search
for
 About Bioline  All Journals  Testimonials  Membership  News  Donations


African Crop Science Journal
African Crop Science Society
ISSN: 1021-9730 EISSN: 2072-6589
Vol. 9, Num. 3, 2001




African Crop Science Journal, Vol. 9. No. 3, pp. 537-547

DETERMINANTS OF MARKET PRODUCTION OF COOKING BANANA IN NIGERIA

M. TSHIUNZA, J. LEMCHI1 and A. TENKOUANO

International Institute of Tropical Agriculture, Oyo Road, PMB 5320, Ibadan, Nigeria
1Department of Agricultural Economics and Extension, Federal University of Technology, PMB 1526, Owerri, Nigeria

Received 1 December, 1999
Accepted 12 January, 2001

Code Number: cs01073

ABSTRACT

The factors that influence farmers' decisions to produce cooking banana for market in southeast Nigeria were examined. Data were collected from a random sample of 217 farmers through the use of a structured questionnaire. Results of the study indicate that about 80% of the farmers interviewed produce cooking banana both for household consumption and for sale. The proportion of cooking banana sold ranged from 10% to 90% with an average of 45%. Thus, cooking banana performs the dual role of providing food for the households, as well as being an additional source of cash income. Tobit regression analysis revealed that the price and the ripening stage at sale of cooking banana, as well as the presence of middlemen in the marketing chain were the most important determinants of the proportion of cooking banana planted for market. This indicates that cooking banana growers readily respond to market forces. Age and gender ownership of cooking banana also influenced the proportion of the crop planted for market. Increased involvement of wholesalers and processors in the marketing chain of the crop will probably enhance its market in the region.

Key Words: Commercialisation, farmers' decision, market factors, Musa spp. (ABB)

Résumé


Cette étude a examiné les facteurs qui influencent la décision du paysan de produire la banane à cuire pour le marché dans le sud-est du Nigéria. Les résultats de l'étude montrent qu'environ 80% de paysans interrogés produisent la banane à cuire à la fois pour l'autoconsommation et pour la vente. La part destinée au marché varie entre 10% et 90% avec une moyenne de 45%. Ces résultats suggèrent que la banane à cuire sert autant de nourriture que de source de revenu monétaire pour le paysan. Les résultats de l'analyse de régression indiquent que la décision de produire la banane à cuire pour le marché dépend surtout du prix, de la présence d'intermédiaires dans le circuit de commercialisation ainsi que du stade de maturation du fruit au moment de la vente. Ceci signifie que le paysan répond positivement aux force du marché dans la production de la banane à cuire. L'âge et le sexe du propriétaire de la banane à cuire influencent également la proportion de la production destinée au marché. Une intervention accrue des grossistes et des transformateurs dals le circuit de commericialisation de la banane à cuire contribuerait à accroîte l'importance commericiale de cette culture dans la region.

Mots Clés: Commercialisation, decision de production, facteurs du marché, Musa spp. (ABB)

Cooking Banana (Musa spp., ABB genome) was introduced into southeast Nigeria in the late 1980's from Asia by the International Institute of Tropical Agriculture (IITA) as a short-term strategy to combat the incidence of black sigatoka disease on plantain (Vuylsteke, 1995; Ferris et al., 1996; 1997). Since its introduction, research efforts have been concentrated mainly on the agronomic aspects (Hahn et al., 1990; PBIP, 1994; 1995; 1996) and processing methods (Oyesile, 1987; Hahn et al., 1990; Ferris et al., 1996, 1997) with little attention given to its market potential. As a result, little is known about cooking banana commercial status and its marketability.

The crucial role of marketing in stimulating agricultural production and consumption has been emphasised by many authors. For instance, Southworth (1981) observed that growth in agricultural output could scarcely be achieved without markets. Annon (1989) pointed out that the adoption of new technologies by farmers depends heavily on market opportunities, while Lynam (1990) noted that the potential to increase the production of a particular crop is dependent on its marketability. In a recent study on the market potential of cooking banana, Ferris et al. (1997) asserts that for successful adoption, a new crop or cultivar should offer a combination of good agronomic traits and a viable market. Research on markets and marketing systems provides a better understanding of the factors affecting demand and supply, and thus allows prioritisation of agricultural research and investment needs (INFOMUSA, 1998). Therefore, if cooking banana is to be widely adopted and integrated in Nigerian cropping systems, it has to be marketable. A recent study by Tshiunza et al. (1998) showed that apart from production for household food needs, cooking banana is also produced by Nigerian farmers for market, and that farmers who sold more bunches had more cooking banana mats (the main stem and its suckers). However, their study did not establish the driving forces behind the farmers' decision to produce cooking banana for market in Nigeria. Therefore, the major objective of this study was to determine which factors affect farmers' decision with regard to the proportion of cooking banana planted for market.

