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BY 4.0 license Open Access Published by De Gruyter Open Access July 14, 2020

Trends and constraints in the production and utilization of cowpea leaves in the arid and semi-arid lands of Kenya

  • Joshua Ombaka Owade EMAIL logo , George Ooko Abong’ , Michael Wandayi Okoth and Agnes Wakesho Mwang’ombe
From the journal Open Agriculture

Abstract

Cowpea (Vigna unguiculata) leaves are nutritious indigenous vegetables that are produced and consumed among local communities in Kenya. However, seasonal production limits their utilization. The study investigated the changing trends in the consumption and utilization of cowpea leaves among cowpea producing households in arid and semi-arid land (ASAL) areas. A cross-sectional survey of randomly selected households producing and consuming cowpea leaves was carried out in Eastern and Coastal ASALs of Kenya to determine the trends and constraints in the production and utilization of the vegetable, thus evaluating its efficiency as a food security crop. The average household production in a season was found to be 3.03 ± 0.9 of 90 kg bags. Lesser severity of the constraints, poor soils, drought, lack of access to seeds and massive spoilage with an odds ratio of 0.4, 0.9, 2.0 and 2.3, respectively, significantly (p < 0.05) predicted the production quantities among households, R2 = 0.21. The study also found that the reliance on own production among households for sourcing the leaves in-season and off-season was 97.5% and 24.9%, respectively. The households consumed the leaves in boiled (87.5%), sundried (27.5%) or blanched (13.6%) forms. Households in the coastal ASALs significantly (p < 0.05) consumed more of dried forms (odds ratio: 3.3) but less of boiled ones (odds ratio: 0.1) than those in the Eastern parts. Households that had more members or a female deciding the food to be bought had significantly (p < 0.05) higher frequency of consumption of cowpea leaves. Marketing challenges, lack of access to inputs and inadequate postharvest technologies for preservation of the vegetables constrained the production and utilization of cowpea leaves. In order to promote the availability and utilization of cowpea leaves both in and out of season, accessibility of good quality seeds and postharvest management are necessary.

1 Introduction

Cowpea (Vigna unguiculata) is a multi-purpose indigenous crop that grows largely in the tropics of sub-Saharan Africa (SSA) (Enyiukwu et al. 2018a; Sobda et al. 2018). FAOSTAT (2019) reported that 95.6% of the area under cultivation of cowpea leaves worldwide in 2017 was in SSA. The crop is also known to be short-term and drought tolerant. The leaves and the grains of the crop are utilized for food in various cuisines among local communities in Kenya (Owade et al. 2019). Additionally, the crop also has the shade tolerance property that has made it easier to intercrop it with other major crops including maize and sorghum. The leaves of the crop have been identified as one of the African leafy vegetables for the improvement of food and nutrition security in SSA (Kirigia et al. 2018). On top of being a human food, the crop has also been utilized for forage.

With the rising interest in orphan crops that are well suited to the harsh environmental conditions in arid and semi-arid lands (ASALs), cowpea leaves are one of the vegetables that are being promoted for both the leaves and the seeds. The annual production of cowpea leaves in 2016 was reported to be 1,15,801 MT (Horticultural Crops Directorate 2016). The leaves are consumed fresh, dried or fermented among local communities in the country. The utilization of the leaves of the crop for food avails nutrients such as beta-carotene, iron and protein whose deficiency is rampant among the vulnerable population of SSA (Kirigia et al. 2018). Moreover, the cowpea leaves are also rich in calcium, zinc, fibre and phytonutrients (Enyiukwu et al. 2018b). Due to this, there are nutrition intervention programmes that are promoting the cultivation of the crop for its leaves.

Even with the known nutritional benefits of cowpea leaves, their utilization and production for food have been less than optimal. The crop has largely been neglected and has a limited value chain due to limited research on its utilization and value addition (Mfeka et al. 2019). The production and utilization of cowpea leaves have largely been seasonal owing to a myriad of challenges including limited postharvest handling technologies. The producers of the leafy vegetable lack appropriate storage and postharvest technologies that would enhance its availability in and out of season (Kirigia et al. 2018). Additionally, during glut, there are massive postharvest losses of cowpea leaves. Local communities in Kenya have indigenous value-addition techniques that they employ to enhance the availability of this vegetable; however, documented studies are yet to report on such practices, their scope and their constraints. The current study seeks to avail this information with a view of ensuring that good traditional practices can be improved, scaled up and replicated in these areas to enhance the availability of the vegetable and contribute to the efforts aimed at alleviating food and nutrition security.

