Livestock Research for Rural Development 27 (3) 2015 Guide for preparation of papers LRRD Newsletter

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Economic analysis of natural pasture rehabilitation through reseeding in the southern rangelands of Kenya

J K Manyeki, E C Kirwa, P B Ogillo, W N Mnene, R Kimitei, A Mosu and R Ngetich

Kenya Agricultural and Livestock Research Organization, Arid and Range Lands Research Institute, P.O. Box 12 – 90138, Makindu


Of rate, there has been a national effort to rehabilitate the degraded area of arid and semi-arid lands (ASALs) of Kenya through disseminating reseeding technology. The technology was selected based on its early attempts as a means of rehabilitating degraded natural pasture in Kenya that reported encouraging success. Due to geophysical constraints, severely resource constrained livestock keeper and some socio-cultural factor prevalent in ASALs of Kenya, the economic potential of reseeding technology in terms of outputs, costs of production and profit are very important factor for farmers’ decision making which has received little attention. This study aimed at evaluating the economics of reseeding natural pasture in the southern rangelands of Makueni County using the range grass species. The recommended grass species were Cenchrus ciliaris, Chloris roxbohurghiana, Enteropogon macrostachyus and Eragrostis superba.

Based on cost benefit analysis, all the grass species gave a positive net present value and gross margin and a cost benefit ratio above one implying that the costs invested in the improvement of pasture through reseeding are recovered and benefit realized. Income per hectare earned from seed and hay production was higher than that obtained from maize production. There was also an increase in tropical livestock unit (TLU) and milk production. For a year long proper use factor of 50%, safe stocking rate varies from 1.44 to 2.43 ha/TLU/year with Chloris roxbohurghiana recorded the highest while Enteropogon macrostachyus the lowest.

Keywords: cost benefit ratio, economic, gross margin, natural pasture improvement, net present value, tropical livestock unit


In Kenya, arid and semi-arid lands (ASALs) cover over 88% of the country’s landmass (Muthee 2006; RoK 2011). These areas have undergone increasing land use pressure resulting to land degradation, largely due to a number of factors that threatened the sustainability of livestock production systems. Natural pasture degradation was established as one of the primary problem limiting livestock production in these areas (RoK 2011). With respect to natural pasture, degradation is a process and involves one or more of the following: Net loss of vegetation as a result of heavy grazing without sufficient time to rest and reduction in palatable forage species, such as Cenchrus ciliaris, Chloris roxbohurghiana, Digitaria macroblephara, Enteropogon macrostachyus, Eragrostis superba and Sporobolus pellucidus among others. The same scenario may occur as a result of wrong land uses and agricultural practices, cutting vegetation and drought which lead to deterioration and erosion of soil properties (Alemu et al 2000; Munyasi et al 2011). The natural pasture in Kenya are degraded so intensively that their vigour is reduced, less productive grasses and weeds invade the pastures reducing further soil fertility. The effects of land degradation has far much impacts on livestock production (Nyangito 2005) with direct effects on reduced feed supply, reduced carrying capacity and the frequently observed livestock mortality due to starvation.

Historically, the emphasis in Kenya has always been on range management and utilization and research on reseeding techniques started only recently. Kenya Agricultural Research Institute (KARI) in partnership with development agencies instituted a research programmes namely National Agricultural Research Project II (NARP II) and Kenya Arid and Semi-Arid Land (KASAL) which run between 1998-2004 and 2007-2012 respectively, to undertake rehabilitation of those areas of the country's rangelands that had been most severely affected by pasture degradation (Mnene et al 1999; Gitunu et al 2003; Dolan et al 2004; Mnene 2006). Reseeding technologies was recommended as an options that would rehabilitate pasture especially where pasture are heavily invaded by weeds, bushes and shrubs—and is lacking in or has few desirable grass species. The technology was selected based on the it’s early attempts as a means of rehabilitating degraded natural pasture in Kenya that reported encouraging success (Pratt 1963; Pratt et al 1964; Bogda et al 1967; Mnene et al 1999). The range grass species recommended for reseeding were Eragrostis superba (ERSU), Cenchrus ciliaris (CECI), Enteropogon macrostachyus (ENMA) and Chloris roxyburghiania (CHROX) all being perennial range grasses. These grass species has proved useful for pasture and soil retention in a wide range of environments due to their drought tolerance, relative high biomass and rapid response to rains. They are also easy to establish, provide good quality herbage that are palatable to animals and resistance to overgrazing. In addition they are able to produce adequate amount of viable seed which can be easily harvested and planted (Mnene et al 1999; Mnene 2006).

