




































American International Journal of Multidisciplinary Scientific Research 

Vol. 1, No. 1; 2018 

Published by Centre for Research on Islamic Banking & Finance and Business 

 

 

13 
 

Output Commercialization as Three-Way Traffic for Sugarcane 

Farming Households in Kwara State of Nigeria 

 
 

Sadiq, M.S
1
; Singh, I.P

2 
; Lawal, M

3
;  Yisa, P.B

4 

 

1
Department of Agricultural Economics, FUT, Minna, Nigeria 

2
Department of Agricultural Economics, SKRAU, Bikaner, India 

3
Department of Pure and Applied Chemistry ,University of Science and Technology. Aliereo Kebbi State, Nigeria 

4
Department of Agricultural Education, Federal College of Education, Katsina, Nigeria 

Correspondence: Sadiq, Mohammed Sanusi, Department of Agricultural Economics, SKRAU, Bikaner, India.  

E-mail: sadiqsanusi30@gmail.com 

 

Received: July 29, 2018                            Accepted: August 8, 2018                  Online Published: August 18, 2018   

           

 

 

Abstract 

The study empirically determined the factors that influenced household sugarcane output commercialization in 

Kwara State of Nigeria using undated data elicited via structured questionnaires complemented with interview 

schedule from 105 active sugarcane farmers chosen through multi-stage sampling design during the 2017 production 

season. The collected data were analyzed using both descriptive and inferential statistics. The empirical findings 

showed poor extension services, inadequate credit facilities, failure of the farmers to utilize their social capital, lack 

of scientific storage facilities and health-related issues to be the major factors that affected sugarcane output 

commercialization the studied area. Therefore, the study recommended that the farmers in the studied area should be 

advised to pool their social capital together in order to become economically viable thereby maximizing the 

pecuniary economic advantages of sugarcane value chain in the studied area.   

 

Keywords: Commercialization; Sugarcane output; Farmers; Kwara State; Nigeria.   

 

1. Introduction       

Agriculture commercialization involves a transition from subsistence-oriented to increasingly market-oriented 

patterns of production and input use. The economists have long advocated cash crop production as part of a broader 

strategy of comparative advantage. According to Timmer (1997) and Pingali (1997) as reported by Egbetokun 

(2014), the underlying basis is that markets allow households to increase their income by producing goods which 

turn-in the highest returns to land and labour, and then use the cash to buy household consumption items, rather than 

be constrained to produce all the various goods that the household needs to consume. 

Small-scale agriculture commercialization is an indispensable pathway towards economic growth and development 

for most developing countries depending on the agrarian sector. Therefore, output commercialization, especially for 

the smallholder farmers is three-way traffic as it minimizes poverty, double farmers’ income and enhances the 

growth of the economy. However, having a glance from a larger perspective, smallholder commercialization could 

be seen as the strength of the linkage between farm households and markets at a given point in time. Without the 

ability to sell, irregular bumper harvests dampen farm prices, undermining the income of small farmers who manage 

to produce the surplus, thus leading to convergent cobweb cycle of low-price due to glut followed by scarcity. 

It is obvious that subsistence agriculture in the long-run may not be a viable activity to ensure sustainable household 

food security and welfare. Kurosaki (2003) reported that smallholder commercialization typically leads to an 



www.cribfb.com/journal/index.php/aijmsr           American International Journal of Multidisciplinary Scientific Research           Vol. 1, No. 1; 2018 

 

14 
 

increased diversity of marketed commodities at a national level and increased specialization at regional and farm 

levels. 

Moreover, commercialization has a linking power between input and output sides of a market. Demand for modern 

technologies promotes the input side of production and facilitates the development and advancement of 

technological innovations. In turn, the use of modern technologies can result in increased output due to high yield 

entering the markets. 

Smallholder agriculture remains the major engine of rural growth and livelihood improvement in the studied area. 

Meeting the challenges of eliminating food insecurity and improving rural incomes in the studied area will require 

transformation and transition out of the semi-subsistence, low-input, low-productivity farming systems that currently 

characterized most of the rural economies in the studied area.  

Lacunas in the literature still exist particularly on the comprehensive and concurrent conceptualization of the drivers 

of output commercialization at the household level. Therefore, this research intends to close these gaps particularly 

by the comprehensive conceptualization of the drivers of output commercialization at household level in the wake of 

promotion of collective action initiatives targeted towards poverty alleviation especially in the rural areas were 

agriculture is the driver of the economy. The specific objectives of this study were to describe the socio-economic 

profile of the farmers in the studied area; determine the factors influencing output commercialization in the studied 

area; and, determine the constraints affecting sugarcane production in the studied area.  

2. Research Methodology 

The Kwara State of Nigeria lies between longitudes 4
0
 20

’
 and 4

0 
25

’
 East of the Greenwich meridian and latitudes 8

0
 

30
’
 and 8

0
 50

’
 North of the equator. The population of the state is approximately 2.3 million and has a landmass of 

approximately 36,825 square kilometres with varying physical features like hills, lowland, rivers etc. Its vegetation 

is derived savannah with two distinct wet and dry seasons, with mean annual precipitation and monthly temperature 

of 1000-1500mm and 25
0
C-34

0
C, respectively (Anonymous, 2010). The major occupation of the inhabitants is 

agricultural activities complemented by trade, artisanal, Ayurvedic medicine etc. The present research used undated 

data elicited through structured questionnaire complemented with interview schedule from 105 active sugarcane 

farmers during the 2017 production selected via multi-stage sampling design. In the first stage, one agricultural 

zone, namely zone B was purposively selected due to its comparative advantage in the production of sugarcane. In 

the second stage, the two LGAs viz. Edu and Patigi which made-up the selected agricultural zone were automatically 

selected as both have the comparative advantage in the production of sugarcane. Because of the limited number of 

villages producing sugarcane in the selected LGAs all the villages were considered. Therefore, a total of seven 

villages: five (5) villages from Edu LGA and two (2) from Patigi LGA were the areas of coverage. In the last stage, 

fifteen sugarcane farmers from each of the selected villages were randomly selected: seventy-five (75) and Thirty 

(30) active farmers from Edu and Patigi LGAs respectively. Thus, a total of 105 active farmers made-up the sample 

size for the study. 

