Farmers Perceptions of the Effectiveness of the Cocoa
Transcript Of Farmers Perceptions of the Effectiveness of the Cocoa
American Journal of Experimental Agriculture
7(5): 257-274, 2015, Article no.AJEA.2015.128
ISSN: 2231-0606
SCIENCEDOMAIN international www.sciencedomain.org
Farmers’ Perceptions of the Effectiveness of the Cocoa Disease and Pest Control Programme
(CODAPEC) in Ghana and Its Effects on Poverty Reduction
Emmanuel Kumi1,2* and Andrew J. Daymond2
1Centre for Development Studies, Department of Social and Policy Sciences, University of Bath, Claverton Down, Bath, BA2 7A, United Kingdom.
2Policy and Development, School of Agriculture, University of Reading, Whiteknights, Reading, RG6 6AR, United Kingdom.
Authors’ contributions
This work was carried out in collaboration between both authors. Author EK was involved in the study design, data collection and analysis. He managed the literature review as well as the writing up of the
introduction and the first draft of the results of the manuscript. Author AJD was involved in the analysis, writing up of the discussion and the proof reading of the manuscript. Both authors read and
approved the final manuscript.
Article Information
DOI: 10.9734/AJEA/2015/16388 Editor(s):
(1) Juan Yan, Sichuan Agricultural University, China. Reviewers:
(1) Tuneera Bhadauria, Department of Zoology, Feroz Gandhi College, Kanpur University, Uttar Pradesh, India. (2) Kanmogne Abraham, Department of Industrial and Mechanical Engineering , National Advanced School of Engineering
(University of Yaoundé I), Cameroon. Complete Peer review History: http://www.sciencedomain.org/review-history.php?iid=919&id=2&aid=8364
Original Research Article
Received 30th January 2015 Accepted 18th February 2015
Published 7th March 2015
ABSTRACT
The study examined the contribution of the Cocoa Disease and Pest Control Programme (CODAPEC), which is a cocoa production-enhancing government policy, to reducing poverty and raising the living standards of cocoa farmers in Ghana. One hundred and fifty (150) cocoa farmers were randomly selected from five communities in the Bibiani-Anhwiaso-Bekwai district of the Western Region of Ghana and interviewed using structured questionnaires. Just over half of the farmers (53%) perceived the CODAPEC programme as being effective in controlling pests and diseases, whilst 56.6% felt that their yields and hence livelihoods had improved. In some cases pesticides or fungicides were applied later in the season than recommended and this had a
_____________________________________________________________________________________________________
*Corresponding author: E-mail: [email protected], [email protected];
Kumi and Daymond; AJEA, 7(5): 257-274, 2015; Article no.AJEA.2015.128
detrimental effect on yields. To determine the level of poverty amongst farmers, annual household consumption expenditure was used as a proxy indicator. The study found that 4.7% of cocoa farmers were extremely poor having a total annual household consumption expenditure of less than GH¢ 623.10 ($310.00) while 8.0% were poor with less than GH¢ 801.62 ($398.81). An amount of money ranging from GH¢ 20.00 ($9.95) to GH¢ 89.04 ($44.29) per annum was needed to lift the 4.7% of cocoa farmers out of extreme poverty, which could be achieved through modest increases in productivity. The study highlighted how agricultural intervention programmes, such as CODAPEC, have the potential to contribute to improved farmer livelihoods.
Keywords: Cocoa disease and pest control (CODAPEC); poverty reduction; standard of living; mirids; black pod disease; Ghana.
1. INTRODUCTION
Ghana is the second largest producer and exporter of cocoa beans, after Côte d’Ivoire. In 2012, cocoa accounted for about 30% of Ghana’s total export earnings, 19% of agricultural Gross Domestic Product (GDP) and 3.0% of national GDP [1,2]. For Ghanaian cocoa farmers, the contribution of cocoa to annual household income is estimated between 70% to 100% and employs about 3.2 million workers representing 60% of the national agricultural labour force [3]. Smallholder farmers contribute to about 90% of global cocoa production and typically operate within a farm size of 1 to 5 hectares [4]. Similarly, in Ghana, smallholder farmers dominate cocoa production which therefore makes the crop an instrumental vehicle for employment creation and poverty reduction.
From 2003 onwards, the impressive growth performance and poverty reduction recorded in the Ghanaian economy is mainly attributed to the agricultural sector, which is largely driven by cocoa production. Between 2003 and 2007, economic growth rates in Ghana increased from 5.2% to about 6.3% which has resulted in an increase in average income from $1,430 in 2008 to US$2,500 in 2010 [5,6]. The growth in the agricultural sector has been underpinned by the sturdy output performance of the cocoa sector from 0.5% to 16.4% year-on-year growth in output between 2003 and 2012 [7]. However, Ghana’s cocoa sector operates at lower yield productivity compared to their counterparts in some countries like Côte d’ Ivoire, Indonesia and Malaysia [8]. Research has shown that cocoa farmers in Ghana have the potential to produce an estimated dry bean yield of 1000 kg ha-1 or more [9] but currently the national average yield is estimated at 400 kg ha-1. The relatively low yield in Ghana is attributed to factors such as high prevalence of pests and diseases, poor
agronomic practices, decline in soil fertility and the use of low yielding varieties [10].
Among the above factors, the impact of pests and diseases is one of the greatest challenges to farmers. In Ghana, common cocoa diseases include Phytophthora black pod caused by the species Phytophthora palmivora and Phytophthora megakarya and Cocoa Swollen Shoot Virus Disease (CSSVD) while that of pests include insects mostly of the bug or miridiae family such as Distantiella theobroma and Sahlbergella singularis. Such diseases and pests can have devastating effects on the economies of cocoa production by reducing yields [11]. Although difficult to quantify, Acebo-Guerrero et al. [12] have argued that Phytophthora megakarya and mirids could cause an estimated 70%-90% annual crop loss if control measures are not taken and consequently significant economic loss to farmers. For example, between 2008 and 2010, an average estimated value of more than US$300 million of annual crop loss in Ghana was attributed to black pod disease while loss due to mirids infection was estimated at US$172 million [13]. The loss in productivity translates into low income which implicitly affects the standards of living of farming households. This invariably creates apathy on the part of farmers in making productive investments such as the use of fungicides, insecticides and fertilisers on their farms. Consequently, the long term growth and sustainability of the cocoa sector is threatened [14].
