ARID ZONE JOURNAL OF ENGINEERING, TECHNOLOGY &
ENVIRONMENT

AZOJETE September 2020. Vol. 16(3):531-542
Published by the Faculty of Engineering, University of Maiduguri, Maiduguri, Nigeria.

Print ISSN: 1596-2490, Electronic ISSN: 2545-5818
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ORIGINAL RESEARCH ARTICLE
PRODUCTIVITY AND ALLOCATIVE EFFICIENCY OF QUAIL (CORTUNIX
COTURNIX JAPONICA) PRODUCTION USING DIFFERENT REARING

TECHNIQUES IN NIGERIA

Y. U. Oladimeji1*, H. O. Yusuf2, H. A. Yusuf2, H. Shuaibu2 and T. O. Olarewaju3
1Department of Agricultural Economics / Institute for Agricultural Research, Ahmadu Bello University, Zaria, Nigeria

2Department of Agricultural Extension and Rural Development / Institute for Agricultural Research, Ahmadu Bello University,
Zaria, Nigeria

3Department of Agricultural Engineering, National Agricultural, Extension and Research Liaisons Services, Ahmadu Bello University,
Zaria, Nigeria.

*Corresponding author’s email address: yusuf.dimeji@yahoo.com

1.0 Introduction
Poultry has been domesticated for thousands of years as archaeological evidence suggests that
domesticated chickens existed in China 8,000 years ago (Alders 2004) when humans ceased to
be hunter-gatherers (Burt, 2007). Domestic chickens appeared in Africa many centuries ago,
which are now part of African life (Copland and Alders, 2005). The Red Jungle Fowl is thought
to be the source of all poultry (Fumihito et al., 1994).

Over the last decades’ poultry production and its technology in Nigeria has been increasingly
improved. For example, Food and Agriculture Organisation (FAO, (2018) observed that poultry
meat production has increased from 30,000 in 1961 to 201,493 tons in 2017 with standard
deviation of 67,351.8 tons and about 571.6 % increased. Over the same period, poultry egg
production has increased by 588% (Figure 1). Furthermore, the volume of feed used in Nigeria
has increased by 600% from 300 thousand to 1.8 million tons in about one decade and this is
driven both by massive investments in large feed mills in southwest Nigeria and a growing

ARTICLE
INFORMATION

ABSTRACT
Small scale poultry production plays a major role in bridging the protein deficit
and sustain rural livelihood in Nigeria. This study assesses the productivity and
allocative efficiency (AE) of quail (Cortunix coturnix japonica) production using
different rearing techniques in Nigeria. In this study, both primary and secondary
data were collected from 193 quail poultry farmers comprising of 78 battery
cage system (BCS) and 115 deep litter system (DLS) operators using a multi-
stage random sampling procedure. Descriptive statistics, profitability indices and
stochastic frontier function were used to analyse the data. The stochastic frontier
cost function was used to estimate the factors influencing AE of farmers in quail
production. The results show a gross margin of N1, 455.51, net poultry returns
of N1157.47 per quail bird for BCS thrives better compared to N800.00 and
N751.96 estimated in DLS respectively. The estimated profit margin (26.81 %)
and return on investment (1.37) in BCS were also higher than 26.54 % and
1.36 respectively in DLS. The ROI result indicates that a N1.00 investment in
BCS and DLS yields N0.37 and N0.36 respectively. AE results revealed that the
coefficient of costs of feed (0.287), hired labour (-0281), family labour (0.309)
and depreciation of fixed items (-005) were found to be statistically significant
variables in BCS quail production. Conversely, costs of feed (0.109), cost of hired
labour (-0.007) and family labour (0.188) statistically influence DLS quail
production. The inefficiency sources model for BCS showed that age, formal
education, access to credit and investment are the significant factors.
Furthermore, formal education, access to production credit and level of
investment contributed significantly to the explanation of efficiency in DLS
production unit. Therefore, it is suggested that quail farmers should strive to
optimize efficient use of inputs to increase output and profit. This will be an
impetus to achieving sustainable poultry production in the studied areas.

© 2020 Faculty of Engineering, University of Maiduguri, Nigeria. All rights reserved.

Submitted 20 Sept., 2019
Revised 24 May, 2020
Accepted 30 May, 2020

Keywords:
quail chick
return on investment
allocative efficiency
Profit
technology

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Oladimeji et al.: Productivity and Allocative Efficiency of Quail (Cortunix Coturnix Japonica) Production using Different Rearing Techniques
in Nigeria. AZOJETE,16(3):531-542. ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng

Corresponding author’s e-mail address: yusuf.dimeji@yahoo.com 532

number of small and medium enterprises in poultry production scattered around the country
(Liverpool-Tasie et al., 2017).

