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Deutscher Tropentag 2005 – Hohenheim, October 11 - 13, 2005 Conference on International Research on Food Security, Natural Resource Management and Rural Development Quality Management Practices in Cocoa Production in South - Western Nigeria Opeyemi Anthony Amusan1, Fidelis Olumide Amusan2, Ademola Braimoh3, Philip Oguntunde4: 1 University of Bonn, Agricultural Sciences & Resource Management in the Tropics and Sub-Tropics (ARTS), Institute of Agriculture Water Engineering, Nussallee 1, 53115 Bonn, Germany [email protected], [email protected] 2 Alcon Labs, Clinical Research Scientist, United Kingdom [email protected], [email protected] 3 United Nations Institute of Advance Studies (UNU-IAS), Japan [email protected] 4 University of Technology Delft, Water Management, The Netherlands [email protected] Abstract The main objective of this study was to investigate quality management practices in the major cocoa production areas of Nigeria. Socio - economic surveys covered resource quality, agronomic practices, and constraints to agricultural production, whereas soil sampling and analyses were carried out to assess contribution of soil to yield. Farm budget analysis was used to determine the profitability of the two major management options of sampled farmers. Linear multiple regression was used to relate biophysical and agronomic data to cocoa yield. Owing to high level of multicollinearity, independent variables were reduced to six, which are Organic C, Age of farm, Plant density, Proportion Replaced, Crop Variety and ECEC. Among the variables in the model, two (Organic C and Age of farm) are negatively related to cocoa yield, whereas other variables are positively related to cocoa yield. However, soil variables are not significant to the model (p>0.05), whereas three management variables (plant density, proportion of dormant plants replaced and crop variety) are significant (p<0.1). All the variables explain 97% of the variability of yield and the model can be used to predict yield at 99% confidence level. Results indicated variability in yield across the three main locations studied. The highest yields were obtained in areas where farmers have access to training in management practices. Soils of the three locations are not significantly different from one another in terms of chemical properties. This probably reflects similarity in the parent materials from which the soils have developed. Farm budget analysis revealed that minimal management involving fertilizer and pesticide use is less profitable than extensive management. For sustainable cocoa production in the study areas, a high premium should be placed on the quality of cocoa product for export. 2. Backgrounds and Aim of the Study One of the many factors responsible for the decline in cocoa production in South-western Nigeria is the ageing cocoa farms. Many farms are over 40 years old and such farms constitute as much as 60% of the cocoa farms in the country today (Adegeye, 1997). Orderly marketing of cocoa also almost stopped with the abolition of the Nigerian Cocoa Marketing Board (NCB) (Ajayi and Okoruwa, 1996). The immediate effect was the bad quality cocoa that was leaving Nigeria for Europe and hence loss of premium price which had been placed on Nigerian cocoa. This study is aimed at assessing the quality management practices in cocoa production in the study areas in south - western Nigeria. The specific objectives include: 1. 2. 3. To highlight which management practices affect the overall quality in the cocoa production chain among the cocoa growers in Nigeria, To determine the biophysical and socio-economic constraints to cocoa production, and To assess possible techniques for improved management practices for higher yield and profitability for cocoa farmers. The study examines farm units in the three cocoa producing centres in Nigeria in respect of their agro management practices. Empirical analyses of the farm units is intended to provide insights into available options in optimising management practices for cocoa cultivation and show the resulting effect on producer incomes. In general, the study will determine what pre-requisites must be fulfilled in the pursuance of good management practices aimed at improving farmers´ income through efficient production processes, and realising full and sustainable production potential of the farm holdings. 3. Methods The methodology adopted for this study falls under three broad but integrated categories. First, socio-economy survey was carried out to elicit information on farm-farmer characteristics vis-à-vis constraints to cocoa production. Secondly, soil sampling and analysis were carried out to examine the role of soil properties in crop yield. Socio-economic and soil data were thereafter integrated to study their influence on crop yield. Lastly, financial analysis comprising project costing and investment projections for two management levels of cocoa production was carried out to highlight profitability. 