For reliability test of the questionnaire, the questionnaire was pre-tested in a pilot survey made up of 15 farmers 

from the sampling population and the estimated Cronbach Alpha value was 0.86, indicating high reliability and 

consistency of the questionnaire. With the aid of trained enumerators, ex-post data of 2017 sugarcane cropping 

season were collected in the year 2018. The collected data were analyzed using both descriptive and inferential 

statistics. Objective I was achieved using descriptive statistic; objective II was achieved using Gini coefficient index 

in conjunction with Lorenz curve; objective III was achieved using censored regression (Tobit regression); and, 

Kendal coefficient of concordance (KCC) and Exploratory factor analysis were used to achieve objective IV. 

2.1 Model Specification 

2.1.1 Gini coefficient index: The Gini index is defined as a ratio of the areas on the Lorenz curve. As shown by 

Sadiq et al. (2017a), the formula is specified as follows:  

G = A/0.5 = 2A=1-2B ………………….........................…….. (1) 

2.1.2 Censored model: Following Sadiq et al. (2018), the original Tobit model developed by James Tobin a Nobel 

laureate economist (Tobin, 1958) is given below:  

 Yi* =  𝛼 + 𝑋𝛽 +𝜀i  ..................................................................... (2) 

Where Yi* is an observable variable. Now Yi = 0 if Yi*  0 

 = Yi* if Yi* > 0 

Yi*=𝛼+X1β1+X2β2+X3β3+X4β4+X5β5+X6β6 + ……+ Xnβn+𝜀i  ................. (3) 

Where: 

Yi* = censored latent observation (HCI) for i
th

 household 

HCIi = Household commercial index for i
th

 household 



www.cribfb.com/journal/index.php/aijmsr           American International Journal of Multidisciplinary Scientific Research           Vol. 1, No. 1; 2018 

 

15 
 

X1 = Age (Year) 

X2 = Marital status (Married =1, Otherwise = 0)  

X3 = Educational level (Formal = 1, Otherwise = 0) 

X4 = Household size (Number) 

X5 = Land ownership (Yes =1, Otherwise = 0) 

X6 = Farming Experience (Year)  

X7 = Farm size (Hectare) 

X8 = Non-farm activity (Yes =1, No = 0) 

X9 = Co-operative membership (Yes =1, No = 0) 

X10 = Access to credit (Yes =1, No = 0) 

X11 = Extension contact (Yes = 1, No = 0) 

X12 = Sickness (Number) 

X13 = Security threat (Yes = 1, Otherwise = 0) 

X14 = Income (N)  

X15 = Unit price of output (kg) 

X16 = Yield (kg) 

𝛼 = Intercept 

Β1-n = Coefficients 

𝜀i  = Error term 

The most common approach used in measuring the degree of commercialization at the household level has been the 

proportion of sales from the total value of agricultural production (Von Braun, 1994). This is actually the revealed 

marketing decision of a household, particularly for commodities that are potentially used for sale and home 

consumption (Randolph, 1992). The HCI is conceptualized in this study as a ratio of the gross value of marketed 

sugarcane output to the gross value of produced sugarcane per household per cropping season and it is given as: 

 

𝑯𝑪𝑰𝒊 = [
𝐺𝑟𝑜𝑠𝑠 𝑣𝑎𝑙𝑢𝑒 𝑜𝑓 𝑚𝑎𝑟𝑘𝑒𝑡𝑒𝑑 𝑠𝑢𝑔𝑎𝑟𝑐𝑎𝑛𝑒 𝑜𝑢𝑡𝑝𝑢𝑡

𝐺𝑟𝑜𝑠𝑠 𝑣𝑎𝑙𝑢𝑒 𝑜𝑓 𝑝𝑟𝑜𝑑𝑢𝑐𝑒𝑑 𝑠𝑢𝑔𝑎𝑟𝑐𝑎𝑛𝑒 
] × 100 …………….. (4) 

 

2.1.3 Kendall’s Coefficient of Concordance (W): Kendall’s coefficient of concordance (W) uses the χ
2
 statistic for 

testing. If the test statistic W is 1, then all the survey respondents have been unanimous and each respondent has 

assigned the same order to the list of subjects or situations. If W is 0, then there is no overall trend of agreement 

between the respondents and their responses may be regarded as essentially random. Intermediate values 

of W indicate a greater or lesser degree of agreement among the various respondents. Following Sadiq et al.(2017b), 

Kendall’s coefficient of concordance developed by Kendall and Smith (1939) and Wallis (1939) is given below:    

 W  
12𝑆

𝑘2𝑛 (𝑛2 −1) – 𝑘𝑇
   ………………………........................................ (5) 

Where; 

S = Sum over all subjects 

k = Number of respondents ranking the attributes or objects 

n = Number of attributes or objects that are evaluated by respondents 

            T = Tie-correction factor 

            T = ∑ (tk
3
-tk)   …………………………………………….. (6) 

‘tk’ is the number of tied ranks in each (k) of g groups of ties. The sum is computed over all groups of ties found in 

all m variables of the data table. T is 0 when there are no tied values. 