Therefore, Nigeria had a success in poultry production trend and high demand due to rapid
population growth. This is also couple with its ability to supply protein rapidly in the short-run.
A cursory examination of FAO data computed in Figure 1 shows that poultry and ruminant
production has been dwindling in recent year (2011-2017) compared to mono-gastric (pig) and
total meat production. This is envisaged due to effect of insurgence in the north eastern part of
the country and multi-various farmers-herdsmen, cattle rustling and banditry spreading across
the six geopolitical zones in the country. Several studies also have indicated that the north has
more of the small farmers’ poultry, particularly chicken holdings compared to the south
(Liverpool-Tasie et al., 2017).

Figure 1: Trend of poultry egg and total meat production in Nigeria (1961-2017); Source:
Authors computation from FAO Statistic data (2017)

The poultry industry in Nigeria has hitherto been dominated by rearing of domestic chickens.
However, recently there have been several entrants into the sector. Interestingly, one of the
poultry species gradually gaining prominence is the Japanese quail (Cortunix coturnix japonica)
of Galliformes family which is suitable for commercial rearing under intensive management
(Egbeyale et al., 2013). Quail production is considered as a viable and feasible alternative means
of livelihood for the unemployed and civil servants. It is an important income-generating
strategy for both urban and rural farmers with a supplementary income. Nationally, there is
deficiency of animal protein security, with the consumption put at about less than 10g / caput /
day as against the daily intake of 65g recommended by the FAO to be the minimum
requirement for the growth and development of the body (Odunsi et al., 2007; Mailafia et al.,
2010; El-Katcha et al., 2015; Mohammed and Ejiofor, 2015). Consequently, boosting the poultry
industry with a short generation interval is an alternative means of alleviating the deficiency of
animal protein in Nigeria.

It was, therefore, expedient and imperative to accumulate data on productivity and profitability
of quail production in Nigeria for analysis geared towards meaningful policy formulation for the

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Arid Zone Journal of Engineering, Technology and Environment, September, 2020; Vol. 16(3) 531-542. ISSN 1596-2490; e-ISSN 2545-
5818; www.azojete.com.ng

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poultry sub-sector especially emerging quail production in the country. It was also essential that
to have in-depth knowledge on quail production for being a laboratory animal for poultry and
biomedical research. This is in addition to it is being commercially exploited for production of
meat and eggs recently in Nigeria. The objective of this study is to describe the socio-economic
status of quail farmers, estimate the profitability, analyze the productivity and allocative
efficiency of quail (Cortunix coturnix japonica) production using different rearing techniques in
Nigeria.

2.0 Material and Methods
2.1 The Study Area
The study was conducted in southwest (Oyo, Ekiti, Ondo States) and north-central (Kwara,
Kogi States) Nigeria. This was crucial because the two regions are the main production of quail
birds. Nigeria lies between Longitudes 2°49' E and 14°37' E and Latitudes 4°16' N and 13°52'
North of the Equator (Oladimeji, 2018). The climate is tropical, characterized by high
temperature and humidity as well as marked wet and dry seasons, though there are variations
between South and North. It has a total land area of 923,768.6 km2 and 139 million people in
2006 (NPC, 2006) and the latest United Nation estimate in year 2019 at growth rate of 2.48%
(United Nation, UN 2019) put the country over 190 million people with average human density
of 204 person km-2. Total rainfall decreases from the coast northwards. The south (below
latitude 8°N) has an annual rainfall ranging between 1,500 and 4,000 mm and the extreme
north between 500 and 1000 mm. The research was carried out in two geopolitical zones and
five states in Nigeria viz: Kwara and Kogi states from north-central and Oyo, Ekiti and Ondo
states from southwest of Nigeria.

2.2 Data Collection and Sampling Procedure
Both primary and secondary data were collected from 193 quail poultry farmers using
structured questionnaire with personal interview method by trained enumerators. Secondary
data were collected from the production records of the quail farmers. Primary data
compliment with their records were search for and these include inputs data such as human
labour, quantity of feed, water and fuels used. Output data collected include quail meat, egg and
manure.

The collected data belonged to the 2016/2017 production year. Before collecting data, a pre-
test survey was conducted from a group of randomly selected quail poultry farmers in the two
sampled regions. Information on socio-economic and institutional characteristics, input and
output, energy input sources were obtained from the quail farmers to achieve the objectives of
study.