The successful implementation of reseeding technologies would not only improve the understory biomass which is the basal diet for livestock reared in ASALs of Kenya, but also the livelihood of the people leaving in these areas. However, this particular strategy is important where high monetary returns are expected although it requires high management and is costly (Ogillo 2010). Unfortunately, there is inadequate information on the expected economic returns of reseeding natural pasture resulted to relatively low priorities assigned to range improvement by farmers and the government. This was clearly demonstrated in the recent study by Manyeki et al (2013) that reported low adoption of reseeding technologies in Makueni County. As a result of this, an in-depth ex-post economic analysis of the disseminated reseeding technology which was recommended by Dolan et al (2004) and Kibet et al (2006) was necessary to enhance wider adoption and diffusion of reseeding technology. The need was necessitated by the fact that the economic potential of reseeding technology in terms of outputs, costs of production and profit are very important factor for farmer and government in decision making. The evaluation of the economic effects in terms of cost and benefit of the disseminated reseeding technology for rehabilitating natural pasture is, therefore, important for ensuring diffusion and sustainability of improved pasture. In this regard the premise of this study was designed to assess the economics of improving natural pasture in the rangelands of Kenya by estimating the cost and benefit of improving pasture through reseeding and the tropical livestock unit.


Study sites

This study was conducted in Kathonzweni, Makindu and Kibwezi areas of Makueni County. These sites were purposively selected based on the earlier attempt and success of the disseminated reseeding technology during ARSP II and KASAL by KARI in southern rangelands of Kenya. The three sites are situated in eastern Kenya and stretches from latitude 1º 35 ́S to 3º 01 ́S from north to south and longitudes 37º 10 ́E and 38º 30 ́E from east to west and lies in the transitional zone between agro-ecological zones IV and V (RoK 2010). The soils are sandy and have very humus content and low water holding capacity. The soils are very susceptible to soil erosion due to their coarse textured nature. Just like any other soils in ASALs environmental, the soils of three sites contain low organic matter with carbon content between 0.1- 0.5 percent making it vulnerable to degradation (El Beltagy 2002). The areas are generally characterized by high temperature throughout the year, with the minimum and maximum temperatures ranging from 12°C to 18°C and 25°C to 28°C respectively. The rains in these areas are low, erratic and unpredictable in nature, varying between 250 and 900 mm in a year. Due to their proximate position along the equator, the area experiences a bimodal pattern of rainfall with long rains from March to May and short rains from October to December. The short rains are more reliable than long rains and therefore more important. The largest ethnic group in the study area is the agro-pastoral Kamba community (Nyangito et al 2008). Their mainstream economic activity is raising livestock and cultivating cereal and pulses (Nyangito et al 2008).

Study Description

The community based forage seed system was the approach used in disseminating reseeding technology in the three sites. The main objective of this approach was to enhance production of adequate quantities of grass seeds of better quality to match the increasing demand of range grass seeds for rehabilitation of degraded rangelands of Kenya (Gitunu et al 2003; Dolan et al 2004; Reynolds et al 2005; Mganga et al 2010). This approach targeted the common interest farmers’ group in grass seeds multiplication at the community level for rehabilitation and pasture establishment for improved livestock production. This was done through on-farm establishment of demo plots, organizing farmers’ group workshops and training of trainers (ToT). The ToT includes of two groups; farmers’ group representative and extension staff. Each ToT was supposed to establish pasture demonstration plot for backstopping farmers at their respective site. A two day workshop was jointly organized by the technical support team and ToT for farmers at their respective site and farmers were extensively trained on how to prepare land, seed planting, hay and seed harvesting and storing. Each farmer was supposed to establish an acre of pure stand from the four range grass species (Eragrostis superba, Cenchrus ciliaris, Enteropogon macrostachyus, Chloris roxyburghiania) recommended for reseeding the degraded pasture (Kimitei et al 2008). An acre was estimated at 100 feet wide and 435.6 feet long (100 x 435.6 = 43,560 square feet) which is about 40% of a hectare and approximately 4,047m². This was followed by regular monitoring by technical expert /ToT. The farmers were not allowed to graze the animals in the established plot for two consecutive season to allow quick and uniform pasture establishment. No grass seed was harvested in the first season, but allowed to fall down in the pasture plot for self-under-sowing. By the end of the second season an ocular evaluation was done and estimated establishment were ranging from 50 - 100% (Kimitei et al 2011).

