Determinants of Market Participation among Pineapple Farmers in Aiyedaade Local Government Area, Osun State, Nigeria

Abstract

This study examined the determinants of market participation among pineapple farmers in Aiyedaade Local Government Area of Osun State, Nigeria. Interestingly, in spite of major constraints, such as bad roads, inadequate storage facilities, and low level of government support, almost all of the farmers participated in the market. This could be sustained if market centers are established at strategic locations not too far from farms and if loans are made accessible to the farmers with low interest rates requiring simplified procedures for processing. Intervention strategies for improvement of pineapple farmers’ market participation should also be guided by farmers age, farming experience, and marital status.

KEYWORDS:

• market participation
• pineapple farmers
• Osun State
• Nigeria

INTRODUCTION

Pineapple (Ananas comosus) is among the important horticultural fruit crops. It is cultivated mainly for its fruit, which is consumed fresh, canned, or juiced (Adinya et al., 2010). The fermented juice of the fruit is used to make vinegar and alcoholic spirit, while the covering and other wastes from the fruit are used as livestock feed (Iwuchukwu et al., 2013). It is also used as an ingredient in a variety of foods, including pizzas, condiments, sweets, savouries, cakes, pastries, yogurt, punch, and ice-cream (Medina and Garcia, 2005; Rohrbach et al., 2003). Pineapple, the second most important harvested tropical fruit after bananas, contributes to over 20% of the world’s production of tropical fruits (Coveca, 2002). According to the Food and Agriculture Organization (FAO, 2013), the world’s highest producers of pineapple are Thailand, Philippines, Brazil, China, India, Nigeria, Kenya, Indonesia, México, and Costa Rica. On the global scene, Nigeria has the largest land area for pineapple production and is ranked the eighth largest pineapple producing country. The fruit is an economic crop that has encouraging potential for foreign exchange earnings. It can also increase national income, resulting in higher income for farmers and expansion of local industries (Fawole, 2008). Marketing of pineapple is as vital as its production, since an efficient marketing system helps to complement demand and supply and also stimulates production (Adesope et al., 2009). However, pineapple farmers are frequently faced with problems that prevent them from participating in the market. These include low income, fluctuation in the price of produce, inadequate access to credit, and storage facilities and many other unappealing conditions. These negatively affect their market participation and consequently their welfare. The pineapple farmers most times have low bargaining power, while the buyers are the dominant actor in price setting. The irregularity in price frustrates them and mostly leaves them with no choice than to sell the produce at ridiculous prices to avoid post-harvest losses (Amao et al., 2011). This is reflected in the analysis of the state of Nigerian food losses during marketing, which showed that pineapple accounts for up to 70% of post-harvest losses (Amao et al., 2011; Malcom, 1999;). Nigeria was the 6th largest producer of pineapple in the world in 1999 but because production and marketing trends were not effectively encouraged, the country is presently the 8th largest producer (FMARD, 2013). This is an indication that commercial production for export and local consumption is not properly enhanced (FAO, 2013).The current production of pineapple in Nigeria is about 17,000 metric tons per annum (Onwualu, n.d). However, according to Iwuchukwu et al. (2013), Nigeria can produce 364,490 metric tons of pineapple per annum if its production and marketing challenges are properly addressed.

Increased market participation is therefore pertinent to ease the farmers’ shift into commercial agriculture, which will consequently result into improved economic development (Ohen et al., 2013).

REVIEW OF EMPIRICAL STUDIES ON MARKET PARTICIPATION AMONG FARMERS

Several studies have been carried out on the determinants of market participation of farmers. For instance, Gani and Adeoti (2011) in their study on market participation and rural poverty among farmers in Northern part of Taraba State, Nigeria discovered that high transportation cost, poor infrastructure, high dependency ratio, distance, cooperative membership, and output size (output commercialization ratio) were important variables affecting effective market participation. Similarly, a study in South Africa by Schalkwyk et al. (2012) on strategies to unlock market access to smallholders revealed that factors, such as poor infrastructure, lack of market transport, lack of market information, insufficient expertise on use of grades and standards, inability to conclude on contractual agreements, and poor organizational support, have led to inefficient use of different markets. However, some literatures report conflicting findings on the relationship between infrastructure and market participation decisions, while some studies report infrastructure as an influential factor in market participation (Boughton et al., 2007; Goetz, 1992; Heltberg and Tarp, 2002; Key et al., 2000; Renkkow et al., 2004). Other studies indicate infrastructure as not being correlated with market participation (Lapar et al., 2003). However, in some other studies, correlation between infrastructure and market participation was found to differ among sellers and buyers (Goetz, 1992; Key et al., 2000).