2 Materials and methods

2.1 Study area

The study was conducted in Kitui and Taita Taveta Counties (Figure 1) which are rated among the highest producers and consumers of cowpea vegetables (Horticultural Crops Directorate 2016). Taita Taveta County is located in the coastal ASALs and is divided into 4 sub-counties and 20 administrative wards (County Government of Taita Taveta 2018). The county is situated between the latitudes 20°46′ and 40°10′ North and the longitudes 37°36′ and 39°14′ East (Apollo et al. 2017). According to the Kenya National Bureau of Statistics (KNBS), the estimated population of Taita Taveta County in 2018 was 3,23,867 persons of which 57.2% were living in absolute poverty (contributed 1.1% to national poverty) (GoK 2015).

Figure 1 Map of Taita Taveta and Kitui Counties. Source County Government of Kitui (12) and GoK (10).
Figure 1

Map of Taita Taveta and Kitui Counties. Source County Government of Kitui (12) and GoK (10).

Kitui County is the sixth largest county by land area in Kenya covering 30496.4 km2. The County is the largest in the eastern ASAL areas; a region that has erratic rainfall and drier conditions than the coastal ASAL areas (County Government of Kitui 2014). It lies between the latitudes 0°10′ South and 3°0′ South and the longitudes 37°50′ East and 39°0′ East (County Government of Kitui 2018). Kitui County is divided into eight sub-counties that are further divided into wards that are 40 in number in the whole county. The population of the county according to the 2009 census stood at 1.013 million people (County Government of Kitui 2014), with a projection for it to have increased to 1.1 million in 2018. The main economic activity of the county is Agriculture (Wambua et al. 2016). Crops grown in the area include vegetables, fruits, sweet potatoes, cassava, green grams, maize, beans, sorghum and pigeon peas (Mutunga et al. 2017).

2.2 Study design

The study involved a cross-sectional survey of randomly sampled households that were involved in the production of cowpea leaves in Kitui and Taita Taveta Counties. Households that were producers and consumers of cowpea leaves were incorporated into the study. A semi-structured questionnaire was administered using the open data kit (ODK) mobile application.

2.3 Study population and sampling

2.3.1 Sampling criteria

Kitui and Taita Taveta Counties were purposively selected for the study as they ranked among highest producers and consumers of cowpea leaves. Nguuni ward in Kitui and Mwanda Mgange and Wumingu and Bura wards from Taita Taveta which were the highest cowpea leaves producing areas in the study areas were further purposively selected for the study. These wards were located in Kitui Central Sub-County in Kitui County and Mwatate and Wundanyi Sub-Counties in Taita Taveta County. The respondents from households involved in the production of cowpea leaves from these wards were then randomly selected for the study.

2.3.2 Sample size determination

The study included 405 respondents as per the minimum sample size determined using the Yamane 1967:886 formulae as explained by Israel (1992), equation (1):

(1)n=N1+N(e)2
n=2,76,581(1+2,76,581(0.05)2)=399.42(400), where N (2,76,581) is the total number of households in the two counties as per KNBS (2013) and e is the maximum variability (0.05) permitted.

2.4 Data collection procedures

2.4.1 Data collection tools

A semi-structured questionnaire was developed evaluating the production, processing and utilization of cowpea leaves. The questionnaire was pretested among 20 households in Wundanyi Sub-County that were not included in the actual study. Additional questions and multiple responses were generated from the exercise.

2.4.2 Recruitment and training of enumerators

Enumerators and research assistants were recruited and trained on ODK application for data collection and the data collection tools. The enumerators were trained on data collection ethics, administration of the questionnaire and operation of the ODK application. The questions were also explained to the enumerators. The questionnaire was then pretested among ten randomly sampled respondents in areas in the study area that were not part of the study. Data collection was done by administering semi-structured questionnaires to randomly selected households that were producers of cowpea leaves. Written consents of the respondents were sought once the study objective had been explained to them but before their participation in the study.

2.4.3 Statistical analysis

The data were analysed in R Project for Statistical Computing, R-3.6.3 (R Core Team 2019). Summary statistics such as frequencies for the socio-demographic and economic characteristics, challenges faced and forms of utilization were obtained. Chi-square (χ2) test of association was used to ascertain the influence of the county of residence on the trend of utilization and production. Generalized linear model was used to test the predictor constraints of production on the quantity of cowpea leaves produced. Dummy variables were first generated from the categorical variables for ease of creating a linear model. Linear modelling was used to determine socio-demographic factors that would predict the utilization and intake of cowpea leaves. Significance was tested at p < 0.05.

