Status of cassava production in southeast and south-south Nigeria by International Institute of Tropical Agriculture

\\TA Status of cassava production in southeast and south-south Nigeria: A baseline report

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USAID IS.Trh UQM

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N100CAN I'fOI'l1

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Status of cassava production in southeast and south-south Nigeria A baseline report 2004 C. Ezedinma, J. lemchi, R. Okechukwu, F. Ogbe, M. Akoroda, L Sanni, E. Okoro, P. \Ion a, C. Okarter, and A.G.O. Dixon

International Institute of Tropical Agriculture, Ibadan

2007

ÂŠInternationallnsrirure of Tropical Agriculture ([ITA), 2007 Ibadan, Nigeria Telephone: (234 2) 2412626 Fax: (234 2) 24 12221 Email: iira@cgiar.org

Web: www.iita.org

To Headquarters from outside Nigeria:

00 Lambourn (UK) Ltd Carolyn House 26 Dingwall Road, Croydon CR9 3EE, UK

Within Nigeria: PMB 5320, Oyo Road Ibadan, Oyo State ISBN 978 13 1 2874 Printed in Nigeria by liTA Correct citation: Ezedinma, c., J. Lemchi, R. OkechUkwu, F. Ogbe, M. Akoroda, L. Sanni, E. Okoro, P. Ilona, C. Okana, and A.G .O. Dixon. 2007. Status of cassava production in southeast and south-south Nigeria. A baseline repon 2004. [ITA, Ibadan. Nigeria. 54 pp.

Contents

AdUlowledgements .................... .. ........ .. ......... ...................... ...... ....... .... .... ..

Institutions and Collaborators ......... ..... ..... ... ..... ............... .. ..... ........... ,...... ..

Introduction .... ........... ..................... .. ..... .. .... ..... ..................... ..... .............. . Methodology ..... .... .... ... ....... .................... ...................... ...... ..... .................. .

H ousehold characteristics and income ...... ......... ... , .. ................. ...... ........... .

Status of cassava production in southeast and souch路sQuch Nigeria .. ......... ..

Trend in Cissava co mmercialization in sou theast and sO~l(h-sourh Nigeria "

Use of improved cassava varieties and mher inputs in cassava production .. ..

Productivity of labo r in the cassava enterprise ............. .. ............ ...... ... ,........ .

Farmer associations and (he: organization of the cassava subsecto r in N igeria

Conclusion .. .... ....... ... ....... .... ........ .. ...... ... .... ... .. ... ........ .... .... ...... ....... .... ..... ..

References ........ ......... ............ ......... ..... ... .. ... .. ... .... ........ ... ....... .... ..... .. ...... .. ..

Annex ..... ...................... ...... ............... ........... ..................................... ..... .... .

iii

Acknowledgements

This document was prepared to provide baseline information for the Cassava Enterprise Development Project in the 11 states of (he southeast and south-south geopolitical wnes

of Nigeria. The srates are Abia. Akwa [born Anambra. Bayelsa. Cross River. Delta. Ebonyi. Edo, Enugu, Imo, and Rivers. We thank several coUaboraro cs and institutions (lined in the next page) for thei r ass ista nce in various ways duri ng the dara collecti on and writi ng

of th e rep,?rr. Chyka Okarrer. Ese Udumughere. and No ra Akp.n provided comp uting assisrance. Editorial input was made by th e editOrial department of lITA, while Richardson Okechukwu made preparat io ns for publiatio n. Funding for the survey and report were provided by the United States Ageney for International Development.

Institutions and Collaborators

Michigan State University ProfF.1. Nweke, Agricultural Economist

National Root Crops Research Institute, Umudike Dr G Asumugha, Agricultural Economist Dr A Olojede, Agronomist Dr Chiedozie Egesi, Breeder Dr

o. Eke-Okoro Agronomist

Mr M.C. Okwusi, Rural soc iologist

Projects Coordinating Unit Dr C.C. Molokwu, Agricultural Economist

Federal University of Technology, Owerri Dr P.C. Obasi, Agricultural Economist Dr C.1. lwuoha, Food Technologist Dr C.C. ElO, Agricultural Economist Dr o. Adesope, Rural Sociologist Mr A.E. lbeh, Agronomist (Weed Science) Mr C. Korie, Agricultural Economist Mr Sixtus Anyanwu, Agricultural Economist Mr A. Ugochukwu, Agricultural Economist

University of Nigeria, Nsukka Prof Charles As.du. Soil Scientist Mr Simon ElO, Agronomist

University of Ibadan Mr Simon lI>ana, Agricultural Economist Mr C. lroocheonwu, Agricultural Economist

University of Calabar Mr G. Odok, Agricultural Economist

University of Uyo Dr E. Ekpe, Agronomist

Agricultural Development Programs Mr E. Nwogu, Extension Specialist, Abia State Agricultural Development Program Mr R.O. As.nime, Food Technologist, Delta State Agricultural Development Program

Rivers State Institute of Agricultural Research Dr L.D. Gbaraneh, Agronomist

Mr J.MA Torunanah, Agronomist Private Sector Mr Ben Iiesanmi, Entrepreneur

Introduction Nigeria grows more cassava than any other country in the world. The production of cassova is concentrated in the hands of numerous smallholder farmers loca<ed primarily in the south and central legions of Nigeria. According to the FAO (2003) about 50% of the cassava harvest is wasted due to production and postharvest inefficiencies at the farm level. The rest is consumed as food in a few, limited ways as its production is nO[ commercially oriented to serve the needs of industry. Presently, 46% of the population of Nigeria lives in urban centers, which arc: currently growing at a rate of 4% per annum. With more Nigerians living in urban areas, the demand for convenience foods will continue to rise.

Traditionally, Nigerian farmers and processors seem 10 have responded 10 the demand lOr urban convenience foods from cassava especially gan. But the cyclical rise and fall in gari prices observed every twO to three years is an inherent produccion risk, justifying the need to diversify posrharvcst options from (he cassava enterprise. The International Institute of Tropical Agriculture (IITA) is currently implementing fWO complementary projec(s. namely the Pre-emptive Management of the Cassava Mosaic Disease in Nigeria Project (CMD Project) and the Cassava Enterprise Development Project (CEDP). The core activities of both projeclS originate in the south-south and southeast states of the counlry (and Ondo State in the case of the CMD project). The rationale is that there is evidence that the virulent form (Ugandan strain) of the cassava mosaic disease is advancing towards the eaStern flank of the country. Funding for the CMD project came initially from the United States Agency for International Development (USAID) prO\'iding the scc:d moncy that was used to assess the status of the disease in Nigeria (Ogbe et al. 2005). The Federal Government of Nigeria, the Niger Delta Development Commission, and the respective State governments currently fund the CMD project al IITA. Funding for the CEDP project is from the United States Agency for International Development and the Shell Petroleum Development Company. In implementing the CEDP project Ihe InStitute is building on the activities of the CMD project but with greater emphasis on the postharvest and enterprise development of (he cassava subsector in Nigeria. There is therefore a need for a benchmark study to serve as a basis for evaluating the CEDP interventions. The objectives of the currenr survey were to provide basic data for evaluating the impact of the CEDP implemented by IITA. The CEDP includes three objectives each with several activities to be implemented over a period of five years . The activities are: (1) (0 [educe the impact of cassava mosaic disease in selected communities in the south-south and southeast states of Nigeria, (2) increase the productivity of cassava, and (3) develop and expand postharvest processing and marketing oudets for cassava produclS. A diagnostic survey of the prevalence of the CMD disease has been concluded. The survey found that mixed infections of the two CMD viruses are widespread in southern Nigeria (Ogbe et al. 2005). The spread of the Ugandan variant of tbe virulent fOlm of the CMD in Nigeria is therefore possible and threatens to. devastate Nigeria's cassava production.

Methodology This baseline survey cove red 11 States located in the souchcas( and sourh-south geopolitical zo nes of Nige ria. T he Slates are Abia. Akwa Tborn , Anambra. Barelsa. C ross River, Delta, Ebonyi, Ecla. Enugu, Imo, and Rivers. By Nigeria's adminisU3tive definit ion the)' fa ll within rhe southeast and south -south g('opo litical reg ions of Nigeria. The so utheast states arc (Fig. I) Abi3, Anamb ra, Ebonyi. Enugu. and Imo stales while the sO Ulh-south States arc Akwa (born, Bayelsa, Cros~ River. Delta. Edo, and Rivers. The su rvey covered 54 villages in the abo\'e named stat('s. (Table I ),

&~---4i+ 1 ----~9~~------~I~~Okm

Figure 1. Location of survey s ites by state in the southeast and south.south states.

Table 1. Distribution of villages by state. St.lte

No of villagc$

Abia

Akw.lbom

Anambra

8.1.}"dsa

Crou River

Deha

Ebonyi

Edo

Enugu

Imo

Rivers

Total

Sampling frame The villages were selecred following rhe COSCA merhodology. In rhe COSCA survey, c1imare, popularion density, and marker infrastructure formed rhe bases for sampling. Following Carter and Jones (I989), four basic c1imaric zones wc,,' defined from rem路 perature and duration of dry periods within [he: growing season. Information available on all-wearher roads, railways, and navigable rive[S derived from Michelin travel mfp' was used to divide a market access infrasrcucture map into good and poor wnes according fO rhe density of rhe roads, railways, or navigable waterway', Human population dara from the United States Census Bureau were used to divide a population map of Africa into high demographic pressure zones with 50 or more persons per square kilometer and low if less. The three maps of climare, human population density. and market access infrastructure were overlaid to create zones with homogenous climate, demographic pressure~ and market access conditions. T he sampling frame was derived from a 12 km by 12 k m grid map based on a climate, population density, and market access framework. A total of 56 villages were surveyed in 11 scates of Nigeria. T hree survey instruments were used to collect data at the village, household, and field levels. The village level questionnaire focused on postharvest iss ues, namely processing and marketing. The houS(hold level questionnaires focused on income from farm enterprises including cassava as well as so urces of household income. T he field level survey involved destructive sampling to determine cassava yield. Geographic positioning system (CPS) equip路 ment was used to measure farmers' fields while weighing scales we re used to measure yield of cassava from nine months of age in 20 m2 or 40 m l plo rs. Soil samples were obtained from each sampled cassava field 3t a depth of 40 cm using a soil augur. The specific field activities in each village include group interviews, farmer interviews. field measurements, yi eld measurements, disease scoring, and soil sampling. Each team comprised four members

and where necessary, they used paid labor for intensive field act ivities such as yield and soil sampling and slashing paths. The survey commenced in March and ended in August 2004. Unlike ,he COSCAsurvey, th e village. household, and field level instruments were administered once in a village following a process of <a) village level interviews whece the village groups were gathered in the Chief/village heads compound or village square; (b) a random sample of three households selec,ed from the group gathered after the group interviews and later interviewed individually in the ir respec,ive houses; and (c) all fields cultivated by the household in the last planting season visited and information recorded for each field. Du,ing the village level interviews, the list oHarmers was compiled. It is from this list that three farmers were randomly selected for the household level interviews. All fields of the selected farm household pl;mrcd in the last: season were measured durlng the survey. A validation exercise was also undertaken after the fidd survey between October and November

2004. Data was entered into a Microsoft Access database and cleaned before analysis using SPSS and Excel. The units of analysis for chis Study comprise 56 villages, 168 farm families , and about 210 farmers' fields. Two teams of enumerators were used to collect data. The enumerators were drawn from

the Slate agricultural development programs, universities (Federal UniversiryofTechnology Owerri, Universiry of Nigeria Nsukka, University ofJbadan, Universiry ofCalabar, Rivers State Universiry of Science and Technology). and research insritutes especially the National Root Crops Research lnsricucc. Umudike. The enumera{ors were drawn from yarious disciplines (agronomy. postharvest, agricultural economics, agriculcural extension, crc.) and trained at UTA Onne becween 28 January and 3 February 2004. The major resource person at the training was Professor F. Nweke, Visiting Professor at Michigan State University, and former leader of the COSCA survey. The instruments that were used for the survey were: pretested by the team in cwo villages and responses assessed together afeer the pretes,. The least qualified of the enumerators had a higher n.rional diploma. Several had PhD degrees and. had participated in similar surveys in the ir respective disciplines and institutions.

