USE OF GIS IN THE IMPLEMENTATION OF NIGERIA’S CASSAVA INDUSTRIAL REVOLUTION

Malachy O. Akoroda and Tunrayo R. Alabi

Geospatial Laboratory, International Institute of Tropical Agriculture (IITA), Ibadan, PMB 5320, Oyo Road, Ibadan, Nigeria, Email: T.alabi@cgiar.org,

Phone: 234-2-2412626 ext 2289, Fax: 234-2-2412221

ABSTRACT

Nigeria’s economy is heavily dependent on the oil-sector and this has led to neglect of the agricultural sector in the past. The diversification of the economy is an absolute necessity to pull the economy away from extreme dependence on the capital intensive oil sector, which provides 33% of GNP, 95% of foreign exchange earnings, and about 85% of budgetary revenues. Hence to help to reverse this trend, there is a Presidential Initiative on cassava production and export, which seeks to diversify the use of Nigerian cassava through industrial processing and utilization options. This is to access new opportunities within the domestic and export markets and generate more foreign exchange. Although Nigeria is the world’s largest producer of Cassava, the yield is still much lower than in many Asian Countries. In order to meet the target of industrialization, improved technologies must be employed and targeted at potentially high yielding areas considering all the environmental factors of production. To this effect, the Federal Government of Nigeria, the USAID and Shell Petroleum Development company have provided funds and mandated the International Institute of Tropical Agriculture (IITA) to support farmers with improved varieties through the Cassava Mosaic Disease (CMD) Project .

In this study, GIS has been used to bring biophysical and socioeconomic factors namely rainfall, sunshine hours, temperature, soil slope, soil depth, Nitrogen, Potassium, Phosphorus, human population density and road networks together using weighted overlay techniques in ArcGIS 9 to delineate areas of high potential for cassava production in Nigeria. Areas of high profitability for large scale cassava production are highlighted for industrialists and prospective investors.

1. INTRODUCTION

Cassava (Manihot esculenta Crantz) was brought to Africa in the 16th century by Portuguese merchants and has been grown in Nigeria for over four hundred years. Since then it has played an important role in providing dietary energy and food security for over 200 million people in sub-Saharan Africa (Asadu and Nweke, (1999)). Cassava is a perennial woody shrub with an edible root, which grows in the tropical and subtropical areas of the world. It is grown as an annual crop for 10-15 months.

With a variable annual root production of 27-34 million tonnes from 2.25 million hectares, Nigeria is the world’s largest producer of cassava (FAOSTAT, 2004). However, her output is all mostly traditionally used for human food as gari, fufu, chips/chunks/flour, and kpokpogari, abacha, and starch. Much less than 10 percent of the output is used in industry compared with Brazil and Thailand with industrial uses of 62% and 95% respectively (Quin et al. (1995)). Hence great potentials exist for industrial uses both locally and for export as is the case in many other countries and so help to transform the economy of Nigeria. Nigeria’s target is to earn N691 billion (about $5 billion) from cassava annually with ready markets in some drought prone Southern African countries that have already targeted Nigeria as a source of cassava for their animal feed industries.

Although cassava has the ability to grow on marginal lands where cereals and other crops do not grow well, since it can tolerate drought and can grow in low nutrient soils, the output under these conditions will be far from optimal. Profitable industrialization of cassava products depends on selection of optimum areas.

Research has been conducted at International Institute of Tropical Agriculture (IITA) to enhance cassava productivity through the introduction of high yielding and disease-resistant varieties. These have been disseminated in all cassava-growing areas of Nigeria. Specific areas need, however, to be targeted for high outputs at minimum production costs. This study seeks to provide decision makers, farmers and industrialists Proceedings of the AfricaGIS2005 Conference 31 October to 4 November 2005 Organised by: The Geo-Information Society of South Africa Tshwane (Pretoria), South Africa Produced by: Document Transformation Technologies cc ISBN Number: 1-920-01710-0

with information of the better endowed areas for cassava production after considering some key biophysical and socioeconomic factors of production.

