ABSTRACT
This study was conducted to compare three strains (Arbor Acre, Marshal and Ross) of broiler chickens using growth traits, biochemical profile and mathematical models (Gompertz, Logistics and Simple linear regressions) with the view of identifying the best strain and the most suitable model for fitting growth curve in broilers. A total of 225 birds (75 per strain) were used. The traits recorded at 2, 4, 6 and 8 weeks of age were body weight, shank length (SL), thigh length (TL), body length (BL) and breast width (BRW) while the traits recorded at 4 and 8 weeks for biochemical profile were glucose (GLU), urea, creatinine (CRE), albumin (ALB) and total protein (TP). At the end of 8 weeks of age, 27 birds from 3 treatments, (9 birds per treatment) were used for carcass traits analysis. The carcass traits measured were carcass weight (CW), breast weight (BRW), thigh weight (TW), drum stick weight (DS), shank weight (SW), gizzard (GZ) and liver. Statistical analysis was done using General linear model procedure of Statistical Analysis System and Python programming interface. The mean body weights obtained at 2, 4, 6, and 8 weeks of age for Arbor acre, Ross and Marshal were 168.40, 494.52, 1085.14 and 1458.96g, 172.14, 505.40, 1044 and 1377g and 145.64, 401.65, 946.58 and 1272.06g, respectively. SL obtained at 2, 4, 6, and 8 weeks of age for Arbor acre, Ross and Marshal were 6.71, 9.42, 13.15, and 14.59cm, 7.24, 10.34, 13.08, and 14.13cm and 7.07, 9.45, 12.19 and 13.72cm, respectively. BRW obtained at 2, 4, 6, and 8 weeks of age for Arbor acre, Ross and Marshal were 13.12, 16.86, 25.04 and 27.49cm, 13.86, 20.71, 23.68 and 27.10cm, 13.22, 17.81, 23.68 and 25.70cm respectively. Similarly, TL obtained at 2, 4, 6, and 8 weeks of age for Arbor acre, Ross and Marshal were 4.95, 6.33, 9.13 and 9.85cm, 5.00, 6.83, 9.26 and 9.34cm and 4.62, 6.22, 8.38, and 8.52cm, respectively. Lastly, BL obtained at 2, 4, 6, and 8 weeks of age for Arbor acre, Ross and Marshal were 24.17, 32.21, 45.81 and 52.92, 26.16, 35.01, 45.45 and 51.97cm, 24.17, 32.54, 44.67 and 50.27cm, respectively. Effect of strain on blood
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biochemical traits were not significant (P>0.05) between the three strains. Similarly, effect of strain on carcass traits were not significant (P>0.05) except for drumsticks weight (DS) which no significant (P>0.05) effect between Ross and Arbor acre with corresponding values of 161.33±6.15g and 145.66±6.15g respectively while Arbor acre and Marshal (140.33±5.77) also had no significant (P>0.05) effect. Correlation coefficients between body weight (g) and body linear measurement (cm) traits were moderate to highly significant (P<0.01) for all the strains at age 2, 4, 6 and 8 weeks. Blood biochemical traits had low positive to high negative associations with other traits of all the strains at 4 and 8 weeks of age. Carcass weight had positive and highly significant (P<0.01) associations with BRW (0.92), TW (0.84) and DS (0.97) in Arbor acre. Similarly corresponding values of BRW (0.82), TW (0.86) and DS (0.76) were recorded for Ross while BRW (0.94), TW (0.98), DS (0.91) were recorded for Marshal. Ross and Arbor acre used for this study showed a good difference for body weight than Marshal strain. The comparison of growth curves using mathematical models in this study showed that, based on the leading key indicators of low Mean square errors (MSE), high coefficient of determination and high correlation coefficients, simple linear regression (SLR) was more appropriate to describe growth pattern of Arbor acre, Ross and Marshal strains compared to Gompertz (GOM) and Logistics (LOG).