Ana/ysis of data Statistical analyses were limited to the estimation of means and frequencies. Empirical results ar< presented in the form of tables and figures in this reporr. Informatio n is presented by geopol~[ical z.ones namely for the southeast and south-south. The southeast zone consists of Abia. Anambta. Ebonyi. Enugu. and Imo states. The south-south states include Akwa Ibom, Bayelsa, Cross River, Delta Edo, and Rivers.

For the purposes of this report the following variables were calculated from the database: Yield (t/ha) was computed as : Yield (t/ha)

samp~e outP~t(~ x

IO ............................... -{ I)

area arvest m

The productivity oflabor in technical te rms was computed from the database as follows: Labour productivity=fr~

. . . . . . .-..... .... . . . . . . . .

(2)

Where YLO is yield (t/ha) and PO is the total amount oflabor input for all farm activities (person days/ha) Labor cost per unir of oucpuc was obrained as:

LLABCOST

················(3)

YLO Where lAB COST = total cost oflabor for all field activities in cassava fields (Niha) YLO = Yield of fresh cassava tuber (tfha) These were calculared only for fields where sample OUtpUts were estimated during the survey,

Household characteristics and income

Household characteristics Cassava production in Nigeria is predominantly in the hands of small farmers. What follows is a descriptive analysis of the characteristics of smallholder farming households and (h e sources

or income in the somheast and 5Outh~sourh zones of the country.

A household uni t is defined in drjurr terms, which relies on the concept of normal residence whether or not an individual member of the household was present at time of interview. Two other criteria are imporram in classifying (he household members. A ho use-

hold is recognized as people who usually live and eat together in a dwelling. Secondly, they acknowledge the authoriry of a single head of household, regardless of wherher the lalter is living with the household members or living away. The average household size is about seven perso ns in [he survey area. The largest households were recorded in Ebonyi State with an average of 10 members per farm household. The least household size was recorded in Rivers Stare with an average of six members in a household. Women headed about 13% of these households. In a typical household there were about four males and abour four females. Mean age of the household head was 56 years indicating that the principal decision makers in rural farm production are aging in the survey a.rea. The household head had spent an average of eight years in school. This may indicate that the rural farm household heads have only completed primary school. Table 2 shows that the primary occupation of the household head is farming (75%). This is followed by teaching and civil service (about 9%). The third in ranking is crafts and artisan (about 4%) while transporting as vehicle owner/driver/motorcycle ranks fourth. Farming is also ,he main secondary occupation (38%) for households in which it is not a ptimary occupation. Another major secondary occupation is trading (about 17%).

Table 2. Primary and secondary occupations of the household head. O ccupa rion type

Primary occupcH ion

Agriculture. own fid ds/labor on O{ht'f.5 fiel ds

Perce nt

Frequency

Percent

11 9

.18. 1

0.6

10.7

3.6

3.8

9.5

O ther primary product io n: ti mber, hum ing. fishing Gent nl household rasks

Artisan or craftsman

T unsportcr: veh icle oWllcr/drivcr/motorcydt T u der: wholcS2lc1 (ctail! hdper/appn=n tice T eaeher/civil servant

Resr.auf3teu rl food vendor/seller Retired/ pensio ner

Secondary occ upacio n

Frequency

•

6 2

2.5 3 .8 8 .8

1.3

1.9

Clcrgy (Reverend/pastor)

I. 7

• •

16 .7

4.8 4.8

0,6

Herbalist/soolhsayer

No t working for heahh

8.3

1. 2 OT

age reasons

Tmai

1.3

158

100.0

1.2 83

100.0

Sources of household income In rural N igeria, the sources of cash inco me are diverse and include farm and nonfarm sources. Farm income sources include cash earned from sale of crops and livestock. Farmers in the study area produce d ifferenr types of crops includi ng cassava. For convenience. Ihe crops were grouped into root and tubers, cereaJs, legumes. vegetable, fruif crops, traditional cash crops, and livestock. The distribution of farming households that grow these crops and keep livestock are shown in Table 3. M ost farming households (96% ) in the survey area grow cassava, 80% grow maize. 70°;6 grow yams, 680/0 grow vegetables. 650/0 keep chicken, 60% grow plantain, 52% glOW cocoyam, 52% grow melon (egtm). and so on. Poultry (65%). goats (41%), and sheep 05%) are kept under the traditional but less capital free range methods.

Table 3. Distribution of fann households by crops grown and livestock owned. Frequency

I"ÂŤa:nt

Cassava

161

Yam

Crops Root & tuber

11 8

Cocoyam

Sw eet potato

Irish potato

3 101

134

Sorghum

Mi llet

J:\eniseed

Pigeon pea

Groundnut

3 19

Bambara gro undnut

a ther beans and peas

Melon (tguu)

\1 4

l rving;a

Cocoa

Oil Palm

Cocon ut

39 22

Rubber

Plantain Cooking banana

Cereal s

Mai7.c Rice

Legum es and pulses

CO'.... pea

Vegc:tables Vegetabl es

Lemon grass T.raditional cash crop'

Table 3. Distribution of farm households by crops grown and livestock owned contd. Crops Kolanuc

Frequency

C ashew

Sugar a n f:

5 14

Sweet banana

Orange

Peu.:c:1lt 7

Frui.( <TOp.

C irrus

Mango

Pineapple:

40 40

Papaya

24 20

Gu.ava

Chicken

109

Sheep Coa.

15 41

Pig

Cattle

u.estock

IUbbi.

Other liVC5cock

Income from crops During the household interviews, farmers were asked to indicate how much income (gross) they earned from different crol'" in the last planting season. The results are presented in Table 4. Most farming households (90%) <arn their income from cassava, which averages about N65 472.45 per year. Another important crop in terms of number of producing households is maize in which 76% of the farming households <arned an average of N 13 056.34 per annum. Mai"" is produced in the study area but is mostly sold and consumed fresh. Yam is also an important crop in terms of number offarming households (54%) and income earned which averages about N58 828.68 per annum. Even though yam is associated with a rich cultural tradition in the study area, the number of households that produce yam is about half the number of households that produce cassava. Besides yam is not a crop [har is easily processed into other forms like cassava such that more household income may likely accrue from cassava when jt is processed infO several Olher for.ms. OTher importa nt

crops in Lerms of ,he number of household were vegeta bles (57% of households), plantain (49% of households) an d melon (4 0% of households) for which the produci ng households e"rn ed about N8602.11. N 55 342.1 7, an d N 7637.65 per an num. respcctively.

Table 4 . Cash income earned by farm households from different cropâ&#x20AC;˘.

Crop description

Mean

SId. d"ialion

Cassava

HOus<hold, (%)

151

65472.4 5

174958.40

89.88

Yam

58828.68

130410.19

54.17

Cocoyam

9754.55

14 031.29

39.29

Sweet porato

8246.67

13792.49

8.93

Irish potato

6000.00

5656.85

J.l9

Planlain

55342. 17

287 125.53

49.40

C. Banana.

10894. 12

14489.37

10.12

127

13056.34

45240.65

75.60

Maize

45909.16

70379. 14

13.10

So rghum

1666.67

2886.75

1.79

Millet

1475. 00

2359.91

2.38

300. 00

67 443.06

0.60

1880.00

1987.17

8.93

Pigeon pc..

1550.00

3053.69

2.98

Groundnut

11155.1 7

17989 .51

17.26

8amba r. nut

5745.4;

6979.45

6oS 5

Rice

Beni.secd Cowpea

24857 .14

55237.91

4.17

Melon (Et"SI)

7637.65

109n.85

4D.48

Irvingia

13 680.00

15805.98

8.93

Vt'getables

8602 . 11

21658.25

56.55

Other buns/peas

25666.67

34063.67

1.79

Oil' p.lm

83994 .00

283 591.90

32.74

Coconut

10 016.07

20612.40

16.67

Cocoa

Rubl>< ,

60 000. 00

Koian ul

J2 171.43

21369.89

4.17

Cashew

6000.00

3605.55

1.79

Sugar c:tne

2096.63

3241.00

4.76

S..... eet bananil

6651.85

7186. 12

16.07

Or:lnge

7029.03

10356.78

18.45

Citrw

7166.67

13 644.29

3.57

Mango

5342.86

11 517.75

12.50

Pint-apple

11 280.65

20 291.58

18.45

Papaya

2032.73

2658.69

13 .10

844.00

787.20

Guava Respo nsc

168

0.60

2.98 100.00

Livestock income Farming households also earn cash inco me from livestock sales as indicated in Table 5. The important livestock kept by farmers in the zone were chicken. goat. and sheep. Farmers earned [he teast income per annum from goat and the highest income from other types of livestock even though more households kept goats than sheep. Table 5. Cash income earned by fann households from different livestock. Livestock description

Mean

Households (% )

Srd. deviation

Chicken

53.38

13998

47 083

Sheep

11.49

20000

17899

Goat

29.05

109 18

14820

Pig

0.68

100000

Cattle

2.03

52667

29687

Other

3.38

106 040

220369

148

100.00

Response

Sources of nonfann income Trading and small businesses and government civil services provide the major source of nonfarm income: in the survey area (Table 6). Other sources of nonfarm income incl ude bricklaying and building contractor. The fact that these occupations exist in the villages is intereSting, as a previous study (Ezedinm. an d Kor ie 200 I) has shown that they are driven by migrant remittances, which are used predominantly for construction of houses in the rural areas and not for agricultural purposes. Other imponam nonfarm activities include crafts, vehicle driving. mechanic, and herbalists. Table 6. Sources of nonfann income. Nonfarm accivi'Y <kscrip[ion

Craftsman (han dicrafts)

Frequency

Pc:rcent

Bricklayer

Building contraccor

4.9

30.5

3 3

3.7

15.9

Trading/small business Beer/wine mal.:ing Vehicle dri~r/mechanic Government services

4.9 6.1

3.7

Hunting

1.2

Butcher

1.2

Herbalist/soothsayer

3.7

Unskilled nonfarm labor

2.4

Other (specifY)

19.5

Total

100.0

None at all

Earnings from nonfarm activities Income from nonfarm income so urces averaged about Nl14 759.74 per annum as shown in Table 7. The south-so uth stan:s earn more inco me per annum from n onfarm income so urces th an th e so utheast states of the survey area. Ie should be noted that income expectations are much higher in the south-south states especially Rivers. Baydsa. and the southern pan s of Delta Srate due CO the presence of oil producing and prospecting companies in the region. Table 7. Cash income from nonfarm sources by zone. Zone: Mon N Std. de\Âˇi:llion 77 085.7 1

134598.52

SOUlh-sout h

136287.76

182285.86

Total

114 759.74

168059.89

Sou theast

Earnings from harvested cassava stems Figure 2 shows th at abo ut 27% of th e fa rm ers also earll ed inco me fro m the sale of cassava stems. Cassava stems were not sold by most (73%) of the households. Those who do not sel l Clssava either leave it in their fields or give it om as gift (Table 8). The fuct that farmers rel y on self-saved s ((~ ms implies that over the yea rs fa rmers are unlikely to plant dean stems and even the improved varieties are likel y to break down , due to disease pressure. T able 9 shows that, 011 the average. cassava stems were more expensive per bundl e in the so udlCaSt rela ti ve lO the so uth -so uth sta tes. The mean number of sticks in a bund le is about 98 stems. A bundle contai ns about 80 stems in the so uth -solHh srates and 120 stems in the south east sra res The sale of stems indicates that there is an opportuniry to build strategic reserves for improved seed suppli es using private ste m out growers.