In addressing the challenges of the cocoa sector, a number of policies, programmes and interventions aimed at improving farm level productivity among farmers such as the Cocoa High-Technology Programme (Cocoa Hi-Tech) have been implemented over the years, with the aim of improving the livelihood of farmers [15]. In 2001 the government of Ghana initiated the Cocoa Disease and Pest Control Programme
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(CODAPEC), a national cocoa spraying programme with the objective of facilitating increased production among farmers through the control of mirids and black pod disease. Over the years, yield improvements in the cocoa sector have been linked at least in part to CODAPEC. For example, the level of national cocoa output increased from 632,000 to 1,025,000 metric tonnes for 2009/2010 and 2010/2011 growing seasons respectively. This was accompanied by an increase in the farm gate producer price from GHȼ 2,400 to GHȼ 3,200 per metric tonnes of cocoa beans [16]. It has been argued that the increased production levels and the price incentive has led to an increase in farmers income and has therefore resulted in the reduction of poverty among cocoa-farming households [17].
In Ghana, poverty abounds especially among rural farming households, even though, poverty according to the Ghana Living Standard Survey 5 is said to have reduced at an unprecedented rate from 51.7% to 28.5% between 1991 and 2005 [18]. However, since the inception of CODAPEC in 2001, relatively little is known about the poverty levels and standards of living among cocoa farmers. This study was conducted in the Bibiani- Anhwiaso Bekwai District (hereafter, BABD) in the Western Region of Ghana. Poverty is a common phenomenon that is often experienced in the district as 35.1% of farmers are classified as extremely poor [19]. Similarly, Boon et al. [19] found that about 58% of the population of BABD lives under the national poverty line. This raises key research questions such as: Has the living standard of cocoa farmers improved since the implementation of CODAPEC? What percentage of farmers can be classified as living below the upper and lower poverty lines? What is the perception of cocoa farmers of their living conditions? Despite the previous studies on CODAPEC and cocoa production in Ghana, there is relatively little empirical research that focuses directly on assessing the effects of the programme on poverty reduction and standards of living among cocoa farming households in the context of Ghana.
This paper therefore attempts to analyse the poverty levels and standards of living of cocoa farmers in the BABD of the Western Region of Ghana by using farmers’ household expenditure in 2012 as a proxy indicator in comparison with the national poverty lines set by the Ghana Statistical Service [20]. The paper also explores
farmers’ perceptions of the CODAPEC programme and identifies policy gaps in the implementation of CODAPEC. We take cognisance of the fact that in taking an instrumental view of asking project beneficiaries or farmers directly about attribution or their perception of the programme, there is a possibility of confirmation bias [21] or what Copestake [22] calls ‘project bias’ where ‘‘someone consciously or otherwise conceals or distorts what they think they know about an activity in the hope that doing so will reinforce the case for keeping it going’’. Despite this potential, ex post consultation or econometric evaluations cannot be used as a substitute for cocoa farmers in whose name the programme was implemented. As Copestake [22] argues, it is ethically correct to involve at least some direct beneficiaries in project evaluation even if it presents methodological challenges.
Up to date, research on cocoa farmers and CODAPEC in Ghana is largely skewed towards quantitative approach which focuses mainly on an axiomatic view of the project while others have also focused on factors that influence the adoption of the programme by farmers [23]. In this paper, we argue that such a view is insufficient, thus creating a gap in knowledge about farmers subjective assessment of the programme. There is therefore little empirical research on the subjective evaluation of the programme with respect to farmers’ perception and its effects on their households and standards of living in general. This research seeks to fill this scholarly gap. The novelty of the paper lies in its potential contribution in deepening our understanding about the effects of government agricultural policy initiatives on the livelihood of cocoa farming households of which little is known.
2. MATERIALS AND METHODS
2.1 Study Area
The study was conducted in the BABD located at the North-western part of the Western Region of Ghana. The district, which is located between latitude 6º N, 3º N and longitude 2º W, 3º W (Fig. 1) is an important cocoa producing area in Ghana and covers an estimated land area of 873 km2. An estimated 62% representing 39,829 hectares out of the 54,240 hectares of the available total arable land is under cultivation for both cash and food crops such as cocoa, coffee, plantain and cassava [24,25]. Topographically,
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the land rises from about 350m to 660m above sea level [26]. The district is located in the wetsemi equatorial rainforest zone which is marked by a bimodal rainfall pattern between MarchAugust and September-October. Average annual rainfall is between 1200mm and 1500mm with the peak periods between June and October [27]. The dry season is between November and January. BABD has a uniform average temperature of around 26ºC throughout the year with relative high humidity, daily averages being between 75% and 95% [24]. The favourable climatic conditions combined with the high fertility of forest ochrosols soil supports cocoa production and makes it the most important cash crop cultivated by farmers [20,27]. Furthermore, food crops like plantain, cassava, rice and black pepper are also cultivated on an average farm size of 1.5 hectares [25].
expenditure and standards of living while the
closed-ended questions elicited information
for the quantitative analyses [28]. The
questionnaires were pre-tested in two
communities; Domino No. 1 (6º N, 22º N, 2º W,
17º W) and Bibiani Old Town (6º N, 27º N, 2º W,
19º W) (Fig. 1). The pre-test survey was used to
test the feasibility of the questionnaire [28].
Corrections were made to the questionnaire after
the pre-test exercise in order to ensure that there
was no ambiguity in the questions asked. A team
of enumerators pre-tested and administered the
questionnaires in the local dialect of
respondents. Data collected included those on
socio-economic
characteristics
and
demographics, detailed household income and
expenditure, the perception of farmers about
their living standards and the effectiveness of
CODAPEC in improving yield and income.
BABD is basically agrarian with an estimated 61% of the active labour force engaging in agricultural activities such as crop and mixed farming in addition to animal husbandry. Mining activities in gold and bauxite in Bibiani, Chirano and Awaso respectively dominates the industry sector. BABDA’s population according to the 2010 Housing and Population Census of Ghana was estimated at 123,272 with 49.4% male and 50.6% female [24].
