MARKETING OF ONION IN ALIERO LOCAL GOVERNMENT AREA, KEBBI STATE NIGERIA

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2 Int. J. Agric.Sc & Vet.Med Abdullahi Auwal Gindi et al., 2014 Research Paper ISSN Vol. 2, No. 4, November All Rights Reserved MARKETING OF ONION IN ALIERO LOCAL GOVERNMENT AREA, KEBBI STATE NIGERIA Abdullahi Auwal Gindi 1*, Bamidele A Adeshina 1 and Kaka Yahaya 1 *Corresponding Author: Abdullahi Auwal Gindi, gindiauwal@yahoo.com The study attempts to investigate marketing of onion in Aliero Local Government Area, Kebbi State Nigeria, and the structure in existence in onion market and compare the cost and returns for both market participants. Market information was collected through a purposive sampling technique from which 70 respondents each from both the wholesalers and retailers were selected. Costs and returns of wholesalers and retailers were obtained with average gross return of N19,875 k and N19,666 k per bag respectively. The Lorenz curve and Gini coefficient were used in determining relative concentration and equality/inequality distribution in the market. The graph of the Lorenz curve was plotted from the cumulative proportional aggregate sales versus the proportion of the retailers population per month. The Gini coefficient was also calculated using the Lorenz curve graph and the value of 0.42 was obtained. The value indicates the difference or level of concentration by the few groups of retailers. The study suggests the need for government to develop an orientation program for the onion marketers in the study area on measures of establishing satisfactory marketing strategies in the onion market of the study area. Keywords: Marketing, Lorenz curve, Aliero, Onion INTRODUCTION Onion ( Allium Cepa. L.) belongs to the family Alliacee, genus allium. Onion is a product from Asia and Middle East and it is second only to tomatoes among vegetables in the world trade (Gandi et al., 1982). The world leading producers of onion are United States of America, China, Russia and Japan. Other important producing countries include; Turkey, Spain, Brazil, Italy and Egypt (FAO, 1997). The crop is grown primarily for its bulb while the immature ones are used as flavoring and seasoning due to its composite aromatic volatile substances ( ally prophyldisulphide). Onion and its wastes can be fed to livestock. The plant is used by traditional folk as medicine (Purseglove, 1978). Since introducing the production of onion in Nigeria, it has been an important commercial vegetable in the Northern parts of the country where the bulk of it (onion) is produced during dry season in 1 Department of Agricultural Economics and Extension, Faculty of Agriculture, Kebbi State University of Science and Technology, Aliero, Kebbi State, Nigeria. 11

3 lowland Fadama as well as other irrigable area (Amans et al., 1990). The production of onion is of great importance to the people of the area as source of income, food and livestock feed, etc., particularly in Kebbi state, which has the suitable land for the cultivation of the crop. The production of onion in the area also provides employment opportunities to others that are not engaged directly in dry season farming such as local transporters who convey onion from the farmland to the market and then to various parts in Nigeria; and to the retailer who sells onion in rural markets. Onion production farmers have double opportunities of engaging in both production of rain fed crops and irrigable crops (such as tomatoes, pepper and so on). Researchers on field of marketing, like Green (1971) reported that the marketing of onion in Northern Nigeria has never been organized thus, a trader can buy onion in parts of the Northern states and by transporting down to the south, he may obtain more than 50% return of what he paid for the bulbs even at the peak period of harvest. Efforts to satisfy the need of consumers with respect to space and time are among the functions of marketing performed by the middlemen. Pricing efficiency studies therefore, attempts to appraise the system by comparing actual prices with the ones that are generated by perfectly competitive markets (Bressler and Kings, 1970). It is against this background, the study intends to investigate marketing of onion in Aliero L.G.A with a view to addressing the following research questions; Is the marketing of onion profitable in the study area? Who participate in onion marketing in the area? In attempt to find answers to these questions, the objectives of the study are: To identify structure in existence in onion market and to compare the costs and returns for both retailers and wholesalers in the study area. The extensive use of onion both for human consumption and the medicinal uses have created increasing demand for onion in the study area which has lead to the search for a more effective way of marketing the crop. Owing to its high demand there is a need to meet this demand. Although there are many literatures on the marketing of onion in different areas in Kebbi state, there is little or no any literature on the compositions of wholesalers and retailers existence in the market area. Also the study will add to the existing literatures on marketing of onion in the study area. The findings of this research would be useful in generating information on the marketing systems of onion in the study area, which can alleviate some problems encountered by traders and producers. We hope that the method that will be employed and the information generated during this research will be used for better planning of onion market in the study area. MARKET AND MARKETING Generally, marketing involves the movement of commodities from their point of production to the point of consumption. Agricultural marketing especially, involves the movement of agricultural products or commodities from thousands of scattered small and large sized farms where they are produced to the thousands of consumers located in both rural and urban areas (Adegeye and Dittoh, 1982). Akinwunmi (1990) reported that the marketing of agricultural products involves large numbers of people, including the product assemblers, transporters, bulk breakers and retailers; the final stage being an interaction between the sellers or retailers and the buyers or 12