3.1 Socioeconomic Survey A survey was carried out among cocoa growers in South-western Nigeria in June and July 2002. Three locations having similar agro-ecological features were selected, namely Ibadan, Ife and Akure. Thirty cocoa farmers were randomly selected and interviewed on their farms using standardised questionnaires. Farmers interviewed in Ibadan belonged to three different groups of cooperative societies or farmers´ organisation. The farmers interviewed at Ife and Akure belonged to the respective cooperative multipurpose unions (CPMU) in these towns. These cooperatives are profit -making organisations, however, they offer more than just marketing services for their members. Access to the farmers and their farmlands was obtained under the auspices of the Association of Nigerian Cooperative Exporters Limited (ANCE) and ongoing Project for Improvement of Cocoa Marketing and Trade in Nigeria (ICMT) sponsored by the International Cocoa Organisation (ICCO). While cocoa farmers in Ife and Akure are fully integrated into the ICMT project, the cocoa farmers in Ibadan are non-participants. The selection along the line of participation or non-participation on the project moreover enabled the evaluation of the project’s overall influence on cocoa yield. The interview comprised of qualitative and quantitative components, covering aspects of agronomic activities, resource quality and availability, problems perceived and objectives set both at individual and cooperative levels. Additional information was collected in key-persons interviews from cocoa exporters, cocoa processors, cocoa researchers and representatives of governmental and nongovernmental institutions. Official statistics and other secondary data served as background information. 3.2 Soil Sampling and Analyses Biophysical data was obtained by analysis of soil samples taken from cocoa farms. Soils were analysed for chemical analyses. The soils were analysed for basic cations (determined in 1N NH4OAc), total N (Kjedahl method), available P (Bray P method) organic C (Walkey-Black wet oxidation method) and pH (0.1M CaCl2). 3.3 Farm Budget Analysis The objective of the farm budget analysis was to determine strategies for improving profitability of cocoa production. Thus analysis was carried out for two different management levels. The first is ‘minimal management level’ involving the use of farms inputs such as fertilizer, pesticides etc at a reduced level. The second is ‘extensive management level’ where fertilizer and pesticide application is not involved. An illustrative financial model based on the study findings was prepared for 1 ha land for cocoa production, each at the two management levels to show estimate of expenditure and expected gross margins. 4. Results 4.1 Soil Properties, Land Use History and Crop Yield The topography of the land at all study farms ranges from flat to gentle slope (2-8%). Soil analyses (Tables 3 and 4) showed that the soils are fairly high in total N (mean = 0.20%), organic C (mean = 1.89%), available P (mean = 3.19 ppm), but low in Na. The pH is close to neutral (mean 6.5). In terms of variability, pH is the least variable (cv = 7%) while available P is the most variable property (cv = 69%). Statistics of soil properties at the sampled locations are presented in Tables 3 and 4. Soil pH is the least variable across locations (CV=3-9%). Highest CV (100%) among Ibadan soils occur for EA, while the highest CV of 119% occur for P for Ife soils while Ca and K manifests the most variable soil property amongst Akure soils (C=55%). This suggests that cations are the most variable properties among Akure soils. Table 1 Estimates for Maintenance Labour required per Hectare for two Cocoa Management Systems (Source: own computation) Management System Type of practice Man-days/ha/year Extensive pod harvesting and breaking fermenting and drying manual weed control; pruning Total 5 5 11 21 Minimal regular pod harvesting and breaking fermenting and drying regular manual weed control structural pruning disease / pest control (chemical) / fertilizer Total 10 10 10 4 7 41 Table 2: General Statistics of soil properties (N=16) –(Source: own soil data analyses) EA= Exchangeable Acidity, ECEC= Effective cation exchange capacity Mean Std Cv (%) min max Ca (cmol/kg) Mg (cmol/kg) Na (cmol/kg) K (cmol/kg) EA a (cmol/kg) ECEC (cmol/kg) a 4.34 2.08 48 1.11 0.48 43 0.07 0.02 29 0.38 0.21 25 0.02 0.02 100 1.49 7.51 0.30 1.22 0.04 0.10 0.06 0.76 0.00 0.07 5.90 2.55 43 Total N (%) 0.20 0.05 27 2.15 9.77 0.14 