2.2 Sampling Procedure, Data Collection and Analysis
Purposive sampling was used in selecting the BABD for the study. Cluster sampling was also used in dividing the district into three zones: Bibiani Zone, Anhwiaso Zone and Bekwai Zone because of the expansive nature of the district. Simple random sampling was further employed in selecting five communities; Kwamekrom (6º N, 25º N, 2º W, 18º W), Dominibo No. 2 (6º N, 21º N, 2º W, 16º W), Tanoso (6º N, 20º N, 2º W, 18º W), Ntakam (6º N, 16º N, 2º W, 19º W) and Humjibre (6º N, 08º N, 2º W, 16º W) (Fig. 1). We then employed the random sampling technique in selecting 150 cocoa farming households, 30 from each community. The same sample size was used for the three zones because of similar population characteristics among cocoa farmers. Data for the study were obtained through the administration of structured questionnaires which were made up of both closed and open-ended questions. Open-ended questions were used to capture qualitative data representing the respondent’s own views about their household
Descriptive statistics in the form of frequencies, percentages as well as pictograms such as pie charts and bar charts were used to present data whilst associations between socio-economic characteristics and yield were analysed by means of chi-square using the Statistical Product and Service Solutions (SPSS) package, version 20.0. Annual household expenditure in Ghana Cedis (GH¢) was converted into United States Dollars (US$) based on the prevailing market exchange rate (US$ 1= GH¢ 2.01) in June, 2013. The results were compared to the dollar equivalent of the upper and lower poverty lines set by the Ghana Statistical Service [18] and also from poverty lines calculated from the minimum wage index. The average interbank exchange rate for June, 2006 was at $1= GH¢ 0.92.
3. RESULTS
3.1 Socio-economic Characteristics of Respondents
3.1.1 Gender profile, marital status and age of respondents
The results of the descriptive statistics of the socio-economic characteristics of 150 cocoa farmers are presented in Table 1. The results indicated a high ratio of male (62%) to female (38%) farmers. About 82.7% of respondents were married or had married before but are currently divorced, living in consensual union or widowed. The average age of respondents was about 40 years with the 31-40 years age bracket
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being the modal age class. The age of farmers ranged from 18 to 70 years. The results demonstrated a fair distribution of ages across
the population with majority of farmers (92.7%) being in their economically active age (18-64 years).
Fig. 1. Bibiani-Anhwiaso-Bekwai district showing location and selected communities for the study
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Table 1. Descriptive statistics of the socioeconomic characteristics of respondents
(n=150)
Socio economic Frequency
variable
1. Gender profile of respondents
Male
93
Female
57
Total
150
2. Marital status of respondents
Percentage
62.0 38.0 100.0
Married
78
52.00
Single
26
17.3
Divorced
16
10.7
Widowed
27
18.0
Consensual Union 3
2.0
Total
150
100.0
3. Experience in cocoa cultivation
Less than 5 years 25
16.7
5-10 years
33
22.0
11-20 years
47
33.1
21-30 years
27
18.0
Above 30+
18
12.0
Total
150
100.0
4. Educational level of respondents
Basic (Primary and 35
23.3
Middle School)
Secondary (Senior 29
19.3
High School)
Tertiary
11
7.4
No education
44
29.3
Non formal
31
20.7
education
Total
150
100.0
5. Household size
1-5 member(s)
82
54.7
6-10 members
58
38.7
11-15 members
8
5.3
16-20 members
2
1.3
Total
150
100.0
6. Number of household
on farm
1-2 person (s)
100
3-4 persons
39
5-6
10
Above 6 persons 1
Total
150
members working
66.7 26.0 6.6 0.7 100.0
Source: Field survey, 2013
3.1.2 Cocoa farmer’s level of education and experience
The adult illiteracy rate (percentage of persons aged 15 years and over who cannot read and write) was found to be 29.3% although 23.3%
were educated to the basic school level while a few had attained tertiary education. The average working experience was about 15 years while the years of experience in cocoa farming ranged from 5 to 30 years (Table 1). There was a highly significant relationship between respondent’s experience in cocoa cultivation and their yield ha-1 (X2 = 70.50, P=<0.01). Farmers with more years of experience in growing cocoa had higher yield ha-1 compared to farmers with less experience.
3.1.3 Farm size and cocoa output
Fig. 2 presents the distribution of cocoa farm sizes as reported by farmers. About 68.7% of surveyed farmers claimed to have farm size between 1.0 and 4.0 hectares while a small proportion (2%) had above 10 hectares. Results indicate that smallholder farmers dominate cocoa farming in the study area. The average farm was 1.6 hectares, with the range being from 0.40 to 15 hectares.
Results on cocoa output (64 kg/Bag) and kg ha-1 produced by farmers are presented in Table 2. The results show that farmers had an average yield of 574 kg ha-1, the range being from 300 kg ha-1 to 685 kg ha-1.
Table 2. Descriptive statistics of the output of cocoa (Bags) and (Kg ha-1) of the sampled
cocoa farmers (n=150)
Variable
Frequency Percentage
Output of cocoa (64 kg/ bag of dry beans)
< 10
26
17.3
10.5 – 20
51
34
20.5 – 30
31
20.7
30.5 – 40
22
14.7
40.5 – 50
4
2.6
Above 50+
16
10.7
Total
150
Output of cocoa (Kg ha-1)
100.0
Less than 300 12
8.0
300-400
15
10.0
401-500
34
22.7
501-600
61
40.7
Above 600
28
18.6
Total
150
100.0
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Peercentage of respondents
40
35
30
25
20
15
10
5
0
0--1
1--2
2--4
4--6
6--8
8--10
10+
Farm sizes in hectares
Fig. 2. Distribution of farm size hectares (n=150)
3.1.4 Variations in the first month of spraying
Fig. 3 presents the responses of farmers on the timing of the first pesticide/fungicide spray. A majority of respondents (94.7%) had their farms sprayed within the months of July, August, September and November, which is the recommended spraying period. However, a smaller proportion (5.3%) reported that their farms were sprayed beyond November. The results of the Chi-square tests statistic (X2 =228.68; P=0.04) on the association between the period of spray and yield ha-1 shows a statistically significant relationship at 5% level of significance. The highest yields were recorded for farms that were sprayed in the month of July while farms had lower yields when sprayed in November.
