Agricultural Economics and Extension Project Topics

Economic Analysis of Layer Productions

Economic Analysis of Layer Productions

Economic Analysis of Layer Productions

Chapter One


The major objective of this study is to analyze the economics of Layer production in Kwara State, Nigeria. The specific objectives are to:

  1. Describe the socio-economic characteristics of Layer farmers in the study area.
  2. Estimate profitability of Layer production in the study area.
  3. Identify the factor contributing to Layer production in the study area.




This chapter will review literature related to the study, it will focus on Layer production, Layer management, problem facing Layer production and solution to the problems, economics of Layer production and analytical techniques used in economics of Layer production.


The term “Layer” in agriculture generally applies to a wide variety of birds of several species including chicken, guinea fowls, pigeons, ducks, geese, turkey, swans, peafowl, ostriches, pheasants, quails and other game birds kept for eggs or meat production (Alders, Robyn). Chicken (Gallus domesticus) is the most common Layer dominating the small holder Layer production systems of Africa hence, it is sometimes considered synonymous with Layer. The domestic fowls (chickens) belong to the order “Galli” it originated in the tropical countries of the world, therefore birds from any country in the world can be easily introduced to the tropics with little difficulty of adaptation (Mgbakor Miriam Ngozi and E. Nzeadachie Chinonso 2013).

Commercial hybrids (layers and broilers) all over the world are being propagated for production of eggs and meat. The hybrid layers usually start laying, at about 20 weeks of age and peak egg production is attained during the first production cycle. The average production rate of commercial layers usually remains very close to 0.9 eggs per day (Ashagidigbi et al., (2011)).

However, as the age increases, their egg production decreases. This situation is further aggravated during the second production cycle. Appetitive behaviour of hens is also affected during the later stage of production age. The climatic conditions have also been known to affect the production behaviour of the laying hens (Ashagidigbi, W.M, S.A. Sulaiman and A. Adesiyan (2011)). In areas where climate is hot and humid, commercial hybrids produce an average of 180 200 eggs per year, while in more temperate climate, birds can produce between 250 and 300 eggs per year. The production cycle of eggs may also be influenced by many other factors such as breed, mortality rate, body weight, laying house lightening schedule, feed and culling (Spielman, D.J. & Pandya-Lorch, R. 2009.).





The study was conducted in Kwara State. It is located between parallels 8º and 10º north latitudes and 3º and 6º east longitudes east. The state covers an area of 35,705 Sq kilometres, the climate of the state is characterized by both the wet and dry seasons, with the rainy season starting from march and last till October, while the dry season begins in November, it has a population of 2,371,089 (Nigeria, 2007 population census figures) with a population density of 66 people/Sq Km, it population makes up 1.7% of Nigeria’s total population. Kwara State is one of the seven states that make up the north central Geo-political zone in the north central part of Nigeria with its capital at Ilorin. It shares an international boundary with the republic of Benin to the west and interstate boundaries with Niger state to the north, Oyo State to the southwest, Osun and Ekiti States to the southeast and Kogi State to the east. Ilorin climate is characterized by both wet and dry season each lasting for about six months. The raining season begins towards the end of April and last till October while the dry season begins in November and ends in March. Days are very hot during the dry season; from November to January, temperatures typically range from 33°C to 34°C, while from February to April, the temperature is between 34.6°C and 37°C. The total annual rainfall in Ilorin is about 1318mm with the mean temperature being between 30°C-33°C (Ilorin atlas, 1958). Relative humidity at Ilorin in the wet season is between 75 and 80% while in the dry season it is about 65% (tinuoye, 1990). The daytime is always sunny with the sun brightly shinning for about 6.5-7.7 hours daily from November to May (olaniran, 1983). The climate supports tall grass vegetation, which is interspersed with short scattered trees (guinea Savanna). Hence, it provides high quantity of feed for livestock animals. The only trees able to survive in this climate are those which are biologically suited to withstand dry conditions. Such trees have deep roots and they are adapted to conserve moisture in the dry season. The baobab, acacia, shears butter trees are typically examples of trees in the area. The vegetation on the other hands is dominated by derived scattered trees. Chicken species available in Ilorin include gallus gallus (red jungle fowl), Gallus sonnerati (gray jungle fowl) and gallus lafayutti (cylon fowl) besides the indigenous chickens the vegetation provides reasonable quantity of feed for livestock animals especially during the rainy season.



This chapter is concerned with the presentation of analysis and the interpretation of data collected during the distribution of the questionnaires of the study.


The socio-economic characteristics of Layer farmers considered in the study area include the age, gender of farmers, marital status, household size, educational level, main occupation, years of experience and method of land acquisition by farmers.


Age is defined as the length of existence of a person; it is a major determinant of productivity even Layer keeping. In Nigeria, most common system of Layer management is the deep litter system which employs manual labour, the quality of this labour is dependent on the age. Table 4.1 shows the distribution of respondents/farmers according to their age.

TABLE 4.1: Age distribution of respondents/farmers



An attempt to examine the economics of Layer production in selected local government area of Kwara State was the principal focus of this study. The specific objectives were to: describe the socio-economic characteristics of Layer farmers in the study area, estimate profitability of Layer production in the study area, and determine the relationship between inputs and output obtained in Layer production. Primary data were collected from 80 Layer farmers selected through multi-stage random sampling technique from Asa LGA, Ilorin east, Ilorin south and Moro Local Government Areas of Kwara State, using structured questionnaire. Descriptive statistics, farm budgetary technique, benefit cost analysis and ordinary least square regression analysis was used to analyze the data.

The results of the analyses revealed that majority (72.5%) of the respondents were male   with the mean age of 38.7 years. (63.8%) of these youths had keen interest in Layer production and chose Layer farming as their main occupation. Result of the cost and returns to estimate the profitability of Layer production in the study areas revealed that there is profit in Layer production in the study area with net farm income from layers production stood at ₦1,534,093.53 while that of broilers was ₦ 1,966,086.49 in one production cycle respectively. The finding reveals that Layer production is profitable in the study area. Analysis of the result also showed that inputs such as cost of day old chick, labour, feeds, depreciating cost of equipment and operating expenses have significant relationship with Layer output in the study area.


This study investigated the economics of Layer production in the selected local government areas of Kwara state. Three important findings emerged; first, Layer production in Kwara state is dominated by highly educated youths, a positive sign for future Layer activities. Second, Layer production is highly profitable in Kwara state; however, broiler production contributed the highest return in the area of study. Thirdly, the costs of inputs as revealed by the regression analysis were high and increasing with the size of production thereby depriving the farmers the full benefit of their efforts.


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