weeks. Fig 1 explains that an increase of 1 week in layer’s age will decrease 457.4 eggs/week in a hen-housed flock of 10000 hens. A 87.5% of the total variation of the HHEPPW can be explained by the variation in the age (week). The value of Pearson Correlation, -0.935 shows that there is exist strong negative relationship between HHEPPW with age (Table 5). It is also supported by value of Pearson Correlation. Fig 2 suggests that for every week advancement in hen’s age a decrease of 0.039 egg/hen/day does happen.The coefficient of determination ( R2 ) indicates that 83.8% of the total variation of the HHEPPD is explained by the variation in the age (week). Not many literature are available to compare present results. However, Zatter and Nofal (2009) demonstrated that polynomial regression line suits best to predict the relationship between age of hens in week and the number of eggs laid in Mamourah layers which is Y = -2.743 + 3.248x – 0.545x2 + 0.048x3 – 0.002x4 + 5.81266 E-05 x5 – 5.84542E-07x 6 (p<0.001). Hen-day percentage of the same strain was predicted by the same authors with the equation Y = 101.468 +133.369x – 36.033x2 + 3.997 x 3– 0.1604x4 (p<0.001). Durrani (2012) reported age of point-of-lay and age of peak-of-lay of Hisex and Babcock strains of layers in Pakistan to be 116.81, 136.80 and195.26, 204.40 days respectively (strain difference significant, p<0.05) which are in line with the present findings. Current study reveals that peak production did exist between 148 and 308 days (21-44 weeks) and birds started laying at 17 weeks. Peak egg production percent (calculated from Table 2) obtained in this investigation was 86.78 where as Durrani (2012) showed 91.85 and92.72 percent peak egg production in Hisex and Babcock layers. This discrepancy might be because peak egg production in terms of HHEPPD was reported in this case by a mean for a period of 3 months in which HHEPPD was in decreasing trend. Zatter and Nofal (2009) showed that egg number and hen day percentage were significantly (p<0.001) increased with the advancement of age to reach peak at the 5th week of laying and reached at peak at 14th week of production in Mamourah and Silver Montazah local strain in Egypt. In the current study laying was started at 17th week and reached peak at 21st week which is in good agreement with the results of Zatter and Nofal (2009) although strains are different. Age at point-of-lay, age at peak-of-lay and persistency of egg production determine mostly the shape of the laying curve. Table 4. Mean difference (Tukey’s test) of HHEPPD between weeks Age of hens (weeks) I, J Mean difference (I-J) Sig I J 21-32 33-44 45-56 .1392 .791 1.0577(*) .000 57-68 1.3591(*) .000 69-80 .000 -.1392 .791 .9186(*) .000 57-68 69-80 45-56 1.7649(*) 21-32 45-56 33-44 1.2199(*) 1.6258(*) .000 .000 21-32 -1.0577(*) .000 www.iosrjournals.org 79 | Page
  • 4. Behaviour of laying curve in Babcock-380 brown commercial layers in Kelantan, Malaysia 33-44 .3013 .119 .7072(*) .000 21-32 33-44 -1.3591(*) -1.2199(*) .000 .000 45-56 -.3013 .119 69-80 .4058(*) .014 21-32 -1.7649(*) .000 33-44 -1.6258(*) .000 45-56 57-68 69-80 .000 69-80 57-68 -.9186(*) 57-68 -.7072(*) .000 -.4058(*) .014 HHEPPW 80000 60000 40000 y = -457.4x + 73268 R² = 0.875 20000 0 0 10 20 30 40 50 60 70 80 90 AGE (WEEK) HHEPPD Fig 1. HHEPPW against age of hens in week 7 6 5 4 3 2 1 0 y = -0.039x + 7.203 R² = 0.838 0 20 40 60 80 100 AGE (WEEK) HHEPPW Fig 2. HHEPPD against age of hen in week 60000 50000 40000 30000 20000 10000 0 y = 6.243x + 2662. R² = 0.132 0 2000 4000 FEED (KG) 6000 8000 Fig 3. Relationship of feed consumed with HHEPPW www.iosrjournals.org 80 | Page
  • 5. Behaviour of laying curve in Babcock-380 brown commercial layers in Kelantan, Malaysia Table 5. Pearson correlation matrix of HHEPPW with age of hen (week) and feed consumed (kg) Pearson HHEPPW 1 Age of hen (week) -0.935** Feed consumed (kg) 0.674** Sig. (2-tailed) N HHEPPW correlation 60 0.000 60 0.000 60 -0.935** 1 -0.560 0.000 60 0.674** 60 -0.560** 0.000 60 1 0.000 60 0.000 60 60 Age of hen Pearson correlation Sig. (2-tailed) N Feed consumed Pearson Correlation Sig. (2-tailed) N **p<0.01 HHEPPD Feed consumption: Some 900 to 1100 kg feed was provided daily to the hen after first week of placement although birds had access of 400-850 kg feed/day during first week. Fig. 4 shows that relationship between feed intake and HHEPPD is positive but week. Variation in the feed intake might be due to some variation in the house temperature and humidity ( Atta, 2010). However, feed intake positively and significantly (p<0.001) affected HHEPPW (Table 5) and HHEPPD (Fig 4). 