The Study Area

Figure 1: Map of the Study area showing the relief of Nigeria

Nigeria is situated in West Africa and occupies a land area of 92.4 million hectares. It stretches between latitudes 4°-14° N and longitudes 2°- 15°E. The population in 2000 is estimated at about 120 million (CIESEN, 2004), 70% of which are dependent upon agrarian resources for their livelihood. The population density is relatively high in the south western area and the Niger Delta regions while the middle belt, North West and North East have lower population density (Carter et al. (1992).

The major part of the country has elevation below 600 m above sea level, except for the Jos Plateau and the mountainous areas in the north-east. The Benue and Niger valleys and the coastal zone are situated well below 150 m (Figure 1).

There is a wide variation in agroclimatic and vegetation zones which are latitudinal across the country, spanning the humid through the savannas to semi arid zones as one proceeds from the south to the north. The length of the crop growing seasons varies from less than 3 months in the extreme north east to 8 months in the south. Annual rainfall is highest in the south and decreases northwards. It varies from about 3000 mm in the Niger Delta to around 1000 mm in the middle belt and less than 500 mm in the extreme north-east.

2. METHODOLOGY

The suitability evaluation for cassava was based mainly on the method as described by FAO (1983). Land units resulting from the overlay process of the selected land qualities were established. The selected land qualities include water availability (W), oxygen availability (O), nutrient availability index (NAI), water retention capacity (R) root conditions (D), sunshine hours (S), annual mean Temperature (Te) and topography (T). The requirements of each crop were reviewed from the following publications; FAO (1983), Delante (1993) and Mongkolsawat et al. (1999). Determinations of the various factor rating and values assigned for each land quality are summarized in Table 1.

Data Sources

Annual rainfall data used were derived from CRU/SAMRC, (1998) CD ROM. The CD contains monthly rainfall for Africa for the period of 1951-1995. Rainfall data for the period of 1996-2003 were obtained from RFE version 2.0 (xie and Arkin, 1997). The data was further processed at IITA to obtain annual average for the period of 1951-2000. Soil properties such as Nitrogen, Phosphorus, and Potassium, pH, and soil depth were obtained from the Digital soil map of the world (FAO, 2003) at a scale of 1:5 million. Other data used are the population density from CIESEN database at a resolution of 3 arc seconds (approximately 1 km) (CIESEN, 2004). Slopes were derived from a high resolution (90 meters) digital elevation model (DEM) from the Shuttle Radar Topographic Mission (SRTM, 2000). Sunshine hours were obtained from the IITA weather database and interpolated using ordinary Kriging with Geostatistical Analyst. The road network was from the IITA GIS database, digitized from LANDSAT imagery acquired in the years 1999-2002 at Geospatial Laboratory, IITA.

Data Processing and Analysis

The water availability indicative of rainfall was derived from mean annual rainfall data for Africa (1951-2000). The nutrient availability index (NAI) was calculated using the method developed by Radcliffe et al. (1983) and is given by NAI=N*P*K*pH. The spatial information for each diagnostic factor of NAI, soil depth, soil texture and soil drainage were derived from the FAO digital soil map.

Rainfall, soil and population density data were clipped from Africa continental coverages to Nigeria. The soil properties coverages were converted from vector format into raster using Vector to Raster Tool. Each raster was reclassified according to the cassava suitability classes obtained from Mongkolsawat et al. 1999 (Table 1). The raster were combined using a weighted overlay technique as shown in Figure 2.

The biophysical factors considered were given weights based on their relative importance to cassava production. Rainfall was considered the most critical factor and hence given a weight of 40%, while nutrient availability index was given a weight of 20%. Solar energy was also considered very important in selecting suitable area for profitable cassava production and hence given a weight of 20%. Other factors such as soil slope, soil texture, soil drainage and soil depth were given equal weights of 4% each and temperature was given a weight of 4% since it was non-limiting in almost all the parts of the country except in the high altitude area (Figure 1). In the weighted overlay tool, the areas in which temperature is much lower than required were set to “Restricted” in order to eliminate them from the classification. A similar procedure was employed for rainfall in the north eastern part of Nigeria where rainfall is lowest and hence not suitable for cassava production (Table 1).