According to Egbetokun and Omonona (2012) in their study on the determinants of market participation in the food market in Ogun state, factors such as marital status, family size, years of experience, and farm size were found to be the major factors explaining participation in the food market. Specifically, a year increase in the age of the farmers as well as a higher level of education led to a decrease in market participation. Similarly, Oduro et al. (2004) reported that the age of rural farmers had a negative effect on market participation. This they attributed to the fact that older people tend to have more dependents and more subsistence activities, which may affect their participation adversely. However, contrary to these findings, Enete and Igbokwe (2009) in their study on cassava market participation decisions of producing households in Africa, found out that as the farmers get older, the higher the probability of their participation in the market.

Several approaches were used by investigators to examine the level of market participation among farmers. For instance, Onoja et al. (2012) employed a Logistic Regression Model to examine the determinants of the level of fish farmers’ participation in the market. The implicit form of the model was used to find the rate of change in a level of participation in fish marketing while chi-square values were used to indicate the variations in the probabilities of participating in fish marketing. Similarly, econometric approaches were used by Arinloye et al. (2012) to examine the factors affecting market channel participation. Selected market channels were evaluated using the Pearson chi-squared (χ²), while the multivariate Probit model assumed correlation and interdependency in farmers’ market participation decisions. In the same vein, Egbetokun and Omonona (2012) used the Probit model in their study to examine the determinants of farmers’ participation in the food market in Ogun State, Nigeria. On the other hand, Shephard et al. (2011), in their study on the determinants of cereal market participation in sub-Saharan Africa, used an ordinary least square (OLS) regression model to identify the factors influencing farmers’ level of participation in the cereal output market.

In addition, market participation has been conceptualized based on different assumptions. For example, Boughton et al. (2007) viewed market participation as both a cause and a consequence of economic development. According to them, markets offer households the opportunity to specialize according to comparative advantage and thereby enjoy welfare gains from trade. Omiti et al. (2009) opined that as the market share of agricultural output increases, input utilization decisions and output combinations are progressively guided by profit maximization objectives. Similarly, Doll and Orazem (1984) explained utility in terms of profits that chain actors gain from their activity. Farmers obtain different levels of profit in different contexts, implying that the choice of producing and supplying is influenced by profit prospects. A farmer’s decision to sell in a given market is assumed to be derived from the maximization of expected utility or profit he or she expects to gain from this market (Frank & Glass, 1991; McFadden, 1986; Salvatore, 2003).

The review of literature above shows clearly that there is a dearth of studies on the determinants of market participation among crop farmers, but most especially pineapple farmers. Based on this foregoing, this study seeks to examine the level of market participation of pineapple farmers in Aiyedaade Local Government Area of Osun State, Nigeria.

MATERIALS AND METHOD

This study was carried out in Aiyedaade Local Government Area of Osun State. Osun State is located in the Southwestern part of Nigeria. It is bounded in the north by Kwara State, in the east by Ondo State, in the south by Ogun State, and in the west by Oyo State. The state has 30 local government areas and the people of the state are mainly traders, artisans, and farmers. Aiyedaade Local Government Area was purposively selected for this study because of the high level of pineapple production by farmers in the area. The Local Government Area (LGA) is headquartered in the town of Gbongan and bounded by Isokan, Irewole, and Aiyedire Local Governments to the East and Ife North Local Government to the West. It is geographically located between Latitude 7° 28′ 00″ N to 7.46667° N and Longitude 4° 21′ 00″ E to 4.35000° E. It has an area of 1,113 km² (430 sq m), and a population of 150,392 (NPC, 2006). The region has an average high temperature and high relative humidity with two distinct seasons, namely, the rainy season, which lasts from March/April to October/November and the dry season which lasts from October/November to March/April. Pineapple (Ananas comosus) is mainly grown during the rainy season in Aiyedaade Local Government Area and the people are mainly peasant/subsistence farmers predominantly living in rural communities.