4 consumers. Olukosi and Isitor (2007) defined marketing as the performance of all business activities, which is directed towards the flow of goods and services to the consumer in order to satisfy the producer s objectives. Marketing is not limited to selling or transforming of products to another person for a price. It entails packaging, storage, transporting, financial risk bearing and even designing of the products. Marketing is also described as part and parcel of production and consumption process (Olukosi and Isitor, 2007). Market is a system that exists when buyers wishing to exchange money for goods and services are in contact with the product and are ready to purchase such products (Johnson, 1990). Another definition of market is any organization in which the buyers and sellers of a commodity are in constant touch with each other and, there is no need for a market to be housed in a single building. More so, a market is one of many varieties of systems, institutions, procedures, social relations and infrastructure whereby parties engage in exchange. While parties (buyers and sellers) may exchange goods and services by barter, most markets rely on buyers. For a market to be competitive there must be more than a single buyer or seller. It has been suggested that two people may trade but it takes at least three persons to have a market; so that there is competition on at least one of its two sides. However, competitive markets rely on much larger number of both buyers and sellers. Marketing channels refers to the path of a product as it moves from the producers to the final consumers (Olukosi and Isitor, 1990). They indicate how various products, market participants are organized to accomplish the movement of a product from the producer to a final consumers. In addition, a marketing channel is an organized network of agencies and institutions which, in combination, performs all activities required to link producer with users (consumers) to accomplish the marketing task (Benneth, 1988). Dogondaji et al. (2006) examine the marketing system of onion on both Sokoto and Kebbi, categorizing traders in the areas into retailers and wholesalers which differs based on quantity they bought and mode of reselling the products. According to Dogondaji et al. (2006), marketing costs are the actual expense incurred in the performance of the marketing functions as commodities move from farm to the ultimate consumer; which may include the cost of transportation and handling, marketing charges, sale promotion and advertisement, etc. It is very important to note that in discussing marketing cost, transfer cost, processing and storage costs are to be mentioned. Market structure relates essentially to the degree of competition in a market. It aims to consider whether the firms are equal in size or dominated by small group. It is also concerned with whether the purchase of the product is in a competitive state or not. Market structure can be defined as those characteristics of the organization of the market which seems to influence strategically, the nature of competition within the market (Olukosi and Isitor, 2007) In economics, markets are classified according to the structure of the industry variables, which are believed to determine the extent and characteristic of competition. Those variables which have received the most attention are number of buyers and sellers, extent of product substitution, cost of production, ease of entry and exit of product into the market and the extent of mutual independence. In the traditional framework, these structural variables are distilled 13