Figure 2. Proportion of household selling cassava stems.

Sale

â&#x20AC;˘

Non Sale

Table 8. Disposal 01 cassava stems. US<' description

Frequen cy

Percent

Sci I

26.7

Leave in field

30.8

5lort':

19.9

Gift

17.1

Firewood

2.1

Others

3.4

146

100.0

Total

Table 9 . Sale of cassava stems by zone.

Zone

S talistics

Amount

Numlxr of S(ems in one bundle of cassava nicks sold

Amoumsold per bundle:

Sou rheas,

Mean

2807.69

121.33

702.78

13.00

15.00

18.00

Std. deviation

1889.21

74.22

1101.00

Minimum

200.00

35.00

50.00

Maximum

6000.00

250.00

4000.00

Mean

5550.00

81.39

245.65

21.00

22.00

23.00

Std. dNiation

10760.85

73.36

243.51

Total

Minimum

500.00

20.00

50.00

Muimum

50000.00

300.00

1200.00

Mean

4501.47

97.58

446.34

34.00

37.00

41.00

Std. deviation

8561.95

75.34

774.95

Minimum

200.00

20.00

50.00

Maximum

50000.00

300.00

4000.00

Table 10 shows ,he income earned from ail sources of cash income by zone. Generally, households in the southeast and south~sou(h regions of Nigeria earn their highest in comes from ,he sale of roars and tuber crops (N104 622.55) . This is followed by traditional cash crops with a mean incomeofN73 677 while ,he least mean income ofN 13 787.54 is earned from fruit. The south ~south has a higher mean income from [he following enterprises: roO[ and tuber crops (1'<122 553.80), vegetables (Nil I 72 .88), traditional cash crops (1'<109 821.75, fruit (N18 038.67), and livestock (N33 793.67). Income from plantain and banana (NI16 476.00), legumes (N Is 448.75), and cereals (N23 137.96) is higher in the sourheast zone. The details are in Table 9.

This survey focused primarily on the Status of cassava production by farmers in the southeast and south-south statts and so info rmacion on wealthlinves tment status of the households was not obrai ned at this time. However, observations show that farm households may spend their income on several items, w hich may be tangible or intangible. These may include housi ng con struction or rent, material possessions. food , clothing, C'ducation of children, religious :md social conrributions. health ex penses. agricultural implements and machi nery. veh icles including bicycles and motorcycles. livescoc k, and several others. Expenses by rural ho useholds are too numerous and will therefore require a defin itio n of an index thac can consider a basker ofgooos. Such an index can be used to classilY households into diffe re nt socioeconomic profil es. The index , which will be defined later. may cons ider h ousehold profile and type. material possessions. and social, educational, occupational and income profiles of rhe households. Further information on household expenditure will be collected in subsequent surveys fro m househol ds benefi ting directly from project interventions and used to define thei r wealch/investment S[atus.

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Status of cassava production in southeast and south-south Nigeria Relative importance of cassava by land area The status of cassava prod.uction is assessed in relative terms. The proportion of hdJ~ and land area d(:votcd to cassava is compared to that devoted to other crops in the study area. The farming system in the sample fields is such that about 44% (or 100 fields) of the sample fields are monocropped; ahout 32% (72 fields) ate made up of a three-crop combination; about 19% (44 fields)are made up of a two-crop combination; and about 45 (nine fields) are made up of a four-crop combination. Table 11 shows that the mean land area plamed by farmers in 2004 was 0.57 ha per farmer. Mean land area devoted to crop produclion (Table 12) ranged from 0 .23 ha in Abia Stare to as high as 1.7 ha per farmer in Edo State. Most fatms carried more cassava (48%) than any other crop. About 43% of the cassava fields (98 fields) were sole-cropped fields . Maize (78 fields) and yam (59 fields) were the second and third most important crops planted by farmers in the survey area. Per capita land area devoted to cassava was 0.6 ha. Highest land area per household devoted to cassava was 1.66 ha in Edo State. Mean land area (0.83 hal devoted to maize in 2004 was 39% higher than th .. devoted to cassava even though the number of fields carrying cassava was 1.9 times more than the number offield, carrying ma ize:. All (100%) maize fields (98 fields) also carried cassava. Similarly, per capita land area (0.81 hal devoted to yam in 2004 was 36% higher than that devoted to cassava even though the number of fields carrying cassava was 2.9 times mot< .han the number of fields carrying yam. Table 11 . Distribution of crops cultivated by field (ha) size in 2004. Crop description

Mean

T ow (%)

Ca5sava Yam

0.60

227.00

48 .09

0.81

59.00

12.5

Coco)'am

1.1 7

15.00

3.178

Swttt potatO

2.40

5.00

1.059

Plantain Maize

1.08

15.00

3178

0 .83

78.00

16.53

Riel'

5.57

2.00

0.424

Millet Cowpea Pigeon pta Groundnut Other be-ms Melon Green grain

1.77

7.00

1.483

3.7 5

3.00

0.636

2.87

4.00

0. 847

3.84

3.00

0.636

3.10

4.00

0 .847

0.87

32.00

6.78

0.06

1.00

0.212

Vege(2bl ~s

0.28

10.00

2.11 9

Pinc:lpple Fidd

0.27

7.00

1.483

0.57

472.00

100

The production of multiple crop' by farmers in one field suggests that the project should strive co un dersta nd rhe local farming systems. This will enable the project to effectivdy introduce slistainable farming pracrices that will be socially and economically benefi cial to the local farmers. Table 12. Mean field area (hal of major food crops in the study area. StOltes

Abia

Statistic Mean

N Ak~Ol l bolO

Mnn

AnambrJ.

Mean

N Baydn

M~n

N C ross Rivet

MC.ln N

Dc-ha

Mean

N Eoon)"j

Me:;. n N

Edo

Mean

N Enugu

Me", N

Imo

Mean N

Rivers

Mean

TOial

Mean

Field

Cdssa' "a ha

Maiuba

Yam ha

DAD

1.05

0. 10

29 .00

25.00

500

2.00

0.4 1

0.48

1.01

26.00

15.00

2.00

0.36

0.6 1

0.08

19.00

2.00

0.29

0.35

0.38

18.00

2.00

0.86

1.73

1.32

35.00

10.00

12.00

0.49

0.50

0.63

0.80

31.00

25 .00

13.00

9.00

0.87

0.70

0.80

0.70

20.00

7.00

3.00

7.00

1.66

2.88

2.66

22.00

6.00

5.00

0.26

0.28

0.48

33.00

12.00

3 .00

0.23

0 .40

0. 10

38.00

37.00

15.00

9.00

0.63

0.44

1.07

0 .23

36.00

34.00

7.00

11.00

0.57

0.60

0 .8 3

0.8 1

307.00

227.00

78.00

59.00

land resource allocation to crop production by fann households Table 13 shows that land used for cultivation by the farm households was mostly in herited (77%). About 13% of the farms wete rented. 6% were purchased. while the community head allocated about 3% of the land. The fact that land for agricultural production is inherited provides a serious consuaint to cassava industrialization and commercialization in Niger ia. However, land can be rented after the necessary traditional obligations have been mer. Rent varies from community to community and the values vary. It is important 10 make one critical distinction on land ownership and use. Except for a few a reas in the study area (namely Ohana and Afikpo wnes). all the communities surveyed operate a patrilineal system of descent. This suggests that land is inherited and owned by men and in so me cases were land is abundant such land could be held in trust by the community head. Even in the exceptional areas of Afikpo and Ohalia. land is still owned by men on the maternal side. However, [he use of the land for agricultural purposes is made accessible by marriage or some other means (rent , allocation) to women . It however beco mes more complicated for women ro access land fo r other uses unless the husband or the extended fami ly/co mmunity and/o r the co mmunity head agree to it. Hence while it is easy for women [0 cuh:iv3tC thei r family land (by marriage), access to land for other non agricultural purposes has to be granted by the comm unity. Similarly. the size of the la nd available to women depends on the size of land inherited by her husband or the extended family. Hence many families rend to negotiate for morc land by rent especially when the family size is large or when they wish ro engage in production of a crop or set of crops for sale. Bmh men and women can negotiate land for rent for agricultural purposes and so it is nOt exclusive to men to do so on behalf of th eir wives. Table 13. Method of land acquisition for crop production in the survey villages. Pc:rcc:nt

Type of ownc:rship

Frc:quc:ncy

Inhc:ritc:d

234

76.47

Borrowedl rr:nr

14.38

Purchased

6.209

2.941

Allocated by community head

Tot.u

100.00

306

Trend in cassava production Figure 3 shows thac cassava production is increasing in southeast and south-south Nigeria as indicated in 81 % of the villages and decreasing in 19% of the villages. This response is based on the pÂŤctption of the groups thar were interviewed in the villages. T he gro up was required ro respo nd to the question: what has been the trend in cassava production in the last 20 years?

Decrea sing

â&#x20AC;˘

Increasing

Figure 3. Perception of fanners by trends in cassava production in the last 20 years .