3.1.5 Farmers’ perception on the effectiveness of the spraying process and economically important pests and diseases
3.1.6 Inefficiencies and challenges facing CODAPEC
Fig. 5 illustrates the key inefficiencies and challenges of CODAPEC identified by farmers and spraying gangs. The untimely supply of insecticides and fungicides was cited by both by farmers (26%) and spraying gangs (50%) as the major challenge. The perception of sprayers on the programme was also sought since they are the workers on the ground. This helped in providing a deeper understanding of the challenges that confronts them in undertaking their spraying exercise. Their perception on the challenges facing CODAPEC is presented in Fig. 5.
3.2 Effect of CODAPEC on Crop Yield, Household Income and Standards of Living
3.2.1 Farmers perception on the effect of CODAPEC on crop yield
A large proportion (53%) of farmers claimed that the spraying process was effective in controlling the incidence of pests and diseases. However, a much smaller proportion (14%) claimed spraying under COPAPEC was ineffective as the programme is faced with numerous institutional constraints.
Fig. 4 shows the pests and diseases reported by farmers in terms of economic importance. A large proportion of farmers identified mirids and black pod (45% and 23% respectively) as the most economically important pest and disease. Cocoa swollen shoot virus disease was cited by 17% of respondents as the most important disease, whilst 10% cited mistletoe growth in the cocoa canopy.
The perception of farmers on the effect of CODAPEC on crop yield was assessed by asking the respondents to compare their yield before and after the implementation of CODAPEC. The majority (56.7%) of respondents claimed the spraying exercise was effective in increasing the yields of cocoa. About 17.3% of respondents claimed there have been no significant variations in their yields, whilst 20% claimed their yields had decreased. A statistically significant relationship was found between month of first spray and farmer’s perception of an increase in cocoa yields since the inception of CODAPEC (X2 = 59.59; P=<0.01). Farmers who reported late spraying tended not to see a yield advantage (X2= 23.6; P=0.75).
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Fig. 3. Variation in the first month of spraying under CODAPEC for the 2011/2012 cocoa growing season (n=150)
Fig. 4. Farmers’ perception of the most economically important pests and diseases (n=150) 264
Percentage of respondents
Kumi and Daymond; AJEA, 7(5): 257-274, 2015; Article no.AJEA.2015.128
50
40
30
Farmers
Sprayers 20
10
0
Challenges faced by farmers and sprayers under CODAPEC
Fig. 5. Summary of farmers and sprayers response of the inefficiencies and challenges facing CODAPEC (n=160)
Fig. 6. Perception of farmers on the relationship between CODAPEC and yields (n=150) 265
Kumi and Daymond; AJEA, 7(5): 257-274, 2015; Article no.AJEA.2015.128
3.2.2 Sources and proportion of household income from cocoa farming
The mean annual household income from cocoa was GH¢5,073.75 ($2,525.25), the range being from GH¢ 615.00 to 16,400.00. Cocoa farming was the main occupation of respondents and accounting for 75.3% of total household income on average. Sales from cocoa beans were cited as the highest income source for farmers in addition to food crops (Table 3). Households were highly reliant on the income from cocoa.
3.2.3 Household
consumption
and
expenditure
The household expenditure excluding on-farm expenditure level is presented in Table 4. Food expenditure accounted for a large proportion (45.2%) of the household total expenditure while a small proportion (6.1%) was spent on education and health.
3.2.4 Comparative analysis of average and
total
household
consumption
expenditure to Ghana living standards
survey (GLSS 5)
Poverty levels of respondents were determined by using household consumption expenditure as a proxy indicator. The mean household expenditure from the study was compared to that of the Ghana Living Standard Survey (GLSS) 5 mean household expenditure GH¢ 1,918.00 ($2,084.78) in 2006 (GSS, 2008). Results from Table 5 indicates that respondents could spend more money GH¢ 3,383.00 ($1,683.08) and could be suggested that monetary wise, they are better off in 2013 than in 2006 in terms of Ghana Cedis (GH¢). The average expenditure is about 1.7 and 2.0 times more than the national and rural forest average household expenditure. Table 6 presents the percentage of respondents living below the national poverty line computed from the upper and lower poverty lines which were GH¢ 370.90 and 288.50 per adult per year respectively in 2006 [29]. When these figures were inflated to 2013 levels by adjusting for the change in exchange rates, they were GH¢ 623.10 and GH¢ 801.62 respectively. Based on the annual household consumption expenditure, 4.7% and 8.0% of farmers are also classified as extremely poor and poor respectively in accordance with national poverty lines. When comparing the household consumption expenditure with the Minimum Wage Index used in Ghana, 14% of respondents were classified as
living in poverty. An amount of money ranging from GH¢ 20.00 to GH¢ 89.04 per annum is needed to lift the 4.7% of respondents out of extreme poverty to the poor line when using the poverty gap.
3.3 Farmers Perception about Their Poverty Level and Standards of Living
Fig. 7 illustrates the perception of farmers about their standard of living based on the multidimensionality of poverty approach (defining poverty in terms of non-income dimensions of human well-being and people’s own lived experiences). Respondents were asked about their poverty levels and living conditions on a scale of four, from very good standards to very poor standards of living.
The results illustrated in Fig. 7 suggest a higher level of perceived poverty than those presented in Table 6. About 11% and 6% of farmers considered themselves to be poor and extremely poor respectively.
Table 3. Proportion of household income from cocoa farming (n=150)
Sources of household income Food stuffs (Plantain, Cassava, Yam, Cocoyam) Cocoa Beans Vegetables (Pepper, Tomatoes etc.) Total
Frequency 23
113 14 150
Percentage 15.30
75.30 9.30 100.0
4. DISCUSSION
4.1 Socio-economic Characteristics of Respondents
The current study has demonstrated the dominance of an economically active farmer population in the production of cocoa in the BABD district of Ghana. Results from the present case study area are consistent with the findings of Danso-Abbeam et al. [30] who reported that about 61% of cocoa farmers in the BABD were aged between 20 and 50 years. The results are however in contrast with studies from other parts of the country that indicates an aging farming population [23,31,32]. As cocoa farmers are ageing, there is the need for a replacement by younger farmers to ensure the sustainability of
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7(5): 257-274, 2015, Article no.AJEA.2015.128
ISSN: 2231-0606
SCIENCEDOMAIN international www.sciencedomain.org
Farmers’ Perceptions of the Effectiveness of the Cocoa Disease and Pest Control Programme
(CODAPEC) in Ghana and Its Effects on Poverty Reduction
Emmanuel Kumi1,2* and Andrew J. Daymond2
1Centre for Development Studies, Department of Social and Policy Sciences, University of Bath, Claverton Down, Bath, BA2 7A, United Kingdom.