METHODOLOGY

Study area and selection of respondents. The study was conducted between June and October 1998 in southeast Nigeria. It was confined to Bayelsa, Imo, and Rivers states, where cooking banana was initially introduced, and where it is most commonly found (Tshiunza et al., 1999). Twenty villages were randomly selected from a list of 702 villages where cooking banana has been introduced. Based on the intensity of cooking banana cropping in each village (i.e., number of cooking banana farmers), farmers growing cooking banana were selected randomly. In total, 217 farmers, comprising 21 from Bayelsa state, 64 from Imo state and 132 from Rivers state, were selected for interview.

Data collection and analysis. Data were collected from the selected farmers using a structured questionnaire. The data were classified as farmer-related or market-related. Farmer-related data included socio-economic information, such as age, household size, gender ownership of cooking banana, major occupation, educational back-ground, and farmer's experience (years) in cropping and selling cooking banana and plantain. Market-related data included the proportion of cooking banana sold, major place(s) of sale of cooking banana (home or market), major buyers of cooking banana (consumers or middlemen), as well as the presence of regular buyers of cooking banana. Other data are the average selling prices of cooking banana and plantain by farmers as well as the major ripening stages in which cooking banana is sold. The above variables are defined and presented in Table 1.

Due to incomplete data (omission of household size from some respondents), data analysis is based on information obtained from 147 farmers. Descriptive statistics such as percentages, means, and frequencies are used for data analysis, while a tobit regression analysis is used to determine which factors explained the proportion of cooking banana produced for market.

The regression model: Theoretical framework. The tobit model presents a suitable regression alternative for the analysis of the determinants of a variable so distributed (Akinola and Young, 1985; Zegeye, 1990; Nweke, 1996). According to these authors, the theoretical framework of the tobit model is explained by the threshold paradigm. Following Nweke (1996), the decision to sell cooking banana by farmers may be considered as a dichotomous choice between two mutually exclusive alternatives. By implication, there is a 'break point' in the dimension of explanatory variables below which a stimulus elicits no observable response (Zegeye, 1990; Adesina and Baidu-Forson, 1995; Nweke, 1996). It is only when the strength of the stimulus exceeds the threshold point that a reaction occurs, and the second decision on the proportion to sale is taken (Nweke, 1996). Let Y be the decision variable (the perceived benefit from selling), which is the dependent variable, Y* an underlying latent variable that indexes the decision on proportion to sell, and X a vector of explanatory variables. Y takes on two values: Y = Y* if Y* > 0 (if the decision results in sale), and Y = 0 if Y* <= 0 (if decision results in no sale or home use). At values of X greater than the break point, there is a probability of 1 for sale, and the proportion sold, represented by Y* is continuous. At X values equal to or less than the break point, then the probability of sale becomes zero and the proportion sold is zero. Following Adesina and Baidu-Forson (1995) and Nweke (1996), the stochastic tobit model becomes:

Yi = Yi* = Xiβi Xi if Xiβ + εi > T

= 0 if Xiβ + εi < T ............. (I)

i = 1, 2, ..., N

where: N = number of farmers

Yi = the proportion sold variable,
Xi = n x k matrix of explanatory variables,
β = the k x 1 vector of parameters to be estimated,
T = the threshold point, and
ei = error term, assuming normal distribution N (0, σ2).

The parameters of the tobit model are estimated through the maximum likelihood method (Zegeye, 1990) as follows:

L = ? [1-F(Xiβ/δ)] ? δ - 1F[(Yi- Xiβ)/δ] ...... (II)
yi=0 yi=1

where L = the likelihood function.