In villages where C.1SS.tva prodllcrion is increasing. it is primarily repl ac in g ya m (31 0/0) (;1l1ow ( 17%) , COCO)'.1111 ( 16%). and pa.srure ( 1Gq&) as indiGHed in Tab le 14. Acco rd ing lO respondents in the vilbge level survey. cassava. produc ti o n is increJsing because or popubtio n grow th o r imm igration. and greater market d em and. in villages when.: cassava production is d ecl inin g, yams and cocoya ms arc p rim arily replacing caSSJ.V3 (T ab le 15) . Table 14. Crops displaced by increased cassava production. C rops

Frequency

Percent

Yams

J 1.9

Cocoya rm

15.9

1.4

$WCl'! potJ.1O

Mail.e

1.4

Ricc

5.8

Co .....pc::&

2.9

Vcgc!ablc

2.9

1.9

17.4

COffl'C Pbntain

Fo..llow

1.4

15.9

100.0

Table 15. Crops displacing cassava where there is decreased cassava production. C rop

Frequency

Pcrccnt

Yams

8.2

Cocoya ms

6.1

Cowpca

2.0

rincapplc

2.0

Planlain

Tmal

2.0

100.0

Productivity of cassava in southeast and south-south Nigeria The average roOt yield obtained from 149 sample fi elds during the survey across the II States is 8.4 tlha (Table 16). On the average therefore cassava toot yields are poor and lowe r than the natio nal a....erage in the southeast and south-south states of Nigeria. Cassava fresh root yield ranged from 800 kg/ha to 38.93 tlha in the 149 sampled fields. Th is result bring' into focus the fact mat even under poor inpur production systems, farmers can still attain above

30 t/ha. However 87% of the field sample, had yield, that were below 20 t/ha. Thi, brings a major challenge for the Cassava Enterprise Development Project suggesti ng that small farmers have to be assisted in the project states ro improve their yields with the introduction

of high yielding and disease-resistan t (CMD) varieties. To produce efficiently for industrial purposes farmers need to anain an average

yield of at least 20-25 tfha. This is considered

the break even yield at which it i, assum ed that rhe farmer can make a profir. The tacr that smallho ldcr farmers in Nigeria are nor producing cassava efficiently also justifies the need for investors in the ca.<;saV:l agroindustry to consider the sourcing of at least 75% of their raw material from their own nucleus farm in [he early years of the investment,

Table 16. Yield and other output parameters by state in southeast and south-south Nigeria, 2004. State name

Statistic

Abia

Mran

Ddu.

Ebonyi

16340.91

40215.9 1

22.00

4.00

5';18. 12

13 7i6. 11

Minimum

2.50

3.00

5000.00

17500.00

Maximum

36.50

21. 10

27500 .00

65000.00

7.32

5.33

6820.00

24341.30

23.00

25.00

13.00

Std. deviation

4.67

2.64

2906. 10

18027.43

Minimum

1.10

1.23

1500.00

1250.00

Maximum

20.50

11.73

10750.00

80000.00

Mean

25.65

27.00

13250.00

26500.00

2.00

Std. devi ation

12.52

19.09

6010.41

6363.96

Minimum

16.80

13.50

9000.00

22000.00

Maximum

34.50

40.50

17500.00

3 1 000.00

Mean

5.86

7.21

II 428 .57

33714.29

7.00

3.72

3.09

4595.55

14727.69

Minimum

2.00

4.50

6000.00

14 500.00

Maxi mum

13.00

13.50

18000.00

55000.00

Mean

13.13

8.91

7722.22

33 535.23

27.00

22.00

Mean

Std.

Cross River

9.52

Roo[s/ha

6.94

Baydsa

8.05

Scands/ru.

22.00

Anambra

Top wt (t/ha)

Std. deviation

Akwa Ibom

Root yld (tfha)

d~iati o n

22.00

Std. deviation

7.20

4.91

2362.9 1

II 350.08

Minimum

3. 15

3.60

4000.00

14000.00

Maximum

32.50

26.75

12000.00

60500.00

Mean

13.43

13.15

12450.00

36755.00

10.00

Std. deviation

51 17.78

25 159.44

12.08

8.24

Minimum

3.50

4.25

Maximum

38.93

27. 13

19000.00

88500.00

Mean

9.66

10.24

4005.56

14920.83

4.00

Sed. deviation

4500.00

9500.00

14.27

12.88

2433.13

10 937.63

Minimum

1.05

\.25

2222.22

6750.00

Maximum

30.88

29.3(,

76(JO.no

j (J HO IJ ,O()

Table 16. Yield and other output parameters by state in southeast and south-south Nigeria, 2004 cont'd. Srale name

Edo

Enu&u

Statis ti c

ÂŤIha)

Scands/ha

Roots/h.

7.29

12.27

6916.67

26583.33

6.00

6 .00

Std. dc:v iation

4.94

5.29

.~862.21

14 227.32

Minimum

1.4 5

2500.00

12750.00

Maximum

16.03

21.93

13 250.00

45 500.00

Mean

16.04

10.72

17066.67

43725.00

5.00

Std. devi:lIion

7.67

5.21

5166.13

18300.10

Minimum

3.95

2.70

8500.00

13000.00

M:aximum

24.10

16.25

22 500.00

58000.00

Mean

Sid. deviation

4.09

8.34

19 740.74

26703.70

27.00

2.29

4.34

7887.88

9844.23

Minimum

0.80

'1.00

6500.00

12 000.00

Maximum

10.50

24 .50

36000.00

44000.00

5.44

46.05

27571.43

34345.24

Mean

21.00

Std. deviarion

2.11

174 .16

8874 .52

10 754.79

Minimum

2.25

3.50

15 500.00

17000.00

10.50

806.00

25000.00

59000.00

8.38

14.26

14258.69

31671.03

Maximum

Total

Mean

Rivers

Top

Imo

Roo( rid ÂŤIha)

Mean

149.00

156.00

149.00

Std. d eviation

7. 23

65.54

9093.61

15268.53

Minimum

0.80

1.23

1500.00

2250.00

Maximum

38.93

806.00

25000.00

88 500.00

Table 17 shows that generally, yield pcr hec.. re was higher in the south-south states than in rhe sourheas, "ates. However. Anambra Srate obtained the highest yield of25.6 t/h. followed by Enugu in rhe same sourheasr zone wirh 16.04 t/ha. The state with the lowest yield in the sou theast state is Imo with 4.1 tfha. In the south-sout h zone [he leading state is Delta with 13.43t/h. followed closely by Cross River wirh 13.3 rfha. The state accounting for the lowest yields in the so uth-south lOoe is Rivers Srate with 5.44 tlha.

Table 17. Yield and other output parameters by zone in southeast and Nigeria, 2004. Zon. Southeast"

RoO( yld (rlha) Mean

Sourh-50Uth

Top wr (r/h,)

7.63

9.72

south~outh

S[an d ~ / ha

Roors/ha

17005.9.\

284.3 1

60.00

S,d. deviation

7.7 1

6.45

7516.88

14495.02

Mini mum

0.80

1. 25

2222.22

6750.00

Maxim um

56.50

40.50

36000.00

65 00 0.00

8.88

17. 32

12541.67

3 1 25 7.58

89.00

96.00

89.00

Std. deviat ion

6.88

84.70

9596.03

15836.14

Minimum

1.10

1. 23

1500.00

2250.00

Maximum

38.93

80G.00

25 000.00

88500.00

Mea n

60.00

The average number of stands per hectare ranged from 1500 [0 25 000 with a mean of about 14259 plants per hectare in the survey area. This falls within the recommended range fot sale cassava fields (Ezumah and Okigbo 1980). T he mean number of stands differs from region ro "gion. The planting densiry is higher in the southeast with 17005 plantslhectare while rhe sourh-south has abour 12 542 planrs/heccare. T he top weight consists of rhe cassava Stems and rhe leaves. The lOp weight averaged about 14.3 r/ha in the survey area wirh a range of 1.23 to 606 t/ha. T op weight is higher in ,he south-south regio n (17.32 r/ha) relative ro rhe southeaSt. which recotded 9.72 r/ha. This suggesrs rhat the south-south zone of Nigeria has the best comparative advantage in cassava foliage and perhaps stem production (TableI 8). Table 18. Yield (tlha, for local and Improved cassava varieties in the southeast and south-south zone of Nigeria. Southeast

South-south

All

Variety

Mean

Improved

7.73

local

3.68

Total

7.63

Improved

1l.l01

local

5.27

Total

8.88

Impro~d

10,49

Local

4.48

Total

8.48

% Difference

110

I II

134

In rhe sourheasr zone, yield afloeal cassava varieries averaged abour 3.68 t/ ha and 5.27 rfha in rhe south-south zone (Tlblc 18). On the whole, yield oflo eal cassava varieties averaged abot!{ 4.48 t/ha. Yield ofimpron路d varieties averaged about 7.73 t/ha in the southeast zones and. 11. 1 r/ha in the .'iouth-S(IlHh zone. In both zo nes yidd of improved cassa\'a varieties c.:xctl"'ocd thar of local C;1SSi\V;t "aric-ries by over 100%. Yields of improved cassava. varie ties would have been much higher if farmers had ado pted good agronomic practices ;Lnd improved in puls.

Trend in cassava commercialization in southeast and south-south Nigeria

Proportion of cassava sold by farm households One variable that can be used to assess the uend in cassava commercialization at the rural farm level is the proportion of cas<>J,vJ, outpu t (hac farmers sell after harvest from their fields. Cassava roots can eit her be sold {in roots or processed form} o r consumed at home. The proportion sold suggests a higher degree of commercialization uf (he commodity. COSCA had used these variables along with others as indicators of cassava commercialization to show that on [he average Nigerian farmers were willing to sell about 45% of their cassava output 15 years ago (Nweke 1996). Table 19 shows that in 2004. the proportion of cassava output that farmers intt" nd to 5(.,1 1 has illcreased on the avcfJ.gc [0 about GI %. The proporrion of cassava sold had incr<ased from 45% (in the COSCA villages) in 199 1 to 63% in the same villages in 2004. The proportion of cassava output rhat is sold is hi gher in the south-sourh zone (60.3%). compared to the sOUlheast zone (52.6%). 01\ a 5tate-by-'racc basis. rhe proportion ,old is hi ghest for farmers in Cross River Stare (72.5%) and is lowest for farmers in Ebonyi State (28%). This also suggesrs tha t the proportion consumed at home in the rural villages is relatively hi gher in Ihe sout heas tern states chan in the sou rhsouth zone of the COlIntry. Table 19. Proportion of cassava output sold in the southeast and south-south zone of Nigeria. Proportion of cassava output sold. State路 name

Mean

Std. deviation

Abia

57.60

25.00

15.08

Akwa Ibom

66.00

2500

17.32

Anambra

56.25

1600

20.94

Baydsa

57.00

20.00

10.81

Cross River

72.50

3400

15.68

Delta

53.46

26.00

23.99

Ebonyi

28.16

19.00

12.6 1

Edo

50.95

21.00

21.66

Enugu

56.2 1

29.00

20.60

Imo

57.1 I

38.00

8.98

Rivers

56.97

33.00

13.80

Southeast

52.6

127.00

18.5

South-south

60.3

159.00

19.0

Total

56.89

286.00

19.1.l

Cassava processing and contribution to rural employment Table 20 s.hows (hat [ht proponion of cassava (hat is processed from farm ers' harvest is about 73%. This suggests that farmers process a greater proportion of their cassava before selling rather th an scll roots in fresh form. The proportion of cassava that is processed by farmers in the sO Ulh-south zone (74%) compared to rhe southeast zone (72%) remains rel atively the same. The fact that m OSt farmers process cassava before sale suggests thac rh.ey understand the high er returns [hat can be obtained from selling processed cassava products. Table 20. Proportion of cassava output processed by small fanners in southeast and south-south of Nigeria. ran or cassava output processed

Std. deviation

State

Mean

Ab i<l.