The Chi
2
 (

2
) statistic is given as follow: 

2 
= k (n -1) W …………………………………………. (7) 

Where; 

k = Number of respondents 

n = Number of objects or attributes being ranked 

W = Kendall’s coefficient of concordance (KCC)  

2.1.4 Friedman’s Chi-square Statistic 

The Friedman’s Chi-square statistic proposed by Friedman (1937) was developed primarily to test the hypothesis 

that the ratings assigned to subjects under investigation come from the same statistical population. This is an indirect 

way of evaluating the extent of agreement among raters. Due to its close mathematical relationship with Kendall’s 



www.cribfb.com/journal/index.php/aijmsr           American International Journal of Multidisciplinary Scientific Research           Vol. 1, No. 1; 2018 

 

16 
 

coefficient of concordance (W) it is used in studies of inter-judge reliability. The Friedman’s Chi-square statistic is 

given below: 

 2
r = k (n-1) W …………………………………………………… (8) 

Where;  


2
r = Friedman’s chi

2
 statistic 

k = Number of respondents 

n = Number of objects or attributes being ranked 

W = Kendall’s coefficient of concordance (KCC)  

 

3. Results and Discussion 

3.1 Socio-Economic Profile of the Farming Population  

Presented in Table 1 are the socio-economic profiles of the sugarcane farming population in the studied area. The 

results showed the sugarcane farming population to have an effective labour force which will enhance production as 

indicated by the mean and standard deviation values of 44.09 years and 8.63 respectively. The mean and standard 

deviation values of 13 persons and 4.47 respectively, depict a large household under the control of the farming 

household head. The implication is that large household mostly composed of able-bodied people is an asset as the 

farmer will have access to free farm labour supply which if properly utilized would increase the farm production. In 

addition, a large farm family will have access to a stream of income, thus boosting the aggregate income base of the 

farming household. However, large household mostly made-up of weak people or dependants such as children and 

old people would drain farmers income due to high expenditure on food and non-food items which is required for 

keeping the body and soul together. The results showed sugarcane farming to be mainly male affairs in the studied 

which may be due to tedious nature associated with the cultivation of the crop. The non-participation of women at 

the primary production level may be attributed to cultural and religious beliefs in the studied area which limits 

women to domestic house choir and agricultural marketing. The results depicted a responsible social setting in the 

studied area as the majority of the respondents were married. Marriage is an asset as married farmers stand the 

chance of benefiting from the twin advantage of economic and social capitals. Furthermore, the findings showed a 

literate farming population as majority possessed one form of formal education or the other. Though, farmers who 

exceeded secondary educational level dominated sugarcane farming in the study area. The ability of a farmer to read 

and write will encourage him to source for innovative information on production and potential market for input 

demand and output supply, thus enhancing production of sugarcane in the studied area. The results showed 

sugarcane cultivation in the studied to be carried-out mostly on small-scale (1.76±0.81) which may be attributed to 

pressure on the use of land for various agricultural purposes coupled with capital paucity, thus limiting farmers from 

exploring the commercial potential of sugarcane production owing to the establishment of BUA Sugar Company in 

the studied area. The results showed the majority of the farmers to have adequate years of experience in sugarcane 

production in the studied area (5.58±3.39, thus making them to be efficient managers in the allocation of their farm 

resources. The low productivity level of sugarcane production observed in the studied area is attributed to the sole 

cultivation of local variety which may be due to poor extension contact, the poor relative advantage of improved and 

hybrid varieties during the studied period. Also observed was that majority of the farmers were not into enterprise 

diversification, thus making them liable to food insecurity in any situation when risk or uncertainty arises. Most of 

the respondents had no extension contact during the studied period, thus indicating that most of the farmers had no 

access to any innovative technologies on sugarcane production during the last cropping season. A similar scenario of 

abysmal extension contact in the same studied area was observed for rice production (Sadiq et al., 2018). The 

findings showed that majority of the sugarcane farmers were not members of social organization and have no access 

to credit facilities during the studied period, thus indicating inability of the farmers to benefit from pecuniary 

advantages such as bulk discount for input purchase and bargaining power for co-operative marketing; and inability 

to procure adequate inputs for sugarcane production during the studied period respectively.  Most of the farmers 

reported a moderate number of family members been sick during the last production season, thus affecting their 

income base as they have to contend with the expenditure of securing medication for the sick family members. In 

addition, they firmly stated that their farm labour efficiency and their attention towards farming have been distorted 

during the illness period/moment. However, the farming environment during the production period had relative 

peace devoid of crises such as herdsmen/farmers and communal conflicts. Though, a pocket of minor communal 

conflict occurred during the production period in the studied area. The results showed that most of the farmers 

possessed title of ownership i.e. owned the land which they used for sugarcane cultivation, with the land been 

acquired by inheritance. The implication is that lands acquired by this means mostly do not permit commercial 



www.cribfb.com/journal/index.php/aijmsr           American International Journal of Multidisciplinary Scientific Research           Vol. 1, No. 1; 2018 

 

17 
 

production being subject to fragmentation and dispute, as any member of the household who attained adulthood 

would ask for his own share or piece of land.   