Figure 2: GIS technique used in weighted overlay of all the biophysical factors

Table 1: Land quality and biophysical factor rating for cassava

Land use requirement Factor rating

Suitability classes Highly suitable

Moderately Suitable

Marginally suitable

Least suitable

Land Quality Diagnostic factor unit 1.0 0.8 0.5 0.2

Water availability (W) Annual rainfall mm 1,100-1500 900-1100 1500-2500

500-900 2500-4000

^lt;500 >4000

Oxygen availability (O) Soil drainage - well moderate poor very poor

NAI >0.60 0.40-0.60 0.10-0.40 <0.10

Nutrient availability Index (NAI)

N P K PH

% ppmppm-

>0.2 >25 >60 6.1-7.3

0.1-0.2 6 - 25 30-60 7.4-7.8 5.1-6.0

<0.1 <6 <30 7.9-8.4 4.0-5.0

- - - >8.4 <4.0

Water retention capacity (R) Soil texture - L, Si, SiL, SC,

L, CL SiCL, LS, SiL SlC, S C, G, SC, AC

Root Conditions (D) Soil depth cm >150 100-150 50-100 <50

Temperature (Te) Annual mean Temperature °C > 25.6 24.7- 25.6 23.7-24.7 < 23.7

Solar energy (S) Mean Sunshine hours/day hour > 7.1 6 – 7.1 4.9 – 5.9 < 4.9

Topography (T) slope % <5% 5-12% 12-20% >20% Soil texture: C=Clay, CL=Clay Loam, L=Loam, Si=Silt, Sil=Silty Loam, SiC=Silty Clay, SL=Sandy Loam, LS=Loamy Sand, SCL=Sandy Clay Loam, Sicl=Silty Clay Loam, S=Sand, G=Gravel soil, AC=Alluvial Complex, Sc=Slope Complex

3. RESULTS AND DISCUSSION

Figure 3(a-h): Biophysical factors considered for cassava suitability.

Figures 3(a-h) show the maps of the various biophysical factors considered for cassava suitability in the study area. Rainfall is the most important weather factor that influences crop yields and production (Alabi and Ibiyemi, (2000)). About 95% of the total land area is at least marginally suitable which suggests potential for growing cassava in most parts of the country, knowing that cassava tolerates low rainfall (Carter et al.

(1992)). More than 60% of the total land is good for cassava production (Figure 3a) combining high and moderate suitability classes. For commercial production, however, area under high and moderate suitability should be given priority.

Nutrient availability index (Figure 3b) was another major variable considered for cassava production. Nitrogen is the major nutrient responsible for the vegetative growth of plants above ground. With a good supply, plants grow sturdily and mature rapidly, with rich, dark green foliage. The second major element in plant nutrition, phosphorus, is essential for healthy growth, strong roots, fruit and flower development, and greater resistance to disease. The third major plant nutrient, potassium is essential for the development of strong plants. It helps plants to resist diseases, protects them from the cold and protects during dry weather by preventing excessive water loss. Although pH is in itself a nutrient, it affects the availability and uptake of these nutrients in the soil (Asadu and Nweke (1999)). It is clear from Figure 3b that only 16% of the total land area is highly suitable which occurred mostly in the central middle belt of Nigeria. Cassava is tolerant of marginal soils (Asadu and Nweke (1999)) and this might explain why more than 40% of the land was indicated as marginal even in areas where cassava is a major crop. This map suggests that for commercial production of cassava in most parts of Nigeria, farmers need to apply adequate levels of fertilizers and manure to enhance soil productivity.

Table 2: Percentage area of Nigeria suitable for cassava in terms of biophysical factors

Suitability factors Highly suitable (%)

Moderately suitable (%)

Marginally Suitable (%)

Least suitable (%)

Nutrient availability index (NAI) 16 35 49 0 Water availability 33 33 29 5 Sunshine hour 50 24 17 9 soil slope 35 59 4 2 Soil depth 13 67 6 13 Soil texture 5 51 13 31 Soil drainage 65 20 4 11 Mean Temperature 90 6 2 2

From Figure 3c, even though the northern-most part of Nigeria is highly suitable in terms of solar energy, yet rainfall is a limiting factor in that region (Figure 3a). The cloudiness (inverse of sunshine hours) is highest in the far south and this renders the area marginally suitable according to this factor. Topography is a factor that limits production in areas where slope is greater than 12%. Soil slope is suitable for most part except in the area of high altitude of Plateau and Taraba state. This high altitude area also has low temperatures which is a critical factor for cassava production (Figure 3g).

