Assessment of Constraints in Technology
Transfer System and Policies which Limit theRealisation of High Green Leaf Production in
the Smallholder Tea Sector of the Kenya Tea
Industry: An Empirical Analysis of Economic
Efficiency and Supply of Tea
Part II

Philip Okinda Owuor

ATPS RESEARCH PAPER No.3

Published by the African Technology Policy Studies Network, P.O. Box 10081, 0100
General Post Office, Nairobi, Kenya.

© 2005 African Technology Policy Studies Network (ATPS)

PUBLISHED BY THE ATPS COMMUNICATIONS DEPT.
PRINTED BY ZEALOT PRINTERS

ISBN: 9966-916-82-2`

ABOUT THE AFRICAN TECHNOLOGY POLICY STUDIES NETWORKThe African Technology Policy Studies Network (ATPS) is a multi-disciplinary network of researchers, policymakers, actors in the private sector and other end users interested in generating, promoting and strengthening innovative science and technology policies in Africa. With a regional secretariate
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ABSTRACTTechnological recommendations for maximizing green leaf production have been made available tosmallholder farmers by the Tea Research Foundation of Kenya (TRFK) through various publications.
Indeed TRFK has released clones, which are yielding in excess of 4000 kg mt/ha. Consequently, thesmallholder tea areas are planted with these clone compared to the estate sub sector with large areas ofland planted with old seedling tea cultivars, yielding lower than 2500 kg mt/ha per year. Nevertheless, tea
productivity in the smallholder sub sector has been relatively lower than in the estates sub sector over theyears and the yields are still well below potential. The Kenya Government projects to produce 350 thousand
metric tones by the year 2008, through putting emphasis on efficient use of strategic inputs such as
fertilisers and adoption of intensive technologies of tea production to enhance yields. This study investigatedthe efficiency of adoption of tea production technologies and some policy factors contributing to low tea
productivity in the smallholder tea sub sector. Specific objectives were:1.
to identify the major resources being used by farmers in tea production, estimate the tea production
function and identify which of the identified resources significantly influenced tea production in
the smallholder tea sub sector;2.
to determine whether the farmers were utilising the identified resources efficiently;
3.
to determine the economic rationality of small scale tea farmers;
4.
to determine compare the relative efficiency between east and west of the Rift Valley regions;5.
to identify the factors influencing the supply of green leaf, estimate the green leaf supply function
and determine which of the identified factors significantly affect the supply of green leaf in thesmallholder tea sub sector and6.
to identify the major factors limiting tea production, green leaf supply, farm profits and seek
solutions to the problems.
The results of this study have policy implications at both the micro- and the macro-economic
levels. If the factors that constrain tea production at the farm level are identified, suitable measures can be
drawn to address the problems within the current policy framework in the short run. For example, if farmers
are inefficient in the use of strategic inputs such as fertilizer, they may profitably reduce the amount spent onthat input or increase supervision especially where labour for tea plucking is adequate. If the monthly
producer price has a significant effect on green leaf supply, it can be adjusted upwards in the short run togive farmers incentives to supply more tea leaf etc.
Both primary data and secondary data were used in the study. Primary data were collected using
a questionnaire instrument from a randomly selected sample of 259 smallholder farmers in Kirinyaga,
Nyambene, Nandi and Nyamira Districts. Secondary data were obtained from Kenya Tea Development
Agency Limited (KTDA) and Tea Board of Kenya. The analytical procedures used were: Cobb-Douglas
production function, supply function and correlation and profit function analyses.