5 into the following taxonomy of market structures. Perfect competition: many sellers and buyers of a standardized product; Monopolistic competition: many sellers of a differentiated product; Oligopoly: few sellers of a standardized or differentiated product; and Monopoly: a single seller of a product for which there is close substitute. Market structure is important in that it affects market outcomes through its impact on the motivations, opportunities and decision of economic literates participating in the market. Marketing and industrial literatures have shown that market structure can be measured in both absolute and relative terms. In this study Lorenz curve and Gini coefficient were used to measure the relative level of concentration and inequality distribution among onion market players (retailers and wholesalers) in the study area. Gini Coefficient The Gini coefficient also known as the Gini index or Gini ratio) is a measure of statistical and dispersion developed by the Italian statistician and sociologist Corrado Gini and published in his 1912 paper variability and mutability. The Gini coefficient measure the inequality among values of a frequency distribution (for example level of income), is mostly associated with descriptive approach to inequality measurement. A Gini coefficient of one (100 on the percentile scale) expresses maximal inequality among values where only a single person received 100% of the total income and the remaining people receives none (G = 1-1/N); and the most equal society will be one in which every person receives the same income. The Gini coefficient can theoretically range from 0 to 1: it is sometimes expressed as a percentage ranging between 0 and 100. A low Gini coefficient indicate a more equal distribution, with 0 corresponding to complete equality, while higher Gini coefficient indicates more unequal distribution, with 1 corresponding to complete inequality. The formula for computing Gini coefficient was depicted below n 1 2 n G n n 1 i xi xi where xi is the ordered from the least to the greatest, n is the number of observation in the population. Like the used of Gini coefficient, the Lorenz curve has been widely used by economist to assess the distributional properties of family income and wealth, by demographers to quantify the degree of population concentration (Neil Higgs, 2002). Different areas used different methods in plotting the Lorenze s curve graph, doctors used cumulative percentage of diseases against cumulative percentage of the non disease (Wen, 1999). Economist often plot the cumulative percentage of income against the cumulative percentage of the population and demographers used cumulative percentage of population number against the cumulative percentage of the land area (Neil Higgs, 2002). Also academics used Lorenz curve and Gini coefficient to assess the performance or inequality among universities (Halffman, 2010). They all call the curve Lorenz curve, since it involves same procedures of categorizing, recording, summing and plotting. METHODOLOGY The study was conducted in Aliero central market in Aliero Local Government Area of Kebbi state, Nigeria; where the bulk of onions are sold for local consumption as well as transported to other parts of the country. Aliero is located in the South-East of Kebbi State. The area is located on latitude 14

6 12º16' to 42º N and on longitude 4º27' to 6º E of the equator. It has a total area of 412 square kilometer with an estimated population of about one hundred and twenty-five thousand, seven hundred and eighty three people (125,783) (NPC, 2006). It is bordered in the North-East with Gwandu local government area, in the South- West with Jega local government, and in the North-West with Birnin Kebbi local government area. Aliero community is among the major producers of onion in North and has the largest onion markets in Northwest Nigeria (Dogondaji et al., 2006). Market information was collected through a purposive sampling technique to select two sets of onion marketers (i.e., wholesaler and retailer) in the study area. 70 wholesalers and 70 retailers were choosing each month using simple random sampling technique throughout the market period (December to April); this gives a total sample size of 140 respondents each month. Primary data were collected through the use of structured questionnaire and supplemented with oral interview. The data collected from the study was subjected to statistical analysis. Specification of the Tools of Analysis The following tools were used for the analysis Gross margin was used to determine profitability of onion marketing i.e., GM = GI-TVC, Where: GM = Gross margin, GI = Gross income and TVC = Total variable cost Ginico-efficient was used to analyze market structure i.e., n 1 2n 1 i xi G n n xi where xi is the ordered from the least to the greatest, n is the number of observation in the population. RESULTS AND DISCUSSION Average Cost and Returns by Wholesalers The average cost and returns is usually used in determining the profitability of the marketing of a particular commodity. Table 1 shows the average cost per bag as well as other costs of onions by the wholesaler. The total variable cost is (i.e., sum of all factors or costs incurred during the purchase of the commodity N15,237.12). Table 1 also shows the cost of selling the onion by the wholesalers as N19,875 and the gross margin, i.e., the profit realized after selling the onion is N4, k. Table1: Average Cost and Returns by Wholesaler (per bag) Item Cost (N) Average cost per bag 14, Average cost of transportation Average cost of loading and per bag Average commission per bag Total variable cost 15, Average selling price per bag 19, Gross margin 4, Average Cost and Returns for the Retailers % of Total Cost Table 2 shows the average cost and profit realized by the retailers during the marketing of onions. The essence of this table is to determine the profitability of onion marketing in the study area. From Table 2 the total variable costs incurred by the retailers is N15, k while the selling price per bag is N19,666 k. The Table 2 also shows the gross margin (i.e., total profit realized by the retailer) to be equals N4, k. 15