Multistage sampling procedure was adopted for the study. The first stage involved purposive
selection of two regions comprising north central (Kwara and Kogi states) and south western
(Oyo and Ekiti/Ondo states) Nigeria due to predominance of poultry farmers and, availability of
quail production records among the poultry farmers. The list of registered cooperative poultry
farmers was obtained in the states’ Agricultural Development Project (ADP). Thereafter,
stratified sampling technique was used to sieve the quail poultry farmers from layers and
broilers poultry farmers. Thereafter, all the sieved quail farmers were sampled due to small
sample size. Finally, additional quail farmers were sought for using snowball-sampling technique
based on information from sampled farmers. This means that initially selected quail poultry
farmers from ADP group provided addresses of additional quail farmers who were neither a
cooperative member nor a registered poultry farmer with ADP for their interviewers (Salganik
and Heckathorn, 2014; Oladimeji et al., 2019). A total of 193 quail farmers comprising of 78
battery cage system (BCS) users and 115 deep litter system (DLS) users were sampled in the
chosen states.

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Oladimeji et al.: Productivity and Allocative Efficiency of Quail (Cortunix Coturnix Japonica) Production using Different Rearing Techniques
in Nigeria. AZOJETE,16(3):531-542. ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng

Corresponding author’s e-mail address: yusuf.dimeji@yahoo.com 534

2.3 Analytical Technique
Descriptive statistics, profitability indices and stochastic frontier function were used to analyse
the data. The stochastic frontier cost function was used to estimate the factors influencing
allocative efficiency of farmers in quail production adopted from Aigner et al. (1977), Battese et
al. (1996) and Oladimeji et al. (2017).

Stochastic Allocative Function Model used in the study was specified explicitly as

(1)

Where: = natural log; = total cost of production (₦/bird); = cost of feed (₦); = cost

of quail chick (₦); = cost of hired labour used (₦); = cost of family labour (₦); =

cost of vaccine and drugs (₦), depreciation cost of machinery which include electricity,

generator, fuels, borehole, electric motor, steel and battery (₦); = regression

coefficients; = random variability in the production that cannot be influenced by the quail
producers.

= deviation from maximum potential output attributable to allocative inefficiency.

� �� = δ� + δ� ln Z� + δ� ln Z� + δ� ln Z� + δ� ln Z� + δ� ln Z� + δ� ln Z� + U (2)

Where: = allocative inefficiency effects, = age of farmers (years), = household size

(number), = formal education (years), = poultry rearing experience (years), = access

to credits (₦); = level of investment (₦); = constant and = parameters to be
estimated (Aigner et al., 1977; Battese et al., 1996).

The profitability indices involved the estimating the following items:
Net Farm Income for quail poultry production was estimated using equation below:

(3)

Where: = Net Farm Income per quail bird in the states (₦); = Total sales revenue

accruing to the quail farmers per bird in the states (₦); = Total cost incurred by

the quail farmers per bird (₦); and = Total number of quail farmers in the states.

Total Revenue ( ) is the total return or total value product (the total output multiplied by
the price per unit of produce). That is;

(4)

Where; = quantity of quail bird (kg) and = price per unit of quail bird ; Total Cost

was computed using equation below

(5)

= Total Variable Cost incurred by the quail farmer in the states (₦) and =

Total Fixed Cost incurred by the quail farmer in the states (₦).

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Arid Zone Journal of Engineering, Technology and Environment, September, 2020; Vol. 16(3) 531-542. ISSN 1596-2490; e-ISSN 2545-
5818; www.azojete.com.ng

Corresponding author’s e-mail address: yusuf.dimeji@yahoo.com 535

Profitability indices were also computed as:

ttotal
incomegrossROI
cos

 (6)

(7)

(8)

(9)

(10)

Where: = return on investment, = profit margin and = gross ratio.

Total Fixed Cost involved depreciated value of equipment used in quail bird rearing
expressed as:

(12)

Where:

= depreciation on production equipment (₦), = Purchase value (₦), = salvage value (₦)
and = life span of asset (years).

3. Results and Discussion
3.1 Technological, Socio-Economic, Institutional Characteristics
Figure 2 depict a typical description of quail battery cage system and Table 1 showed the
summary of technological characteristics used in quail production by the sampled farmers.
Table 2 summarizes socio-economic and institutional variables employed in the model
estimation. The level of technological investment, number of day old chicks acquired by quail
poultry farmers and credit accessed for quail rearing revealed that quail production practices
are still not developed and are largely subsistent and rudimentary as evidence in Table 1.