Primary data used in the study were collected from the respondents with the aid of a well structured questionnaire. A multi-stage sampling technique was used in selecting the respondents. The first stage was the purposive selection of one Local Government area out of the 30 local governments in Osun State. The second stage involved the random selection of 3 wards out of the 11 wards in the Local Government while the third stage involved the random selection of 40 pineapple farmers from each of the 3 wards, which gave a total of 120 pineapple farmers.

The analytical methods used in this study include Descriptive Statistics, Sales Indexing, and the Ordinary Least Square Model. Descriptive statistics, such as frequency distribution tables, percentage, mean, and standard deviation were used to analyze the respondents’ socio-economic characteristics. Indexing (sales index) was used to examine the level of market participation in terms of sales as a fraction of total output. It is defined as follows:

where:

• SI = Sales index;

• ΣCS = Crop sales in dozen/hectare;

• ΣCP = Crop production in dozen/hectare.

This definition follows the one used by Rios et al. (2009).

The Ordinary Least Square Model was used to examine the factors influencing the level of market participation among the pineapple farmers. It was used for analyzing the mean response of the variable Y, which changes according to the magnitude of an intervention variable X. The Ordinary Least Square Model for the participation of pineapple farmers is specified as follows:

where

• Y* = Latent variable representing levels of market participation, i.e., the dependent variable (Y*) is the sales index (proxy for the level of market participation);

• β_i = The independent variable which is a vector of farmers’ characteristics relevant in explaining the levels of market participation;

• μ_i = Error term.

The independent variables included in the model are specified as follows:

• X₁ = Age of farmer (years);

• X₂ = Farming experience (years);

• X₃ = Household size (number);

• X₄ = Agric marketing training (1 if yes, 0 if otherwise);

• X₅ = Access to market information (1 if yes, 0 if otherwise);

• X₆ = Distance to nearest market (Km);

• X₇ = Rejection by buyers (1= yes, 0 if otherwise);

• X₈ = Access to credit (1 = yes, 0 if otherwise);

• X₉ = Secondary education (1 if secondary, 0 if otherwise);

• X₁₀ = Gender of household head (1 if male, 0 if otherwise);

• X₁₁ = Cooperative membership (1 if member, 0 if otherwise);

• X₁₂ = Extension visit (1 if visited, 0 if otherwise);

• X₁₃ = Land ownership (1 if owned, 0 if otherwise);

• X₁₄ = Marital status (1 if married, 0 if otherwise).

RESULTS AND DISCUSSION

Table 1 presents selected socio-economic characteristics of the respondents. The result of the analysis showed that the respondents’ mean age and household size were about 58.8 years and 13 members, respectively. This implies that a good number of the sampled pineapple farmers are aged with a relatively large household size. Also, most of the pineapple farmers were males (96.7%) and married (95.0%) with more than one-quarter having no formal education. While a considerable proportion of respondents had between 21 and 30 years of farming experience, about three-fifths (60.0%) of the respondents inherited the land that they cultivated, with the majority (78.3%) cultivating between 0.1 and 1.0 hectares. Also, more than half of the respondents (55%) grew two types of cultivars, namely, the Smooth Cayenne and the Common Rough/Queen, respectively.

TABLE 1 Selected Socioeconomic Characteristics of the Respondents

Variables	Frequency	Percentage
Sex
Male	116	96.7
Female	4	3.3
Total	120	100.0
Age (in years)
40–50	28	23.3
51–60	51	42.5
61–70	29	24.2
≥71	12	10.0
Total	120	100.0
Mean	58.8
SD	9.0
Marital Status
Single	3	2.5
Married	114	95.0
Separated/Divorced	3	2.5
Total	120	100.0
Household Size
1–10	47	39.2
11–20	70	58.3
21–30	3	2.5
Total	120	100.0
Mean	12.6
SD	4.8
Educational Status
No formal education	34	28.3
Primary education	60	50.0
Secondary education	26	21.7
Total	120	100.0
Years of Experience
1–10	4	3.3
11–20	33	27.5
21–30	46	38.3
>30	37	30.8
Total	120	100.0
Farm Size (Hectares)
0.1–1.0	94	78.3
1.1–3.0	15	12.5
3.1–5.0	11	9.1
Total	120	100.0
Mode of Acquisition of Land
Inheritance	72	60.0
Rent	32	26.7
Lease	16	13.3
Total	120	100.0
Variety of Pineapple Grown
Smooth cayenne	23	19.2
Queen variety	31	25.8
Both	66	55.0
Total	120	100.0

(Continued)

TABLE 1 (Continued)

Variables	Frequency	Percentage
Access to Credit
Yes	102	85.0
No	18	15.0
Total	120	100.0
Membership of Association
Member	118	98.3
Non member	2	1.7
Total	120	100.0

Source: Field Survey (2013).