iThe Cobb-Douglas production function was used to determine the economic efficiency of thesample of farmers in the four districts. The data for each district was further categorized and analysed
according to tea growing agro-ecological zones (AEZs) i.e. Lower High Zone and Upper Midland Zone I.
The objective was to ascertain resource use efficiency not only for the districts but also for each agroecological zone. It was hypothesised that efficient use of inputs, particularly fertilizer, in each district surveyed
and the respective agro-ecological zones would improve productivity. The predictors of tea output/year
were: fertilizer bags used per year, number of tea bushes and the total labour used i.e. hired labour andfamilylabourinman-hoursperyear.Theresultsshowedthatfertilizerinputsignifica
<nt
0.01)
ly(Pinfluenced
tea output in the UM1 agro-ecological zone in every one of the four districts, and all the districts surveyed
except Nyamira District. The test of price efficiency indicated that the fertilizer input was efficiently used in
UM1 zone of all the districts, Nyambene and Nandi Districts. However, fertilizer use was inefficient in all the
LH zones. The lack of response to the input in the zone could be due to the high altitude leading to slow
growth rates. The results suggest a need to develop fertilizer use recommendations based on agroecologicalzones rather than the present single blanket for the whole country. Factors leading to inefficient use offertiliser in Lower Highland Zone should be further investigated so as to remove the impediments andimprove tea yields. For the whole of the sample, fertilizer significantly influenced green leaf output. However,an analysis of pricing efficiency showed that fertilizer input was inefficiently used in the smallholder sub
sector. Labour input influenced green leaf output significantly at 10 % level in Nyamira District and 5% levelin Nyamira LH zone. The analysis of price efficiency showed that labour was efficiently allocated in
Nyamira District and in particularly Nyamira LH zone. The labour input was inefficiently used in all otherDistricts and AEZs.
One of the major concerns for smallholders is product quality. The recommended plucking
standard in KTDA is two leaves and a bud, resulting in high quality tea, while some estates harvest morethan two leaves and a bud, reflecting more but lower quality of made tea per plucking round. As a result, thesmallholder teas fetch high prices in the auction markets than the estates teas. It is therefore expected that
farmers would be guided by the price factor in the output markets to make quality decisions in the allocationof strategic inputs, within the context of their variable factor price regimes and quantities of fixed factors.
Hence, they would be price-efficient in their operations. The extent of price-efficiency, which is a componentof economic efficiency, among the small-scale tea farmers needed to be determined. It was hypothesizedthat the extent of rationality in allocation of resources in the tea enterprise is relatively low. Hence, thesmallholder tea productivity has remained relatively lower than in the estate sub sector, high yielding
clones and useful agronomic recommendations extended in the smallholder sub sector notwithstanding.
“A Test of Economic Rationality Model” was used whereby, the index of economic rationality, r is the
product moment coefficient of correlation between log (total variable costs-excluding labour costs) andlog (labour-in man-days) for each tea district and region.
The results showed that the product moment coefficient of correlation, r was: - 0.647 in Kirinyaga
District, 0.651 in Nyambene District, 0.793 in Nandi District, 0.743 in Nyamira District, 0.595 in the east of
the Rift Valley region, 0.752 in west of the Rift Valley region and 0.674 for all farms surveyed. It w as notedthat the lowest value of r was 0.595 in east of the Rift Valley Region. It means that at least 59% of the variancein the logs of both inputs is due to the variation in the systematic profit-maximizing component of these
inputs. The balance of 41% is the maximum that could be occasioned not only by poor technology and/or
knowledge gaps but also by errors in the model and noise in the universe. The null hypothesis was rejectedii

in favour of the alternative hypothesis. The conclusion is that smallholder tea farmers in Kenya are quite
price efficient in tea production.
The profit function was used to determine the efficiency of resource use in the districts surveyed
and their respective tea agro-ecological zones. This method assumes that farms are relatively homogeneousin the way they use technology in the process of production. However, it is not a suitable method to use
when farm groups are relatively heterogeneous. For example, tea in Kenya is grown in the east and thewest of the Rift Valley regions. Tea farmers in these two regions face different regimes of prices of variablefactors such as fertilizer and labour for plucking tea. They also have different quantities of fixed factors
particularly land. Hence, it is imperative to determine relative efficiency between the two tea blocks. It is
assumed that these farms in the two regions behave according to a certain decision rule termed as profit
maximization. An estimation of the profit function for the tea farms in the two regions and comparison of therelative economic efficiency between them was done. “A test for relative economic efficiency “ was performed
to bring forth an overall comparison of economic efficiency for the two sets of farms. A profit function model
was fitted on 212 smallholder farms. The dependent variable was gross margin per farm per year. The
independent variables were: number of tea bushes per farm per year, cost of fertilizer (KShs.) per hectare
per year, labour wage rate (KShs.) per man-day per year in each farm and a dummy variable where D=1 forthe east and D=0 for the west of Rift Valley, respectively. The results depicted that the coefficients of thenumber of bushes, fertilizer cost/ha/year and labour wage rate/man-day were all positive and significant(P< 0.01). It had been hypothesized that there is no efficiency difference between east and west of the Rift
Valley in tea production. Hence the coefficient of the region dummy would be zero. The results rejected the
hypothesis of equal efficiency between the two regions (P< 0.10). Further more, the positive sign of thedummy variable indicates that east of the Rift Valley tea farms are more profitable, that is more economic
efficient, at all observed prices of the variable inputs given the distribution of the fixed factors of production.
It is concluded that east of the Rift Valley smallholder tea farmers are more successful in responding to theset of prices (Price efficiency) and/or have higher quantities of fixed factors of production, including
entrepreneurship (technical efficiency). Factors responsible for low efficiency in the west of the Rift Valley
should be studied and alleviated to increase tea production.
The secondary data collected from KTDA was used to determine some of the factors contributing
to the low tea productivity in the whole of the smallholder tea sub sector. Part of the data was used to fit a
production function of the smallholder tea sub sector. It was hypothesised that efficient use of inputs would
improve productivity. To measure efficiency, Cobb-Douglas production function was used. The predictorsof tea yield/hectare were: fertilizer used/hectare, number of bushes/hectare, number of growers/hectare
and the number of extension staff/hectare per district. The results showed that fertilizer input significantly (P< 0.05) influenced tea yield in 1994/95, 1995/96, 1996/97 and 1997/98. The test of pricing efficiency
indicated that the fertilizer input was inefficiently used at 1% level in the four consecutive years. The other
inputs were not significant (P< 0.05). The results suggest that fertilizer use efficiency can be increased to
improve tea production. Farmers need to be educated about the benefits arising from the application of thefertilizer input according to agronomic recommendations in order to enhance efficiency and ultimately
increase tea productivity.
The other part of the secondary data was used to estimate the supply function of the green leaf inthe smallholder tea sub sector. The major factors considered to be influencing supply of green leaf were:- the number of tea growers, price of fertilizer, monthly price of green leaf, and end of year price of green leafiii