77. 14

28.0n

27.74

Akwa Ibum

79. 17

24.00

18.86

Anamb ra

8 1.05

19.00

19.97

8a)路d sa

58.50

20.00

9.33

Cross Rivc:r

61.29

35.00

29.74

Dc-Ita

98.57

28.00

7.56

Ebonyi

84.2 1

19.00

26.31

Edo

97.00

20.00

9.79

Enugu

73.55

31.00

25.37

Imo

56.58

38.00

12. 14

Rivers

59.69

32.00

11.21

Southeu:t

n07

135.00

24.35

So urh ~sou(h

74.37

159.00

24 .!7

Total

73.32

294 .00

24.24

Observations suggest that there may be some degree of specialization in which small farmers in the survey area are specializing jn the production and sale of cassava fresh TUbers to tcade rs. middlemen, and processors. This is especially true for states like Bayelsa and Cross River. It was observed that farmers in thCS(: states mostly sell their cassava fresh foors [Q processors who conven the roots to gari or Jufo. Many farmers also sell their cassava on the ground \"ithoul harvesting co processors and middlemen. This also indicates thar fa rmers are uan sferrtng the cost aflabar for harvesting to others in the cassava commodity chain. It will be interesting to further investigate the price djfferenrial to the farmer who harvested and sold his/her cassava vis-a.-vis the farmer who sold unharvcsled cassava in (he field in order t D understand whether the price differential is greater or less (han the cost of labor foregone by the farmer. This emerging class of prod ucers may be a phenomenon that can su pport the growth of outgrower schemes in the commercial production of cassava for indust ria l purposes.

Cassava processing centers exist in 61% of {he villages visited. On average, there arc about seven processing centers per village that employ about three (3.3) persons per center. Table 21 shows that the most common types of cassava processing machinery were me grater only (in 39% of the villages) or in combination with a press (35%) or a grater, press, and milling machine (17%). The cassava grater is the ubiquitous machinery used for cassava processing in many villages and can be moumed in a shed or on a mobile truck. Processing centers and machines are owned by individuals in 38% of the villages and provide services to rural micro and homestead processors on a custom-service basis. Table 21. Distribution of villages by type of microprocessing equipment. Processing equipment

Number

Percent

Grater, milkr. chipper. press

4.00

7.69

Grater. millet, press

9.00

17.31

Grater and press only

18.00

34.62

Gra[er only

20.00

38.46

Miller only

1.00

1.92

Chipper only

0 .00

0.00

Press only

0.00

Fryer

0.00

Other specify

0.00

Toral

52.00

100.00

The availability of cassava processing cemers is very common in the southeast and southsouth zones of Nigeria. In all the 54 villages in the survey rhere is at least one cassava processing centrer located within the village. The number in the villages ranged from a unit in Owerri-Ebiri, Obinikpa, and Ikot Amborn to 40 in Afuze. Small to medium-scale cassava processing factories were not observed in the sample villages. However, chere is evidence to suggest that such scales of factories exis[ in the survey zooe. Examples include the Nigerian Starch Mills. Others such as the Brazilian Gar; plant at Iriebe, near POrt Harcourt and the Miragate Factory at Obudu in Cross River State have become moribund. However. it must be said that none of [he processing centers have built in environmental mitigation procedures. Secondly, many of the centers do not observe simple hygiene and protection from hazards and accidents, This is one critical faeror that the Cassava Enterprise Development Project has to deal with. Table 22 shows that the important processed cassava products by farmers are primarily gari (39%), fermented dough (akpu) (26%), and local tapioca (19%). Others are edible starch, lafon, and cassava biscuits.

Table 22. Cassava products fanners process from their fields by zone. 2004. Southeast Product

Survey area

SouthÂˇsouth

Co ...,

CoWl'

17.00

42.50

27.00

36.99

44.00

38.94

0.00

1.00

1.37

1.00

0.88

15.00

20.55

21.00

18.58

9.59

10.00

8.85

2.74

7.00

6.19

CoUll'

Gari

Search tapioca

Local rapioca

6.00

Starch

3.00

7.50

7.00

LAfim

5.00

12.50

2.00

Biscuit

0.00

1.00

1.37

1.00

0.88

Aft,.

9.00

22.50

20.00

27.40

29.00

25.66

Toral

40.00

100.00

73.00

100 .00

113.00

100.00

The C ..sava Enterprise Development Project would be required to introduce processing centers and new produc~ in order to diversify the income base of the rural populace in the project wne. The centers may be micro or small- to medium-scale enterprises depending on a parriciparory assessment of the communities. Such products like dried fofo Rour. high qualiry cassava Rour. and tapioca may have potential for adoption. as locals in rhe project area seem to consume them presently in their wer forms (e.g .â&#x20AC;˘ alrpu). However. in order to counter the "entitlement mentality" that is common in the region, the project would follow a parricipatory approach in which it will require the beneficiaries to make commitments and inveSlmenrs towards rhe ownership and development of the enterprise. The potential beneficiaries wiU need business development support services such as training in management. machinery maintenance. book keeping. and so on. The beneficiaries will need to organize themselves into sustainable associations and groups to ensure a wid~r impact of [he project in terms of income and job creation in the region.

Use of improved cassava varieties and other inputs in cassava production Spread of improved cassava varieties Improved Cas5:lV3 varieties arc varieties that wen: developed in research s {,Hions and intro· duced through the nation:t1 ext ensio n sys tem to farmers. Hi stori c31l~'. research. devd o pmt'nt, and di ss~mina[ion ofimprovc:d cassava v.trit.·tit·s starred lo ng ago in 'I·an7_lni.1 ill 19.3 ) and in 19 58 in Ni geria. Figure 4 shows ,hat 53q.'cJ of rh e fidds vi sitcd durin g the survcy ca rried 10c.al cassava varieties onl y. 40% carri ed improved CaSS3 VJ varieties. whi lc 7°/n carried both local and improved cassava varicties. By ddinition slich fidd~ (ould be.:: ddiIH::d 3 S fidds with improved (assay.! varieties. This rcsulr has (Q be inrcrprc[cd with more..' ( .unio n 3S it is likely thai so me of the so-called cassava \'arieties were improved variet ies inlrodl.cl"d much carlicr in tht' 1970s following the work of Beck, Ekandem. S. K. Hahn. and o thers. such that rhe), were only identified by their local names. NWl"ke l"t al. (1999) has traced the hislOrical development of cassava research in N igeria :md d st.·where su££cs tin g that s('"\'e:ral cassava varieties hOld origin:ue:d from reseMch ~ [ 3 tion s ca rlit.·r dtan th e: pre:se:m ~ [lId r can determine, These varieties Illay tod.,), be c01lside:rcd local varictics e:ven though they origi. nat ed from rcse;lfch S[:1IiOn 5 much earlier. One point to note. however, is that improved C;lSS;tVa varie:li e:s uriginatin g fro m IITA and the NRCRI were observed in fidds in all th e villages visited duri1lg the survey.

Improved

•

Local

Both

Figure 4. Proportion of fields with improved and local cassava varieties.

Table 23 shows that rhe proponion of fields carrying o nly improved cassava \'arieries was higher in rhe south·sourh region (480/0) , compan.:d to the: sourht.'asr region (24 0/0) This suggests rhat more effon has to be put in place to e:xrend improved planting m:Hcriab to more farmers ill the southeast S1311:S by thc CEDP, Secondl y. improved cassava v3ril'ties He: gender neutral as it is not 3 lumpy rechnology. Thc:refun: si nn: women an: the dominant produccrs of cassava in rhe study area. greatcr cmpha~ i s should be pur to givc women farm· en' grea ter access to the culrivation of improved C3.5S3V3 v3 rieli es.

Table 23. Percentage distribution of fields carrying improved and local cassava varieties South -south

So utheast

Survey area

Va rl\'I }'

Frequ ency

Pefn'm

Frcqucnll'

Perce llt

Frt'qucllC)'

Percen t

Implo \'cJ

::!4 . 1

2?0

48.3

.% .0

40.4

Loca l

7 '\ ,9

2).0

4 1.7

47 .0

) 2.8

0.0

6.0

10.0

6,0

6.7

1()O ,O

60.0

100.0

8~.O

100.0

Luc ll ll mpwvnl TUI.lI

.!~

The.: fact that farmers plant bOlh improved and local va ri et ies on thL' same field has imp lications for industrial productio n sys u:rns. The move towards cassava indusuiali7..3rion dcmands thal farmers do not onl}' h.lVe to pbm sale caSSaY.1 crops. they also n~cd (Q plam pure stands of:1 spl'cific va ri ct), p~.T fic.:ld . Eac h C3.'isava v:Iri c l), h3S specific agrono mic and postharn:sl characlc..'ristics suitt:d 10 spt.:cific t:nd llses. \,(/ith th t: pn.:scl1t system of produc-

tion. it would be difficult for fa rmers to meer ~lgroprocess ing ;lnd indusrry s[and ards .md qU:llity requirements. The important improved caSS3V3 va rieties ohserved in f:lrmers' fields

include TMS 30572. TM S 30555. NR8082 . NR8093. and TMS 4(2) 1425. No nc of these varieries are resistant to the viru lent form ofCMO. Specific efforts should rhe refore he 1l1 3de by the Cassava Enterprise Development Project to use private-secto r entrep reneurs in the multiplica tio n 3nd di stribution of improved C MD-rc:sis ranr cassava v3rietics in rhe 11 somhe3sr 3nd somh-so urh States.

Sources of planting materials and improved inputs Figure 5 shows thar farmers usuall y sou rce the cassav:., stems they "bnt from their own old fields. On ly in 200/0 of the cases did farmers purchase cassava stems from th e ope n marker. Farmers sourced rhcir caSS3va from Ihe ADPs and OIher sources only in 2% of rhe cases. The pattern remains the same irrespective of rhe zo ne (Table 24.) . 2%

o Purchase

â&#x20AC;˘ Own fie lds o ADP/Olhers

Figure 5. Proportion of fileds by source of planting materials.

Table 24. Proportion of fields by sOIRes of cassava planting material in the southeast and

south-60uth zone. Sourh~as{

Survey area

South-south

Description

Frequency

Own produe<d

124.0

80.0

140.0

76.9

264.0

77.9

27.0

17A

39.0

21A

68.0

20.1

Pu rchased MinisuyfADP/mhers Total

Percent

frequency

Percent

Frequency

Pacem

4.0

2.6

3.0

1.6

7.0

2.1

155.0

100.0

182.0

100.0

339.0

100.0

That the majoriry of farmers sourced their cassava stems from their own fields suggests that

small farmers do not buy cassava stems. This has implications for stem sanitatio n. Training is therefore required at the grassroots level on cutting sanitation in planting mater ial

productio n.