0.33 Available P (ppm) 3.19 2.19 69 Organic C (%) 1.89 0.61 32 pH 6.46 0.44 7 0.99 7.05 1.16 3.33 5.70 7.30 Table 3: Location Statistics of soil properties (N=16) – (Source: own soil data analyses) Location No of Statistics Ca samples Ibadan 8 Ife 4 Akure 4 Mean Std. dev CV (%) Mean Std. dev CV (%) Mean Std. dev CV (%) Mg 4.46 2.06 46 3.89 2.37 61 4.73 2.61 55 Na 1.09 0.44 40 0.97 0.47 48 1.31 0.64 49 K 0.07 0.02 29 0.06 0.01 17 0.08 0.02 25 EA 0.33 0.23 70 0.42 0.12 29 0.44 0.24 55 ECEC N 0.02 0.02 100 0.02 0.01 50 0.02 0.01 50 5.96 2.39 40 5.36 2.74 51 6.58 3.44 52 P 0.19 0.05 26 0.21 0.08 38 0.2 0.04 20 OrgC 3.48 2.53 73 5.5 6.56 119 2.33 0.93 40 1.84 0.57 31 2.11 0.88 42 1.79 0.45 25 pH 6.45 0.49 8 6.56 0.57 9 6.38 0.22 3 4.2 Effects of biophysical and management variables on crop yield Linear multiple regression was used to relate crop yield to biophysical and socio-economic data. Owing to high level of multicollinearity, independent variables were reduced to six. Relative importance of variables in the multiple regression model Source: own computation 0.6 0.5 s ta n d a rd ize db e ta Figure 1 0.4 0.3 0.2 0.1 0 -0.1 Organic C Age of farm Plant density Proportion Replaced Crop Variety ECEC Table 4 Multiple regression of yield versus soil and management variables Source: own computation Independent variables Organic C Age of farm Plant density Proportion Replaced Crop Variety ECEC Squared Multiple R Standardized β -0.05 -0.07 0.17 0.48 0.42 0.02 t -0.55 -0.95 2.00 4.05 3.32 0.20 Probability 0.59 0.37 0.08 <0.01 0.01 0.85 0.97 F Probability <0.01 Among the variables in the model, two (Organic C and Age of farm) are negatively related to cocoa yield, whereas other variables are positively related to cocoa yield. However, soil variables are not significant to the model (p>0.05), whereas three management variables (plant density, proportion of dormant plants replaced and crop variety) are significant (p<0.1). All the variables explain 97% of the variability of yield and the model can be used to predict yield at 99% confidence level. Figure 2 further shows the relative importance of the variables as measured by the standardized β coefficients. Proportion of dormant plants replaced is the most significant management variable affecting yield, followed by crop variety (that is, F3 Amazon). 4.3 Farm Expenditure and Gross Margin A summary of farm budget under ‘minimal’ cocoa holding is presented in Table 5. Table 5 Summary of budget under ‘minimal’ cocoa holding in 2001/02-(Source: own C) Yield (kg/ha) Price =N=/kg TOTAL REVENUE (/ha) INPUTS (/ha) Seedlings (replacement of dormant trees) Pesticide: Gammalin 20 Fungicide: Perenox Fertilizer: NPK 450 110 Hired Labour cleaning and cultivation planting and pruning weeding and spraying harvesting and processing Bags and Packaging material Estimated 41 man days/ha @ 400 Naira/day for 1 ha to cover a cocoa season 16400 About 3600 Naira for a cocoa season 3600 TOTAL INPUT COST (A) FIXED EXPENSES Leased Land Depreciation of equipment TOTAL FIXED COSTS (B) TOTAL COSTS (A) + (B) GROSS PROFIT =N= =N= =N= 49500 Costs (Naira) 12 Naira @ 115 seedlings/ha 800 Naira @ 3 liters/ha 875 Naira @ 4 liters/ha 2200 Naira @ 1 bag/ha Total 1400 3200 3500 2200 30300 10% of Total Revenue 2000 4950 6950 47250 2250 The table shows that total fixed cost is N6950, while the total variable cost per unit 30300 = 67 Naira . The model shows that, at this management 450 6950 = 210kg and provides a gross profit of 2250 Naira per ha. (110 − 67) is level, the farm breaks-even at A summary of farm budget under ‘extensive’ cocoa holding is presented in Table 6. Table 6: Summary of budget under ‘extensive’ cocoa holding in 2001/02-(Source: own C) Yield (kg/ha) Price =N=/kg TOTAL REVENUE (/ha) INPUTS (/ha) Seedlings (replacement of dormant trees) Hired Labour cleaning and weeding planting and pruning harvesting and processing Bags and Packaging material TOTAL INPUT COST (A) FIXED EXPENSES Leased Land Depreciation of equipment TOTAL FIXED COSTS (B) TOTAL COSTS (A) + (B) GROSS PROFIT 230 110 =N= =N= =N= 25300 Costs (Naira) 12 Naira @ 115 seedlings/ha 1400 Estimated 21 man-days/ha @ 400 Naira/day for 1 ha to cover a cocoa season 8400 About 1800 Naira for a cocoa season 1800 11600 10% of Total Revenue 2000 2500 4500 16100 9200 The Table 6 shows that total fixed cost is N4500, while the total variable cost per unit is The model shows that, at this management level, the farm breaks-even at 11600 = 50 Naira . 