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 y = 0.001x - 0.249 R² = 0.260 0 200 400 600 800 1000 1200 FEED (KG) Fig 4. Relationship of feed consumed with HHEPPD Coefficients of multiple determination and estimated value of β: When amount of feed consumed and age of the hens were considered as contributing factors of HHEPPW in the regression model it was able to explain about 91% of the variability (Table 6 ). The regression equation appears to be very useful for making prediction since the value of R2 is close to 1. Table 7 shows the estimated value of β, t and level of significance of the contributors in HHEPPW. Both the independent variables such as amount of feed provided daily and age of the hens (month) contributed significantly (p<0.001) in HHEPPW. The standard fitted multiple regression equation becomes 𝐻𝐻𝐸𝑃𝑃𝑊 = 35176.99 − 397.374𝐴 + 5.065𝐹where A and F stands for age of the hens in month and daily feed conssumption in kg.It tells us that age in month linearly and negatively influenced HHEPPW but daily feed intake positively influenced egg production measured in terms of HHEPPW and the t values for both the independent factors are highly significant (p<0.001). Table 6. Coefficient of multiple determination Model 1 R 0.953a R square 0.908 www.iosrjournals.org Adj R square 0.905 81 | Page
  • 6. Behaviour of laying curve in Babcock-380 brown commercial layers in Kelantan, Malaysia Table 7. Estimated value of β Unstandardized Coefficients 1 (constant) Age (month) Feed (kg) B 35176.990 -397.374 5.065 CUMULATIVE DEATH Model Standardized Coefficients Beta SE 8464.270 23.684 1.117 1000 900 800 700 600 500 400 300 200 100 0 t 4.156 -16.778 4.535 -0.813 0.220 Sig. 0.000 0.000 0.000 y = 14.82x - 344.5 R² = 0.979 0 20 40 60 80 100 AGE (WEEK) Fig 5. Cumulative mortality/culling of hens Cumulative death/culling: Fig 5 denotes the cumulative death/culling of hens plotted against age of hens in week. It interpretes that in a 10000 hen-housed flock 14.82 dead/culled birds are added in each week with number of birds died/culled until previous week. The reason of death/culling was not available in the records. In an infectious-disease-free flock cannibalism and vent pecking might be the major cause of death/culling.No literature was found to compare this finding. However, in a large flock under normal condition death/culling rate could be guessed from this curve. References [1]. [2]. [3]. [4]. [5]. [6]. [7]. [8]. [9]. [10]. [11]. Amin, M.R. 2012. Incipient production efficiency of Babcock-380 layers in a control house in Kelantan. J bioentrepreneurship 2: 22-27. Amin, M.R. and Hamidi, E.N. 2013. Effect of phytase supplementation on the performance of Babcock-380 layers. J tropical resource and sustainable science 1(1):36-41. Anonym1 2013. Strain responses of laying hens to varying energy level. www2.ju.edu.jo....accessed on 2013. Atta, M., Eljack, B.H. and El Obied, A.A. 2010. Use of mathematical modeling to evaluate production performance of some commercial layer strains under Khartoum State conditions (Sudan) Animal science Journal 1(1): 19-22. Chowdhury, S.R., Chowdhury, S.D. and Smith, T.K. 2002. Effect of dietary garlic on cholesterol metabolism in laying hens. Poultry Science 81 (12):1856-1862. Durrani, M.F. 2012. Egg production performance of commercial layers in Chakwal, Pakistan. Eprints.hec.gov.pk/460/1/347.html.htm. accessed on 12/12/2012. Kaps, M. and Lamberson, W. 2009. Fixed effect one-way analysis of variance. In: Biostatistics for animal science. Cabi. pp 231271. Singh, R, Cheng, K. M. and Silversides, F.G 2009. Production performance and egg quality of four strains of laying hens kept in conventional cages and floor pens. Poultry science 88:256-264. Singh, R.P. and Kumar, J. 1994. Biometrical methods in poultry breeding (First edi.). Kalyani publishers, India. pp Silversides, F.G., Singh, R., Cheng, K.M. and Korver, D.R. 2012. Comparison of bones of 4 strains of laying hens kept in conventional cages and floor pens. Poultry Science 91(1):1-7. Verma, I.C. and Singh, K.S. 1997. Cost and return structure in layer farming. Indian J. Poultry science 32 (2):152-158. www.iosrjournals.org 82 | Page