2Policy and Development, School of Agriculture, University of Reading, Whiteknights, Reading, RG6 6AR, United Kingdom.
Authors’ contributions
This work was carried out in collaboration between both authors. Author EK was involved in the study design, data collection and analysis. He managed the literature review as well as the writing up of the
introduction and the first draft of the results of the manuscript. Author AJD was involved in the analysis, writing up of the discussion and the proof reading of the manuscript. Both authors read and
approved the final manuscript.
Article Information
DOI: 10.9734/AJEA/2015/16388 Editor(s):
(1) Juan Yan, Sichuan Agricultural University, China. Reviewers:
(1) Tuneera Bhadauria, Department of Zoology, Feroz Gandhi College, Kanpur University, Uttar Pradesh, India. (2) Kanmogne Abraham, Department of Industrial and Mechanical Engineering , National Advanced School of Engineering
(University of Yaoundé I), Cameroon. Complete Peer review History: http://www.sciencedomain.org/review-history.php?iid=919&id=2&aid=8364
Original Research Article
Received 30th January 2015 Accepted 18th February 2015
Published 7th March 2015
ABSTRACT
The study examined the contribution of the Cocoa Disease and Pest Control Programme (CODAPEC), which is a cocoa production-enhancing government policy, to reducing poverty and raising the living standards of cocoa farmers in Ghana. One hundred and fifty (150) cocoa farmers were randomly selected from five communities in the Bibiani-Anhwiaso-Bekwai district of the Western Region of Ghana and interviewed using structured questionnaires. Just over half of the farmers (53%) perceived the CODAPEC programme as being effective in controlling pests and diseases, whilst 56.6% felt that their yields and hence livelihoods had improved. In some cases pesticides or fungicides were applied later in the season than recommended and this had a
_____________________________________________________________________________________________________
*Corresponding author: E-mail: [email protected], [email protected];
Kumi and Daymond; AJEA, 7(5): 257-274, 2015; Article no.AJEA.2015.128
detrimental effect on yields. To determine the level of poverty amongst farmers, annual household consumption expenditure was used as a proxy indicator. The study found that 4.7% of cocoa farmers were extremely poor having a total annual household consumption expenditure of less than GH¢ 623.10 ($310.00) while 8.0% were poor with less than GH¢ 801.62 ($398.81). An amount of money ranging from GH¢ 20.00 ($9.95) to GH¢ 89.04 ($44.29) per annum was needed to lift the 4.7% of cocoa farmers out of extreme poverty, which could be achieved through modest increases in productivity. The study highlighted how agricultural intervention programmes, such as CODAPEC, have the potential to contribute to improved farmer livelihoods.
Keywords: Cocoa disease and pest control (CODAPEC); poverty reduction; standard of living; mirids; black pod disease; Ghana.
1. INTRODUCTION
Ghana is the second largest producer and exporter of cocoa beans, after Côte d’Ivoire. In 2012, cocoa accounted for about 30% of Ghana’s total export earnings, 19% of agricultural Gross Domestic Product (GDP) and 3.0% of national GDP [1,2]. For Ghanaian cocoa farmers, the contribution of cocoa to annual household income is estimated between 70% to 100% and employs about 3.2 million workers representing 60% of the national agricultural labour force [3]. Smallholder farmers contribute to about 90% of global cocoa production and typically operate within a farm size of 1 to 5 hectares [4]. Similarly, in Ghana, smallholder farmers dominate cocoa production which therefore makes the crop an instrumental vehicle for employment creation and poverty reduction.
From 2003 onwards, the impressive growth performance and poverty reduction recorded in the Ghanaian economy is mainly attributed to the agricultural sector, which is largely driven by cocoa production. Between 2003 and 2007, economic growth rates in Ghana increased from 5.2% to about 6.3% which has resulted in an increase in average income from $1,430 in 2008 to US$2,500 in 2010 [5,6]. The growth in the agricultural sector has been underpinned by the sturdy output performance of the cocoa sector from 0.5% to 16.4% year-on-year growth in output between 2003 and 2012 [7]. However, Ghana’s cocoa sector operates at lower yield productivity compared to their counterparts in some countries like Côte d’ Ivoire, Indonesia and Malaysia [8]. Research has shown that cocoa farmers in Ghana have the potential to produce an estimated dry bean yield of 1000 kg ha-1 or more [9] but currently the national average yield is estimated at 400 kg ha-1. The relatively low yield in Ghana is attributed to factors such as high prevalence of pests and diseases, poor
agronomic practices, decline in soil fertility and the use of low yielding varieties [10].
Among the above factors, the impact of pests and diseases is one of the greatest challenges to farmers. In Ghana, common cocoa diseases include Phytophthora black pod caused by the species Phytophthora palmivora and Phytophthora megakarya and Cocoa Swollen Shoot Virus Disease (CSSVD) while that of pests include insects mostly of the bug or miridiae family such as Distantiella theobroma and Sahlbergella singularis. Such diseases and pests can have devastating effects on the economies of cocoa production by reducing yields [11]. Although difficult to quantify, Acebo-Guerrero et al. [12] have argued that Phytophthora megakarya and mirids could cause an estimated 70%-90% annual crop loss if control measures are not taken and consequently significant economic loss to farmers. For example, between 2008 and 2010, an average estimated value of more than US$300 million of annual crop loss in Ghana was attributed to black pod disease while loss due to mirids infection was estimated at US$172 million [13]. The loss in productivity translates into low income which implicitly affects the standards of living of farming households. This invariably creates apathy on the part of farmers in making productive investments such as the use of fungicides, insecticides and fertilisers on their farms. Consequently, the long term growth and sustainability of the cocoa sector is threatened [14].