7 Table 2: Average Cost and Return by Retailers Item Cost (N) Average cost per bag 14, Average cost of transportation per bag Average cost of loading and offloading/bag Average commission per bag Total variable cost 15, Average selling price per bag 19, Gross margins 4, Source: Field Survey (2012) % of Total Cost From Tables 1 and 2 average gross returns of N19,875 k and N19,666 k per bag was received by wholesaler and retailer respectively. This gives a net income of N4,637 k and N4, k for the wholesaler and retailer respectively. The difference in income realizes by the wholesaler and retailer is very small (N296.33), it could be due to bulk demand for the commodity from the wholesaler compared to the retailer who sells in smaller quantity directly to consumers. Lorenz s Curve and Gini Coefficient The Lorenz curve and Gini coefficient were used to determine relative level of concentration and inequality distribution in the market. The data was obtained from the retailers of onion market in the study area. The market usually starts operating from early November and ends between March and April (period of onion production in the area). The numbers of retailers that operate per month together with their average monthly sales were obtained. The percentages of the number of retailers and their monthly sales are depicted in Table 3 below: The percentages of the retailers and that of their sales in each month were obtained by dividing the number of retailers and that of their sales of each month by their respective totals of the whole months. The cumulative percentages of both retailers and sales were obtained by adding up the percentages of each month as shown in Table 3. The lowest number of retailers per month (December) sales about 4.3% of the total sales in the market, while the highest group number of retailers (70) in the month of April, 58.52% of the total sales in the market. Period in Month Table 3: Retailers Distribution by Monthly Sales of Onion in the Study Area No. of Retailers (X) % of Retailers (X) Cumulative % of Retailers (X) Average of Monthly Sales (Y) November December , January , February , March , April , Total ,6406 Source: Field Survey (2012) Average % of Sales (Y) Cumulative % of the Sale (Y) 16

8 A graph of the data in Table 3 was obtained by plotting the cumulative proportional of aggregate sales versus the proportion of the retailer s population per month as shown in Figure 1. From the Figure of the Lorenze curve, about 15% of the lowest group of the retailers who participates in marketing of onion in the month of December was able to have about 4% of the total sales of the whole marketing period (December to April). Likewise, the lowest two groups of the retailers (32%) of the total population have about average of 8.6% of the total sales of the market. The highest group (75%) of the total population has about 58% of the total sales in the market for the whole marketing period. Looking at the Lorenz curve, one can only deduce the sales proportions of individual groups, but to make any conclusion about market concentration in which few groups of individuals dominate and control the market, there is need to calculate the Gini coefficient. Gini coefficient or index is calculated by either using the Gini formula as the one we presented before or from the Lorenze curve graph. The value of Gini coefficient ranges from 0 to 1 as explained in the previous section. For this research, we used the Lorenz curve procedure in calculating the Gini Figure 1: Lorenz Curve and Gini Coefficient coefficient, and obtained the value of 0.42, the procedure was explained in detail in the appendix. SUMMARY This research was conducted to study the marketing of onion in Aliero central market of Aliero local government Area of Kebbi state, Nigeria. Data for this research were collected from 70 wholesalers and 70 retailers, giving a total of 140 respondents to be interviewed in each month throughout the marketing period. The result obtained was analyzed using descriptive statistics such as frequency and percentage, gross margin, and marketing structure were analyzed using Gini co-efficient and Lorenz curve. The profitability analysis showed that an average marketers incurred an average total variable cost of N14, k and N15, k for both wholesalers and retailer respectively which indicated that an average marketer earned N5, k and N4, k for both wholesalers and retailers as gross margin, the result of Gini co-efficient was 0.42 value. This indicates that about 58% of the total sales was controlled by small group of the retailers which indicates relatively low level of equality of the retailers. CONCLUSION Despite the fact that onion trade is old in the study area, it is still profitable. The study concluded that since both wholesalers and retailers are engage in marketing of onion in the study area. There is need for government through complete packages of extension services to develop an orientation program for the onion marketers in the study area on measures of establishing satisfactory marketing strategies in the onion market of the study area. 17