Table 1: Description of technology characteristics employed by quail poultry farmers
Technology traits Type used Standard

Quail cage Plank with wire (600 X 600 mm) Galvanized sheets & wire materials
(1200 X 600 mm)

Feed system Manual with feeder Automatic feed carriages

Drinking / watering
system

Manual drinker Pipes with nipples

Egg collection system Manual plastic plate Automatic egg collection made up
of galvanized sheet & wire materials

Manure collection Manual with shovel Manure transfer conveyors

Source: Swain et al. 2010

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Oladimeji et al.: Productivity and Allocative Efficiency of Quail (Cortunix Coturnix Japonica) Production using Different Rearing Techniques
in Nigeria. AZOJETE,16(3):531-542. ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng

Corresponding author’s e-mail address: yusuf.dimeji@yahoo.com 536

Figure 2: A typical description of quail battery cage system
Source: Dewulf et al. (2011)

Table 2 indicates that sampled quail farmers were dominated by male (0.67) and married
farmers (0.89) with mean age of 48 years and household size of 6.

Table 2: Description and measurement of variables employed in allocative efficiency model
Variables Unit Min. Max. Mean Stdev COV %

Gender (male=1) dummy 0.67 0.22 32.83
Marital status (married=1) dummy 0.89 0.09 10.11
Age years 25 65 48 6.1 12.71
Quail poultry experience years 1 13 7.4 3.7 50
Level of formal education years 6 15 12.8 0.3 2.34
Adjusted household size number 3 11 6 1 16.67
Credit for quail rearing Naira 0 200,000 61,900.92 34,003.3 43.1
Poultry coop. membership years 0 7 5 2.04 40.8
Investment in quail
production

Naira 12.600 276,000 149,730.0 38,440
25.67

Number of quail birds kept number 25 500 251 35 13.94
Hired labour per two cycle man-days 109 201 167 34 20.36
Family labour per two cycle man-days 54 113 89 21 23.60

Source: Field survey, 2016/2017; denote million, stood for coefficient of variance

This mean age revealed that the quail farmers sampled were agile and productive, an essential
ingredients to quail production activities. It is believed that old people tend to adhere strictly to

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traditional methods of poultry, while young people tend to be more willing to adopt new
production methods in order to increase production. Therefore, it could be concluded that the
preponderance of active and virile poultry farmers in the study area has a multiplier effects on
increased availability of able bodied labour for primary production; ease of adoption of
innovations; reduction in the degree of risk-aversion and positive implication to sustainability of
poultry enterprise in the State. The result is comparable to Oladimeji et al. (2017) on profit
efficiency of broiler production among public servant household heads in Kwara State, Nigeria.

3.2 Estimated Profitability Indices and Return to Investment in Quail
Production
Table 3 depicts profitability indices and return to investment in battery cage and deep litter

quail rearing techniques. The results showed that under battery cage system ( ), the total
variable cost constituted 90.57% while the fixed cost constituted only 9.43% while in deep litter

system ( ), the total variable cost constituted 96.75 %.
The gross margin per quail bird (N1, 455.51), net poultry returns per quail bird (N1157.47) for

thrive better compared to N800.00 and N751.96 respectively estimated in . These

imply that quail production in is more profitable than DLS. The estimated profit margin

(26.81 %) and return on investment (1.37) in were higher compared to 26.54 % and 1.36

respectively in . The result indicates that a N1.00 investment in and yields

N0.37 and N0.36 respectively. This, therefore, implies that yielded more returns to
investment. The result is comparable to Adelomo and Owoeye (2017) and Bakoji et al. (2013)
on economic analysis of quail farming in Southwest and Bauchi State, Nigeria respectively.