     

Table 1b: Socio-economic profile of sugarcane farmers  

 

Variables  Frequency  Percentage  

Inheritance  67 63.8 

Borrow  8 7.6 

Communal  27 25.7 

Rent  3 2.9 

Total  105  100  [𝟏𝟒𝟎. 𝟔𝟕∗∗∗] 

 

Source: Field survey, 2018 

 

 

3.2 Income Distribution of Sugarcane Farmers in the Studied Area 

The estimated Gini coefficient value indicated a fair equality in the distribution of sugarcane farmers in the studied 

area (Table 2). In addition, the graphical representation of the income distribution showed the Lorenz curve not to be 

farther from the line of equality (Figure 1). Therefore, it can be inferred that the sugarcane farmers in the studied 

area belong to the low-income category as earlier revealed that majority of the farmers were smallholder farmers.        

 

Table 2: Annual Income distribution of sugarcane farmers 

 

Item  Coefficient  

Gini coefficient index  0.301282 

Estimate of population 

value  

0.304179 

Source: Field survey, 2018 

   

 
  

3.3 Determinants of Sugarcane Output Commercialization Level  

A perusal of Table 3 showed the censored regression to be the best fit for the specified equation and the predictor 

variables are different from zero as indicated by the significance of the Chi
2
 value at 1% degree of freedom. In 

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0.6

 0.7

 0.8

 0.9

 1

 0  0.1  0.2  0.3  0.4  0.5  0.6  0.7  0.8  0.9  1

Figure 1: Income distribution of sugarcane farmers in Kwara State of Nigeria

Income

Lorenz curve



www.cribfb.com/journal/index.php/aijmsr           American International Journal of Multidisciplinary Scientific Research           Vol. 1, No. 1; 2018 

 

18 
 

addition, the multicollinearity test showed no presence of collinearity between the predictor variables as evidenced 

by the variance inflation factors (VIF) of the explanatory variables which were less than the benchmark of 10.0. 

However, the residual is not normally distributed as shown by the Chi
2
 test statistic which is different from zero at 

10% degree of freedom. Though, non-normality in the distribution of error term is not considered a serious problem 

as data in their natural form in most cases are not normally distributed. Thus, these results are valid for prediction.      

The results showed that commercialization in the production of sugarcane in the studied area is been influenced by 

output unit price, farm size, yield, household size, farm experience, mode of farm ownership, extension contact, co-

operative membership, access to credit and sickness as shown by the significance of their respective estimated 

parameter coefficients at less than 10% risk level. Furthermore, the decomposition detail showed output unit price, 

farm size, household size, mode of farm ownership and access to credit to increase output commercialization while 

the hosts of the remaining significant variables decrease output commercialization in the studied area.   

The positive significance of the estimated coefficient of output unit price with commercialization means that an 

increase in the unit price would encourage the farmers to increase the commercialization of sugarcane production in 

the studied area. This result conforms with a prior expectation stipulated by the theory of supply which showed that 

price is directly related to output supply. Therefore, the marginal and elasticity implications of a unit increase in the 

output price would increase sugarcane commercialization by negligible marginal value and 0.03% respectively. The 

direct relationship of farm size with commercialization level implies that an increase in farm size would increase the 

commercialization level of sugarcane output in the studied area. The implication of an increase in the hectare 

allocated to sugarcane production would increase farmers’ marketable surplus, thus increasing farmers’ marketed 

output. However, an increase in marketable surplus can only guarantee an increase in output commercialization in 

the absence of glut as prices in the future time will likely be remunerative, thus increase in the output marketed. But 

in the situation of a downward fluctuation in the price of output, the large and average farmers’ marketable surplus 

would be greater than marketed surplus i.e. they will retain most of their output till in the future time when the price 

become remunerative. It is worth to note that it is only small-scale farmers that mostly engaged in force sell due to 

pressing cash requirements as against the large and average farmers who resort to distress sale only in rare cases. 

The marginal and elasticity implication of an additional hectare would make farmers to increase sugarcane output 

commercialization level by 0.002 and 0.007% respectively.  

The direct relationship of household size coefficient with output commercialization showed that farmers with large 

household size would increase their marketed output in order to meet its household consumption needs. In addition, 

a large household composed of able-bodied people will provide the farming household with free labour which will 

enable the farmer to produce more output/ marketable surplus, thus increase in the marketed output of the farming 

household. The marginal and elasticity implication of a unit increase in the family size of the farm family would 

increase output commercialization level by 0.0004 and 0.005% respectively. The positive significance of the credit 

coefficient implies that farmers with access to credit facility would engage in output commercialization, as credit 

being a catalyst will give them access to procure required quantity of farm inputs at the right time. In addition, it will 

enable them to carry out marketing function involved in sugarcane marketing without much hindrance. Therefore, 

the marginal and elasticity of farmers with access to credit would increase sugarcane output commercialization by 

0.018 and 0.015% respectively.  

The positive significance of the title of farm ownership showed that farmers who owned their farmland will 

participate more in commercial production. The farmers who owned their land can take to commercial sugarcane 

production with no restriction to the use of land, thereby increasing their output commercialization, as when 

compared to the lease or communal land which will limit full potential utilization of the land resource, thus affecting 

household output commercialization level. The marginal and elasticity implication of farmers who possessed the 

title of land ownership would increase sugarcane output commercialization by 0.004 and 0.0026% respectively. 