9 REFERENCES 1. Adegeye A J and Dittoh J S (1982), Essentials of Agricultural Economics, pp , Impact Publishers Economics Nigeria, Limited, Ibadan. 2. Akinwumi J A A, Ezedinma F O C and Onazi O C (Eds.) (1990), Agricultural Economics and Marketing in Youdeowei, Introduction to Tropic Agriculture, pp , Longman Group, England. 3. Amans M K, Ahmed and Tatock J Y (1990), Storage Losses in Onion Bulbs as Affected by Plant Spacing Nitrogen Fertilization and Date of Sowing, Journal of Horticultural Science, Vol. 1, pp Benneth F (1988), Suggestions on Onion (Allium Cepa. L), Variety Improvement in Nigeria, Mimeograph, p. 25, Plant Science Department, L.A.R Abu, Zaria. 5. Bressler R G and Kings R A (1970), Market Prices and International Trade, John Willey and Sons Inc., USA. 6. Dogondaji S D, Baba K M and Mohammed I (2006), Marketing Analysis of Onions in Sokoto and Kebbi States of Nigeria, Journal of Agriculture, Vol. 1, No. 2, pp , Savannah, ISSN: FAO (1997), Statistics of Dry Onion Production, FAO Year Book for 1997, pp Gandi H, Currah L and Proctor F J (1982), Onion in Tropical Region, Bulletin, p. 232, National Resource Institute, Chartham, UK. 9. Green J H (1971), The Potential for Bulb Onion Crop in Northern States in Nigeria Samaria, Zaria, Vol. 13, pp Johnson D T (1990), The Business of Farming, a Guide to Farm Business Management in the Tropics, 2 nd Edition, p. 9, Macmillan Publishers Ltd. 11. Johannesburg N P C (2006), National Population Commission, Aliero Local Government Area, Kebbi State, Nigeria. 12. Olukosi J O and S U Isitor (2007), Introduction to Agricultural Marketing and Price Principle and Application, 3 rd Edition, p. 34, Living Book Series, GV Publication Abuja Nigeria. 13. Purseglove J W (1978), Tropical Crops Monocotyledons, Longman Singapore Publishers, PTC Ltd., pp Neil H (2002), Measuring Socio-Economic Status: A Discussion and Comparison of Methods or Letting the Gini Out of the Bottle Plus, August, Some Thoughts on Well- Being Research Surveys (Pty) Ltd. 15. Wen-Chung L (1999), Probabilistic Analysis of Global Performances of Diagnostic Tests: Interpreting the Lorenz Curve-Based Summary Measures, Journal of Statistics in Medicine, Vol. 18, pp Willem H and Loet L (2010), Is Inequality Among Universities Increasing?, Gini Coefficients and the Elusive Rise of Elite Universities Minerva, Vol. 48, pp

10 APPENDIX Procedure on how to calculate Gini coefficient using the Lorenz curve graph The area under the Lorenz curve was calculated using the properties of trapezoid formula ½(b1 + b2)h. 1. The area under Lorenz curve (B), was subtracted from the area of perfect equality (A + B). This is the area between the line of perfect equality and the Lorenz curve (A). 2. The Gini coefficient was obtained by taking the ratio of the area between the lines of perfect equality and Lorenz curve to the area under the line of perfect equality. Area under Lorenz curve = ½( ).2 + ½( ).2 + ½( ).2 + ½( ).2 + ½( ).2 = 0.29 Area under perfect equality = ½(0 + 1)1 = 0.5 Area A = (A + B) B = = 0.21 Gini coefficient G = A/ A+B = 0.21/

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