over the years. The General Linear Model fitted the data best. The results revealed that, monthly mean
price lagged once (Pmt-1) and end year price (“bonus”) lagged five times (Pet-5) significantly (P < 0.05)
influenced the supply of green leaf. Elasticity of supply of green leaf was 32.88 for monthly average price(Pmt-1) and 6.69 for the end year price lagged five times (Pet-5). Hence green leaf supply was relatively
responsive to tea price changes. Policy intervention should therefore be focused on improving producer
prices particularly the monthly payment in order to increase the quantity of green leaf in the short run andend of year payment in the long run.

iv

TABLE OF CONTENTS
List of Tables and Figures
Abstract
Chapter 1. Introduction
1.1 Background information
1.2 Research problem statement

11
6

Chapter 2. Methodology
2.1. Data sources and collection
2.2. Research design and survey methods
2.3. Research design and sampling
2.4. Analytical procedures

12
12
13
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Chapter 3. Results and Discussion
3.1 Social-economic frequency statistics on the factors inhibiting flow of tea production
technologies to smallholders
3.2 Descriptive statistics on the level of farmers’ application of agronomic

19

Chapter 4: Conclusions and Recommendations
4.1. Conclusions and recommendations

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64

References

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53

LIST OF TABLES AND FIGURES

Table 2.1
Table 2.2
Table 3.1
Table 3.2
Table 3.3
Table 3.4
Table 3.5
Table 3.6
Table 3.7
Table 3.8
Table 3.9
Table 3.10
Table 3.11
Table 3.12
Table 3.13
Table 3.14
Table 3.15
Table 3.16
Table 3.17
Table 3.18
Table 3.19
Table 3.20
Table 3.21
Table 3.22
Table 3.23
Table 3.24
Table 3.25
Table 3.26
Table 3.27
Table 3.28
Table 3.29

Administrative districts of the KTDA, area under each district, number of growers per
district and mean production per hectare during the 1997/98 financial year
Sample size per district.
Information on the farm operations interviewed
Details on household
Objectives, experience in tea growing of tea growing and land holdings details
Mean rainfall, farm visited altitudes and zone of growing tea
Methods of land preparation by farmers (%)
Mean number of plant per farmer and recommended planting density
Sources and types of planting materials (%)
Assessment of how smallholders prepare mother bushes and/or obtain cuttings
Assessment of how smallholder tea growers prepare cuttings for nursery planting
Assessment of nursery management techniques
Assessement of field planting methods and inputs by smallholder tea growers
Bringing young tea into bearing by smallholder tea growers
Plucking arrangements in the smallholder tea farms
Timing leaf delivery to buying centres by smallholder tea farmers (%)
Assessment of problems of leaf collection and state of roads (%)
Information on pruning technology and vacancies in the field
Assessment of fertilizers and manures use on tea
Tea pests and diseases and their control by smallholder (%) tea growers
Smallholder tea growers labour use(%) and tea output
Assessment of extension services and training
Assessment of smallholder tea growers training (%) on tea production technologies
Assessment of acceptability (%) of production technologies
Views of smallholders (%) on the KTDA extension system
Views smalholders (%) on additional sources of technology and methods of transfer
Views of smallholders on green leaf payment policy
Assessment of factors contributing and method to overcome low green leaf production
and productivity (%)
Percentage responses for the various recommendations in Kirinyaga, Nyambene, Nandi
and Nyamira Districts
Testing recommendation level against farmers practice level in Kirinyaga District
Testing recommendation level against farmers practice level in Nyambene District