The significance of the individual coefficients is tested by the ratio of the estimated coefficient and its corresponding standard error (asymptotic t-value). The significance or fit of the coefficients is assessed through the log likelihood ratio test (LRT), which is the Chi-square distributed with k degrees of freedom, where k is the number of parameters in the model minus the constant (Zegeye, 1990), calculated thus:

LRT= 2logλ=-2(logLmin.-logLmax)...... (III)
where Lmin=log likelihood value for the constant only,
Lmax=log likelihood when all variagbles are included

There is a positive relationship between the dependent variable and the explanatory variables if the value of the statistic exceeds the chosen critical value (Aldrich and Nelson, 1984).

Empirical model. The proportion of cooking banana sold by the farmers was obtained by asking the respondents to indicate the number of parts out of ten, of total cooking banana harvested in a year that was consumed or sold. To facilitate response, they were asked to indicate the number out of every ten bunches harvested that is usually sold or consumed. Through this, an approximate proportion of total production sold was obtained. This was regressed in a tobit model on both farmer- and market-related variables and the maximum likelihood method applied to estimate the parameters.

The personal characteristics of farmers such as age, household size, extent of formal education, and primary occupation are among factors which have in previous studies been identified as influencing commercialisation of farm enterprise (Nweke et al., 1994; Nweke, 1996). Younger farmers are usually more market-oriented than older farmers. Farmer's age (AGE) is therefore expected to negatively affect the proportion of cooking banana produced for market. Larger households usually have more food needs, and as a result are likely to produce more for home consumption than for market. The size of household (HHOLD) is therefore expected to have a negative impact on the proportion of cooking banana production sold in the market. More educated farmers are usually more market-oriented. Level of education (EDUC) is therefore likely to positively impact the proportion of cooking banana produced for market. People whose primary occupation is not farming usually get involved in agricultural business as an additional source of income and tend to be more market-oriented than professional farmers whose first production objective is traditionally that of subsistence. Farming as a primary occupation (OCCUP) is therefore expected to negatively affect the proportion of cooking banana planted for market. In a rural African setting, women are more often responsible for food expenditure in the household (Hahn, 1985); as a result, produce from women's fields is more frequently used for subsistence than produce from men's fields. Male ownership of cooking banana crop (OWNER) is therefore likely to lead to a greater proportion of cooking banana sold in the market. Years of cropping cooking banana (CBEXP), as well as the number of years a farmer has been selling the crop (YRSELLCB) are likely to influence positively the extent of cooking banana production for market. As the farmer acquires experience through years of continuous cropping and sale of the crop, the farmer's knowledge about the characteristics of the market demand increases. This stimulates increased production for market.
Places of sale and types of buyers of agricultural products are good indicators of the level of market pressure exerted on agricultural production and the level of response of farmers. Farmers whose primary point of sale is their homes are unlikely to produce more for market, as opposed to farmers who sell mostly in the market. If markets are a major place of sale of cooking banana this indicates a high demand for the crop. The attendance of markets (MARKET) by cooking banana farmers is therefore expected to positively affect the proportion of cooking banana produced for market. Also, farmers that have regular buyers of cooking banana fruit (CUSTOMER) are likely to produce more for market, while those that sell mostly to consumers (CONSUMA) are likely to be less commercial oriented in production. Sales to consumers by producers do not increase market opportunities for farmers, and thus, tends to restrict the level of production for market.

The demand for the different maturation stages of cooking banana is likely to affect the amount produced for market. If some ripening stages are in less demand than others, the overall demand for the product will be reduced. The demand for cooking banana is likely to be restricted to the green form since it is known to quickly spoil at ripening stage. Green form (SOLDFORM) as the major ripening stage demanded by cooking banana users is therefore likely to have a negative impact on the proportion of cooking banana produced for market.

In places where the demand for cooking banana is high, the price of cooking banana is likely to be high and therefore to positively influence its commercialisation by farmers. Cooking banana price (PRICECB) is therefore expected to positively influence the proportion produced for market.

The plantain price is likely to impact the demand for cooking banana: when plantain price increases, many people are likely to substitute cooking banana for plantain, and consequently exert a pressure on cooking banana producers. Plantain price (PRICEPB) is therefore expected to positively affect the proportion of cooking banana produced for market.

Both full and step-wise regression models were carried out. The default (P = 0.2) was the basis for variable entry. The step-wise model was used to identify variables that were the most important in driving the decisions of farmers to produce cooking banana for the market.