Table 3: A summary of profitability indices and return on investment per quail bird per ⃰ ⃰ 2
cycles

BCS DLS Pooled
Cost item values (₦)
Total fixed cost 298.04(9.43) 48.04(2.31) 84.79 (3.25)
Total variable cost 2,861.09(90.57) 2,033.25(97.69) 2,523.40(96.75)
Total cost 3,159.13(100.0) 2081.29 (100.00)

2,608.19(100.0)
Average output per bird (Naira)
Egg sales (₦ 19 per egg) 3,979.6(92.19) 2,550.00(90.00) 3,211.00(90.81)
Spent quail bird sold 287.50(6.66) 222.90(7.87) 270.00(7.64)
Manure 49.50(1.15) 60.35(2.13) 55.09(1.56)
Total revenue(gross income) 4,316.6 (100) 2833.25 (100) 3,536.09 (100)
Gross margin per bird per annum 1,455.51 800.00 1,012.69
Net poultry income / bird /
annum

1157.47 751.96 927.90

Profit margin (%) 26.81 26.54 26.22
Return on investment 1.37 1.36 1.36
Gross ratio 73.19 73.46 73.76
Net margin to cost ratio (%) 36.64 36.13 35.58
Number of observations 78 115 193
Source: Field Survey, 2016/2017; production and financial records; ⃰ labour consist of cost of
hired, family and return to management; ⃰ ⃰ 2 cycles ranges from 340 – 422 days averaged
approximately 365 days; N or ₦ stood for Naira, Nigeria currency

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Oladimeji et al.: Productivity and Allocative Efficiency of Quail (Cortunix Coturnix Japonica) Production using Different Rearing Techniques
in Nigeria. AZOJETE,16(3):531-542. ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng

Corresponding author’s e-mail address: yusuf.dimeji@yahoo.com 538

3.3 Estimate the factors influencing Allocative Efficiency of farmers’ investment in
quail production
Table 4 showed the result of the allocative efficiency (and inefficiency) frontier model of quail

production in Nigeria. Allocative efficiency results of quail production revealed that a unit
increase in the coefficients of costs of feed (p < 0.01), and family labour (p < 0.05) will lead to a
corresponding increase in total cost by 0.287 and 0.309 units. However, the coefficients of

hired labour (p < 0.05), and depreciation of fixed items (p < 0.005) in quail production will
reduced the total cost by 0.281 and 0.005 units respectively. Likewise, results also revealed that
a unit increase in the coefficients of costs of feed (p < 0.01) and family labour (p < 0.01) will
lead to a corresponding increase in total cost by 0.109 and 0.188 units respectively of DLS quail
production. On the other hand, a unit increase in hired labour (p < 0.01) will lead to a unit
decrease in total cost by 0.007 units of DLS quail production.

Table 4: MLE Results of allocative frontier efficiency function of quail production
Variables Battery cage Deep litter Pooled

β |P[|Z|>z] β |P[|Z|>z] β |P[|Z|>z]
Cost Function
Constant 0.003(0.029) ** 0.015(0.100) 0.038(0.008) ***
Cost of feed (X1) 0.287 (0.000) *** 0.109(0.007) *** 0.521(0.000) ***
Cost of quail chick (X2) -0.0004(0.521) -0.061(0.381) -0.122(0.203)
Cost of hired labour (X3) -0.281 (0.029)** -0.007(0.000) *** -0.400(0.000) ***
Cost of family labour (X4) 0.309 (0.019) ** 0.188(0.004) *** 0.097(0.005) ***
Cost of vac. and drugs (X5) 0.002 (0.798) 0.001(0.503) 0.003(0.421)
Dep. of fixed items (X6) -0.005 (0.019) ** 0.117(0.204) -0.310(0.069*)
Inefficiency variables
Age -0.007 (0.002) *** 0.002(0.343) -0.118(0.072) *
Household size 0.395(0.400) 0.003(0.219) 0.002(0.176)
Formal education 0.004(0.000) *** 0.011(0.004) *** 0.001(0.002) ***
Poultry rearing experience 0.208(0.251) -0.306(0.199) 0.005(0.095) *
Access to production credit -0.009(0.062) * -0.200(0.000) *** -0.306(0.007)
Level of investment -0.505 (0.005) *** -0.118(0.004) *** -0.301(0.000)
Diagnostic statistic
Number of observation 78 115 193
Sigma-square (σ2) 0.541(0.002) *** 0.219(0.025) ** 0.473 (0.005) ***
Gamma (γ) 0.289(0.054*) 0.054 (0.009) *** 0.233(0.001***)
Log likelihood function L/f -103.07 -112.81 -109.00
LR test 42.00 45.00 57.09
Mean allocative efficiency 0.87 0.77 0.79
Asterisk indicate significance ***1%, **5%, *10%.

