ATTENTION:
BEFORE YOU READ THE ABSTRACT OR CHAPTER ONE OF THE PROJECT TOPICS BELOW, PLEASE READ THE INFORMATION BELOW.THANK YOU!
INFORMATION:
YOU CAN GET THE COMPLETE PROJECT OF THE TOPIC BELOW. THE FULL PROJECT COST N5,000 ONLY. THE FULL INFORMATION ON HOW TO PAY AND GET THE COMPLETE PROJECT IS AT THE BOTTOM OF THIS PAGE. OR
YOU CAN CALL: 08068231953, 08168759420
WHATSAPP US ON: 08168759420
GENETIC CHANGE IN THE NIGERIAN HEAVY LOCAL CHICKEN ECOTYPE THROUGH SELECTION FOR BODY WEIGHT AND EGG PRODUCTION TRAITS
ABSTRACT
The study was carried out to determine the genetic change in the Nigerian heavy local chicken ecotype (NHLCE) through selection for body weight and egg production traits. Progenies (G0 generation) generated from breeding parents randomly selected from the parent stock of the NHLCE formed the materials for the research. On hatching, the chicks were grouped according to sire families using colour markers. The chicks were brooded and reared according to standard management practices. They were fed a starter mash containing 18% crude protein and 2800 Kcal/kgME from 0 – 8 weeks and a growers mash containing 15% crude protein and 2670 Kcal/ kgME from 8 weeks to 20 weeks. At 20 weeks, all pullets were moved into individual laying cages for short-term (16 weeks) egg production. From then the birds were fed layers mash containing 16.5% crude protein and 2600Kcal/kgME. Data were collected on body weight, egg weight and egg number. A control population was maintained for each generation and was used to measure environmental effects. At the end of the 16 weeks egg production period, hens were subjected to selection using a multiple trait selection index incorporating body weight at first egg (BWFE), average egg weight and total egg number. The relative economic weights of the traits and their heritabilities were used to weight the phenotypic values of each trait in the index. The index score of each bird became a univariate character, which enabled the hens to be ranked for purposes of selection. Males were selected based on their individual body weight performances at 39 weeks of age using mass selection. Selected parents from G0 generation were used to generate the G1 generation which in turn yielded the parents of the G2 generation. Data on body weight, BWFE, egg weight and egg number were subjected to statistical analysis to obtain means, standard error of means and standard deviation using the SPSS 2001 statistical package. Analysis of variance yielded sire component of variance from which the additive genetic heritabilities of the traits were calculated. Genetic, phenotypic and environmental correlations between pairs of traits in the index were estimated. Indicators of selection response, namely, selection differential, expected, predicted and realized genetic gains were determined for each trait. There were significant increases (P £ 0.05) in all the traits selected. Body weight performances (sexes combined) increased across the age periods (0 – 20 weeks) from the starting mean values in G0 generation to the final values in G2 generation. The body weight at hatch increased from a mean of 30.30g in G0 generation to 33.48g in G2 generation. Body weights at 4th, 8th, 12th, 16th and 20th week of age also showed similar increases. Body weight of males and females were similarly significantly improved. Mean body weight of males at 12, 16, 20 and 39 weeks of age were 791.40 ± 8.79g, 932.25 ± 7.83g, 1112.60 ± 11.98g and 1693.75 ± 19.91g, respectively for G0 generation as against 825.28±7.54g, 1027.83 ± 9.90g, 1156.69 ± 11.74g and 2000.00 ± 31.34g, respectively for G2 generation. For females, body weights at 12, 16 and 20 weeks as well as BWFE were 667.98 ± 6.30g, 791.52 ± 6.24g, 911.59 ± 6.33g and 1330.44 ± 2.141g, respectively in G0 generation. The corresponding values for G2 generation were 673.94 ± 6.48g, 812.54 ± 7.72g, 939.64 ± 7.28g and 1428.48 ± 3.051g, respectively. For egg production, significant improvements were also made. Total egg number and average egg weight increased from 75.60 eggs and 41.27g, respectively in G0 generation to 79.38 eggs and 