This study targeted those household with pasture establishment rate of above 70%. The sampling was done from a total of 68 successful farmers in reseeding between 22nd November to 4th December 2010 with the guidance and assistance of local extension officers. The data for estimating biomass was collected by establishing two diagonal transects in an acre. Each transect consisted of twelve 0.25 m² plots evenly distributed along the transect. At each transect, twelve plots of 0.5× 0.5 m were delineated, each separated by ten metres. For each transect we estimated canopy areas (CA) and basal areas (BA), following Johnson et al (1998) and plant density. The highest vegetative tiller was defined as plant height, excluding reproductive tillers that may surpass vegetative tillers (whose biomass is negligible, Guevara et al 2002). All plants were hand clipped at ground level leaving a stubble height of less than 2.5 cm and weighed. Following Ramsay et al 2001, fixed dead material (that is, dead leaves still attached to the tussocks, Waren et al 1994) was harvested, but ground litter was not. We then used allometric relationships to estimate species-specific biomass. The reason for adopting aforementioned biomass estimate was because most understory biomass equations are developed using fairly subjective ocular estimates of percent cover as the independent variable. Ocular estimates have the disadvantage of varying between observers as well as over time for a single observer, introducing unknown, but potentially substantial, error into the biomass estimates. We felt that using some combination of basal area, plant height, or number of seed heads might overcome these problems.

A seed yield were determined by hand harvesting of mature and ripened seeds from an acre. This was done at the time of full maturity and ripened seeds. The method used in harvesting CECI and ERSU grass seeds was stripping while ENMA and CHROX grass seed were harvested through stock-cutting. The seed were then air dried, threshed, cleaned and weighed for cost and revenue estimation using a spring balance.

The direct benefits of the improved pastures through reseeding were estimated as the numbers of 15 kg hay bales and kilograms of grass seed harvested per acre from the four range grass species. The technique used for valuing input and outputs are as stipulated below;

Table 1. Techinque of valuing inputs and outputs of reseeding
Item Valuation technique
Land preparation per acre Market price
Grass seed Selling price from institution
Harvesting grass seed Wage rate of hired labour
Hay harvesting Wage rate of hired labour
Weed and pasture management Wage rate of hired labour
Sisal twine Market price
Gunny bag Market price
Seed output Market price sold by farmers
Hay output Market price sold by farmers

We also estimated tropical livestock unit (TLU). The concept of TLU provides a convenient method for quantifying a wide range of different livestock types and sizes in a standardized manner (HarvestChoice, 2011). The standard used for one TLU was one cattle with a body weight of 250 kilograms. The estimation were based on assuming an average daily dry-matter (DM) intake of 2.5% of bodyweight (Boudet et al 1968; Minson et al 1987; Mulindwa et al 2009), each TLU would consume 6.25 kg of forage dry matter daily. An attempt was also made to estimate the carrying capacity (CC) of an improved natural pasture land. Under the normal circumstance, the rate at which herbage disappears is higher than animal intake because of wastage, trampling, fouling and decomposition. In this study, the most common year long ‘proper use factor' or a utilization rate of 50% of standing herbage yield for sustainable rangeland (Mugerwa 1992; Kavana et al 2005) was used; this gives a herbage allowance of 12.5 kg DM/TLU per day. The following equation adopted from work of FAO (1991) and Mulindwa et al (2009) for estimating the proper use of forage in rangelands was applied:

Where CC is the carrying capacity, AR is the animal requirement, WSC is the weight of the standing hay and PUF is the proper use factor.

Result and discussion

Generally, there was increase in reseeding between the year 2008 and 2010 with Eragrostis superba (ERSU) recording the highest acreages followed by Cenchrus ciliaris (CECI), Chloris roxyburghiania (CHROX) and Enteropogon macrostachyus (ENMA) in that order (Table 2).