2.5 Results

2.5.1 Socio-economic and demographic characteristics

The socio-demographic and economic characteristics of the study population are summarized in Table 1. Of the households that were involved in the study, 50.6% were from Coastal ASAL areas (Taita Taveta County), whereas 49.4% were from Eastern part (Kitui County). The household heads were mainly males (72.3%) and had farming (72.9%) as their main occupation. Majority (97.5%) of the households sourced their vegetables from their farm. Reliance on the farm as the major source of the vegetable was significantly (p < 0.05) associated with the county of residence. Cowpea leaves were the most preferred priority vegetable across the two counties with over 80% of the households preferring them (Figure 2). The county of residence of the households and the gender of the household head significantly (p < 0.05) influenced the prioritization of the cowpea leaves as a vegetable and the reliance on the farm as their major source. The cowpea leaves were regarded more in the Eastern region as a major farm produce based on the yields compared to Coastal areas (p < 0.05) as shown in Figure 3.

Table 1

Socio-economic and demographic characteristics of households producing cowpea leaves

Socio-economic and demographic characteristicsCounty of residenceTotalχ2 (p-value, df)
Taita TavetaKitui
Number of respondents (%)50.649.4100Na
Gender of household head (%)
Male66.878.072.36.3 (0.012, 1)
Female33.222.027.7
Level of education of household head (%)
Never went to school 12.721.016.847.4 (<0.001, 4)
In primary 3.421.512.4
Completed primary 47.524.536.1
In secondary 1.52.01.7
Completed secondary 14.215.014.6
University and Tertiary 4.95.05.0
Main occupation of the household head (%)
Salaried employment5.97.56.75.8 (0.325, 5)
Farmer71.874.072.9
Trading and other informal businesses9.410.510.0
Casual labour7.96.07.0
Unemployed4.51.02.7
Not applicable: students and underage0.51.00.7
Who decides food to be bought (%)
Man 46.834.540.721.5 (<0.001, 2)
Woman 52.755.554.1
Both man and woman0.510.05.2
Consumption of cowpea leaves in glut (%)
Yes99.099.599.30.3 (0.573, 1)
No1.00.50.7
Household monthly income (%)
<3,000 KES59.535.547.740.1 (<0.001, 4)
3,000–10,000 KES33.237.035.1
10,000–25,000 KES5.913.09.4
25,000–50,000 KES1.012.06.4
>50,000 KES0.52.51.5
Average age of household head (years)**50.1 ± 16.250.7 ± 16.150.4 ± 16.1 −0.3* (0.731, 403)
Household size (persons)**3.4 ± 2.26.8 ± 3.15.0 ± 3.2−12.5* (<0.001, 359)

Significance for all the dependent variables was tested using Chi-square test except for those indicated with ** where t-test was used. *t-value. na – significance was not tested due to the lack of variation.

Figure 2 Priority vegetables in the study areas. Different letters for an attribute indicate significant difference at p < 0.05.
Figure 2

Priority vegetables in the study areas. Different letters for an attribute indicate significant difference at p < 0.05.

Figure 3 Prioritization of cowpea leaves as a farm produce based farm yields in the different counties. p < 0.001, df = 1 and χ2 = 125.05.
Figure 3

Prioritization of cowpea leaves as a farm produce based farm yields in the different counties. p < 0.001, df = 1 and χ2 = 125.05.

2.5.2 Constraints to the production

Drought and field pests were ranked as the top two severe challenges constraining the utilization of cowpea leaves in the two counties (Table 2). The challenges experienced did not significantly (p > 0.05) differ between the two regions.

Table 2

Extent to which the challenge constrained the utilization and production of cowpea leaves by the households (%)

ConstraintExtent to which the challenge constrain production
LowModerateSevere
Drought7.612.479.9
Diseases9.423.667.0
Field pest11.530.258.4
Extension services1536.248.8
Price fluctuations14.541.643.9
Lack of market23.433.842.9
Weeds1542.442.6
Low prices17.740.342.1
Access to seeds16.560.722.8
Massive spoilage26.551.122.4
Seed scarcity23.454.422.2
Lack of land23.454.422.2
Poor yields31.947.920.2
Poor varieties3052.617.4
Poor soils56.332.710.9

2.5.3 Trends of production of cowpea leaves

The mean average time for initiation of harvesting the leaves was found to be 2.58 ± 1.26 WAE, with an average harvesting period of 2.22 ± 1.79 weeks and a termination period of 7.36 ± 3.99 WAE. The period of initiation, interval and termination of harvesting was not significantly (p > 0.05) different across the two counties. The demographic characteristics of the household head did not significantly (p > 0.05) influence the period of initiation, interval and termination of harvesting of cowpea leaves.