43.18g, respectively in G2 generation. Selection differential values were positive and high for 39 weeks body weight in males across the three generations (mean, 302.19g) as well as for total egg number (mean, 10.74eggs) and average egg weight (mean, 0.47g) in females. It was, however, negative on the average for BWFE (-5.41g). Selection intensity values for mass selection in males were 2.11, 1.75 and 1.16 for G0, G1 and G2 generations, respectively. Mean selection intensity values for total egg number, average egg weight and body weight at first egg were 0.729, 0.106 and -0.277, respectively. For index values, selection differentials (∆SI) were equally positive across the three generations and selection intensity (iI) remained relatively stable viz. 0.703, 0.989 and 0.890 for G0, G1 and G2 generations, respectively. Direct selection responses namely, expected, predicted and realized genetic gains were mostly positive for all traits selected. Expected average direct genetic gain per generation for egg number, egg weight and BWFE were 12.58 eggs, 2.98g and 25.04g, respectively. For gain in index traits due to selection on index score, a mean value of 1.705 eggs was obtained for total egg number, 0.949g for average egg weight and 43.93g for BWFE. The ratio of realized to expected genetic gain were positive across the three generations. Specifically, a mean ratio of 0.61 was obtained for 39 weeks body weight in males, 1.58 for BWFE, 1.70 for average egg weight and 1.75 for total egg number, for females. The estimate of additive genetic heritability (h2) ranged from 0.12 to 0.24 for egg number, 0.34 to 0.43 for egg weight and 0.57 to 0.70 for body weight. Estimates of genetic correlation (rg) in whole populations across the three generations ranged from -0.01 to 0.01 for EN-EW, -0.06 to 0.01 for EN-BWFE, and 0.002 to 0.02 for EW-BWFE. For phenotypic correlation (rp), a range of -0.12 to 0.09, -0.04 to 0.08, and 0.21 to 0.23 were obtained for EN-EW, EN-BWFE, and EW-BWFE, respectively whereas, for environmental correlation, a range of 0.55 to 1.31, 0.52 to 0.69, and 0.38 to 0.85 were obtained, respectively for the same pairs of traits.
GLOSSARY OF TERMS
Control population: A random breeding population used to measure environmental variation from one generation to another in a selection programme.
Ecotype: A sub-species adapted to a particular habitat or ecosystem
Environmental variance: The value of the environmental variation.
Environmental variation: The differences among individuals as a result of differences in environmental influences.
Expected genetic gain: The genetic progress expected as a result of selection applied.Generation interval: The period from birth to reproduction of first progeny.
Genetic variance (VG or ): The value of the genetic variation.
Genetic variation: The differences among individuals in a population in a trait as a result of the genes they carry (i.e. their genotype).
Index score (I): An aggregate value. The combination of the values of two or more attributes into one (aggregate) score or value.
Major genes: Single genes controlling whole traits.
Minor genes: Genes contributing small effects to the manifestation of a character.
Phenotypic variance (Vp or ): The value of the total (observable) variation.
Phenotypic variation: The observable (measurable) total variation between individuals in a population due to genetic and environmental effect.
Polygenes: a group of genes, each contributing small effects to the manifestation of a trait.
Predicted response: The response expected in a trait based on the selection differential and heritability values.
Quantitative trait loci: Chromosomal regions containing one or more genes that influence a multifactorial trait.
Realized genetic gain: The superiority of the progeny of the selected parents over the parental population.
Selection differential: Superior of selected group over their contemporaries.
Selection intensity: The strength of selection applied on a trait.
Variance: A measure of variation
Variation: The differences among individuals in a population in a trait (characteristic) or a number of traits.