Table 2. Average acreages under reseeding for the sample surveyed
Grass species Period
2008 2010
Eragrostis superba 1.61 2.16
Enteropogon macrostachyus 0.688 1.01
Chloris roxyburghiania 1.01 1.28
Cenchrus ciliaris 1.10 1.39

The increase in acreage was attributed to the passion demonstrated by farmer in rehabilitating the degraded natural pasture for increased feed stock compounded with the increasing in demand for uniform pasture improving materials. ERSU grass species was said to be popular and seed are readily available than the rest hence recording more acreage. In addition, ERSU seeds are also easy to harvest and require little moisture to establish.

Production cost

Since a cost estimate is the approximation of the cost of a project or operation, then estimate accuracy is a measure of how closely the estimate is able to predict the actual expenditures for the project or operation and this can only be known after the project is completed. For this study the cost were estimated after two season of pasture establishment. The result indicate that the large portion of the production cost came from land preparation, grass seed for planting, weed and pasture management and seed and hay harvesting (Table 3).

Table 3. Summary of unit cost for seed and hay production in southern rangelands
Item Range of unit cost
Average unit cost
Land preparation per acre 1200-1500 1350
Grass seed per kg 600-1000 800
Harvesting grass seed of CHROX, ENMA and ERSU per kg 50-100 75
Harvesting grass seed of CECI per kg 100-200 150
Hay harvesting (bale) 40-60 50
Weed and pasture management (acre) 1000-2000 1500
Sisal twine (2 kg piece) 200-300 250
Gunny bag (90 kg) 30-50 40

The total average cost per grass species per hectare was also estimated. CHROX and ENMA recorded the highest production cost for both grass seed and hay production while CECI recorded the lowest cost. Majorly, the difference in production cost arises from the different price offered for harvesting a kilogram of each and the amount of seed per hectare for the each type of grass species. This was because a double price was required to harvest a kilogram of CECI.

Table 4. Average total input cost per grass species per hectare (1 ha=2.47 acre) in KES for hay and grass seed production
  Grass species
Land Preparation 3,335.90 3,335.90 3,335.90 3,335.90
Grass seed (seed rate = 6.2 kg/ha) 4,960.00 4,960.00 4,960.00 4,960.00
Weed and pasture management 3,706.60 3,706.60 3,706.60 3,706.60
Hay harvesting
Hay cutting and baling 10,575.00 8,775.00 10,035.00 6,260.00
Sisal twine (1 piece = 30 bales) 1,762.50 1,462.50 1,672.50 1,043.30
Seed harvesting
Grass seed harvesting 26,475.00 17,400.00 19,275.00 31,875.00
Gunny bags 941.30 309.30 514.00 566.70
Total cost 51,756.30 39,949.30 43,499.00 51,747.50
Revenue estimate from marketing of hay and grass seed

Evalution of revenue from hay prodution for the four range grass species per hectare was based on the prevailing market price that ranges from KES 100-250 per 15 kg bale of hay. CHROX recorded the highest biomas production which translated into the higher revenue realised. ERSU, CECI and ENMA were ranked number 2, 3 and 4 respectively both in hay and revenue generation. The difference may be attributed to the variance in morphological characteristics existing in the four grass species that significantly influence the determination of basal area, plant height and density that was used in estimating the biomass production.

Table 5. Average cash flow of air-dried bales of hay harvested per grass species per hectare (KES)
Grass species Biomas
(15 kg)
Average Unit Cost
Total revenue
CHROX 3172 211.5 175 37,012.50
CECI 2632 175.5 175 30,712.50
ERSU 3011 200.7 175 35,122.50
ENMA 1878 125.2 175 21,962.50

Currently the marketing of grass seed in Kenya is informal although the process of range grass seed certification by Kenya Plant Health Inspetorate Services (KEPHIS) is at an advance stage. Meantime, the basic requirement by KEPHIS is that before marketing, the grass seed must be tested for quality assuarance. KARI has been enhancing the marketing of range grass seed through offering testing services to gurantee the quality and linking farmers to the potential buyers. This collabolation has maintained the farm gate selling prices for four grass species at reasonably high level. Generally, the four grass species exbited high revenue in grass seed production compared to hay production. The high revenue in grass seed production was because of the growing demand for pasture grass seeds of better quality for rehabilitate the degraded pasture by farmers and the government. Out of the four grass species, the highest revenue was realised in ENMA followed by CHROX, ERSU and CECI in that order. This is beacause among the four grass species, seed of ENMA are large and hevier and can be easily harvested by hand. The findings concur with those of Koech et al (2014) who reported ENMA as having higher seed yield compared to other three species and that of Mganga, et al (2010), where ERSU was reported as having more yield than CECI. The two study attributed this to inherent morphological characteristics.