About three quarters (73.8%) of the households growing cowpea leaves preferred them to other crops as they gave higher yields. The households planted cowpea leaves for averagely two seasons (1.9 ± 0.3). The landrace (local) varieties were the most grown varieties by up to 86.2% of the households. Nearly all (98.5%) the households preferred plucking the leaves rather than uprooting the plant as the method of harvesting cowpea leaves. Averagely in both counties, both intercropping and monocropping were practiced in equal measure (Figure 4). However, majority (65.7%) of the households in Kitui County preferred intercropping cowpea leaves with other crops, whereas majority (67.2%) of those in Taita Taveta County used the monocropping system for cultivation of the crop. Significantly (p < 0.05) higher proportion of households in Kitui County preferred to harvest in the morning compared to those from Taita Taveta County as shown in Figure 5. Only two thirds (66.9%) of the households were involved in the sale of the produce they harvested. Of the households that sold the vegetable, women were more involved (84.6%) than the men (53.3%). Three quarters (77.8%) of the households would also harvest the grains from the crops. A higher proportion of households in Taita Taveta County (43.1%) than in Kitui County (1.7%) did not utilize the grains (p < 0.001, df = 2 and χ2 = 102.9).

Figure 4 Association between county of residence and system of farming for cowpea leaves. χ2 = 54.8, p < 0.001 and df = 2.
Figure 4

Association between county of residence and system of farming for cowpea leaves. χ2 = 54.8, p < 0.001 and df = 2.

Figure 5 Association between time of harvesting cowpea leaves and county of residence. χ2 = 15.5, df = 3 and p = 0.001.
Figure 5

Association between time of harvesting cowpea leaves and county of residence. χ2 = 15.5, df = 3 and p = 0.001.

The average production quantity of cowpea leaves of the farmers was 3.03 ± 0.9 of 90 kg bags in a season. The production quantity among cowpea growing households in Kitui County was 4.5 ± 0.3 of 90 kg bags per season; this was significantly (p < 0.05, t = 254.8) higher than those of households from Taita Taveta County that had production quantity of 1.5 ± 0.1 of 90 kg bags. The significant (p < 0.05) predictor factors of production quantities of cowpea leaves included access to seeds, availability of market and weeds with an R2 of 0.21 (Table 3). The regression equation for production quantity of cowpea leaves was as shown in the following equation:

(2)y=2.51.0x10.1x2+0.7x3+0.9x4,

where y is the production quantity in 90 kg bags (number of bags); x1, x2, x3 and x4 are the variables: lack of poor soils (moderate), drought (moderate), lack of access to seeds (moderate) and massive spoilage (low), respectively.

Table 3

Beta values for predictor factors of production quantity of cowpea leaves

Constraints on productionBeta values of intensity of constraints on production (odds ratios)
LowModerate
Field pest0.4 (1.4)−0.6 (0.5)
Seed scarcity−0.4 (0.7)−0.4 (0.7)
Lack of land0.6 (1.9)−0.2 (0.9)
Lack of market 0.4 (1.4)0.6 (1.8)
Poor yields−0.6 (0.5)−0.7 (0.5)
Poor varieties−0.5 (0.6)−0.9 (0.4)
Poor soils −0.2 (0.8)−1.0 (0.4)*
Price fluctuations 0.6 (1.8)0.4 (1.5)
Low prices0.0 (1.0)0.8 (2.2)
Drought−1.1 (0.3)−0.1 (0.9)*
Diseases0.6 (1.7)0.9 (2.5)
Lack of access to seeds1.1 (3.0)0.7 (2.0)*
Weeds−0.2 (0.9)2.5 (12.7)
Massive spoilage0.9 (2.3)**−0.4 (0.7)
Lack of extension services0.6 (1.8)0.6 (1.9)

The regression equation has an R2 of 0.21 and a constant of 2.5 at p < 0.05. The reference category for both low and moderate groups is severe. *significant at p < 0.05, **significant at p < 0.001.

The regression equation has an R2 of 0.21 and a constant of 2.5 at p < 0.05. The reference category for both low and moderate groups is severe. * significant at p < 0.05, ** significant at p < 0.001.