TABLE OF CONTENTS
Cover Page …………………………………………………………………………………………………………………….. i
Title Page …………………………………………………………………………………………………………………….. iii
DECLARATION …………………………………………………………………………………………………………. iv
CERTIFICATION ………………………………………………………………………………………………………… v
DEDICATION …………………………………………………………………………………………………………….. vi
ACKNOWLEDGMENT ……………………………………………………………………………………………… vii
ABSTRACT …………………………………………………………………………………………………………….. viii-x
TABLE OF CONTENTS ………………………………………………………………………………………. xiii-xiv
LIST OF TABLES …………………………………………………………………………………………………. xv-xvi
LIST OF FIGURES …………………………………………………………………………………………………… xvii
CHAPTER ONE …………………………………………………………………………………………………………… 1
1.0 INTRODUCTION ………………………………………………………………………………………………… 1
1.1 Background of the Study ……………………………………………………………………………………….. 1
1.1.1 Poultry Breeding …………………………………………………………………………………………………….. 2
1.2 Justification ………………………………………………………………………………………………………….. 3
1.3 Hypotheses ……………………………………………………………………………………………………………. 4
1.4 Objectives……………………………………………………………………………………………………………… 5
CHAPTER TWO ………………………………………………………………………………………………………….. 6
2.0 LITERATURE REVIEW ……………………………………………………………………………………… 6
2.1 History of Chickens……………………………………………………………………………………………….. 6
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2.2 Avian Species and Chicken Strains ……………………………………………………………………….. 7
2.3 Commercial Broiler Breeders ………………………………………………………………………………… 8
2.4 Growth Curve / Model in Poultry ………………………………………………………………………… 12
2.4.1 Linear models ………………………………………………………………………………………………………. 12
2.5 Growth and its Implication on Poultry Production ……………………………………………….. 14
2.6 Growth Performance Traits …………………………………………………………………………………. 16
2.6.1 Body weight…………………………………………………………………………………………………………. 17
2.6.2 Shank length ………………………………………………………………………………………………………… 18
2.6.3 Thigh length…………………………………………………………………………………………………………. 18
2.6.4 Breast width …………………………………………………………………………………………………………. 18
2.6.5 Body length …………………………………………………………………………………………………………. 19
2.6.6 Correlations ………………………………………………………………………………………………………….. 19
2.7 Biochemical Blood Components of Broiler Chickens …………………………………………….. 21
2.7.1 Creatinine ……………………………………………………………………………………………………………. 22
2.7.2 Total protein …………………………………………………………………………………………………………. 23
2.7.3 Albumin ………………………………………………………………………………………………………………. 23
2.7.4 Glucose ……………………………………………………………………………………………………………….. 24
2.7.5 Urea ……………………………………………………………………………………………………………………. 25
CHAPTER THREE …………………………………………………………………………………………………….. 26
3.0 MATERIALS AND METHODS ………………………………………………………………………….. 26
3.1 Location of the Experiment………………………………………………………………………………….. 26
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3.2 Experimental Birds and Management …………………………………………………………………. 26
3.3 Nutrition……………………………………………………………………………………………………………… 27
3.4 Data Collection ……………………………………………………………………………………………………. 27
3.4.1 Growth traits measured………………………………………………………………………………………….. 27
3.5 Carcass Traits Measured …………………………………………………………………………………….. 28
3.6 Blood Sample Collection and Analysis ………………………………………………………………….. 28
3.7 Data Analysis ………………………………………………………………………………………………………. 29
3.7.1 Model for body weight and body linear measurement ……………………………………………….. 29
3.7.2 Model for blood and carcass analysis ………………………………………………………………………. 29
3.7.3 Model for body weight…………………………………………………………………………………………… 29
3.7.4 Statistical analysis ………………………………………………………………………………………………… 30
CHAPTER FOUR ……………………………………………………………………………………………………….. 31
4.0 RESULTS …………………………………………………………………………………………………………… 31
4.1 Body Weight and Body Linear Measurement ……………………………………………………….. 31
4.2 Least Square Mean and Standard Error Mean of Biochemical Traits of Arbor Acre, Ross and Marshal Broiler Chicken ………………………………………………………………………. 34
4.3 Least Square Mean (±SE) of Carcass Traits of Arbor Acre, Ross and Marshal Broiler Chicken ………………………………………………………………………………………………………………. 36
4.4 Correlations among Body Weight and Body Linear Measurements of Arbore Acre, Ross and Marshal Broiler Strain at Two Weeks of Age (Below Diagonal) and Four Weeks of Age (Above Diagonal) …………………………………………………………………………… 38