TABLE OF CONTENTS
Title page – – – – – – – – – i
Certification – – – – – – – – – ii
Dedication – – – – – – – – – iii
Acknowledgement – – – – – – iv
Abstract – – – – – – – – – vi
Glossary of terms – – – – – – viii
Table of content – – – – – – – – – ix
List of table – – – – – – – xiii
1.0 INTRODUCTION – – – – – – – 1
1.1 Research objectives – – – – – – 3
1.2 Problem statement – – – – – 4
1.3 Justification – – – – – – – – 5
2.0 LITERATURE REVIEW – – – – – – 6
2.1 Characterization of the Nigerian indigenous chicken – 6
2.2 Variation among the indigenous chickens – – – 8
2.3 Egg Production in Chickens – – – – 8
2.4 Genetic factors influence egg production – – – 9
2.4.1 Age at sexual maturity (ASM) – – – 9
2.4.2 Body weight at sexual maturity (BWSM) – – 10
2.4.3 Single gene effects – – – – – 10
2.4.4 Other genetic components of egg production – 11
2.5 Environmental factors influencing egg production – – 11
2.5.1 Nutritional factor – – – – – – – 11
2.5.2 Diseases – – – – – – 11
2.5.3 Temperature (Heat) – – – – – 11
2.5.4 Lighting – – – – – – – – 12
2.6 Genetic improvement in chicken – – – 12
2.7 Selection strategies – – – – – – 13
2.8 Genetic relationship between traits – – – 14
2.9 Economic weights (values) of quantitative traits in farm animals 15
2.10 Genetic parameters for body weight, egg number and egg weight
in chickens – – – – – – – – 20
2.10.1 Heritability – – – – – – 20
2.10.2 Genetic relationships – – – – – 22
2.10.2.1 Relationship between growth and reproduction – 22
2.10.2.2 Relationship between egg production and other productive traits – – – – – – – – 23
2.11 Effect of selection – — – – – 23
2.11.1 Effect of selection on genetic variance and heritability – 23
2.11.2 Genetic and phenotypic correlations – – – 24
2.12 Response to selection (R) – – – – 25
3.0 MATERIALS AND METHOD – – – – – 27
3.1 The study site – – – – – – 27
3.2 The reference population – – – – – 27
3.2.1 The foundation stock or base population – – 27
3.2.2 Generation of the starting stock (G0 generation) – 28
3.3 Management of the G0 generation – – – 28
3.4 Establishment of control population – – – 31
3.5 Generation and management of G1 and G2 generations – 32
3.6 Measurement of traits – – – – – 32
3.6.1 (i) Growth trait – – – – – – 32
(ii) Body weight at first egg (BWFE) – – – 32
(iii) Final body weight of cocks – – – – 32
3.6.2 Egg production traits – – – – – 32
3.7 Selection in the G0 generation – – – – 33
3.7.1 Selection within the male population – – – – 33
3.7.2 Selection within the female population – – 33
3.7.3 Construction of selection index – – – 33
3.7.4 Determination of relative economic weights – – – 35
3.7.4. (i) Body weight – – – – – – 35
(ii) Egg number – – – – – – 36
(iii) Egg weight – – – – – – 36
3.7.5 Selection in subsequent generations (G1 and G2) – 37
3.8 Data analysis – – – – – – – 37
3.8.1 Performance statistics – – – – – 37
3.8.2 Estimation of genetic parameters – – – 37
3.8.2.1 Heritability (h2) – – – – – 38
3.8.2.2 Genetic correlation (rg) – – – – 38
3.8.2.3 Phenotypic correlation (rp) – – – – 39
3.8.2.4 Environmental correlation (rE) – – – – 40
3.8.3 Measurement of selection applied – – – 40
3.8.3.1 Selection differential (∆s) – – – – 40
3.8.3.2 Selection intensity (i) – – – – – 40
3.8.3.3 Cumulative selection differential – – – 41
3.8.4 Measurement of response to selection – – – 41
3.8.4.1 Expected direct response (Ri) – – – – 41
3.8.4.2 Cumulative direct response (cumR) – – – 42
3.8.4.3 Average direct genetic response per generation – 42
3.8.4.4 Expected direct genetic gain per year – – – 42
3.8.4.5 Predicted direct genetic response (Rp) – – 43
3.8.4.6 Realized (observed) genetic response (∆GR) – – – 43
3.8.4.7 Expected genetic gain (response) in the index value due to selection
on the index score (I) – – – – – – – 44
3.8.4.8 Expected genetic gain in the component traits of the index due to
selection on index score (I) – – – – – – – 44
3.8.4.9 Effectiveness of selection – – – – – – 44
4.0 RESULTS AND DISCUSSION – – – – – 45
4.1 Body weight – – – – – – 45
4.2 Heritability estimates for body weight at various age periods – – 54
4.3 Selection differentials, phenotypic standard deviation and selection
intensity for males – – – – – 59
4.4 Response to selection in the male population – – 62
4.5 Total egg number, average egg weight and body weight at first egg – – – – – – – – – 65
4.6 Response to selection in the Female population – 69
4.7 Genetic, phenotypic and environmental correlations (rg, rp, and rE) – – – – – – – – – 72
4.8 Estimates of additive genetic heritability for egg number, egg weight and
body weight at first egg – – – – – – – 75
4.9 Relative economic weight for egg number, egg weight and body weight
at first egg – – – – – – – – – 77
4.10 Selection response in egg number, egg weight and body weight at first egg 79
4.11 Mean values, selection differential, phenotypic standard deviation,
selection intensity, heritability and expected response for index score – – – – – – – – – – – 83
4.12 Response in the component traits of the index due to selection on index