In addressing the challenges of the cocoa sector, a number of policies, programmes and interventions aimed at improving farm level productivity among farmers such as the Cocoa High-Technology Programme (Cocoa Hi-Tech) have been implemented over the years, with the aim of improving the livelihood of farmers [15]. In 2001 the government of Ghana initiated the Cocoa Disease and Pest Control Programme
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(CODAPEC), a national cocoa spraying programme with the objective of facilitating increased production among farmers through the control of mirids and black pod disease. Over the years, yield improvements in the cocoa sector have been linked at least in part to CODAPEC. For example, the level of national cocoa output increased from 632,000 to 1,025,000 metric tonnes for 2009/2010 and 2010/2011 growing seasons respectively. This was accompanied by an increase in the farm gate producer price from GHȼ 2,400 to GHȼ 3,200 per metric tonnes of cocoa beans [16]. It has been argued that the increased production levels and the price incentive has led to an increase in farmers income and has therefore resulted in the reduction of poverty among cocoa-farming households [17].
In Ghana, poverty abounds especially among rural farming households, even though, poverty according to the Ghana Living Standard Survey 5 is said to have reduced at an unprecedented rate from 51.7% to 28.5% between 1991 and 2005 [18]. However, since the inception of CODAPEC in 2001, relatively little is known about the poverty levels and standards of living among cocoa farmers. This study was conducted in the Bibiani- Anhwiaso Bekwai District (hereafter, BABD) in the Western Region of Ghana. Poverty is a common phenomenon that is often experienced in the district as 35.1% of farmers are classified as extremely poor [19]. Similarly, Boon et al. [19] found that about 58% of the population of BABD lives under the national poverty line. This raises key research questions such as: Has the living standard of cocoa farmers improved since the implementation of CODAPEC? What percentage of farmers can be classified as living below the upper and lower poverty lines? What is the perception of cocoa farmers of their living conditions? Despite the previous studies on CODAPEC and cocoa production in Ghana, there is relatively little empirical research that focuses directly on assessing the effects of the programme on poverty reduction and standards of living among cocoa farming households in the context of Ghana.
This paper therefore attempts to analyse the poverty levels and standards of living of cocoa farmers in the BABD of the Western Region of Ghana by using farmers’ household expenditure in 2012 as a proxy indicator in comparison with the national poverty lines set by the Ghana Statistical Service [20]. The paper also explores
farmers’ perceptions of the CODAPEC programme and identifies policy gaps in the implementation of CODAPEC. We take cognisance of the fact that in taking an instrumental view of asking project beneficiaries or farmers directly about attribution or their perception of the programme, there is a possibility of confirmation bias [21] or what Copestake [22] calls ‘project bias’ where ‘‘someone consciously or otherwise conceals or distorts what they think they know about an activity in the hope that doing so will reinforce the case for keeping it going’’. Despite this potential, ex post consultation or econometric evaluations cannot be used as a substitute for cocoa farmers in whose name the programme was implemented. As Copestake [22] argues, it is ethically correct to involve at least some direct beneficiaries in project evaluation even if it presents methodological challenges.
Up to date, research on cocoa farmers and CODAPEC in Ghana is largely skewed towards quantitative approach which focuses mainly on an axiomatic view of the project while others have also focused on factors that influence the adoption of the programme by farmers [23]. In this paper, we argue that such a view is insufficient, thus creating a gap in knowledge about farmers subjective assessment of the programme. There is therefore little empirical research on the subjective evaluation of the programme with respect to farmers’ perception and its effects on their households and standards of living in general. This research seeks to fill this scholarly gap. The novelty of the paper lies in its potential contribution in deepening our understanding about the effects of government agricultural policy initiatives on the livelihood of cocoa farming households of which little is known.
2. MATERIALS AND METHODS
2.1 Study Area
The study was conducted in the BABD located at the North-western part of the Western Region of Ghana. The district, which is located between latitude 6º N, 3º N and longitude 2º W, 3º W (Fig. 1) is an important cocoa producing area in Ghana and covers an estimated land area of 873 km2. An estimated 62% representing 39,829 hectares out of the 54,240 hectares of the available total arable land is under cultivation for both cash and food crops such as cocoa, coffee, plantain and cassava [24,25]. Topographically,
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the land rises from about 350m to 660m above sea level [26]. The district is located in the wetsemi equatorial rainforest zone which is marked by a bimodal rainfall pattern between MarchAugust and September-October. Average annual rainfall is between 1200mm and 1500mm with the peak periods between June and October [27]. The dry season is between November and January. BABD has a uniform average temperature of around 26ºC throughout the year with relative high humidity, daily averages being between 75% and 95% [24]. The favourable climatic conditions combined with the high fertility of forest ochrosols soil supports cocoa production and makes it the most important cash crop cultivated by farmers [20,27]. Furthermore, food crops like plantain, cassava, rice and black pepper are also cultivated on an average farm size of 1.5 hectares [25].
expenditure and standards of living while the
closed-ended questions elicited information
for the quantitative analyses [28]. The
questionnaires were pre-tested in two
communities; Domino No. 1 (6º N, 22º N, 2º W,
17º W) and Bibiani Old Town (6º N, 27º N, 2º W,
19º W) (Fig. 1). The pre-test survey was used to
test the feasibility of the questionnaire [28].
Corrections were made to the questionnaire after
the pre-test exercise in order to ensure that there
was no ambiguity in the questions asked. A team
of enumerators pre-tested and administered the
questionnaires in the local dialect of
respondents. Data collected included those on
socio-economic
characteristics
and
demographics, detailed household income and
expenditure, the perception of farmers about
their living standards and the effectiveness of
CODAPEC in improving yield and income.
BABD is basically agrarian with an estimated 61% of the active labour force engaging in agricultural activities such as crop and mixed farming in addition to animal husbandry. Mining activities in gold and bauxite in Bibiani, Chirano and Awaso respectively dominates the industry sector. BABDA’s population according to the 2010 Housing and Population Census of Ghana was estimated at 123,272 with 49.4% male and 50.6% female [24].