Analysis of Market Participation

The result of the analysis of index of market participation presented in Table 2 revealed that on the average, the pineapple farmers sold almost all of their produce (94%) in the market. This is an indication of a high level of market participation among pineapple farmers in the study area. The highly perishable nature of the pineapple fruits leave the farmers with no choice but to sell off their produce most times at ridiculous prices in order to avoid post-harvest losses. Farmers that sold the least, sold 59% of their pineapple produce while, on the other hand, those that sold the most, sold almost all (99%) of their produce.

TABLE 2 Index of Market Participation of Respondents

Index of market participation of respondents
Mean	0.94
Std. Deviation	0.48
Minimum	0.59
Maximum	0.99

Source: Author’s computation (2013).

The profile of pineapple farmers by sales index as presented in Table 3 revealed that female pineapple farmers participated more in the market even though there were more male farmers in the study area. Also, farmers that had access to inputs, such as fertilizer, herbicides, and pesticides, participated more than those that did not have access to farm inputs. Respondents with secondary education participated more than those with primary or no formal education. Likewise, those that had one form of training or the other participated more than those who did not have any form of training.

TABLE 3 Profile of Pineapple Farmers by Sales Index

Variables	Mean	Standard deviation
Sex
Male	0.94	0.049
Female	0.95	0.030
Educational Status
No formal education	0.94	0.036
Primary	0.94	0.057
Secondary	0.95	0.041
Access to Input
Yes	0.94	0.049
No	0.91	0.042
Training in Marketing
Access	0.95	0.050
No access	0.94	0.048

Source: Author’s computation (2013).

The ranking of constraints faced by the pineapple farmers by severity presented in Table 4 showed that the most severe constraint (1st based on ranking) was bad roads. The respondents mainly transported their produce to the market by road. However, as a result of the perishable nature of pineapple, which is due to its high moisture content, bad roads accounted for a huge amount of post-harvest losses during transportation. The 2nd most severe constraint was inadequate storage facilities. Again, this is due to the highly perishable nature of pineapple and the fact that in most cases, farmers do not sell all their harvested produce at one market trip, necessitating the need for storage facilities. Low level of Government support was also reported as a major constraint (3rd based on severity rank) by all the pineapple farmers in the study area. This might be due to the failure of the government to provide modern agricultural technology, such as improved seed, fertilizer, market infrastructure, and necessary extension services to encourage market participation among the farmers within the study area.

TABLE 4 Constraints Faced by the Respondents Based on Severity

Constraints	Weighted score	%	Weighted mean	%	Rank
Low crop income	166	8.3	1.383	8.3	7th
Inadequate access to credit facility	120	6.0	1.000	6.0	8th
Long distance to market	265	13.3	2.208	13.3	5th
High cost of transportation	276	13.8	2.300	13.8	4th
High level of dependant	187	9.4	1.558	9.4	6th
Inadequate storage facilities	317	15.9	2.641	15.9	2nd
Low level of government support	313	15.7	2.608	15.7	3rd
Bad roads	351	17.6	2.925	17.6	1st
Total	1995	100.0	16.624	100

Source: Author’s computation (2013).