2.5.4 Trends of utilization of cowpea leaves

The most preferred forms of cowpea leaves that were utilized in the households included the boiled (87.5%), sundried (27.5%) and blanched (13.6%). Households from Taita Taveta had odds ratios of 3.3 and 0.1 of consuming boiled and sundried forms of cowpea leaves, respectively, compared to those from Kitui County, whereas the male-headed households also had an odds ratio of 2.5 of consuming the blanched forms as compared to the female-headed ones at p < 0.05. In as much as the frequency of consumption of cowpea leaves in the households across the two counties averaged at 3.4 ± 1.7 days in a week, households in Kitui County posted a higher frequency of 4.1 ± 1.7 days in a week as compared to 2.7 ± 1.3 days a week for households in Taita Taveta County (p < 0.05) during in-season.

3 Constraints of utilization of cowpea leaves

The fitted linear model found that the household size and occupation of the household head were significant socio-economic and demographic factors that influenced the frequency of intake of cowpea leaves in the households (Table 4). With increasing household size, the frequency of weekly consumption of cowpea leaves increased with a correlation coefficient of 0.35 (p < 0.001). Additionally, households where the food to be bought was determined by the female had a weekly frequency of intake of cowpea leaves of 3.7 ± 1.9 which was significantly (p < 0.001) higher than that recorded in households where this decision was with the males, 3.0 ± 1.4. In seasons of scarcity, 75.1% of the households would either source the cowpea leaves from elsewhere or not eat them completely. A higher proportion of the households from Taita Taveta County (42.9%) as compared to those from Kitui County (4.5%) used the preserved forms of cowpea leaves during scarcity (p < 0.05).

Table 4

General linear model of the frequency of intake of cowpea leaves in a household based on their socio-demographic and economic factors

Socio-demographic and economic factors of the householdsDegrees of freedomMean squarep-value
Intercept170.6360.000
Gender of the household head11.560.213
Level of education of the household head62.7270.014
Main occupation of the household head51.5140.185
Who decides food to be bought in the household22.5490.020
Age of the household head600.840.791
Number of household members165.3170.000
Monthly income41.6660.158

4 Discussion

4.1 Trends in production and utilization of cowpea leaves

The survey showed that households that produced and consumed cowpea leaves were mainly male headed with the average age of the household heads being 50 years. This implies that the crop is mostly farmed among the elderly population rather than the youthful age. Ddungu (2013) in his study in Uganda also reported a similar trend where the population farming cowpea leaves was dominated by the elderly. However, findings of a study done in Ghana and Tanzania were different as the farming population of cowpea leaves was dominated by the youthful age group (Mamiro et al. 2011; Akpalu et al. 2014). Kenya currently grapples with low involvement of the youth in agriculture and more so in subsistence agriculture like that of the production of cowpea leaves. The subsistence nature of this value-chain results in low revenue generation which has been adduced to low levels of adoption of appropriate inputs (Afande et al. 2015). Additionally, the land tenure system has been another factor that has contributed to the low involvement of youths in production agriculture in Kenya.

The production of cowpea leaves in the study areas was done in both monocropping and intercropping production systems. This finding is similar to that of a study carried out in Taita Taveta and Makueni Counties where farmers in various agro-ecological zones grew cowpeas in both intercropping and monocropping systems (Njonjo et al. 2019). The crop is a legume with nitrogen-fixing property and has always been recommended for intercropping, especially with cereals (Mucheru-Muna et al. 2010; Iqbal et al. 2019). Experimental studies by Egesa et al. (2016) reported more than 50% increase in sorghum yield in an intercropping production system as compared to a solely sorghum monocropping system. Additionally, Sebetha et al. (2010) reported an increase of 26.7% in the leaf protein of the intercropped cowpea leaves as compared to the monocropped. The attribute of the crop of early maturity has made it to be favoured in the ASAL areas (Njonjo 2018). Of the households that produced cowpea leaves, the harvesting began at 2 weeks and was done at an interval of a similar period. Based on the findings by Saidi et al. (2010), such a practise has a mixed impact on the leaf yield as delayed initiation of leaf harvesting to 3 weeks rather than of 2 weeks that was practiced in the current study and harvesting at an interval of 14 days (similar to that of the study) rather than 7 days improved the leaf yields.