The inverse relationship of yield with household sugarcane output commercialization level showed how 

apprehension of market glut as a result of excess supply which mostly dampens the market price would affect 

household sugarcane output commercialization level. Lack of scientific storage facilities and poor technical know-

how on sugarcane processing at local farm level will make it difficult for the local farmers to defer the sales of this 

bulky crop, making them resort to force sale or distress sale during the bumper period, thus affecting output 

commercialization due to slim stream of income caused by downward price fluctuation. The marginal and elasticity 

implication of a unit increase in the yield level of sugarcane would decrease sugarcane output commercialization 

level by negligible value and 0.0076% respectively.     

The negative relationship of experience with output commercialization showed how farmers’ complacency and 

conservatism in price prediction in a dynamic market affect their efficiency in the marketing of sugarcane output 

commercialization in the studied area. Therefore, the marginal and elasticity implication of a unit increase in the 

farming experience will decrease farmers’ output commercialization level by 0.001 and 0.00589% respectively. The 



www.cribfb.com/journal/index.php/aijmsr           American International Journal of Multidisciplinary Scientific Research           Vol. 1, No. 1; 2018 

 

19 
 

negative coefficient of extension contact implies that farmers with no extension contact would be less involved in 

output commercialization as when compared to their counterpart who stand to benefit from innovative production 

and marketing techniques introduced to them. Also, farmers who are not member of co-operative association will be 

less involve in output commercialization as they stand not to benefit from pecuniary economic advantages such as 

bargaining power in the marketing of their outputs as when compared to those who belong to social organization 

whereby bulk marketing is adopted in the sale of their products, thus having bargaining power in the sales of their 

output. Therefore, the marginal and elasticity implications of farmers with no extension contact and not a member of 

co-operative association would decrease their household output commercialization level by 0.008 and 0.0013%; and, 

0.017 and 0.0015% respectively.  

The negative significance of sickness implies that in the situation of any member of the family being sick would 

have an adverse effect on the production capital base of a farmer as much will be expended in seeking for 

medication, thus reducing household output commercialization level. The marginal and elasticity implication of a 

household member being sick will decrease output commercialization level by 0.003 and 0.0089% respectively.  

The positive relationship of security threat coefficient though non-significant, showed that farming environment 

devoid of security threats such as farmers/herders clash and communal conflicts will encourage farmers to produce 

more sugarcane, thus increasing output commercialization level in the studied area. However, the non-significant of 

this variable indicate the presence of relative peace in the farming environment of the studied area. Furthermore, the 

inverse relationship of income despite non-significant indicates how an increase in income will increase farmers 

expenditure level by marrying more wives, purchase of materialistic asset i.e. capital consumption instead of re-

investment in the farm production, thus affecting household output commercialization level. The educational level 

coefficient was non-significant owing to the effect of diffusion across the strata of the farming population in the 

studied area.  The non-significant of the age coefficient is due to the fact that most of the farmers were in their 

youthful age which is economically viable with regard to labour force. However, the inverse relationship of the age 

coefficient showed that when farmer advance in age he will focus on farm family food security rather than having 

the temptation for a higher level of output commercialization in order to satisfy his materialistic needs. Also, the 

non-significant of marital status is as a result of the majority of the farmers been married in the studied area. 

Though, the positive sign of the marital status implies that married farmers will participate more in output 

commercialization in order to meet up with their family expenditure: food and non-food expenditure. The non-

significant of the estimated coefficient of non-farm activity is an indication that much is not earned by the farmers 

from the non-farm activity. However, the positive effect of the estimated coefficient implies that the farmers with 

diversified income will participate more in output commercialization as they have better food security coping 

strategy.     

Table 3: Output commercialization determinants  

Variable Coefficient t-stat Elasticity  VIF 

Constant  0.9673(0.0126) 76.45***   

Age  −0.00014(0.00010) 1.327
NS

 -0.00659 1.816 

Marital status 0.00011(0.00347) 0.032
NS

 0.00072 1.360 

Education  0.00049(0.00168) 0.297
NS

 0.00033 1.411 

Household size 0.00039(0.00018) 2.215** 0.00506 1.479 

Land ownership 0.004008(0.0015) 2.647*** 0.00261 1.222 

Farming Experience −0.00104(0.00026) 3.851*** -0.00586 1.905 

Farm size 0.0021(0.00056) 3.762*** 0.007417 1.909 

Non-farm activity 0.00166(0.0035) 0.483
NS

 0.00022 2.750 

Co-operative mem. −0.01697(0.00596) 2.848*** -0.00154 6.646 

Access to credit 0.01750(0.00561) 3.120*** 0.00150 5.665 

Extension contact −0.00829(0.00228) 3.629*** -0.00129 2.153 

Sickness  −0.00292(0.00071) 4.107*** -0.00888 1.344 

Security threat 0.00197(0.00357) 0.554
NS

 0.00015 1.821 

Income  −8.55E-11(3.02E-10) 0.282
NS

 -0.00013 1.149 

Unit price of output 5.971E-5(2.349E-5) 2.542** 0.029468 1.064 

Yield  −1.299E-6(7.268E-7) 1.787* -0.007630 1.215 

Chi
2
 (𝝌2

) 121.37 [2.9E-18]***    

Normality test (𝝌2
) 35.76 [1.71E-8]***    

Source: Field survey, 2018 



www.cribfb.com/journal/index.php/aijmsr           American International Journal of Multidisciplinary Scientific Research           Vol. 1, No. 1; 2018 

 

20 
 

*, **, *** and 
NS

 means significance at 10%, 5%, 1% and non-significant respectively 

Note: ( ): values in parenthesis are standard error; [ ] values in square brackets are probability levels 