score – – – – – – – 85
5.0 CONCLUSION AND RECOMMENDATION – – 87
5.1 Conclusion – – – – – – 87
5.2 Recommendations – – – – – – 88
REFERENCES – – – – – – – – 89
APPENDICES – – – – – – – – 100
LIST OF TABLES
Table 1: Statistical information required (arbitrary values) for example of
selection index for beef cattle – – – – – 18
Table 2: Example of economic value per unit and per genetic standard
deviation of change for egg production traits – – – – 19
Table 3: Experimental ratio – – – – – – 29
Table 4: Vaccination schedule – – – – 31
Table 5: Descriptive statistics for body weight (g) from hatch to 20 weeks of age for G0, G1 and G2 generations (sexes combined) – 47
Table 6: Mean ± S.E. for body weight (g) for 12 to 20 weeks of age for G0, G1
and G2 generations (sexes separated) – – 48
Table 7: Between sex comparison for body weight (g) (mean ± S.E) for 12 to 20 weeks of age for G0, G1 and G2 generations – 51
Table 8: Between population mean comparison for 39 week body weight (g) for G0, G1 and G2 generations (males) – – – – 52
Table 9: Between generations mean comparison for 39 week body weight (g) for selected, whole and control populations (males) – 53
Table 10: Heritability estimates for body weight (g) from hatch to 20 weeks
for G0, G1 and G2 generations (sexes combined) – – – – 56
Table 11: Heritability estimates for body weight (g) for 12 to 20 weeks of age for G0, G1 and G2 generations (males) – – 58
Table 12: Selection differential (∆s), cumulative selection differential
(Cum∆s); phenotypic standard deviation ; and selection intensity (i)
of 39 weeks body weight (g) (males) – – – – 61
Table 13: Expected, cumulative response, predicted, realized genetic gain,
ratio of realized to expected response and ratio of realized to predicted
response in 39 week body weight (males) – – – – 64
Table 14: Between population comparison for index traits across G0, G1
and G2 generation – – – – – – – 67
Table 15: Between generation comparison of the performances of selection, whol eand control population in index traits – – 68
Table 16: Selection differentials, cumulative selection differential, phenotypic standard deviation and selection intensity for index traits – – – – – – – – – 71
Table 17: Estimates of genetic, phenotypic and environmental correlations for pairs of traits in the index – – – – – 74
Table 18: Estimates of additive genetic heritability for index traits 76
Table 19: Estimates of relative economic weights for index traits – 78
Table 20: Expected direct, cumulative and average genetic responses for index traits across G0, G1 and G2 generations – – 80
Table 21: Predicted and realized genetic responses for index traits -81
Table 22: Mean index values and selection differential, phenotypic standard deviation, selection intensity, heritability, and expected genetic gain for index score for G0, G1 and G2 generations – 84
Table 23: Expected genetic gain in index traits as a result of selection on index Score – – – – – – – 86
CHAPTER ONE
1.0 INTRODUCTION
The report of the FAO expert consultation on animal genetic resources (FAO 1973) recommended the improvement and conservation of animal genetic resources indigenous to countries. However, two major constraints delayed its implementation until the 1980s. These constraints include the lack of funds on the one hand, and the delay caused by the disagreement between scientists concerning the genetic merits of these indigenous breeds on the other hand. Most scientists were at this time locked in the paradigm of economic progress as the only value.
Consequently, the prevailing animal production policy then (1960s and 1970s) was to try to improve tropical breeds by introducing temperate breeds with high genetic merits (AGRI, 2002). Indigenous breeds were considered obsolete. Improving and conserving indigenous breeds were regarded as uneconomic and, therefore, should be allowed to disappear. But Payne and Hodges (1997) had noted that the philosophy of improving animal production in the tropics with temperate breeds did not only fail but also damaged indigenous breed resources.
Humanity shapes biodiversity, knowingly or unknowingly. This biodiversity results both from natural selection for adaptation and artificial selection through human choices for use and/or aesthetic value. The preferential selection of distinct genetic traits is reflected in the breed types and races that are adapted to specific uses or environments. Nigeria is blessed with a vast array of animal biodiversity (Nwosu, 1990). This array of breeds is a human heritage worthy of improvement and conservation. Their loss is bound to deplete the quality of human life (Hodges, 2002).
The population of Nigeria was estimated to be about 144 million people (National Population Commission, 2006). With an estimated population growth rate of 2.9% per annum, the population is currently about 160 million. The provision of adequate food for this teaming population is the mandate of the agricultural sector.