4.5 Correlation between Body Weight and Body Linear Measurement of Arbor Acre, Ross and Marshal Broiler Strain at Six Weeks of Age (Below Diagonal) and Eight Weeks of Age (Above Diagonal) …………………………………………………………………………… 41
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4.6 Correlation between Blood Biochemical Traits of Arbor Acre, Ross and Marshal Broiler Chicken at Four Weeks of Age (Below Diagonal) and Eight Weeks of Age (Above Diagonal) ………………………………………………………………………………………………… 44
4.7 Correlations between Carcass Traits (g) of Arbor Acre, Ross and Marshal Broiler Strains ………………………………………………………………………………………………………………… 47
4.8 Actual Body Weights (g) and Predicted Body Weights (g) of Arbor Acre Strain Using Gompertz, Logistics and Simple Linear Regression Models. …………………………………. 49
4.9 Actual Body Weights (g) and Predicted Body Weights (g) of Ross Strain Using Gompertz, Logistics and Simple Linear Regression Models. …………………………………. 51
4.10 Actual Body Weights (g) And Predicted Body Weights (g) of Marshal Strain Using Gompertz, Logistics and Simple Linear Regression Models. …………………………………. 53
4.11 Goodness of Fit Criteria Results for Gompertz, Logistics and Simple Linear Regression for Arbor Acre, Ross and Marshal Strains. ………………………………………… 55
CHAPTER FIVE ………………………………………………………………………………………………………… 61
5.0 DISSCUSSION …………………………………………………………………………………………………… 61
5.1 Body Weight and Body Linear Measurement of all the Strains ……………………………… 61
5.2 Biochemical Traits ………………………………………………………………………………………………. 62
5.3 Carcass Traits……………………………………………………………………………………………………… 62
5. 4 Correlations between Body Weight and Body Linear Measurement of all Strains, Biochemical Profile Correlation and Carcass Correlation …………………………………….. 63
5.5 Comparative Evaluation of Growth Models …………………………………………………………. 64
CHAPTER SIX …………………………………………………………………………………………………………… 65
6.0 SUMMARY, CONCLUSION AND RECOMMENDATIONS ………………………………. 65
6.1 Summary …………………………………………………………………………………………………………….. 65
6.2 Conclusion ………………………………………………………………………………………………………….. 66
6.3 Recommendations ……………………………………………………………………………………………….. 66
References …………………………………………………………………………………………………………………… 67
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CHAPTER ONE
1.0 INTRODUCTION
1.1 Background of the Study
In many developing countries of the world including Nigeria, the broiler industry plays a major role in supplying the population with meat which is highly nutritious and popularly consumed (Ukwu, 2004). The broiler chicken in Nigeria had served as the major source of protein for the population. Despite their economic importance, poultry production is affected by environmental factors among which include temperature, humidity and nutrition (Orunmuyi, 2006). Evaluation of performance of broiler strains is carried out using various indices, such as growth traits (body weight and body linear -measurement). Ebangi and Ibe (1994) reported that body linear measurement have heritable basis and have been identified to play a major role in the subsequent carcass yield of broiler strains. A range of techniques are available to gain information about broiler mass and body conformation. Some of these techniques use simple and inexpensive equipment, while others required sophisticated and expensive equipment (Kabir et al., 2010a). The most direct way to determine broiler’s mass is to weigh it using digital weighing scale. However, under some circumstances, a scale may not be available. An alternative is to measure a body part and relate the measurement to the body weight. Shank length, thigh length, breast width are some body parts that are commonly measured and related to body weight in poultry ( Nwagu et al., 2009; Kabir et al., 2010b).
Breeders of meat-type chickens over the years introduced the use of mathematical models such as Gompertz, Logistics, Artificial Neural Network (ANN), Wood, Richards, Von Bertalanffy,
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France, Monomolecular and Lopez models as a means of visualizing growth pattern of individual or group of farm animal overtime, and subsequently use equations generated to predict the expected weight of individual or group of farm animals at a specific age (Turgar and Selahiti 1991; Patra et al., 2002; Cetin et al., 2007).