 

3.4 Factors Affecting Sugarcane Production in the Studied Area 

A cursory review of the results revealed the major problems affecting sugarcane production in the studied area to be 

poor transportation network, high cost of agro-inputs, inadequate extension contact, land tenure problem and high 

cost of hired labour as indicated by their respective mean values which were greater than the mean benchmark of 

3.50 (Table 4). However, the remaining identified problems were considered minor problems constraining sugarcane 

production in the studied area as their respective mean values were below the mean benchmark. Furthermore, the 

grand mean value of 3.43 been less than the likert scale benchmark mean value of 3.50 implies that the farmers have 

a negative perception about the identified constraints affecting sugarcane production in the studied area. In addition, 

the perception index showed that approximately 57.09% concurred that these were the problems affecting them in 

sugarcane production in the studied area.  

The Kendall’s coefficient of concordance value of 0.101 implies poor agreement among the sugarcane farmers with 

respect to the ranking. In addition, the significance of the Friedman’s test value means that the attributes assigned to 

the constraints by the farmers come from the statistical population. Therefore, policymakers need not comply with 

this ranking in addressing the identified problems as they are at liberty to start with any of the pressing problems 

affecting sugarcane production in the studied area.  

To reduce the number of research variables and find the common factors affecting sugarcane production in the 

studied area, 13 identified constraints were subjected to an exploratory factor analysis. The Kaiser-Meyer-Olkin 

(KMO) test which measures the degree of inter-correlation among the variables and the appropriateness of factor 

analysis (Hair et al.2010) has a calibration value of 0.712. Following Kaiser and Rice (1974), the calibrated MSA is 

“middling”, implying that the variables are inter-correlated and appropriate for factor analysis. Mansourfar (2006) 

stated that for items to be suitable for factor analysis, the KMO value for sampling adequacy must be between 0.80 

and 1. Therefore following Gindi et al.(2016) who reported KMO value of 0.735 which fall under “middling”, the 

present study adjudged the KMO value of 0.712 for sampling adequacy to be satisfactory.  Also, Bartlett's test 

rejected the hypothesis that the correlation matrix was an identity matrix (at the level of 0.01), indicating a 

significant relationship between the variables. The result of the latent criterion showed that the 13 variables 

subjected to the factor analysis should be extracted to form four dimensions. These four dimensions explained 

53.07% of the variation in the data i.e. the factors that meet the cut-off criterion with Eigen-values greater than 1 and 

generally considered satisfactory in social sciences (Hair et al.1998; 2006 as reported by Sadiq et al., 2017b). 

According to Nunnaly (1978), for the reliability test, a Cronbach’s Alpha score of 0.70 or above is considered to 

show proof of internal consistency. However, Churchill (1979) suggested a cut-off point of 0.60 or higher which is 

lower than what Nunnaly (1978) posited. Therefore, in line with Churchill (1979), the Cronbach’s Alpha values for 

the four extracted factors were appropriate for the exploratory research as their respective values were above the 

suggested cut-off point.   

The behaviour of individual items in relation to others within the same factor provides confirmation of content 

validity because the highest factor loading is central to the domains assessed by these factors (Francis et al., 2000). 

The extracted factors and their respective factor loadings exclude those whose absolute loading value is less than 

0.40. The four extracted factors which account for 55.68% of constraints variance were classified as social and 

biological constraint, institutional constraint, capital constraint and marketing constraint.  

The first factor christened “social and biological constraint” with an Eigen-value of 3.53 and loaded with five items 

accounted for 27.12% of constraint variance. The items loaded on this factor showed farmers concern on social and 

biological factors affecting sugarcane production, thus the need for social capital and strategy for control ravaging 

effect of pest and diseases in order to enhance sugarcane production in the studied area. The second factor christened 

“institutional constraint” with an Eigen value of 1.37, loaded on three items, explained 10.58% of the constraint 

variance. The items on this factor showed farmers concern on ineffectiveness and poor implementation of existing 

government policies and call for harmonization, strengthening, monitoring and re-evaluation of policies to ensure 

efficiency in the sugarcane value chain in the studied area. 

The third factor christened “capital constraint’ with an Eigen value of 1.21, loaded with four items, explained 9.34% 

of the constraint variance. The items on this factor indicate farmers concern about poor infrastructural facilities and 

call for adequate provision of good road network, sufficient and appropriate marketing facilities in order to enhance 

market efficiency in the studied area. The fourth factor labeled “market constraint” with an Eigen-value of 1.12, 

loaded with one item, explained 8.64% of constraint variance. The item loaded on this factor showed farmers 

concern on poor market outlet for their products, and thus, the need for an efficient market which will yield 

remunerative price.   



www.cribfb.com/journal/index.php/aijmsr           American International Journal of Multidisciplinary Scientific Research           Vol. 1, No. 1; 2018 

 

21 
 

4. Conclusion and Recommendation 

From the empirical finding, it can be concluded that sugarcane production in the studied area is gender bias; 

extension services and credit facilities during the study period were very poor, thus resulting in a low yield in the 

studied area. In addition, farmers in the studied area failed to utilize their social capital to ease themselves from the 

vicious cycle of poverty. Furthermore, it was observed that household sugarcane output commercialization is been 

affected by farmer’s conservatism attitude, poor extension contact, failure to take advantage of their social capital 

strength, lack of scientific storage facilities and ill-health of the member of the farming household. The major 

constraints militating against sugarcane production in the studied area were the poor road network, inadequate 

extension services, the high cost of operating capital and problem of land acquisition. Therefore, the followings 

interventions were recommended to ensure the balance between domestic supply and demand for sugarcane 

products in the studied area: 

 Farmers should be enjoined to put their social capital together in order to empower themselves via 

pecuniary advantages since most of them have no economic power.  