The results indicated that cowpea leaves were a priority crop in the ASAL areas of the country. The prioritization of the crop in both the eastern and coastal ASALs of the country is as a result of its drought-tolerance property. According to the Horticultural Crops Directorate (2016), the leading cowpea leaves producing counties are in the ASALs of eastern and coastal regions of the country. The households in the ASAL areas relied on the farm as their major source of cowpea leaves. This has the implication that less marketing of the vegetable is done in the area and the crop is largely grown for subsistence. A study carried out in South Africa also reported that cowpea leaves were one of the least commercialized crops thus less trading on them is done (Lekunze 2014). With such limited commercialization, this exposes the farmers to huge postharvest losses during glut and massive scarcity of the vegetable during drought.

The study also found that cowpea leaves were consumed as boiled, blanched and sundried forms in the ASAL areas. These are majorly the traditional methods of preparation that have remained unchanged over the years. The consumption of cowpea leaves was found to be at least 3 days in a week with the eastern ASAL region of the country consuming about twice as frequent as the coastal ASAL areas. Such a level of intake of cowpea leaves has a nutritional advantage as Enyiukwu et al. (2018a) recommended the consumption of the leaves over the seeds for they are rich in minerals, vitamins and antioxidants that have disease prevention and nutrition-promoting characteristics. Moreover, the vegetables have also been found to be low in antinutrients, and thus the nutrients have a high bioavailability (Chikwendu et al. 2014). All households consumed their cowpea leaves from their own production during glut but had no cowpea leaves to consume or had to source from elsewhere during drought and seasons of scarcity. This shows insufficiency of the postharvest storing technologies of the leaves in this area in ensuring uninterrupted availability of the vegetable.

4.2 Constraints of production and utilization of cowpea leaves

Drought, diseases and field pests were found to be the most prevalent challenges experienced by farmers in the ASAL areas of the country. Another study in Uganda that focused on cowpea production rated similar challenges of pest and diseases together with unreliable rainfall as among the most prevalent challenges constraining production (Ayaa et al. 2018). The challenges of pest and diseases and drought result in pre-harvest losses leading to low production quantities. The rural population also largely relied on landrace varieties for their production. This has the effect of limited yields being realized. Using the generated linear models, increasing severity of massive spoilage and constrained access to seeds as challenges aggravated limited production quantities of the leaves among the households. This limited access to seeds is evidenced by the high proportion of the households that rely on the landraces rather the improved varieties for cultivation. Massive spoilage limits the quantities available for use among the households, lest such households initiate postharvest management measures to preserve the leaves. Increasing severity of drought and poor soils did not constrain the production quantities of the households. The area of study is arid and the communities tend to have coping strategies to the adverse environmental conditions (Opiyo et al. 2015).

Smaller household sizes and households where males decided the food to be eaten recorded lower frequencies of intake of cowpea leaves. Lekunze (2014) in his market analysis study in South Africa reported that with increasing standards of living, households would abandon the cowpea leaves for other foods. Smaller households have usually been associated with higher living standards and this explains the positive correlation between household size and frequency of intake of cowpea leaves. Nevertheless, the consumption of cowpea leaves as reported in various studies has not been satisfactory despite them being nutritious. Gido et al. (2017) reported that the acceptance of cowpea leaves in the urban areas is still lower than in the rural areas as they preferred other forms of vegetables. Additionally, Mamiro (2011) reported a range of 10–500 g daily per capita consumption of cowpea leaves in season among the households with more extremities than the grains, 40–200 g. This is due to the prioritization of the harvesting of the seeds over the leaves as it has been established in other studies that harvesting of the leaves reduce the grain yield (Saidi et al. 2010). The harvesting of the leaves is usually abandoned to allow for development of the grains. Off-season utilization declined greatly as up to 75.1% of the households lacked their own production of cowpea leaves to consume. This is as a result of lack of appropriate postharvest technologies and inadequate production quantities that could sustain the households through the off-season period.

5 Conclusion

Cowpea leaves were a major source of food and a priority crop in the ASAL areas of Kenya. In times of glut, the households majorly relied on their own production for sourcing the vegetable; however, scarcity of the vegetable would have most households not consuming the crop. The major forms of utilization of the cowpea leaves in the ASAL areas were traditional with limited value-addition practices being done. The eastern ASAL regions have lesser diversity of forms in which they consume cowpea leaves as compared to the ASAL areas in the coastal region.

Pest, diseases and drought were major constraints that greatly constrained the utilization and production of cowpea leaves in these ASAL areas. Limited production quantities of the vegetable among the households were aggravated by the lack of access to good quality seeds and massive spoilage. In order to increase the availability and intake of the vegetables, it is necessary to address these two constraining factors among these cowpea producing households in ASAL areas.