RESULTS AND DISCUSSION


Proportion of cooking banana produced for market. The proportion of harvested cooking banana sold by farmers is a proxy for the proportion of cooking banana planted/produced for market. The proportion sold has an upper limit of 100% and a lower limit of zero percent. From the results, the distribution of proportion sold showed that about 20% of farmers are within the zero limit, while zero percent assumed the upper limit of 100%. More than 80% of the farmers interviewed produced cooking banana for both household consumption and marketing; only 18% of the interviewees produced cooking banana exclusively for household consumption (Fig. 1). No farmer produced cooking banana entirely for market. The proportion produced for market varies significantly and ranges from 10% to 90% with an average of 45%. This percentage is very high given the fact that cooking banana is a new crop in the region, introduced only about a decade ago. In Rwanda, survey reports showed that more than half of cooking banana produced is sold, and that farmers with the highest percentage of cooking banana have the highest farm income (Tollens, 1995). Also, Nweke (1996) reported that among the cooking banana producing households in the cassava-growing region of sub-Saharan Africa, 27% were selling cooking banana, and that cooking banana was a major source of cash income for these households.

About 42% of the farmers selling cooking banana sold less than 50% of their production, while 58% sold at least 50% of their production. About 15% of the farmers selling cooking banana produced 80 % to 90% for market. The above results show that cooking banana plays an important role in providing both food and cash income to the producing households.

Determinants of proportion of cooking banana sold by farmers. From the regression results, all the variables together explained about 13% of the variations in the proportion of cooking banana produced for sale by farmers (Table 2). Though the coefficient of determination is low, the overall fit (the likelihood ratio test) is very significant. This indicates that the explanatory variables have a significant effect individually or jointly on the probability of choice (Manyong et al., 1996).

The relationship between farmer's age (AGE) and proportion of cooking banana sold is negative and statistically significant (Table 2). Older farmers are likely to be more subsistence oriented in their production decisions. Nweke (1996) reported that older household heads/farmers include people who had retired from active farming or other economic activities, and thus produce mostly on a subsistence level for home use. The above result and Nweke's findings conforms to earlier reports by Burton et al. (1999), but in contrast with findings of Manyong et al. (1996) and CIMMYT (1993).

The probability that farmers who have regular buyers (CUSTOMER) of cooking banana will increase production for market was positive and significant in the step-wise version (Table 2). When consumers (CONSUMA) were the major buyers of cooking banana this had a highly significant negative influence on the proportion produced for sale (Table 2). This indicates that the proportion of cooking banana meant for market was higher among farmers that sold primarily to middlemen than those who sold mostly to consumers. The probability that farmers will produce more for market was significantly negative both in the full and step-wise models where farmers sold their cooking banana only when it was green (SOLDFORM) (Table 2). In other words, a significantly lower proportion was produced for market where cooking banana was mostly sold green.

As expected, the probability that farmers will produce more cooking banana for market given increased cooking banana prices (PRICECB) was positively significant in both the full model and the step-wise model (Table 2). The proportion of cooking banana sold has a negative, though non-significant, relationship with plantain price (PRICEPB) (Table 2). Higher plantain prices will induce higher demand for cooking banana. This assertion is supported by results in Table 3.

The farmer-related variables. The farmers' age ranged from 21 to 80 years with a mean of 45 years (Table 4). More than 56 % of the farmers were aged between 31 and 50 years while only 13% aged 30 years and below. Thus, the majority of the farmers were within the active age bracket, and were more likely to be commercial oriented in their production. Contrary to expectation, the effect of the size of household (HHOLD) was positive but non-significant. Larger households tended to plant greater proportion of their cooking banana for market than smaller households. As the size of household increased, the need for cash income also increased, thereby increasing the household's farm production for market. If cooking banana were a subsistence crop, the proportion produced for sale would decrease as household size increased. In the UK, Burton et al. (1999) pointed out that household size was found to positively influence farm production and the adoption of organic farming. Households that are in decline have the lowest consumer/worker ratios and thus the least need for increased farm production (CIMMYT, 1993). In the study, the household size ranged from 1 to 60 persons, with a mean of 10 (Table 4). Only about 4% of the respondents had a household size of more than 20 persons while 74% had a household size of less than or equal to 10 persons. The influence of the number of years of formal education (EDUC) on market production was negative and non-significant. The highly educated farmers are less likely to depend on farming (and by implication, on cooking banana) as a primary source of cash income. This observation supports earlier findings by Nweke (1996) that the proportion of cassava planted for sale by farmers was less among the educated households. Amara et al. (1999) believe that educational attainment by farmers leads to better assessment of the importance and complexities of good farming decision-making.