230 4500 = 75kg (110 − 50) and provides a gross profit of 9220 Naira per ha. Comparison of Tables 5 and 6 shows that minimal and extensive management levels result in a gross profit of 2250 Naira and 9200 Naira respectively. Although extensive management generates lower revenue compared to minimal management, gross profit is greater as the input costs are not as high. An estimation of gross margin for the average cocoa farm per hectare for the periods before this study also confirms that a general decrease in input costs improved the profitability ratio (Table 7). Table 7 Gross Margin for the Average Cocoa Farm per Hectare Source: Computed from field survey data (2000) Average farm size (ha) REVENUE Yield (tonnes/ha) Price (=N=/tonnes) Total revenue VARIABLE COST Pesticide Fertilizer Herbicide Labour Total Variable Cost Gross Marginal/ha Profitability ratio (GM/TC) 1985/86 1992/93 1999/2000 4.35 4.50 4.58 0.503 20,000 10,060 0.544 94,660.00 51,495.04 0.579 91,340.00 52,885.86 449.86 35.45 48.0 3,550.00 4,083.00 5,976.6 1.46 506.25 3.10 0.00 7,640.00 8,149.4 43,346.00 5.67 582.10 0.00 13.00 11,400 11,995 40,890.8 3.41 Input cost (cost of pesticide, fertilizer and herbicide) in 1985/86 was =N= 533.31 whereas the profitability ratio in this season was 1.46. In 1992/93, input cost was =N= 509.35 and profitability ratio was 5.67. In 1999/200, input cost was =N= 595.1 and profitability ratio was 3.41. 5. Conclusion and Recommendations This study shows that high yield in cocoa farming does not necessarily imply high profitability. Since farms, which do not apply chemical input, have been able to maintain some level of profitability, extensive farmers should be encouraged to try to get a higher price for their product, which could actually be called ‘organic cocoa’. Farmers, who apply chemical inputs, must consider the aspect of profit making and quality of cocoa due to chemical residues in the product, coupled with the problem of environmental pollution through chemicals. Farmers should be encouraged to practise conservation and rehabilitation agriculture. This involves all steps which negate the processes of degeneration on cocoa farms, for example through consequent replacement of dormant trees, control of tree population for effective ground cover, properly managed canopy, integrated management systems that utilise resistant cultivars and application practices that emphasise proper timing and effective use of fertilizers at lower application rates. This would help not only to improve yield but also has the advantages of profitability, product quality and environmental protection. Given the situation in the international market in and the natural limitations of the cocoa farmers in Nigeria, the development of a market niche for quality was suggested. This research highlighted the management practices, which affect the overall quality in the cocoa production chain on the visited farms. It revealed the biophysical and socio-economic constraints to cocoa production. The suggested improved management practices will help cocoa farmers to realise higher yield and improve the profitability of cocoa farming. References ADEGBOLA, M.O.K. (1977). Rehabilitating cocoa swollen shoot virus infected cocoa th farms- the Offa-Igbo experience. Proc. 5 Int. cocoa Res. Conf. Ibadan, Nigeria 1975: 182-8 ADEGEYE ADEDURO (1997). Paper on Production and Marketing of Cocoa in Nigeria: Problems and Solutions ADENIKINJU, S.A., E.B. ESAN AND A.A. ADEYEMI (1989). Nursery Techniques, Propagation and Management of Cacao, Kola, Coffee, Cashew and Tea. Progress in Tree Crop research (Second Edition) A Commemorative Book to mark the 25th Anniversary of CRIN AJAYI AND OKORUWA (1996). Managing Uncertainties and Risks in Cocoa Production and Marketing in Nigeria AKINBOLA, C.A. (2001). International Project on Cocoa Marketing and Trade in Nigeria Manual on Cocoa Quality and Training Manual for Extension Workers BUCKETT, M. (1988). An Introduction to Farm Organisation and Management Pergamon Books Ltd (2nd Edition) COCOA/CHOCOLATE AND CONFECTIONARY ALLIANCE (1984). Cocoa beans: Chocolate manufacturers quality requirements. The Cocoa, Chocolate and Confectionary rd Alliance, 11 Green Street, London, 3 Ed. Jan. 1984. 19pp DEPARTMENT OF TRADE, COMMERCE AND INDUSTRY (1998). Project Profile Cocoa Production. Trade and Investment Promotion Unit. Cocoa Production. DILLON, J.L. AND HARDAKER, J.B. (1993). Farm Management Research for Small Farmer Development FAO Farm Systems Management Series No. 6 Rome GALLETTI, R.,BALDWIN, K.D.S., DINA, I.O. (1956). Nigerian Cocoa Farmers. An Economic Survey of Yoruba Cocoa Farming Families. The Nigeria Cocoa Marketing Board KAY, R.D., EDWARDS, W.M. (1999). Farm Management Fourth Edition OPEKE, L.K. (1987). Tropical tree Crops, Spectrum Books Ltd., Pub. Woye and sons (Nig.) Ltd., Ilorin 327 pp PRIOR, C (1981). Cocoa replanting practices and the possible dangers from root- rots. Cocoa Industry Board of Papua New Guinea Newsletter 1, 2 REHM S. AND EPSIG G. (1991). The Cultivated Plants of the Tropics and Subtropics. Verlag, Josef Magraf , Germany