  1. Funding: This work was financially supported by the German Federal Ministry of Food and Agriculture (BMEL) based on the decision of the Parliament of the Federal Republic of Germany.

  2. Conflict of interest: The authors declare that they do not have any conflict of interest.

  3. Ethical review: The study did not involve any animal or human testing.

  4. Informed consent: The study did not involve human subjects.

References

[1] Afande FO, Maina WN, Maina MP. Youth engagement in agriculture in Kenya: challenges and prospects. J Cult Soc Dev. 2015;7:4–19.Search in Google Scholar

[2] Akpalu MM, Salaam M, Oppong-Sekyere D, Akpalu SE. Farmers’ knowledge and cultivation of cowpea (Vigna unguiculata (L.) Verdc.) in three communities of Bolgatanga Municipality, Upper East Region, Ghana. Br J Appl Sci Technol. 2014;4:775–92.10.9734/BJAST/2014/6969Search in Google Scholar

[3] Apollo F, Ndinya A, Ogada M, Rop B. Feasibility and acceptability of environmental management strategies among artisan miners in Taita Taveta County, Kenya. J Sustainable Min. 2017;16:189–95. 10.1016/j.jsm.2017.12.003.Search in Google Scholar

[4] Ayaa F, Alumai A, Dranzoa C. Indigenous knowledge influences cowpea (Vigna unguiculata) production among smallholder farmers in Northern Uganda. Sch World-Int Ref J Arts Sci Commer. 2018;VI:85–9.Search in Google Scholar

[5] Chikwendu JN, Igbatim AC, Obizoba IC. Chemical composition of processed cowpea tender leaves and husks. Int J Sci Res Publ. 2014;4:1–5.Search in Google Scholar

[6] County Government of Kitui. First County integrated development plan 2013–2017: planning for sustainable socio-economic growth and development. Kitui: County Government of Kitui; 2014.Search in Google Scholar

[7] County Government of Kitui. Kitui County integrated development plan 2018–2022. Kenya: County Government of Kitui, Kitui; 2018.Search in Google Scholar

[8] County Government of Taita Taveta. Taita Taveta County Integrated Development Plan 2018–2022. Nairobi, Kenya: County Government of Taita Taveta; 2018.Search in Google Scholar

[9] Ddungu S. Farmer market integration of cowpea in Uganda and preferences. MSc. Thesis. Uganda: Makertere University; 2013Search in Google Scholar

[10] Egesa AO, Njagi SN, Muu CW. Effect of facilitative interaction of sorghum-cowpea intercrop on sorghum growth rate and yields. J Environ Agric Sci. 2016;9:50–8.Search in Google Scholar

[11] Enyiukwu DN, Amadioha AC, Ononuju CC. Nutritional significance of cowpea leaves for human consumption. Greener Trends Food Sci Nutr. 2018a;1:1–10. 10.15580/gtfsn.2018.1.061818085.Search in Google Scholar

[12] Enyiukwu DN, Amadioha AC, Ononuju CC. Biochemical composition, potential food and feed values of aerial parts of cowpea (Vigna unguiculata (L.) Walp.). Greener Trends Food Sci Nutr. 2018b;1:11–8. 10.15580/gtfsn.2018.1.080118107.Search in Google Scholar

[13] FAOSTAT, FAOSTAT. http://www.fao.org/faostat/en/#data/QC (accessed 2.10.18), 2019.Search in Google Scholar

[14] Gido EO, Ayuya OI, Owuor G. Consumer acceptance of leafy African indigenous vegetables: comparison between rural and urban dwellers vegetables: comparison between rural and urban. Int J Veg Sci. 2017;5260:346–61. 10.1080/19315260.2017.1293758.Search in Google Scholar

[15] GoK. Taita Taveta County HIV $ AIDS strategic plan 2016–2020. Kenya; 2015.Search in Google Scholar

[16] Horticultural Crops Directorate. Validated Report 2015–2016. Nairobi, Kenya; 2016.Search in Google Scholar

[17] Iqbal MA, Hamid A, Ahmad T, Siddiqui MH, Hussain I, Ali S, Ali A, Ahmad Z. Forage sorghum-legumes intercropping: effect on growth, yields, nutritional quality and economic returns. Bragantia. 2019;78:82–95. 10.1590/1678-4499.2017363.Search in Google Scholar

[18] Israel GD, Determining sample size. Fact Sheet PEOD-6 1–5, 1992. 10.4039/Ent85108-3.Search in Google Scholar