The average number of years of schooling is 7, with a range of 0 to 22 years (Table 4). About 62% did not have more than 6 years of formal education while only 15% had above 12 years of schooling. In essence, the majority of farmers did not go beyond primary education. A greater proportion of cooking banana tended to be produced for market by farmers whose primary occupation was farming (OCCUP), but this trend was not significant. This is expected since income from farming was the major source of household cash income. Among the respondents, 70% had farming as their primary occupation, while the rest had it as their secondary occupation (Table 4). The relationship between gender ownership of cooking banana (OWNER) and the proportion sold was positive and significant. Commercial or market-oriented production was highly influenced by land access, which was usually under the control of husbands. Manyong et al. (1996) reported that male farmers usually have control over household resources, while CIMMYT (1993) observed that women farmers are less likely to command resources (such as land, credit or information) to take full advantage of new technology and market opportunities. About 70% of the respondents reported male ownership of cooking banana, while 30% reported female ownership (Table 4). Also, the probability that a greater proportion of cooking banana produced will be for market increases with the number of years a farmer has cropped (CBEXP) and sold (YRSELLCB) cooking banana. This is in agreement with observations of Amara et al. (1999) regarding potato farmers in Quebec. On the average, farmers had been cropping and selling cooking banana for 6 and 4 years, respectively (Table 4). Only about 7% of the farmers had been growing cooking banana for more than 10 years. This indicates that the potential of cooking banana production for market will probably increase as the years go by.

Market-related variables. Sales of cooking banana in market (MARKET) has a positive though non-significant impact on the proportion sold. Access to market places can boost the production for market. Farmers usually get better prices when they sell in market places, especially if these are easily accessible. Only 17% of the farmers sold their cooking banana primarily from the house while more than 63% of the farmers sell it primarily in the markets (Table 5). Ferris et al. (1997) noted that farmers' early attempts to sell cooking banana at local markets proved difficult. Inability to sell cooking banana or limited market was one of the initial drawbacks experienced by farmers in the region during the early periods of its introduction (Ferris et al., 1997). This was also true for the commercialisation of soybean production in West Africa in the early stages (Kormawa and von-Oppen, 1997). The availability of regular buyers, which is a symbol of ready market, guarantees easy and quick disposal of marketable surplus, increases the chance of additional steady cash income, and is an incentive for farmers to produce more for market. About 35% of the farmers had regular buyers (Table 5). While approximately 35% of the farmers sold primarily to consumers and middlemen, respectively (Table 5). Nweke (1996) remarked that the proportion of cassava marketed by farmers increased as participation by middlemen in the marketing process increased. Cooking banana is known to quickly spoil after ripening. If sales are restricted to the green ones, this means that the demand for ripe cooking banana is lacking in the village/market. By implication, utilisation of ripe cooking banana is not common, and in order to avoid the incidence of spoilage and loss arising from unsold ripe banana, farmers will tend to reduce the proportion targeted to market. The demand for ripe cooking banana means that the awareness for its utilisation is relatively high and that its production for market is likely to increase. Among the farmers, 76% preferred selling their cooking banana green (Table 5). When the market price of a particular crop enterprise is relatively favourable, farmers are likely to allocate more resources to such a crop, thereby increasing the total production and the proportion for market. On the other hand, farmers are likely to diversify away from such crop enterprise where there is price disadvantage, cutting down the level of production for sale. Ferris et al. (1997) remarked that due to initial poor market value of cooking banana, many farmers were producing for home consumption. They reported that bunches of bluggoe and cardaba (the more acceptable cooking banana cultivars) were sold at approximately half the price of plantain. According to them, with progressive increase in its market value over time, farmers began to sell cooking banana bunches within the local marketing system. In Cameroon, Enyong et al. (1999) pointed out that market price was among the major incentives for expansion in improved maize production by farmers.

conclusion


The major objective of this study was to determine factors that affect farmers' decisions regarding the proportion of cooking banana produced for market. Data were collected in southeast Nigeria from a random sample of 217 farmers through the use of a structured questionnaire. Results indicate that about 80% of cooking banana growers interviewed sold an average of 45% of their produce in the market; implying that this crop plays the dual role of food source and cash income for farmers. The price and the ripening stage of cooking banana at sale, as well as the presence of middlemen and especially of regular buyers in the marketing chain were the most important determinants of the proportion of cooking banana planted for market. The cooking banana price, the presence of middlemen and especially of regular buyers in the cooking banana chain positively affected the proportion of cooking banana produced for market, while 'green stage' as the major ripening stage at sale had a negative and statistically significant impact on the proportion of cooking banana sold.