Also, respondents reported high cost of transportation as a major constraint. This was the 4th constraint based on severity. The cost of transporting pineapple to the market in one trip was estimated at ₦3,280. This high cost could be owed to the fact that more than half of the respondents (63.3%) did not have any owned means of transportation. Similarly, farmers reported the long distance to market as one of the severe constraints they faced. This constraint was the 5th based on severity. This could be attributed to the long distance from the farm to the local market where 95.8% of the respondents sold their produce. On the other hand, the high level of dependants in the household was reported as a less severe constraint (6th). This may be attributed to the fact that most of the farmers, though even at their old age, had a number of children that depended on them for their feeding and upkeep; these children were being used as unpaid family labor. Low crop income was the 7th constraint based on severity. In other words, it was not a major constraint faced by the pineapple farmers in the study area. This could be due to a result of farmers’ derived satisfaction from household consumption as well as unsold pineapple given out as gifts because of its highly perishable nature. Finally, the least severe constraint (8th) reported by the pineapple farmers in Aiyedaade Local Government as shown in the table was inadequate access to credit. This could be owing to the fact that the majority of the farmers belonged to one cooperative society or the other where they normally access credit facilities. This is corroborated by the result of the descriptive statistics in this study in which 98.3% and 85% of the respondents belonged to an association and had access to credit, respectively. Consequently, accessing credit was not a major limiting factor for pineapple producers in this area.

TABLE 5 Ordinary Least Square Regression Result of Factors Influencing Market Participation

Variables	Coefficient	T-value
Age	−0.0010^**	−2.23
Farming experience	0.0009^**	2.33
Household size	−0.0009	−1.12
Agric marketing training	0.0066	0.59
Access to information	−0.0025	−0.33
Distance to market	−0.0051^**	−2.44
Rejection buy buyers	−0.0006	−0.09
Access to credit	0.0321^***	2.92
Secondary education	0.0238^**	2.16
Male	0.0085	0.43
Members of association	0.0264	0.98
Access to extension services	0.0263	1.33
Landownership	0.0065	0.82
Marital status	0.0847^***	4.70
_cons^***	0.8817	18.85

Note: ^**Significant at 5% level; ^***Significant at 1% level. Number of observations: 120; F(14, 105) = 8.21; Prob > F = 0.0000; R² = 0.5226; Adj R² = 0.4589.

Table 5 shows the ordinary least square (OLS) estimation of the factors influencing farmers’ level of participation in the market. The result showed that the model was statistically significant at 1% with an Adjusted R² of 0.4589. Six variables were significant in explaining farmers’ level of participation in the market and these variables included: age, farming experience, distance to market, access to credit, secondary education, and marital status of the household head. The coefficient of age was negative and significant implying that a year increase in age will lead to a decrease in the level of market participation. In other words, as the household head gets older, there is a reduction in the level of market participation. This could be attributed to the fact that as they get older they become more inactive and therefore cannot participate fully in the market. This finding corroborates the findings of Fakayode et al. (2012) but is contrary to the findings of Adesope et al. (2009) in which, as the household heads got older, they participated more in the market. Similarly, the coefficient of distance to market was negative and significant indicating that an increase in the distance to market will result in a decrease in the level of market participation of pineapple farmers.

On the other hand, the positive sign of access to credit indicates that the respondents that had access to credit participated more than those without access to credit. Also, farming experience of the pineapple farmers impacted positively on market participation. This implies that farmers who had been engaged in pineapple farming for a higher number of years participated more in the market. In the same vein, the positive effect of the secondary education variable implies that farmers with secondary education are likely to participate in the market more. This may be due to the fact that level of education is an important tool that determines marketing performance and human capital development. The level of market participation also increased for married household heads. This finding is in consonance with the findings of Nnadi and Akwiwu (2008) and Egbetokun and Omonona (2012).

CONCLUSION AND POLICY RECOMMENDATIONS

Most of the pineapple farmers participated in the market, especially the females, those who had access to inputs and those with secondary education. This is particularly noteworthy considering the fact that they were faced with major constraints, such as bad roads, inadequate storage facilities, low level of government support, high cost of transportation, and long distance to market. However, most of the respondents inherited the land that they cultivated and did not have any problem in accessing credit since they were mostly members of one form of association or the other. Since market participation in this area is positively influenced by access to credit, secondary education, marital status, and farming experience and negatively influenced by age and distance to market, efforts should be geared towards establishing market centers at strategic locations not far from farms and on improved access to credit by encouraging associations to form stronger linkages aimed at improving the welfare of these pineapple farmers. Further, loans should be made accessible with low interest rates and procedures for getting such loans simplified to encourage the farmers. In order to ensure higher productivity and efficiency, intervention strategies for improvement of market participation should be guided by farmers’ age, farming experience, and marital status.