In Nigeria, as much as 24 % of the total land area (22 million ha) was found to be most suitable for cassava production (Figure 4). This occurred mainly in the middle belt region consisting of Niger, Kaduna, and Abuja, Nasarawa, Plateau, Taraba and Kwara states. High and moderate suitability was 34% and 27% respectively and this spreads across the South western states and the northern belt. The least suitable area occurred mainly in the northern belt of Borno and Yobe states due to insufficient water of the area. The occurrence of this category in the high altitude of Plateau, Taraba and Adamawa states (Figure 1, 3f and 4) was caused by low temperature and unfavorable topographic conditions. A few patches of this category also occurred in the creeks of Akwa Ibom state possibly due to excessive rainfall.

Figure 4: Land suitability classification for Cassava

Table 3: Cassava area, yield and production for Nigeria (1999-2003) [FAOSTAT 2004]

Year Area Harvested (ha) Yield (Kg/ha) Production ( million tonnes)

1999 3072000 10643.6 32697000

2000 3030000 10564.4 32010000

2001 3430000 9500.3 32586000

2002 3455000 9978.6 34476000

2003 3500000 9536.9 33379000

According to table 3, the FAO statistics for the year 1999- 2003 shows that the area cultivated under cassava ranges between 3.07 -3.5 Million ha of a total cultivated land area of 59 Million ha (FORMECU, 1998) suggesting more land is still available for large commercial cassava production. From Figure 4, however, the middle belt region consisting of Kwara, Kogi, Nasarawa, Niger, Kaduna, Benue and Plateau states have high proportion of most suitable area.

Land Availability for Cassava Production

Land is a fixed asset and as population increases, the pressure on land for all purposes including agriculture increases. In Nigeria, as elsewhere, the pressure on land varies by location/state. Table 4 lists the proportion of the land area in each state in cassava suitability categories and cassava land per farming household. This was derived by combining the total land area in the very high, high and moderately suitable categories for each state and dividing this by the farming population. Farming household was obtained by dividing total

state population by 5 assuming that the average family size is 5. This was then multiplied by 2/3 based on the assumption that only 2/3 of the total population engage in farming.

Table 4: Percentage of State land area suitable for cassava production and cassava land per farming household

Cassava suitability classes

STATE

Total Area ('000 Ha)

Population (Million) (CIESEN, 2004)

Very High (%)

High (%)

Moderate (%)

Marginal (%)

Least (%)

Cassava land (ha) per farming household

Abia 472 2.36 0 0 57 43 0 0.86 Abuja 735 0.52 97 3 0 0 0 10.51 Adamawa 3436 2.46 45 43 1 0 10 9.27 Akwa Ibom 666 2.99 0 0 14 39 47 0.22 Anambra 459 3.89 0 27 36 37 0 0.56 Bauchi 4907 3.80 34 29 25 0 11 8.59 Bayelsa 943 1.49 0 0 20 79 1 0.93 Benue 3131 3.39 15 31 54 0 0 6.89 Borno 6603 3.29 0 55 18 0 27 10.93 Cross River 2056 2.35 0 4 37 47 12 2.62 Delta 1653 3.40 0 0 29 62 9 1.02 Ebonyi 619 1.67 0 1 61 39 0 1.70 Edo 1962 2.90 0 8 89 3 0 4.91 Ekiti 525 1.89 6 86 9 0 0 2.08 Enugu 770 2.70 0 14 67 19 0 1.73 Gombe 1822 1.84 11 59 30 0 0 7.42 Imo 531 3.51 0 0 48 52 0 0.54 Jigawa 2399 4.11 0 13 83 0 4 4.21 Kaduna 4430 4.79 57 30 0 0 13 6.02 Kano 2007 7.52 6 37 55 0 2 1.95 Katsina 2361 4.76 1 43 57 0 0 3.73 Kebbi 3508 2.67 20 43 37 0 0 9.82 Kogi 2896 2.79 18 80 2 0 0 7.79 Kwara 3526 1.94 75 25 0 0 0 13.58 Lagos 314 10.57 0 17 68 14 0 0.18 Nassarawa 2632 1.58 99 0 0 0 1 12.42 Niger 7054 2.94 62 37 2 0 0 18.01 Ogun 1588 3.31 0 62 35 3 0 3.39 Ondo 1426 2.58 0 11 86 3 0 3.99 Osun 923 3.25 6 79 15 0 0 2.13 Oyo 2754 4.72 12 87 0 0 0 4.36 Plateau 2758 2.66 32 37 0 0 32 5.31 Rivers 816 3.55 0 0 26 71 4 0.45 Sokoto 3159 3.07 1 9 91 0 0 7.68 Taraba 5978 2.11 31 42 10 0 17 17.48 Yobe 4554 1.79 0 23 32 0 45 10.58 Zamfara 3456 2.53 8 39 53 0 0 10.24 Total / Mean 90013 117.66 24 34 27 5 10 4.88