1.1.1 Poultry Breeding
From the early 20th century, the breeding of chickens for meat and egg has experienced significant changes in methods of selection, industry, market structure and traits demanded for due to the consumption of poultry meat and eggs that has increased steadily (Aggrey et al., 2003). It has moved from a combined total of 117 million tonnes in 2001 to 147 million tonnes in 2011(EGWPT, 2011) of the current total, 13% is produced from turkeys, ducks or poultry species other than chickens. Although unique issues for other strains exist, development in their breeding has in general been parallel to those of chickens.
The greatest potential for poultry consumption remains in the tropics, where per capita egg and meat consumption levels are increasing (Aggrey et al., 2003). Several traits of importance comes to mind, chief amongst which breeders must select for, body weight, shank length, thigh length among a host of others. However, future developments in the breeding of chickens will be governed by the same factors that have determined developments in the past but with one important difference: the ‘chicken itself’ is likely to play its own role when it presents the limits of its biological capabilities. It has been speculated that genetic progress at the present rate and for the current main traits will be possible for a limited period of less than two decades (Crawford, 1990). Areas of speculation for the future impact of main determinants include: industry developments; consumer demands; breeding technologies; and biological constraints.
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The distributions of indigenous poultry out number that of other livestock and they are the only species that can be kept by the poorer section of the population in the rural areas. Gueye (2000) reported that they represent about 98% of the total poultry numbers kept in Africa. In Malawi, they constitute 83% (Judith and Gondwe, 2004) Nigeria 80% of 120 million poultry birds (Fayeye et al., 2005). Despite their popularity and potentials, Ajayi et al. (2008) pointed out that rural poultry are rarely accorded primary consideration in economic development activities. However, rural farmers often regard this sector as secondary to other livestock and crop farming activities.
1.2 Justification
Live body weight at market age is known to be the most important traits in determining profit from broiler enterprise (Mistra and Mohapatra, 1995). Poultry breeders have tried to establish the relationships that exist between biochemical traits, body weight and body conformation traits as this information reflects on the growth and development of the broiler birds (Adenowo and Omoniyi, 2004; Kabir and Olufemi, 2013; Kabir et al., 2010a). Breeders of meat- type chickens have become interested in adult body weight, the trend being towards a big bodied weight at early age in order to attract better price at market (FDLPCS, 1992).
Growth models are the most adequate means of describing the growth patterns and adequately predicting body weight or body parts of broiler strains by summarizing the information in few parameters that may be interpreted biologically (Turgar and Selahiti, 1991). Generally, growth of broiler can be explained by changes in weight, length and volume of the body during certain period of time. Analysis of these changes have been done mostly by mathematical non-linear models (Turgar and Selahiti, 1991). Growth curves models have been used by several
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researchers. For such as; Gompertz model in Japanese quail and turkey (Anthony et al.,1991), in fowl and ducks (Knizetova et al., 1991) and geese, white and brown Japanese quail (Sezer and Tarhan, 2005). Gompertz and Richards model in heavy white male and female turkey (Heidari et al., 2011) and Artificial Neural Network (ANN) model in male and female partridges (Cetin et al., 2007). Lastly, Logistics and Artificial Neural Network (ANN) model was used in predicting egg production of White leghorn hen (Savegnago et al., 2011). There are few published studies on the use of growth models such Gompertz, Logistics and Simple linear regression in determining growth curves as well as predicting body weight at the inclining phase of growth in Arbor acre, Ross and Marshal broiler strains.
1.3 Hypotheses
This research is designed to test the following hypotheses: Ho: Strain has no effect on growth traits (body weight and body linear measurement), biochemical profile and carcass traits of broiler chicken. HA: Strain has effect on growth traits (body weight and body linear measurement), biochemical profile and carcass traits of broiler chicken. Ho: Growth curves of three strains (Arbor acre, Ross and Marshal) of broiler chickens were similar HA: Growth curves of three strains (Arbor acre, Ross and Marshal) of broiler chickens were different
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1.4 Objectives
I. To determine the effect of strain on some growth traits (body weight and body linear measurement), biochemical profile and carcass traits.
II. To determine the relationship between growth traits (body weight and body linear measurement) serum biochemical profile and carcass traits of Arbor acre, Ross and Marshal broiler strains.
III. To compare body weight curve of Arbor acre, Ross and Marshal strains using Gompertz, Logistic and simple linear regression models so as to identify the best suited model that describes growth in Arbor acre, Ross and Marshal broiler strains.
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