Table 6. Average cash flow of different grass seed harvested per species per hectare (KES)
Grass species Quantity
Price range/kg
Average selling
CHROX 353 200-500 350 123,550.00
CECI 116 500-800 650 75,400.00
ERSU 257 200-500 350 89,950.00
ENMA 425 200-500 350 148,750.00

Collectively, the cash flow from sale of hay and grass seed showed that CHROX had the highest with KES 160,562.50 and CECI the lowest with KES 106,112.50. Compared to maize production in the same area under the same environmental condition, with an average maize yields of around five bags (450kg) (Muhammad et al 2010; Whitfield 2014,) of dried maize per acre and an average market price of KES 12.9 ±0.5 per kg, the expected gross revenue is about KES 13,899.70 per hectare which is far below the estimated net revenue from reseeding natural pasture.

Cost benefit analysis

Cost and benefit associated with reseeding natural pasture were evaluated through estimating the expected net present value (NPV), gross margin (GM) and cost benefit ratio (CBR). Based on these cost benefit parameters, all the grass species analysed gave a positive NPV and GM and a CBR above one. This means that the costs invested in the improvement of pasture through reseeding are recovered and high benefit realised. The discounted net benefit was far above zero implying that it worthy investing in reseeding natural pasture for enhanced future benefit. Among the four grass species, ENMA recorded the highest benefit and CECI had the lowest.

Table 7. Estimate of cost and benefit for seed and hay production per hectare
Item Grass species
GM 108,806.20 66,163.20 81,573.50 118,965.00
CBR 3.1 2.7 2.9 3.3
NPV (30% discounting value) 83,697.10 50,894.80 62,748.90 91,511.50
Estimate of the Tropical Livestock Unit

The concept of tropical livestock units (TLU) provides a convenient method for quantifying a wide range of different livestock types and sizes in a standardized manner. The standard used in this study for one TLU is one cattle with a body weight of 250 kg. The estimation were based on assuming an average daily dry-matter intake of 2.5% of bodyweight, each TLU will consume 6.25 kg of forage dry matter. For a herbage allowance of 12.5 kg DM/TLU per day, safe stocking rate for studied areas varies from 1.44 to 2.43 ha/TLU/year which was higher than the long-term estimated carrying capacity of agroclimatic zones V and VI of Kajiado district, that ranges from 3 and 7 ha per 250 kg TLU (Solomon et al 1991). CHROX recorded the highest while ENMA had the lowest (Table 8).

Table 8. Estimate of the Tropical Livestock Units for a 250 kg cattle per day per grass species per hectare
Grass species Biomass
kg DM/ha/year
No. of TLU Carrying capacity
CHROX 3173 254 1.44
CECI 2632 211 1.73
ERSU 3011 241 1.52
ENMA 1878 150 2.43

The study also estimated the impact of reseeding in milk production. The respondents in these study areas indicated, on average, an improvement in milk production of about 34.8% and 66.4% per day for cattle and goat respectively. Perhaps owing to improved nutrition as a result of improved natural pasture through reseeding.

Table 9. Average milk yield (litres) for different livestock species before and after reseeding
Livestock type Before After
Cattle 0.9 2.5
Goat 0.1 0.2


Based on the results of this study, there was growing effort of improving the degraded natural pasture of arid and semi-arid lands of Kenya. The study also showed how profitable a reseeded pasture could be as compared to other crop such as maize. This means that the costs invested in the improvement of pasture through reseeding are recovered and high benefit realised. Other benefit of reseeding were improvement of the tropical livestock unit and the carrying capacity. However further research is needed to arcertain the performance of livestock as a result of feeding in these grass species and estimate the associated economic value.


The authors acknowledge all government institutions and farmers who either directly or indirectly contributed to the successful completion of this activity. We also appreciate the European Union through KASAL programme and the Government for the financial support. Thanks go to the Director, KARI and the Centre Director KARI Kiboko for the logistic support. Finally we acknowledge Ecology and Natural Resource Management section staff at KARI Kiboko for the tireless support both technically and morally.


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Received 17 October 2014; Accepted 23 February 2015; Published 3 March 2015

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