Age and gender are the major farmers' characteristics that significantly affected the proportion of cooking banana planted for market. Younger male farmers tended to produce more cooking banana for market than older male or female farmers whose first production objective was traditionally to meet food needs of their households.

Increased involvement of middlemen such as wholesalers and processors in the marketing chain of the crop will increase the market role of cooking banana in the region. The study also recommends increased training of end-users on how to utilise cooking banana in other ripening stages other than the green stage.

REFERENCES
  • Adesina, A.A. and Baidu-Forson, J. 1995. Farmers' perception and adoption of new agricultural technology: evidence from analysis in Burkina-Faso and Guinua, West Africa. Agricultural Economics13:1-9.
  • Akinola, A.A. and Young, T. 1985. An application of the tobit model in the analysis of agricultural innovation adoption processes: A study of the use of cocoa spraying chemicals among Nigerian cocoa farmers. Oxford Agrarian Studies XIV:26-51.
  • Aldrich, J.H. and Nelson, F.D. 1984. Linear probability, logout and probate models. Sage Publications Series No. 07-045. Sage Publications Inc., California.
  • Amara, N., Traoré, N., Landry, R. and Ramain, R. 1999. Technical efficiency and farmers' attitudes towards technological innovation: the case of potato farmers in Quebec. Canadian Journal of Agricultural Economics 47:31-43.
  • Annon, I. 1989. Agricultural Research and Technology Transfer. Elsevier Science Publication Ltd., England. pp. 746 - 780.
  • Burton, M., Ribgy, D. and Young, T. 1999. Analysis of the determinants of adoption of organic horticultural techniques in the UK. Journal of Agricultural Economics 50:47-63.
  • CIMMYT Economic Program. 1993. The Adoption of Agricultural Technology: A Guide for Survey Design. Mexico, D.F.: CIMMYT.
  • Enyong, L., Coulibaly, O., Adesina, A., Youri, A., Raman, A. and Thé, C. 1999. Dynamics of maize production, adoption of improved varieties and food security in the northern region of Cameroon. In: Strategy for sustainable maize production in West and central Africa. Badu-Apraku, B., Fakorede, M.A.B., Ouedraogo, M. and Quin, F.M. (Eds.), pp. 365-376. Proceedings of Regional Maize Workshop, 21-25 April 1997. IITA-Coutonou, Benin Republic.
  • Ferris, R.S.B., Adeniji, T., Chukwu, U., Akalumhe, Y.O., Vuylsteke, D. and Ortiz, R. 1996. Postharvest quality of plantains and cooking bananas. In: Plantain and Banana: Production and Research in West and Central Africa.
  • Ortiz, R. and Akoroda, M.O. (Eds.), pp. 15-21. IITA, Ibadan, Nigeria.
  • Ferris, R.S.B., Ortiz, R., Chukwu, U., Akalumhe, Y.O., Akele, S., Ubi, A. and Vuylsteke, D. 1997. The introduction and market potential of exotic black sigatoka resistant cooking banana cultivars in West Africa. Quarterly Journal of International Agriculture 36:141-152.
  • Hahn, N.D. 1985. Exploratory field survey: role of women in agricultural production, marketing and processing. In: Farming Systems Program Research Highlights 1981-1984. IITA, Ibadan, Nigeria. pp. 77-79.
  • Hahn, S., Vuylsteke, D. and Swennen, R. 1990. First reactions to ABB cooking bananas distributed in southeastern Nigeria. In: Sigatoka Leaf Spot Diseases of Bananas. Fullerton, R.A. and Stover, R.H. (Eds.), pp. 306-315. INIBAP, Montpellier, France.
  • INFOMUSA, 1998. Banana and food security. The International Magazine on Banana and
    Plantain 7:24-26.
  • Kormawa, P. and von Oppen, M. 1997. Institutions affecting the adoption of a non-traditional crop: the case of soybean in West Africa. In: Institutions and technology for rural development in West Africa. Proceedings of the International Symposium by the University of Hohenhein, Germany. 16-22 February 1996, Cotonou, Benin. Margraf Verlag, Weikershein, Germany. Bierschenk, T., Le Meur, P. and von Oppen, M. (Eds.), pp.145-152.