From Table 4 the highest land availability of 18.1 ha/per farming household occurred in Niger state and it was closely followed by Taraba (17.48) and Kwara (13.58) states. Incidentally these 3 states fell mostly within the very high and high suitability for cassava according to biophysical factors (Figure 4). This result is more clearly presented in Figure 5. From this map, it is clear that most of the states in the Niger Delta Region have the least available land for commercial cassava production. A similar trend of high population pressure on suitable cassava land occurs in Lagos, Osun, Ondo and Ekiti in the south western part of Nigeria and hence these areas might not be appropriate for large- scale production of cassava. Most of the states that have high proportion of the most suitable land for cassava production also have low population pressures on their lands and hence are suitable for large-scale commercial production (Figure 4 & 5). Costs of obtaining

each unit of land in this area will most likely be relatively cheaper than in the high population density areas. Investors could therefore be safely directed to those states for large scale production at relatively lower costs for land acquisition and other inputs of production.

Figure 5: Map of Nigeria showing cassava land availability index

Population density is shown in Figure 6a. All the areas of very high to high suitability for cassava are within low population density regions. Figure 6b shows market access computed by calculating total road length per unit area in each local government administrative boundary. Best and good market access exists in the south western states of Lagos, Ogun and Ondo and in the south east states of Akwa Ibom and Abia states. The Niger Delta states of Bayelsa, Delta and Rivers have poor market access due to riverine nature of the area. The majority of the Northern states from Sokoto, Zamfara, and Katsina, Kano, Jigawa and Yobe have relatively good market access based on the road density considerations. The area of best to good market access will be appropriate sites for large cassava processing industries while production could best be done in the area of low population density where land holdings are suitable and cheaper to acquire.

Figure 6: Map of Nigeria showing population (a) and road (b) density

4. CONCLUSION

From the results of this work, it is clear that GIS can be an effective tool for combining both biophysical and socioeconomic factors of cassava production to highlight more suitable areas for large industrial production of cassava in Nigeria. It is also possible to use the results of this work to guide farmers, investors, and decision makers in prioritizing and targeting of their resources in cassava industry development and production. Moreover inputs of production could be well directed to areas where they will be of maximum benefits, for instance more NPK fertilizers could be sent to areas of low soil nutrients. Areas that are suitable for production but have high population pressure on cassava production may not be appropriate for large scale cassava farming due to high costs of acquiring sizeable parcels of land. Moreover states with very good markets access are potential area for cassava processing industries due to nearness to consumers.

5. REFERENCES

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[12] Quin F.M., M.O. Akoroda, and L.H. Ouraga-Djoussou 1995. The status of root crops in Africa: current situation and future prospects. Paper presented at the sixth triennial symposium of the International Society for Tropical Root Crops- Africa Branch( ISTRC-AB), 22-28 October 1995, Lilongwe, Malawi.

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[15] Xie, P. and P. A. Arkin, 1997. A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bulletin of the American Meteorological Society 78(11): 2539-58. RFE version 2.0 from http://igskmncnwb015.cr.usgs.gov/adds/datatheme.php