2.2 Sampling Procedure, Data Collection and Analysis
Purposive sampling was used in selecting the BABD for the study. Cluster sampling was also used in dividing the district into three zones: Bibiani Zone, Anhwiaso Zone and Bekwai Zone because of the expansive nature of the district. Simple random sampling was further employed in selecting five communities; Kwamekrom (6º N, 25º N, 2º W, 18º W), Dominibo No. 2 (6º N, 21º N, 2º W, 16º W), Tanoso (6º N, 20º N, 2º W, 18º W), Ntakam (6º N, 16º N, 2º W, 19º W) and Humjibre (6º N, 08º N, 2º W, 16º W) (Fig. 1). We then employed the random sampling technique in selecting 150 cocoa farming households, 30 from each community. The same sample size was used for the three zones because of similar population characteristics among cocoa farmers. Data for the study were obtained through the administration of structured questionnaires which were made up of both closed and open-ended questions. Open-ended questions were used to capture qualitative data representing the respondent’s own views about their household
Descriptive statistics in the form of frequencies, percentages as well as pictograms such as pie charts and bar charts were used to present data whilst associations between socio-economic characteristics and yield were analysed by means of chi-square using the Statistical Product and Service Solutions (SPSS) package, version 20.0. Annual household expenditure in Ghana Cedis (GH¢) was converted into United States Dollars (US$) based on the prevailing market exchange rate (US$ 1= GH¢ 2.01) in June, 2013. The results were compared to the dollar equivalent of the upper and lower poverty lines set by the Ghana Statistical Service [18] and also from poverty lines calculated from the minimum wage index. The average interbank exchange rate for June, 2006 was at $1= GH¢ 0.92.
3. RESULTS
3.1 Socio-economic Characteristics of Respondents
3.1.1 Gender profile, marital status and age of respondents
The results of the descriptive statistics of the socio-economic characteristics of 150 cocoa farmers are presented in Table 1. The results indicated a high ratio of male (62%) to female (38%) farmers. About 82.7% of respondents were married or had married before but are currently divorced, living in consensual union or widowed. The average age of respondents was about 40 years with the 31-40 years age bracket
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being the modal age class. The age of farmers ranged from 18 to 70 years. The results demonstrated a fair distribution of ages across
the population with majority of farmers (92.7%) being in their economically active age (18-64 years).
Fig. 1. Bibiani-Anhwiaso-Bekwai district showing location and selected communities for the study
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Table 1. Descriptive statistics of the socioeconomic characteristics of respondents
(n=150)
Socio economic Frequency
variable
1. Gender profile of respondents
Male
93
Female
57
Total
150
2. Marital status of respondents
Percentage
62.0 38.0 100.0
Married
78
52.00
Single
26
17.3
Divorced
16
10.7
Widowed
27
18.0
Consensual Union 3
2.0
Total
150
100.0
3. Experience in cocoa cultivation
Less than 5 years 25
16.7
5-10 years
33
22.0
11-20 years
47
33.1
21-30 years
27
18.0
Above 30+
18
12.0
Total
150
100.0
4. Educational level of respondents
Basic (Primary and 35
23.3
Middle School)
Secondary (Senior 29
19.3
High School)
Tertiary
11
7.4
No education
44
29.3
Non formal
31
20.7
education
Total
150
100.0
5. Household size
1-5 member(s)
82
54.7
6-10 members
58
38.7
11-15 members
8
5.3
16-20 members
2
1.3
Total
150
100.0
6. Number of household
on farm
1-2 person (s)
100
3-4 persons
39
5-6
10
Above 6 persons 1
Total
150
members working
66.7 26.0 6.6 0.7 100.0
Source: Field survey, 2013
3.1.2 Cocoa farmer’s level of education and experience
The adult illiteracy rate (percentage of persons aged 15 years and over who cannot read and write) was found to be 29.3% although 23.3%
were educated to the basic school level while a few had attained tertiary education. The average working experience was about 15 years while the years of experience in cocoa farming ranged from 5 to 30 years (Table 1). There was a highly significant relationship between respondent’s experience in cocoa cultivation and their yield ha-1 (X2 = 70.50, P=<0.01). Farmers with more years of experience in growing cocoa had higher yield ha-1 compared to farmers with less experience.
3.1.3 Farm size and cocoa output
Fig. 2 presents the distribution of cocoa farm sizes as reported by farmers. About 68.7% of surveyed farmers claimed to have farm size between 1.0 and 4.0 hectares while a small proportion (2%) had above 10 hectares. Results indicate that smallholder farmers dominate cocoa farming in the study area. The average farm was 1.6 hectares, with the range being from 0.40 to 15 hectares.
Results on cocoa output (64 kg/Bag) and kg ha-1 produced by farmers are presented in Table 2. The results show that farmers had an average yield of 574 kg ha-1, the range being from 300 kg ha-1 to 685 kg ha-1.
Table 2. Descriptive statistics of the output of cocoa (Bags) and (Kg ha-1) of the sampled
cocoa farmers (n=150)
Variable
Frequency Percentage
Output of cocoa (64 kg/ bag of dry beans)
< 10
26
17.3
10.5 – 20
51
34
20.5 – 30
31
20.7
30.5 – 40
22
14.7
40.5 – 50
4
2.6
Above 50+
16
10.7
Total
150
Output of cocoa (Kg ha-1)
100.0
Less than 300 12
8.0
300-400
15
10.0
401-500
34
22.7
501-600
61
40.7
Above 600
28
18.6
Total
150
100.0
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Peercentage of respondents
40
35
30
25
20
15
10
5
0
0--1
1--2
2--4
4--6
6--8
8--10
10+
Farm sizes in hectares
Fig. 2. Distribution of farm size hectares (n=150)
3.1.4 Variations in the first month of spraying
Fig. 3 presents the responses of farmers on the timing of the first pesticide/fungicide spray. A majority of respondents (94.7%) had their farms sprayed within the months of July, August, September and November, which is the recommended spraying period. However, a smaller proportion (5.3%) reported that their farms were sprayed beyond November. The results of the Chi-square tests statistic (X2 =228.68; P=0.04) on the association between the period of spray and yield ha-1 shows a statistically significant relationship at 5% level of significance. The highest yields were recorded for farms that were sprayed in the month of July while farms had lower yields when sprayed in November.