Use of fertilizer and agrochemicals by smallholder farmers Table 25 shows that farmers used ferrilizer in 16% of the fields carrying cassava. The use of herbicides and pesticides by farmers was observed only in J% of the fidds. Farmers obtained credit to plant cassava only in 9% of the fields. This again indicates that credit and the use of purchased inputs are hardly used for cassava production in Nigeria. Table 25. Use of Improved inputs In cassava fields. Southeast

South-sol.1th

Survt:)' area

Input cype

Frequency

Percent

Frequency

Percent

Frequency

Pcro:nr

Fertiliz.ers

22.0

28.6

13.0

9.3

35.0

16.1

1.0

2. 1

Herbicides Pesticides O rgan ic m,tnurc

Credit

2.0

4.2

11.0

20.0

1.0

0.8

2.0

1.5

2.0 2.0

1.1

4.0

3.7

15.0

9.3

l.l

Table 26 also shows the type of fertilizer, herbicides, and pesticides applied to the few cassava fields observed during the survey in the southeast and south-south zones. The fact that fertilizer was used in only 10% of the sample cassava fields suggests that the commodity is grossly unavailable. The average cost of fertilizer as reported by farmers who used them was N2700. However the important point to note is whether the farmers applied the adequate dose of fertilizer. About 10% of rhe farmers applied the NPK rype of fertilizer, which is appropriate for cassava production. But the quantity applied was grossly inadequate, perhaps due to unavailability and the cost of purchase. For ,hose who applied fertilizer, rhe survey roveals that one field applied urea while NPK was applied to 100/0 of the fields.

Table 26. Type of purchased inputs used in cassava fields. Frequency Fcrtili7.Crs

Il erbicides

NPK

3 1.0

Urc.."3

1.0

Percent

0.3 0.3

Round up

On-station st udies (F igure 6) show that cassava yields can be increased sig nifi ca ntly if the right fcnilizcr is llsed in cassava production. However, it is important to note dut there arc C35S3va va rieties that do not respond to fertilizer app li ca tion . Therefore while it is imporlant [Q plam improved varieties it is also imponam to plant those that respond ro fertilize r application. All varieties released by research insriuHCS usually take fertilizer responsiveness (ro macro and micronutrients) into consideration. Other economic and agronomic studies (Ospina 2004) have also shown that the lise of fertilizer coupled with mcchaniz;ni on and usc of improved cassava varieties is th e best option to increase productivity of cassava both in the techni cal :lnd economic se nsc.

No Fert

â&#x20AC;˘

NPK

10 0 A

Variety Figure 6. Yield response of improved cassava varieties to NPK fertilizer.

8m thc grcatt:s[ problem had always b(Âˇcn thc unavailability orft:rtili1.er due ro mismanagement of existing fertilizer production and blending plants in Nigeria and their subsequenr collapse. Nigeria started importing fertilizer from the early 1970s but it was nor until 198 5 that local production commenced. Impo rts continued with local production thereby boosting local consumption between 1985 and 1999. Presently local fertilizer production is nonexi stent as all rertilizer plants in Nige ri a are currently out of production. Imports incroased berween 1996 and 2002 bur presen riy, according ro FAO (2005), rhe imporration of rertilizer in Nigeria has declined ro almost zero (Figure 7). At the moment the on ly fenilizer company loc Hed in the project area, the Nationa l Fertilizer Company of Nigeria (NAFCO ). Onnt". Port H arcollrt is nOi functioning but efrons have been made (Q privatize rhe company.

500000

' 50000

- - - - ProductJOn (mi l _ _ _ _ Import Oty (ml)

400000

ConsumptIOn (mi l

350000 _

E -

300000

250000

5 200000 150000 100000

â&#x20AC;˘

50000

Figure 7. Fertilizer production, imports, and consumption in Nigeria, 1961-2004.

Soil fertility status Figure 8 show that most (8 20/0) fa rmers usc bOlh fertile a nd low ferti le so ils in cassava

production. It is also cult ivated in high ferti le soils in I t % of the villages and in low fertil e soils in 7% of the villages. Th is observatio n is co nsislcnc with the gc n ~ ra l impression lhac cassava ca n also be culti vated in low ferti le so ils.

High fertility soil

â&#x20AC;˘

Low fertility soil

Both

82%

Figure 8. Type of soil used in cassava production by fanning households.

Nevertheless. Figure 9 shows {hal soil fertility is decl in ing in mos t (87 010) of the surveyed villages. Again {his is based o n fa rmers' perception on th e starus of soi l fcniliry in their village. T he fa rmer groups res po nded to rhc q ucnion: Is so il ferti lity declining in your fields? Farmers' principal soil fertiliry indicatO rs are consiSlcm redu cti o n in yield over the years. This impl ies that snious efforts have [0 be made to improve fertilizer su pp ly and disr ribution as well as introduce and promore so il fcrtiliry enhanci ng techno logies sllch as the imroduclio n of nitrogell fix ing legum es in the projec r area. Th is will also help to reduce so il mining and deforesta ti on.

No change

â&#x20AC;˘

Declining

Figure 9. Soil fertility status in village.

In view of the f.'CI ,hat farmers believe thaI th e soil fl.: rt ility stat LI S in the stud y area is declining. dTorts will be need,"d [0 inrrodu cc: fc.:niliry and agrochemicals in order to improve th~ productiviry of cassava in rhe S[udy area.

Productivity of labor in the cassava enterprise

Intensity of farm activities in cassava fields Labor is perhaps the major limiting factor in cassava production. Agriculture is considered unattractive involvi ng hard physical work and poor wages by the younger generation. With the increase in rural urban migration, agriculcucallabor is likely to become more expensive in the rural areas since there is little or no mechanizalion to substirute for labor in different fann ac.tivities. Table 27 indicates that seedbed preparation is the most intensive farm activity in caSS3va production in 47% of the farms surveyed. It is the second most intensive accivity in cassava production in 30% of the fields . Land clearing is considered the second most intensive activity in cassava production in 43% of the fields visited during the survey. Farmers in 290/0 of the fields consider if an intensive activity. Weeding is (he mOSt intensive activity in 38% of the cases, the second most intensive activity in 280/0 of [he fields. and an intensive activity in 29% of the fields . Ie was observed that the number of weeding' by farmers ranges from one to six times with an a\'erag(: of three times before harvest. Weeding can therefore be more intensive especially in the rainforest belt in southern Nigeria than in the derived savanna and southern Guinea savanna zones in [he central region. Weeding is also another farm activiry that is of serious concern ro farmers. Good agronomic practices and usc of herbiddes are the best option to the prevention of weed infestation in cassava fields. However. such herbicides are not easily available to the small farmer as observed in the previous section. Table 27. Intensity offarm activities In cassava

Land dearing 'ntC'nsity nnking Mon intensive 2ndmos( in rcnsive Intensive

Low intensivc Least imchiivc

Toc:al

Seed b,d pre:par,UKIn

~roduction.

W('wing

Pl.tnting %

Frcq

0 .0

11 7.0

38.2

3.3

85.0

27.8

6.0

2 .0

24.2

89.0

29. 1

12.0

3 .9

11.0

3.6

141.0

46 .1

F"'l

73.0

23 .9

116.0

-47.0

132.0

73.0

29.6

10.0

89 .0

29 .1

42 .0

17.0

74 .0

9.0

2.9

3.0

1.2

144.0

47 .1

3.0

1.0

13.0

5.3

306.0

100.0

247.0

100.0

Harvcsting

Frcq

Fr"l

Frcq

0.0

0/0

0 .0

78.0

25.5

4.0

147.0

48 .0

306.0

100.0

306 .0

100.0

306.0

100 .0

Use of labor by gender and wages in cassava fields Table 28 shows that land for cass.va production is cleared and prepared manually mosd y by men in 81 % of the fields that were surveyed. These two tasks are [he mos[cnergy LAening in tradi rional farming where the use of hoe and cutlass predominate. fvfostly women do plan(~ ing of cassava (66%). weedi ng (88%). and harvesring (66%). Insight therefore shows that

the gender roles are complementary in (he cassava production enterprise. Besides. Nweke et .1. (2002) had observed that in Nigeria where the cassava transformation has advanced to the stage of a cash crop for urban consumption. men comriburc more labor to cassava production tasks . However, rhe survey shows rhat rhe number offields in which child labor was ~mptoyed for various farm activities were less than 3 % â&#x20AC;˘ T he low level of child labor use in field cro p production may be as a result of the new policy on Uni versal Basic Education (UBE). which provides for free tuition at the primary school l.vel. Table 28. Use of labor (%) by gender in cassava fields. Seed bed prc=paration

Land deating

Planting

F,"l

Weeding

F,,,!

Actor

Freq

0/0

Frc=q

0/0

Mostly men

24,.0

81.1

187.0

80.6

360

11.8

14.0

4.7

26 .0

Mosdy women

40.0

13.3

40.0

17.2

199.0

65.5

263 .0

88. 0

18 1.0

66.1

Both cquJ ll y

17.0

5.6

4.0

1.7

68 .0

22.4

20.0

6.7

66 .0

24 .1

1.0

0.4

1.0

0.3

2.0

0.7

1. 0

0 .4

B2.0

100.0

3a..0

100.0

299.0

100.0

274 .0

100 .0

O ther (children) Total

302.0

100.0

FI'eq

Harvesting

Table 29 shows rhar labor for cassava production is hired primarily for land clearing (27%). land preparation (31.6). and weeding activi ties (24%). A large part of the family labor is used for planting and harvesting activities. Both planting and harvesting are less energy sapping than land preparation and weeding. Farming households th erefore h ave a tendency to hire labor for very arduous farm activities in the cassava enterprise (Ezooinma 1999). Table 29. Use 01 hired labor (%) in cassava field â&#x20AC;˘ â&#x20AC;˘ Land d r-acing Seed bed prrparacion Pbnling Ac{ot

he<!.

Freq

frc:q

Wer-ding %

f'req

H arvesting .Freq

0/0

AJI family

27 .0

8.9

21.0

9.7

45.0

15. 1

24.0

8.0

47.0

17.3

MOidy the f~mily

180

6.0

13.0

5.7

42.0

14. 1

28.0

9.3

37.0

13.6

29 .8

1 16.0

38.8

122.0

40.5

101.0

37.1

23.3

4l.0

14.4

56.0

18.6

41.0

15.1

46.0

16.9

272.0

100.0

H iredJf~mi ly equ~lI y

Mostly hirC'd

All hired Tot~1

107.0 69. 0

35.4

229

68.0 53.0

81.0

26.8

72.0

31.6

53.0

17.7

7 1.0

2J.(j

302.0

100.0

218.0

1lJ{).0

299.0

100.0

301.0

100.0

Table 30 sbows that, in general. rhe average labor wage rat. is N534.79/person day with a range from N382 per person day for women in the southeast to N59L05/ person darior men in the sourh-soutb zone. On a gender basis. average labor rates range from N524 .06/ person day in the southeast states to N59 L05/person day in the south-south states for men, For women. the labor rates range from N382.15/person day in rhe southeast states to N579.73/person day in the south-south states.