Table 5: The generalized LR test for the parameter of the inefficiency sources model
S/no Quail rearing technique LLF ϰ2 tab v:0.95

statistics
ϰ2

calculated
Inferences

i Battery cage system -103.07 1.96 2.67 Accept

ii Deep litter system -112.81 2.01 3.02 Accept
iii Pooled -109.00 1.99 2.91 Accept
Note: LLF denote Log Likelihood Function, ϰ2 implies Chi statistics; LR, likelihood ratio

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5818; www.azojete.com.ng

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The inefficiency sources model for showed that the coefficients of age (-0.007), formal
education (0.004), access to credit (-0.009) and investment (-0.505) are the significant socio-
economic factors influencing efficiency. Similarly, formal education (0.011), access to production
credit (-0.200) and level of investment (-0.118) contributed significantly to the explanation of

efficiency in production unit. The positive coefficients of level of education in BCS or DLS
imply that a unit increase in education will lead to a corresponding increase in inefficiency in
quail production. However, negative coefficients of credit utilized and investment in BCS and
DLS quail technology suggest that a unit increase in these variables will increase efficiency of
both quail production techniques.
Tables 4 and 5 showed that the null hypothesis, which specifies that inefficiency sources model

does not have effects in the allocating resources in both and are accepted. In addition,

values imply that the entire delta ( ) estimates are not zero. It further revealed that the
delta variables estimated contributed significantly to the inefficiency of the quail farmers in the

study area. It suffices to that the chi-square ( ) calculated is greater than the tabulated in

Table 5 indicating the relevance of the variables in both and production units
respectively.

3.4 Relative allocative efficiency indices of quail production techniques
Table 6 shows the distribution of efficiency indices of quail farmers by techniques and pooled
data. The battery-cage system minimum (19.85 %) and maximum (90.71 %) efficiency estimated

were higher compared with of 15.09 % and 82.72 % respectively. The mean allocative

efficiency score of 76.4 % in or 69.5 % in implied that an average quail farmer
sampled could thrive better in allocating resources by 23.6 % or 30.5 % to improve his
allocative efficiency in quail production.

Further analysis indicates that more than half of quail farmers (53.84 %) skewed towards

efficiency level of 0.61-0.80. On the other hand, about half (48.7 %) of quail farmers fell

within efficiency range of 0.41-0.60. Thus, higher allocative efficiency of may be connected
with quail species habitat, which have the tendency to thrive better in their natural
environment. In spite of this, the results implied that both rearing techniques operate at a
relatively high allocative efficiency level and a considerable amount of output can be obtained by
improving allocative efficiency in quail production in the two techniques.

Table 6: Allocative efficiency estimates of quail farmers for different rearing technology
Battery cage (n = 78) Deep litter (n = 115) Pooled (n = 193)

Class F % F % F %
0.21-0.40 4 5.13 21 18.26 23 11.92
0.41-0.60 18 23.08 56 48.7 79 40.93
0.61-0.80 42 53.84 30 26.09 69 35.75
0.81-1.00 14 17.95 8 6.95 22 11.40
Total 78 100 115 100 193 100
Mean 0.764 0.695 0.731
Minimum 19.85 15.09 16.00
Maximum 90.71 82.72 86.09

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Oladimeji et al.: Productivity and Allocative Efficiency of Quail (Cortunix Coturnix Japonica) Production using Different Rearing Techniques
in Nigeria. AZOJETE,16(3):531-542. ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng

Corresponding author’s e-mail address: yusuf.dimeji@yahoo.com 540

3.5 Implications of profitability and the allocative efficiencies on farmers’ output
The result implies that quail production is profitable in both rearing techniques. It could also be
deduced that the allocative efficiencies of the sampled farmers is above the frontier. The
demand-supply gap of poultry products could be bridged and sustainably increases its output
using the available inputs and existing technology, if resources could be efficiently and optimally
utilized as ample opportunity still exist to move closer to frontier as it was revealed in this
study. The presence of inefficiency in quail poultry production system should also be addressed
if quail poultry farmers intend to maximize their profit. Therefore poultry farmers’ level of
efficiencies could be increased if their specific factors such as level of investment, access to
credit and formal education which are statistically significant factors influencing inefficiency, and
in line with a priori expectations are adequately addressed.

4. Conclusion
Filtering the data of quail poultry production into battery cage and deep litter systems as well
as pooled, this study conclude that the two systems exhibit different degrees of profitability and
allocative efficiency in the two production systems. The allocative efficiency factors that
influence battery cage system farmers showed variation from those influencing deep litter
systems. However, where the same variable influenced both BCS and DLS, it is not by the same
magnitude and direction. Therefore, it can be concluded that the battery cage system
performed better with higher return to investment and better allocative efficiency.

Reference

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