3.1.5 Farmers’ perception on the effectiveness of the spraying process and economically important pests and diseases
3.1.6 Inefficiencies and challenges facing CODAPEC
Fig. 5 illustrates the key inefficiencies and challenges of CODAPEC identified by farmers and spraying gangs. The untimely supply of insecticides and fungicides was cited by both by farmers (26%) and spraying gangs (50%) as the major challenge. The perception of sprayers on the programme was also sought since they are the workers on the ground. This helped in providing a deeper understanding of the challenges that confronts them in undertaking their spraying exercise. Their perception on the challenges facing CODAPEC is presented in Fig. 5.
3.2 Effect of CODAPEC on Crop Yield, Household Income and Standards of Living
3.2.1 Farmers perception on the effect of CODAPEC on crop yield
A large proportion (53%) of farmers claimed that the spraying process was effective in controlling the incidence of pests and diseases. However, a much smaller proportion (14%) claimed spraying under COPAPEC was ineffective as the programme is faced with numerous institutional constraints.
Fig. 4 shows the pests and diseases reported by farmers in terms of economic importance. A large proportion of farmers identified mirids and black pod (45% and 23% respectively) as the most economically important pest and disease. Cocoa swollen shoot virus disease was cited by 17% of respondents as the most important disease, whilst 10% cited mistletoe growth in the cocoa canopy.
The perception of farmers on the effect of CODAPEC on crop yield was assessed by asking the respondents to compare their yield before and after the implementation of CODAPEC. The majority (56.7%) of respondents claimed the spraying exercise was effective in increasing the yields of cocoa. About 17.3% of respondents claimed there have been no significant variations in their yields, whilst 20% claimed their yields had decreased. A statistically significant relationship was found between month of first spray and farmer’s perception of an increase in cocoa yields since the inception of CODAPEC (X2 = 59.59; P=<0.01). Farmers who reported late spraying tended not to see a yield advantage (X2= 23.6; P=0.75).
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Fig. 3. Variation in the first month of spraying under CODAPEC for the 2011/2012 cocoa growing season (n=150)
Fig. 4. Farmers’ perception of the most economically important pests and diseases (n=150) 264
Percentage of respondents
Kumi and Daymond; AJEA, 7(5): 257-274, 2015; Article no.AJEA.2015.128
50
40
30
Farmers
Sprayers 20
10
0
Challenges faced by farmers and sprayers under CODAPEC
Fig. 5. Summary of farmers and sprayers response of the inefficiencies and challenges facing CODAPEC (n=160)
Fig. 6. Perception of farmers on the relationship between CODAPEC and yields (n=150) 265
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3.2.2 Sources and proportion of household income from cocoa farming
The mean annual household income from cocoa was GH¢5,073.75 ($2,525.25), the range being from GH¢ 615.00 to 16,400.00. Cocoa farming was the main occupation of respondents and accounting for 75.3% of total household income on average. Sales from cocoa beans were cited as the highest income source for farmers in addition to food crops (Table 3). Households were highly reliant on the income from cocoa.
3.2.3 Household
consumption
and
expenditure
The household expenditure excluding on-farm expenditure level is presented in Table 4. Food expenditure accounted for a large proportion (45.2%) of the household total expenditure while a small proportion (6.1%) was spent on education and health.
3.2.4 Comparative analysis of average and
total
household
consumption
expenditure to Ghana living standards
survey (GLSS 5)
Poverty levels of respondents were determined by using household consumption expenditure as a proxy indicator. The mean household expenditure from the study was compared to that of the Ghana Living Standard Survey (GLSS) 5 mean household expenditure GH¢ 1,918.00 ($2,084.78) in 2006 (GSS, 2008). Results from Table 5 indicates that respondents could spend more money GH¢ 3,383.00 ($1,683.08) and could be suggested that monetary wise, they are better off in 2013 than in 2006 in terms of Ghana Cedis (GH¢). The average expenditure is about 1.7 and 2.0 times more than the national and rural forest average household expenditure. Table 6 presents the percentage of respondents living below the national poverty line computed from the upper and lower poverty lines which were GH¢ 370.90 and 288.50 per adult per year respectively in 2006 [29]. When these figures were inflated to 2013 levels by adjusting for the change in exchange rates, they were GH¢ 623.10 and GH¢ 801.62 respectively. Based on the annual household consumption expenditure, 4.7% and 8.0% of farmers are also classified as extremely poor and poor respectively in accordance with national poverty lines. When comparing the household consumption expenditure with the Minimum Wage Index used in Ghana, 14% of respondents were classified as
living in poverty. An amount of money ranging from GH¢ 20.00 to GH¢ 89.04 per annum is needed to lift the 4.7% of respondents out of extreme poverty to the poor line when using the poverty gap.
3.3 Farmers Perception about Their Poverty Level and Standards of Living
Fig. 7 illustrates the perception of farmers about their standard of living based on the multidimensionality of poverty approach (defining poverty in terms of non-income dimensions of human well-being and people’s own lived experiences). Respondents were asked about their poverty levels and living conditions on a scale of four, from very good standards to very poor standards of living.
The results illustrated in Fig. 7 suggest a higher level of perceived poverty than those presented in Table 6. About 11% and 6% of farmers considered themselves to be poor and extremely poor respectively.
Table 3. Proportion of household income from cocoa farming (n=150)
Sources of household income Food stuffs (Plantain, Cassava, Yam, Cocoyam) Cocoa Beans Vegetables (Pepper, Tomatoes etc.) Total
Frequency 23
113 14 150
Percentage 15.30
75.30 9.30 100.0
4. DISCUSSION
4.1 Socio-economic Characteristics of Respondents
The current study has demonstrated the dominance of an economically active farmer population in the production of cocoa in the BABD district of Ghana. Results from the present case study area are consistent with the findings of Danso-Abbeam et al. [30] who reported that about 61% of cocoa farmers in the BABD were aged between 20 and 50 years. The results are however in contrast with studies from other parts of the country that indicates an aging farming population [23,31,32]. As cocoa farmers are ageing, there is the need for a replacement by younger farmers to ensure the sustainability of
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