  • Lynam, J. 1990. Marketing research on cassava. In: Methodologies and Data Requirements for Cassava Systems Study in Africa. COSCA Working Paper (4), International Institute of Tropical Agriculture, Ibadan, Nigeria.
  • Manyong, V.M., Houndékon, A.V., Gogan, A., Versteege, M.N. and van der Pol, F. 1996. Determinants of adoption for a resource management technology: the case of Mucuna in Benin Republic. In: Advances in Agricultural and Biological Environment Engineering. Proceedings of a conference (ICABE), Beijing, 15-19 August 1996. Senwen, Z. and
  • Youlong, W (Eds.), pp. 86-93. China Agricultural University Press, Beijing, China.
  • Nweke, F.I. 1996. Cassava: A Cash Crop in Africa. COSCA Working Paper (14), International Institute of Tropical Agriculture, Ibadan, Nigeria.
  • Nweke, F.I., Hahn, S.K. and Ugwu, B.O. 1994. Circumstances of rapid spread of cultivation of improved cassava varieties in Nigeria. Journal of Farming Systems Research-Extension 4:93-119
  • Oyesile, O.O. 1987. Comparative studies on cooking banana and plantain products. MSc. Thesis, Department of Food Technology, University of Ibadan, Nigeria.
  • Plantain and Banana Improvement Program. (PBIP). 1994. Annual Report 1993. Crop Improvement Division, International Institute of Tropical Agriculture, Ibadan, Nigeria.
  • Plantain and Banana Improvement Program. (PBIP). 1995. Annual Report 1994. Crop Improvement Division, International Institute of Tropical Agriculture, Ibadan, Nigeria.
  • Plantain and Banana Improvement Program. (PBIP). 1996. Annual Report 1995. Crop Improvement Division, International Institute of Tropical Agriculture, Ibadan, Nigeria.
  • Southworth, V.R. 1981. Food crop marketing in Atebubu District, Ghana. Ph.D. Thesis, University Microfilms International, Stanford.
  • Tollens, E. 1995. The fundamental role of plantain and banana in tropical farming system. In: The King Baudouin Award to IITA. Proceedings of the Celebration at Leuven, 6 April 1995. BADC, Brussels, Belgium. pp. 29-31.
  • Tshiunza, M., Lemchi, J.I., Ezedinma, C.I. and Tenkouano, A. 1999. Market status of cooking banana in southeast Nigeria. In: Bananas and Food Security. Picq, C., Fouré, E. and Frison, E.A. (Eds.), pp. 487-496. Proceedings of the International Symposium, Douala, 10-14 November, 1998. INIBAP, Montpellier, France.
  • Tshiunza, M., Ezedinma, C.I., Lemchi, J.I. and Tenkouano, A. 1998. Dissemination of cooking banana in Southeast Nigeria. Paper presented at INIBAP-CRBP Symposium, Douala, Cameroon, 10-14 November 1998.
  • Vuylsteke, D. 1995. Banana research at IITA: Current status and outlook. In: The King Baudouin Award to IITA. Proceedings of the Celebration at Leuven, 6 April 1995. BADC, Brussels, Belgium. pp. 33-40.
  • Zegeye, H. 1990. The adoption of modern farm practices in African Agriculture: Empirical evidence about the impact of household characteristics and input supply systems in the Northern Region of Ghana. Nyamkpala Agricultural Research Report, No. 7, 1990.

© Copyright 2001, African Crop Science Society


The following images related to this document are available:

Photo images

[cs01073t5.jpg] [cs01073t3.jpg] [cs01073f1.jpg] [cs01073t4.jpg] [cs01073t2.jpg] [cs01073t1.jpg]
Home Faq Resources Email Bioline
© Bioline International, 1989 - 2022, Site last up-dated on 11-May-2022.
Site created and maintained by the Reference Center on Environmental Information, CRIA, Brazil
System hosted by the Internet Data Center of Rede Nacional de Ensino e Pesquisa, RNP, Brazil