Table 30. Labor use (person days), cost (N/ha), and rate (N/person day) by gender and zone in cassava farms. Person days

labor cost N/ha

Wage N/person da),

Mean

Men

N/ p~rson

Men

74.3

114

95687.36

139

504.08

Women

57.2

123

102884.19

142

450. 10

Total

136

187519.83

143

480.50

Men

76.30

120

103389.35

129

560.50

Women

70.44

157

110076.80

153

536.60

Total

94.37

162

222553.87

160

571.2 1

Men

135

137

115027.92

136

575

Women

172

14 162.20

175

450

Total

154

234

267312.42

284

590

Gender

day

Southeast

South-south

Suryer area

Table 31 shows that the trend in labor wage rates for cassava production has changed in real terms. Average labor coS[/day was about N559 for men and N487 for women in 2004. In the revisited villages the average labor COst by gender was about N490 for men and N440 for women in 2004. In 1991, the same villages paid an average of N 15 .30 for men and N 13.0 I for women. Using the dollar rate as a S[able currency these figures show that labor wage rares has increased about four times over the last 10 to 15 years for male and female l.borers. Table 31. Trend in labor use (person days), labor cost (N/ha), and wage rate by gender. Labor cost NIh ...

Person days Gender

Mon

135 95

Wage rate N/lX'fson d3y

N/person day

Mean

137

115027.92

136

575

172

14 162.20

175

450

154

234

267312.42

284

590

142

115

91 239.80

144

490

All 2004 Men Women

Total

Rnuit2004 Men Women

148

119

104635.44

146

440

To.a1

212

156

195512.86

198

450

Men

145

117

4258

15.30

Women

128

113

2229. 10

13.01

Tot.al

138

231

5858.60

121

14.05

1991

It is apparent that in the study area. wages for men are usually higher [han tha[ of women for the various farm operations and this has been consistent over the years. Table 32 shows that men receive on the average N543 for land dearing and N500 for land preparation. Women are rarely involved in chese activities and in the few cases where they were involved they were paid N500 and N590 for land d earing and land prepara[ion. respectively. Men were no[ usually hired for plan[ing of cassa va. Similarly. men were not usually hired for cassava harvesting. When labor is hired for planting of cassava it is most likely to be female labor. \"ifomen were paid an average of N480 for cassava planting. Weeding is the most expensive activity in the cassava enterprise. This is because farmers use hand weeding and they weed a minimum of three times befo re the cassava crop is harvested. Conuary (0 expectations, men were also hired for weeding in cassava fields and were paid N480 on [he average while women received N450. Harvesting of cassava in the survey area is predominantly a women's activity, they (women) are paid ~461on average for hanrcsring cassava but when men rake part in cassava harvest ing, they are paid an average wage of N51 0/ person day. Even though men earn higher wages than women, the number of women engaged in agricultural labor is more than the men. Many of the farm families surveyed hardly provided labor for agricultural production co other farms except as exchange family labor and so i[ is not necessary to estimate their wage labor concribucion to household income. Rather it would be necessary to ascenain the proportion of income that is spent on agricultural wage labor on their farms. Table 32. Trend In labor use (person days/hal. cost (N/ha). and wage rate by gender and farm activity. Men

Women

""' age rare N/pd

Pdlh.

NIh.

Pdlha

NIh.

Men

Women

Land cluring

23 025.32

11 000

543.46

500

Land preparation

27013.5

17113.77

6003

590.13

12003.01

504.80

480.17

23400

480.00

450 .10

24161

510.00

461

Planting

\'('ec:'ding Harvening

75215.20

Productivity of labor in cassava fields Table 33 shows that yield per unit of labor in cassava fields that were sampled is about 140.94 kg/person day for improved cassava varieties and 60.19 kg/ person for when local varieties are used. Labor COSt per ronne of OutpUt is also cheaper when improved cassava varieties are used than in fields with local varieties in the southeast and south-somh zones. This suggeSts that productivity oflabor when imp roved cassava varieties were used in the srudy area under [raditional production systems is 134 times higher than when only local cassava varieties were used. Similarly labor COStS can be reduced by 46% due to the higher yields from cultivating improved cassava varieties. This suggests that farmers who use only

local cassava varieties arc currently producing cassava at greater costs in the study area. Project effons should therefore foem on reducing the CO St of production with (he inuoduClion of labor saving technologies SlKh .h improved cassava varie{ies. Table 33. Productivity of labor in cassava fields. Productivity tlh.a

Improved only

Local only

Southeast

7.73

3.68

South-so uth

11. 1

5.27

Survey area

10.49

4.48

Output Kg/day

Southea5l

123.19

58.65

South-south

131.88

62 .61

Sllrvty area

127.57

60.19

Southeast

17 250.1

48 552.6

South-south

22538.9

46339.1

Survey area

21849.1

47 556.5

Labor cost Nairalt output

Table 34 shows the productivity of labor based on calculated person days for each activity in cass.va fields in the study area. Labor costs/ha total NI07 964 .6. At average yields of 8.38t/ha.laber cemlr will be N 12788.4 in 2004. Iffarmers used improved cassava varieties with yields averaging about 10.49 in the study area; then the cost of laborlt will be about N I 0 216.09/t. If local cassava varieties (with yields of 4.48 t/ha in the study area) are used in producrion. labor costslt of omput are fWO times more expensi,'e at N23 921.4 Sir. This again SUggt5CS that farmers who use local cassava variecies produce at very high costs. Table 34. The cost of labor in cassava production in the southeastlsouth .... outh zones of Nigeria. Product ion cost Operation

Person rlays/ha

Wage rote (N)

Total cost (N)

Land dearing

467.4

28511.4

SB preparation

581.2;

26156.25

Planting

446.8

14744,4

Weeding

450.1

19354.3

Harvesting

468.25

19 198.25

Total

223

107964.6

Fanner assodations and the organization of the cassava subsector in Nigeria

Farmer associations and groups The economic reasons for encouraging group farming and cooperation are based on (a) the fact that economies of scale an: present under ex.isring prod ucdon technologies and marketing arrangemenrs, and (b) a larger scale of operations permi t more productive: technologies to be employed especially for indusrrial mark<ts. Several types of groups and associacions were identified in the survey villages. Each village had more than one type of associarion/gro up. Table 35 shows that the groups/associations include farmers union/associations (in 17% of the villages). village development associations (26%). labor exchange associations or socicc:ies (6%)' farming cooperatives/associations (IO%), processing cooperatives or assoc ia tio ns (3%). market cooperatives or associations (5%). saving/creditlthrift societies (10%). multipurpose socieries/associ.. ions (19%). and emcrcainment/mumal assistance societies/associations (2~o). The cassava growers association was identified in 25% of the randomly surveyed villages in Nigeria (Figure 10). The Cassava Growers Association of Nigeria can be considered a producer associadon concerned only with one crop---cassava. Table 35. Types of farmer associations. Associations

Frequency

Farmers union/associations

Village development :lSsociarions

Labor exchange associ;l(jons/soc.ieties

Farm ing coopc:rativesl.usociations

Saving/creditlthrift societies

Multipurpose societies/ass<Xiations

Processing cooperatives/associations MOlrket co operatives/associatio ns

Entenainmentlmutual assistance societies/associations

Others (sp)

2 10

100

Total

Observations indicate that many groups lack focus. finances, and internal organizational strength. Since the collapse of the marketing boards and the oil boom of the 1970,. cooperati\'es and group advocacy has wa ned. Coopc:racive efforts and group fa rming have failed for several reasons in Nigeria. One major reason for this failure is distrust of individuals in the group. Many farmers fear that some membe rs of a proposed group would seek to

dominate the group to funher their various interests. Another major problem is related (0 managerial and administrative skills. Other problems include lack of production incentives and resentment of outside control. The development of rhe cassava industry will depend on a strong produccr group/association thaI is active in advocacy and self-help.

DYes

â&#x20AC;˘

Figure 10. Proportion of villages with eGAN.

Organization of the cassava subsector in Nigeria The Federal CO\'{'rnm em of Nigcri:l has shown a t.ll1 giblc expression of nadona l will (0 address the constr:l ilHs th:H inhibit the dc:\'e1opmcnr :lIld improvement of the cass:wa subsec(Or. Today in NigL'fia there is. among others. a Presidential Initiative on Cass:lva. The: key isslle is whether the sc.tkeholders and key players see com mon benefit in collahoraring in efforrs to ill1pro\te the performance of the subsecro r. The political will has been expressed in this inili.Hive hUl the c.h:lInpionsllip groups have nOI emerged. The (.1ssav.1 industry In Ni geria tod:lY is not org.lIl izcd and is se:lTching for ch:lmpions. The stak eholders and key players in the CasS:1V.l cOllll1lodiry ch:1in need (0 idemify thl.'l11 selves-a ch:H11pionship group. The:y have: to he: willing to :1crivdy guide: the improvel1lelll effons on behalf of the subs('ctor. In essence, a champio nship group is nced..:d to mobilize the p:1nicip:1rHs ill the cassava cO llllllodi ry chain to become an active self.help community. The process of c113mpioning the subse:ctor must be put on a self-sustaining basis, led by the subsector p~lrti c ipant s (Âˇ.vho b.tsic.tlly are the owners ohhe problem and the solmion). This is to sa)' [hal the cassava subsector cannO[ develop witham the formation of strong formid:1ble groups. The Jormid:1ble: business-o riente:d groups form the bedrock of the champions group in [he cassava industry. It is only the private sector th:H can develop and industrialize the C3S53V3 subseclor on a self-sustaining basis. The criti cal private sector groups can be found in entrepreneurs interested in investments in the food . feed. and agroindustry sector of (he business economy in Nigeria. At the moment only the Cassava Growers Association were identified at the grassroOt Ievcl. The registration of a Cassava Processors Association- anOther missing link in the cassava commodity ch:1in-has been iniliatcd by the International Institute of Tropical Agriculture. Other relevanl associations/groups may include a starch association of Nigeria. whICh at the moment does not exiSi .

The stakeholders and key players have to meet on a regular basis to critically examine the current performance of the subseccoc, and to prioritize:: all the tasks needed to be accomplished in order to achieve subsector im provement. To achieve: the foregoing. someone who is enthusiastic and is credible to the stakeholders and key players has to be willing and able ro convene the subsector at regular in tervals and to implement/monitor the prioritized tasks

which are aimed at improvement of subsec(or performance-a champion. The champion is responsible for several additional casks: continuous lobbying on behalf of the subsector, helping to obtain the necessa ry resources needed for specific tasks, overseeing such investmem interventions. monitoring the: changes in the performance of the subsecroc. maintaining a database on (he subsector, conven ing regular m(Xtings of all

participants, and keeping all participants in the subsectorwell informed (networking among all the actors) on how rhe subsector is changing. To a certain degree the International Instj路 tute of Tropical Agriculture is pe rforming some of these functions with a view to o.talyzing the growth of the: C35sava industry in Nigeria. However, being a non-far-profit institution, sustainable growth in the cassava industry will depend on a privatc:-scclOf champion. This

is because, in ,he long run, the work of the chanlpion has to be put on a self-sustaining b",is, paid for by the stakeholders, rather than an outSide donor.

Conclusion In conclusion we observe that cassava production is predominantly in the hands of small-

holder farme" culrivating an average of 0.60 hectares. Cassava yield from small farmer lidds in the southeast and south region is about 8.38 tlha even though )'ields above 20 tlha were pos.sible under smallholder production systems. This may suggest that yidd per se is not necessarily the problem. Production is not mechanized and there arc no use of agrochemicals and ferci lizcr. While some farmers use improved, cassava varieties, most farmers practiced the unsustainable use of self-saved seeds. To increase cassava productivity in Nigeria. producers have to follow good agronomic practices such as good stem managemcnc, use of impro\'ed high-yield and disease-resistant varieties, mechanization of some farm activities (e.g.. land

preparation), good weed control, and usc of agrochemical.. and fertilizer. There is therefore a strong need to increase fertilizer supply and provide some degree of mechanization at the farm level. Economic reasons will also cominue to drive the use of improved cassava varieties given the inherem advantage to improve land and labor product ivity.