 Government and non-governmental organizations should wax stronger by ensuring that credit facilities 

reached the target group by relaxing some unnecessary bureaucracy or administrative procedures associated 

with agricultural credit. In addition, credit administrators should devise another credit security measures 

other than the collateral requirement as most of these farmers have no economic power.  

 The farmers in the studied area should be advised to adopt farmer to farmer extension approach since there 

is no sign for now in the provision of adequate government extension personals in the studied area. 

 There is the need for gender sensitization as women in Africa are the most affected by poverty as they are 

left to meet up with most of the family needs especially in the polygamous home.   

 Since health is wealth, the farmers need to be given proper orientation on how to put in place the basic 

precautions to maintain a healthy household.  

References 

Churchill, G.A.(1979).A Paradigm for Developing Better Measures of Marketing Constructs.  Journal of 

Marketing Research, 16(1):64-73 

Egbetokun, O.A., Bolarin, T.O., Sulaiman, A.Y., Omobowale, A.O.(2014).Determinants of  output 

commercialization among crop farming households in South Western Nigeria.  American Journal of 

Food Science and Nutrition Research, 1(4):23-27 

Francis, L., Katz, Y. and Jones, S.(2000).The reliability and validity of the Hebrew version of  the computer 

attitude scale. Computer Education, 35(2):149-59. 

Friedman, M.(1937).The use of ranks to avoid the assumption of normality implicit in the  analysis of 

variance. Journal of American Statistical Association, 32(200):675 

Gindi, A.A., Abdullah, A.M., Ismail, M.M. and Nawi, N.M.(2016).Factors influencing  consumer’s retail formats 

choice for fresh fruits purchase in Klang Valley Malaysia.  International Journal of Agricultural 

Research, Sustainability, and Food Sufficiency  (IJARSFS), 3(3):52-61 

Hair J.F. Bush, R.P. and Ortinau, D.J.(2006).Marketing Research: Within A Changing  Information Environment 

(3
rd

 Ed.). New York, USA: McGraw-Hill/Irwin 

Hair, J.F., Anderson, R.E., Tatham, R.L. and Black, W.C.(1998).Multivariate Data Analysis.  5
th

  Edition, 

Prentice Hall, Upper Saddle River, NJ.   

Hair,J.F., Black, W.C., Babin, B.J. and Anderson, R.E.(2010).Multivariate Data Analysis.  Upper Saddle 

River, NJ: Pearson Prentice Hall 

Kaiser, H.R. and Rice, J.(1974).Little Jiffy Mark IV. Educational and Psychological  Measurement, 34(1): 

111-117 

Kendall, M.G. and Smith, B.B.(1939).On the method of paired comparisons. Biometrica, 31(3:4):324-345 

Kendall, M.G. and Smith, B.B.(1939).The problem of m ranking. The Annals of  Mathematical  Statistics, 

10(3):275-287 

Kurosaki, T.(2003).Specialization and diversification in agricultural transformation: The case of  West Punjab, 

1903-92. American Journal of Agricultural Economics, 85(2):372-386. 

Mansourfar, K.(2006).Advanced Statistical Methods: Using Applied Software. University of  Tehran Press.  

Nunnaly, J.C.(1978).Psychometric Theory, 2nd ed., McGraw Hill, New York. 

Pingali, P.(1997).From subsistence to commercial production system: The Transformation of  Asian 

Agriculture. American Journal of Agricultural Economics, 79(2):628-634 

Randolph, T.F.(1992).The impact of agricultural commercialization on child nutrition. A case  study of 

smallholder household in Malawi. Been Ph.D Dissertation submitted to Cornell  University, Ithaca, New 

York, USA.   



www.cribfb.com/journal/index.php/aijmsr           American International Journal of Multidisciplinary Scientific Research           Vol. 1, No. 1; 2018 

 

22 
 

Sadiq, M S., Singh, I.P., Grema, I.J., Usman, B.I. and Yusuf, A.O.(2017).Modelling Profit  Efficiency of 

Small Scale Groundnut Farms in Niger State, Nigeria: Stochastic Profit  Frontier Approach. 

Journal of Agriculture and Agricultural Technology, Vol. 7(1):14- 23 

Sadiq, M.S., Singh, I.P., Isah, M.A., Greima, I.J. and Umar, S.M.(2017b).Strategy of minimizing  the cost of 

cultivation vis-à-vis boosting farm income of small-holder maize farmers in  Niger State of Nigeria 

using Efficiency Measurement System (EMS). Indian Journal of  Economics and Development, 

17(2a):722-728 

Sadiq, M.S., Singh, I.P., Singh, N.K. and Yakubu, G.M.(2018).Improving economic efficiency  and TFP of 

lowland paddy rice farmers in Kwara State of Nigeria. Journal of  Agricultural Sciences, 13(2):110-

129 

Timmer, C.P.(1997).Farmers and Markets: The Political Economy of New Paradigms. American  Journal of 

Agricultural Economics, 79(2):621-627. 