[19] Kirigia D, Winkelmann T, Kasili R, Mibus H. Development stage, storage temperature and storage duration influence phytonutrient content in cowpea (Vigna unguiculata L. Walp.). Heliyon. 2018;4:e00656. 10.1016/j.heliyon.2018.e00656.Search in Google Scholar PubMed PubMed Central

[20] KNBS. Population distribution by sex, number of households, area and density by Administrative Units. Detail Census Rep; 2013.Search in Google Scholar

[21] Lekunze JN. Market analysis of cowpeas-leaves: an indigenous vegetable in North West Province, South Africa. J Hum Ecol. 2014;48:73–81. 10.1080/09709274.2014.11906776.Search in Google Scholar

[22] Mamiro P. Nutritional quality and utilization of local and improved cowpea varieties in some regions in Tanzania. AJFAND. 2011;11:4496–506.10.4314/ajfand.v11i1.65876Search in Google Scholar

[23] Mamiro PS, Mamiro D, Mwanri A, Kinabo J. Nutritional quality and utilization of local and improved cowpea varieties in some regions in Tanzania Volume 11 No. 1. AJFAND. 2011;11:4490–506. 10.4314/ajfand.v11i1.65876.Search in Google Scholar

[24] Mfeka N, Mulidzi RA, Lewu FB. Growth and yield parameters of three cowpea (Vigna unguiculata L. Walp) lines as affected by planting date and zinc application rate. S Afr J Sci. 2019;115:1–8. 10.17159/sajs.2019/4474.Search in Google Scholar

[25] Mucheru-Muna M, Pypers P, Mugendi D, Kung’u J, Mugwe J, Merckx R, Vanlauwe B. A staggered maize-legume intercrop arrangement robustly increases crop yields and economic returns in the highlands of Central Kenya. Field Crops Res. 2010;115:132–9. 10.1016/j.fcr.2009.10.013.Search in Google Scholar

[26] Mutunga EJ, Ndungu CK, Muendo P. Smallholder farmers perceptions and adaptations to climate change and variability in Kitui County, Kenya. J Earth Sci Clim Change. 2017;8:1–7. 10.4172/2157-7617.1000389.Search in Google Scholar

[27] Njonjo MW, 2018. Quality of cowpea seed used by farmers in Makueni and Taita Taveta counties and its effect on crop performance 1–29.10.1155/2019/1607535Search in Google Scholar

[28] Njonjo MW, Muthomi JW, Mwang’ombe AW. Production practices, postharvest handling, and quality of cowpea seed used by farmers in Makueni and Taita Taveta Counties in Kenya. Int J Agron. 2019;2019:1–12. 10.1155/2019/1607535.Search in Google Scholar

[29] Opiyo F, Wasonga O, Nyangito M, Schilling J, Munang R. Drought adaptation and coping strategies among the Turkana pastoralists of Northern Kenya. Int J Disaster Risk Sci. 2015;6:295–309. 10.1007/s13753-015-0063-4.Search in Google Scholar

[30] Owade JO, Abong G, Okoth M, Mwang AW. A review of the contribution of cowpea leaves to food and nutrition security in East Africa. Food Sci Nutr. 2019;8:36–47. 10.1002/fsn3.1337.Search in Google Scholar PubMed PubMed Central

[31] R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2019.Search in Google Scholar

[32] Saidi M, Itulya FM, Aguyoh JN. Effects of cowpea leaf harvesting initiation time and frequency on tissue nitrogen content and productivity of a dual-purpose cowpea–maize intercrop. HortScience. 2010;45:369–75.10.21273/HORTSCI.45.3.369Search in Google Scholar

[33] Sebetha ET, Ayodele VI, Kutu FR, Mariga IK. Yields and protein content of two cowpea varieties grown under different production practices in Limpopo province, South Africa. African J Biotechnol. 2010;9:628–34. 10.5897/AJB09.1132.Search in Google Scholar

[34] Sobda G, Mewounko A, Sakati PD, Ndaodeme K. Farmers’ cowpea production constraints and varietal preferences in the sudano-sahelian zone of Cameroon. Int J Innov Appl Stud. 2018;24:968–77.Search in Google Scholar

[35] Wambua BM, Musimba NKR, Muli E. Socioeconomic analysis of beekeeping technologies in Kenya: a case study of Kitui County. Int J Educ Res. 2016;4:345–54.Search in Google Scholar

Received: 2019-12-10
Revised: 2020-03-04
Accepted: 2020-04-02
Published Online: 2020-07-14

© 2020 Joshua Ombaka Owade et al., published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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