Animal agriculture must also provide the animal protein needs of Nigerians. This is an enormous responsibility. The British Medical Association recommends a minimum animal protein intake of 34g per caput per day (Okuneye, 2002). Also, the food and Agriculture Organization (FAO) of the United Nations (1989), recommends 20g of animal protein per caput per day as the minimum for consumption for developing countries (Okuneye and Banwo, 1990) but 75g as the optimum for normal growth and development (Food and Agriculture Organization, FAO, 1992). This translates to a minimum demand of about 3.4 million kiogrammes and a maximum of 7.5 million kilogrammes of animal protein per day for a population of about a 100 million people. But according to Oluyemi (1979), the average animal protein intake per caput per day in Nigeria was a mere 7.6g or 38% of the FAO minimum recommendation for developing countries and a mere 10% of the requirement for excellent growth and development. The Central Bank of Nigeria, CBN (2000) while analyzing the economic sub-sectors noted that the Gross Domestic Product (GDP) has been on a downward trend. And since the nature of GDP reflects the standard of living of the citizens it means that the standard of living of Nigerians has been on the decline. By extension this also implies that the animal protein intake of the average Nigerian has continued to fall far below the recommended levels.
The Federal Ministry of agriculture and Rural Development (FMARD)(2008) gave the estimated number of indigenous chicken in Nigeria as 166 million. The exotic breeds were believed to number about 5 million. Akinwumi et al. (1979) gave an estimate of about 123.0 million for indigenous fowls and 9.6 million for exotic birds. In addition to the above are thousands of horses, camels and pigs as well as millions of donkeys, cattle, goats and sheep.
The above statistics are impressive but where are the products? In 1998, out of a total of 101 million metric tones of poultry meat projected for production, only 77 million metric tones were realized. In 1999, 109 million metric tones were projected but only 82 million metric tones were supplied by the poultry sector. The figure for the year 2000 was similar as only 88 million metric tones were supplied out of a total projection of 116 million metric tones (CBN, 2002).
Livestock value is not measured in numbers but in terms of amount of useable animal products harvested for human consumption (Nwosu,1990). A reliable yardstick for measuring productivity of animal products is hence the total production and the production per person per year. Thus, it is significant to note that in 1994, 1996, and 2000 the total meat products (of various types) produced per person in Nigeria was 8.224kg, 8.694kg, and 8.772kg, respectively (Okuneye,2002). These figures reveal serious shortages from the recommended 75g per caput daily animal protein intake or its equivalent 25.375kg per person per annum intake (FAO,1989).
To make up for these shortages, Nigeria must import animal milk and meat products from other countries. Thus in spite of the enormous number of indigenous livestock resources, Nigeria remains a net importer of livestock products since the 1980s (Okuneye, 2002). Von Mason (1989) stated that Nigeria was the biggest importer of dairy products in West Africa. The 2,428 metric tones of beef and 198,000 metric tones of milk imported by Nigeria in 1987 cost the nation a whopping sum of US$3.27 million and US$69.00 million, respectively (ILCA, 1991). This trend has not abated till date (Okuneye, 2002). To bridge the animal protein demand and supply gap the Nigerian government in the 1970s and 1980s attempted to improve local breeds of cattle by importing temperate breeds. These efforts failed principally because the exotic breeds could not adapt to the tropical Nigerian environment as the challenges of tropical climate, pests and diseases were unbearable to them. The problem of streptothricosis in crossbred cattle was quite devastating. The importation and rearing of exotic poultry species have not also been able to bridge this gap. The reasons also include the challenges of stressful environment and diseases which reduce performance added to the high cost of inputs (genetic and feed materials, drugs and bio-organics) which discourage so many investors from investing in the industry.
Locally adapted breeds (indigenous species) are better able to survive and produce valuable products in low input and variable environments (AGRI, 2002). A strategy to develop these breeds is, therefore, likely to be more sustainable over the long term than reliance on external genetic resources. Nwosu (1979) had deplored the lack of a co-ordinated effort to preserve, harness, and improve the genetic potentials of Nigeria’s indigenous livestock breeds.
HOW TO RECEIVE PROJECT MATERICAL(S)
After paying the appropriate amount (#5,000) into our bank Account below, send the following information to
08068231953 or 08168759420
(1) Your project topics
(2) Email Address
(3) Payment Name
(4) Teller Number
We will send your material(s) after we receive bank alert
BANK ACCOUNTS
Account Name: AMUTAH DANIEL CHUKWUDI
Account Number: 0046579864
Bank: GTBank.
OR
Account Name: AMUTAH DANIEL CHUKWUDI
Account Number: 3139283609
Bank: FIRST BANK
FOR MORE INFORMATION, CALL:
08068231953 or 08168759420