The greateSt challenge to the development of the cassava indwtry is how to reduce the of product ion and labor COSt is the major component of this cos t in traditio nal production systems. Evidence shows that the cost of Lbor is "cry high while labor product ivity is very low when local cassava varieties are used at ,he farm level. The industrializa tio n of cassava product ion in N igf' ria cannot be comperitive with rel iance on human labor alone. Emerging agroprocessing industries may nOt be able to afflJrd to buy cassava because human labor will continue to be expens ive; neither can land area be expanded beyond current production systems in o rder ro acco mmodate emerging ind ustrial markets. Mechanization complemented. wirh the use of improved inputs is the cri ti ca l entry point to the modernization of cassava producrion in Nigeria. There may also be need to pay attention to sustainable produaion practices with the introduction of cover crops and nitrogen fixing crops in the study area . It has become very necessary to introduce some mechanical intervenrion to remove

COSt

the drudgery ofland prepararion nor just for cassava bur also for other commodities. The power tiller is perhaps the smallest land prepararion (power) equipmcnr especially for the fragile soils of southem Nigeria. It is versarile equipment bur may not be affordable ro the small farmer unles.s ir is purchased as a group (Ezedinma et al. 2004). It is, however, necessary ro encourage the manufacmfe of such machines in Nigeria. The rractor hire service is another option but it can only be sustainable if it is operated by privare individuals and farmer groups and not by government parastatals and public agencies. The prrvious tractor hire services in Nigeria collapsed because they were not administered on a profir-oriented

basis. There was also a lack of standards and most of the tracto" were hardly maintained or serviced. For instance.

it has been observed that 15 different brands of tractors arc used

in Nigeria. All were imported from more than 10 different countries. Finally, there was no effort to build capacity in the local manufacture and maintenance, as the Steyr factory located in Bauchi State was primarily an assembly plant.

Presently, small farmas in Nigeria are commercially oriented as more chan 61 % of the f."me[s sell <heir cassava output compared to 45% 15 years ago. This suggests that presently. small farmers seem to respond to the urban and rural demand for traditional cas5ava-based food products namely gari. There is room [0 expand cassava beyond its present production levels and utilization in Nigeria. However. policy support is nceded [0 stimulate diversification and expansion in utilization of cassava imo alternative products such as ethanol, starch.

flour. and so on. Such poliey support has to be sustained and transcend subsequent changes in government . Policy can only be sustained as producers and processors organize. The organized private seCtor producer and processo r organizations are the only institution s that can continue to shape agricultural policies and defend their interest in me cassava subsectOr beyond the tenure of governments. T his basel ine re port provides infonnation on the status of cassava production in the sourheast and south-south states of Nigeria. However the CEDP should co ntin ue to track several factors in its development process. These include area under improved cassava varieties , number offarm families adopting improved cassava, area under sustainable production systems, number of cuttings distributed. number of technologies introduced. productivity of cassava , and dissemination of improved CMD varieties. From time to lirn~. basic infor-

mation may have (0 be collected from the beneficiaries at <he field level and compared wi<h the baseline information in this document. Information such as cassava fresh root yield

and use of improved CMD varieties may be needed to assess the productivity ofland and labor and the adoption of improved CMD-resiSlant varieties.

References Carter. E. and W . Jones. 1989. COSCA site selection procedure. Collaborative Study of Cassava in Africa (COSCAl Working Paper No 2. International Institu<e of Tropical Agriculture. Ibadan Nigeria. Ezedinma. c.r.. R. Okechukwu. L. Sanni. J. Lemchi. F. Ogbe. M. Akoroda. E. Okoro. and A. Dixon. 2004. Economic profitability and we of the power tiller in cassava production. International Institute of Tropical Agriculture. Ibadan. Nigeria. 4 pp. Ezedinma. c.r. 1999.The effect of population pressure and gender on farm labor use in [he cassava producing wnes of sub-Saharan Africa. African Journal of Root and Tu ber Crops 3(2): 7-11. Ezedinma. c.r. and C. Korie. 200 I. Migrant remittances and rutal development in Imo State. Nigeria. International Journal of Agricultural and Rural Development 2: 87-96. Ezumah. H .C. and B.N. Okigbo. 1980. Cassava planting systems in Africa. Pages 4-49 in Cassava cultural practices. edited by J. Weber.].C. Toro. and M. Graham. Proceedings of a workshop held 18-21 March 1980. Salvador. Bahia. Brazil. FAO.2003. FAO. 2005. www.fao.orglfaostatl. Nweke F.r. 1996. Cassava a cash crop in Africa. COSCA Working Paper No 14. Internationallnstitute of Tropical Agriculture. Ibadan Nigeria. Nweke F.I .â&#x20AC;˘ B.O. Ugwu. A.G.O. Dixon. C.L.A. Asadu. and O . Ajooo. 1999. Cassava production in Nigeria: a function of farmer access to markets and to improved production

and processing technologies. COSCA Working Paper No 20. International Institute of Tropical Agriculture. Ibadan Nigeria. Nwekc F.r.. D.S.C Spencer and j . Lynam. 2002. The cassava "ansformation : Africa's best kept secret. Mkhigan State University Pres.s. East Lansing. USA. Ogbe F.O .â&#x20AC;˘ A.G.O Dixon. J. d'A Hughes. F. Alabi. and R.U. Okechukwu. 2005. The srarus of cassava mosaic diseast', cassava begomovi ruses and whitefly vector populations in Nigeria. ICP Technical Report No 2. International Institute of Tropical Agriculture. Ibadan. Nigeria. Ospina P.B. 2004 . Potential income and employment effect of cassava planting and harvesting mechanization. Paper presented in the Special Ses.sion "Technological needs assessment for cassava development in Africa". at the 9th Triennial Symposium of the International Society for Tropical Roots and Crops. African Branch. 3 1 O"c>ber to 5 November. 2004. Mamba". Kcr.ya .

Annex. Villages visited by state. State:

LGA

Vil lbge name

Lo ngitude

Lat itude

Abia

Ikwuano

O k"",

5.42092

7.57363

Abia

lsia"'. ~Ngwa

No rth

5.142802

7.38754

Abia

Ukwa We"

U mu~kec h j

5.06694

7.28607

Abia

Bende

Isicgbu Bende

5.(,431

7.6127

Abia

Ohafia

Akoli Imenyi

5.6716

7.5548

Akw. lbom

Uruan

Mbiaya Uruan

5. 10545

7.98089

Akwa lborn

it'u

Ikat Ekwerre l am

5.06677

7.90 155

Akwa lbom

Ibesikpo Asuhan

IkotAmho m

4 .96042

7.93483

Akwa Ibom

Ikot Abasi

Ikot Ndic:n

4.64326

7.57493

Anam br.l

Anambra

Igharian

6 .39527

6 .9435R

Ea!i t

Anambra

Idem,)i North

Nkwele Ogidi

6. 15936

6.87606

An3m bra

Ihiala

Amampmu -Uli

5.79362

6.81889

Bay<lsa

Kola Crcek

Elebde

4 .85627

6. 345 37

B.y<lsa

Ogbia Ccocral

Omoke

4.78665

3.1185

Baydsa

G bariam/ Ekpetiama

Ogboloma

5.05076

6.33367

B.yelsa

Sagbama

T u ngbo

5.12733

6. 16775

Cross Rivc:r

Akamkpa

Uyanga

5.38355

8.26185

Crou River

Boki

Ori mr::kpang

6 .06282

8.89095

Cross River

Obanliku

Buscnrung

6 .62894

9.2 1684

Cross River

Abi

&liba

5.86754

8.02692

Cross River

Odukpani

Ikot Nyong

5.18204

8.2709

Cross River

Akpabuyo

Ikot Offiong

4.9372 1

8.42012

Ddta

Oshimili North

Ebu

6.48111

6.60903

Ddra

lka South

Orom:a-Ekuku Agbor

6 .09323

6.30097

Ddt.

lka South

Abavo

6.1339

6.15236

Delta

Ndokwa West

Obetim-Uno

5.74793

6.44602

Delta

Isoko North

Ellu

5.58488

6.28512

Delta

lsako North

OlOm

5.54689

6.23648

Delta

Okpe

Ugb"ikoko

5.89843

5.57467

Ebonyi

Ebyia

NWOk

6.5 1143

8. 16396

Ebonyi

lu i

Ndingde

6.5 175

8.34536

Ebonyi

Onicha

Abaomege

6. 01122

8.00685

Edo

Esan South

Ugboh.

6.73202

6.45957

Edo

U hu nwonde

Ebue

6.33 11 7

5.86678

Edo

Owau East

Afutt

6.96099

6.04013

Edo

Etsako West

Af20na

7.13904

6.29126

Annex. Villages visited by state cont'd. Edo

LGA Orhionmwon

Villlage name Urho nigbc

Longitude 5.99096

Latitude 6.18442

Enugu

Uzowani

Nimbo

6.80062

7.14627

Enugu

Agbogazi

6.61064

7.5869

Enugu

Oji River

Akpugoeze

6.1 2429

7.23075

Enugu

Aninri

Amoji Newe

6. 13804

7.5 1438

State

lmo

Aboh Mbai,.

Umuekitc

5.'16298

7.1 8706

Imo

Odu

Owure路Ebiri

5.77735

7.02 18 1

Imo

Okigw.

Obinikpa Ezihe

5.77083

7.35293

Imo

:-Igor Okpala

Ez.iaIa

5.37425

7. 12678

Imo

Egbema

Obokofi.

5.54027

6.80166

Imo

OgUta

Kalabari Beach

5.69864

6.79805

Imo

Owerri North

Ogbeke Obibiczen:a

5.37646

7.06594

Rivers

Ahoada East

Ula-Ehud ...-Ahoada

5. 10383

6.62736

Rivers

Emo llUa

Ekutche Rumuckpe

4.98939

6.68303

.R,jvers

Emohua

Ogbaki ri

4.833

6.91134

Rivers

Etchc

Umuchoko Chokocho

4.99 14

7.05438

Rivers

Degema

Dtgema

4.75751

6.77341

Rivers

Gobn ..

楼<gh<

4.68664

7.34407

Ri\'crs

Oyigbo

Umuagbai

4.85244

7.37546

About IITA The International Institute of Tropical Agriculture (IITA, www.iita.org) is an Africa-based international research -for-development organization, established in 1967, and governed by a board oftrustees. Our vision is to be Africa's leading research partner in finding solutions for hunger and poverty. We have more than 100 international scientists based in various IITA stations ocross Africa. This network of scientists is dedicated to the development of technologies that reduce producer and consumer risk, increase local production, and generate wealth . We are supported primarily by the Consultative Group for International Agricultural Research (CGIAR, www.cgiar.org) .