Tobin, J.(1958).Estimation relationship for limited dependent variables. Econometrica, 26:24-36 

Von Braun, J.(1995).Agricultural commercialization: Impacts on income and nutrition and  implication for 

policy. Food Policy, 20(3):187-202 

Wallis, W.A.(1939).The correlation ratio for ranked data. Journal of the American Statistical  Association, 

3(207):533-538 

Appendices  

 

Table 1a: Socio-economic profile of the sugarcane farmers 

Variables  Frequency  Percentage  Variables  Frequency  Percentage  

Age  Marginal  7 6.7 

20-29 5 4.8 Small  53 50.5 

30-39 24 22.9 Medium  42 40.0 

40-49 44 41.9 Large  3 2.9 

50-59 28 26.7 Total  105 100  [𝟑𝟒. 𝟓𝟏∗∗∗] 

 60 4 3.8 Seed variety   

Total 105   

(𝟒𝟒. 𝟎𝟗 ±
𝟖. 𝟔) 

100  

[𝟓𝟑. 𝟗𝟏∗∗∗] 
Local variety  105 100 

Household size Improved 

variety  

-  

4-6 2 1.9 Total  105 100 

7-9 13 12.4 Extension 

contact  

  

 10 90 85.7 Yes  14 13.3 

Total  105  

(𝟏𝟑. 𝟓𝟑 ±
𝟒. 𝟒𝟖) 

100  
[𝟏𝟑𝟏. 𝟑𝟕∗∗∗] 

No  91 86.7 

Experience   Total  105 100 [𝟓𝟔. 𝟒𝟔∗∗∗] 

 3 28 26.7 Social 

participation  

  

4-6 41 39.0 Yes  9 8.6 

7-9 26 24.8 No  96 91.4 

 10 10 9.5 Total  105 100 [𝟕𝟐. 𝟎𝟖∗∗∗] 

Total   105  

(𝟓. 𝟓𝟖 ±
𝟑. 𝟑𝟗) 

100 

[𝟏𝟖. 𝟓𝟒∗∗∗] 
Credit access    

Gender  Yes  9 8.6 

Male  105 100 No  96 91.4 

Female  - - Total  105 100 [𝟕𝟐. 𝟎𝟖∗∗∗] 
Total  105 100 

[𝟓𝟏. 𝟗𝟕∗∗∗] 
Non-farm 

activity  

  

Marital status Yes  12 11.4 



www.cribfb.com/journal/index.php/aijmsr           American International Journal of Multidisciplinary Scientific Research           Vol. 1, No. 1; 2018 

 

23 
 

Married  100 4.8 No  93 88.6 

Single  5 95.2 Total  105 100 [𝟔𝟐. 𝟒𝟖∗∗∗] 
Total  105 100 

[𝟖𝟓. 𝟗𝟓∗∗∗] 
Sickness    

Education    1-2 38 36.2 

Illiterate  21 20.0 3-4 60 57.1 

Quranic  14 13.3  5 7 6.7 

Primary  7 6.7 Total  105 100 [𝟒𝟎. 𝟓𝟏∗∗∗] 
36 34.3  25.7 Security 

threat  

  

Tertiary  36 34.3 Yes  7 6.7 

Total  105 100 

[𝟐𝟒. 𝟎𝟗∗∗∗] 
No  98 93.3 

Farm size Total  105 100 [𝟕𝟖. 𝟖𝟔∗∗∗] 

Source: Field survey, 2018   Note: *** NS; are 1% risk level and Non-significant; while values in 

(  ); [ ] are mean and standard error; and, Chi
2
 respectively  

Table 4: Constraints affecting sugarcane farmers in the studied area 

Constraints  Mean  Social & 

Biological 

constraint 

Institutional 

constraint 

Capital 

constraint  

Market   

constraint 

Communal/herdsmen 

conflict 

2.63 (4.88) 0.716    

Weak co-operative 

support 

3.26 (6.78) 0.658    

Land tenure problem 3.68 (7.79) 0.607    

Pest and diseases 3.35 (6.49) 0.525    

Inadequate credit 

facility  

3.30 (6.22) 0.523    

Price fluctuation  3.10 (6.13)  0.747   

Poor implantation of 

Govt. policy 

2.74 (5.45)  0.698   

Inadequate extension 

services 

3.76 (8.26)  0.550   

Poor road network 4.33 (8.65)   0.801  

High transportation 

cost 

3.37 (6.60)   0.567  

High cost of hired 

labour 

3.67 (7.60)   0.482  

High cost of agro-input 3.86 (8.28)   0.476  

Poor output market 3.48 (6.86)    0.867 

Kendall’s coefficient 

(KCC) 

0.101     

KCC Chi
2
 (𝝌2

) 126.83***     

Friedman’s Chi
2
 (𝝌2

)  126.83***     

Eigen-value  3.526 1.375 1.214 1.123 

% of variance   27.123 10.580 9.338 8.641 

Cronbach’s Alpha  0.666 0.658 0.675 - 

Kaiser-Meyer-Olkin 

test 

0.712     

Bartlett’s Test of 

Sphericity (𝝌2
)  

263.637***     

Source: Field survey, 2018 

Value in parenthesis is mean rank 



www.cribfb.com/journal/index.php/aijmsr           American International Journal of Multidisciplinary Scientific Research           Vol. 1, No. 1; 2018 

 

24 
 

 

 

Copyrights 

Copyright for this article is retained by the author(s), with first publication rights granted to the journal. 

This is an open-access article distributed under the terms and conditions of the Creative Commons Attribution   

license (http://creativecommons.org/licenses/by/4.0/). 

 

 

 

 

 