Table 3.30
Table 3.31
Table 3.32
Table 3.33
Table 3.34
Table 3.35
Table 3.36

Testing recommendation level against farmers practice level in Nandi District
Testing recommendation level against farmers practice level in Nyamira District
Testing recommendation level against farmers practice level for the four districts
Comparison of LH and UM1 tea yields/ha and West and East Rift regions
Gross margins for smallholder tea sub-sector in Kenya
Resource use intensities between east Rift Valley and west Rift Valley
Break-even analysis results

LIST OF FIGURES
Figure 1.1.
Figure 1.2
Figure 1.3
Figure 1.4
Figure 3.1.
Figure 3.2
Figure 3.3
Figure 3.4
Figure 3.5
Figure 3.6

Area under tea in different sectors of Kenya
Tea production by different sectors
Tea production per hectare in different sectors
Mean tea price (US$/kg) over time
Percentage of research recommendations below/above 50% response by farmers
Percent number of technological recommendations different/not different from farm
application level
Comparison of nitrogen fertilizer use between east and west of the rift valley
Labour use (man hours/ha/year) in the east and west of the Rift Valley
Average number of bushes per hectare in the east and west of the Rift Valley
Average green leaf output (kg gl/ha/year) in the east and west of the Rift Valley

1

INTRODUCTION

1.1. Background Information
Tea was first introduced in Kenya on experimental basis in 1903, but commercial tea planting started
in 1924 (Owuor 1999). The Africans or indigenous people were not allowed to grow tea at inception.
In the mid 50’s, however, experimental tea growing was introduced for Africans and after attaining
political independence in 1963, the legislation to bar Africans to grow tea was repealed. The indigenous
citizens took immediate and maximum initiatives and commenced massive tea planting programmes
and development, leading to a fast growth of the Kenya tea industry (Figure 1.1). Tea production rosefrom 18.1 thousand metric tones in 1963 to 294 thousand metric tones made tea in 1998, largely due
to expansion in the smallholder sub sector, improved productivity per unit area in the estate sub sectorof the Kenya tea industry and adoption of technical packages developed by the Tea Research
Foundation of Kenya (TRFK), and its predecessor, the Tea Research Institute of East Africa (TRIEA)(Othieno 1981, 1988; Rutto 1995). Kenya is now the leading world exporter of black tea (Anon 19642000).
Figure 1.1. Area under tea in different sectors of Kenya

80
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Estate area

Area (ha)60

KTDA area

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Agricultural industries form the main foundation of Kenyan economy creating the largest
employment opportunities and providing the largest foreign exchange earnings. Tea is a main player
in this sector and is currently the leading foreign exchange earner (Anon 1997). During 1998, Kenya

1

2

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
produced 294.2 thousand metric tones of tea earning US$ 545.418 m from the 263.4 thousand
metric tones exported, while the balance of 30.8 thousand metric tones was consumed locally andgenerated extra incomes to the growers (Anon 1964-2000). This accounted for 15% of total world tea
export and made Kenya the 3rd largest tea producer after India and China. However, due tounfavourable tea growing conditions the production reduced to 248.8 metric thousand tons (Anon
1964-2000).
The Kenya tea industry is composed of the estate sub sector and the smallholder sub sector. The
estate sub sector comprises the multinationals and local farmers whose holdings are generally over
50 ha. The farmers under the estate sub sector operate under the umbrella of the Kenya Tea Growers
Association. Generally, the estate sub sector is composed of large-scale plantations operating as
companies, which depend on hired labour and management. Estates own both tea farms andfactories, and also market their own black tea. It was estimated that in 1995 the estates sub sector of
the Kenya tea industry employed 71,000 workers (Sang 1995) supporting an average of 8 people
each. The smallholder sub sector is composed of indigenous farmers whose average area under tea
is 0.27 ha (Anon 1964-2000). The smallholder tea farmers used to grow tea under license given to the
Kenya Tea Development Authority (KTDA) upto 2000, but now operate as free entities with Kenya Tea
Development Agency Limited (KTDA) as their commercial managing agent. The farm units are
owned as family units in which the individual farmer is the risk-taking manager, with his/her family, he/she provides most of the labour and management and delivers his tea to KTDA factories which
process and market the made tea on his behalf at a fee. The smallholder tea sub sector was composedof 289,270 family units supporting about 3 million Kenyans and KTDA had staff strength of 16,000
employees as at 1995 (Cheruiyot 1995). By 2000, the number of the smallholder tea farmers had
increased to over 315,000. The tea production sector together with other sectors (marketing,warehousing, brooking, packaging, etc) of the tea industry is estimated to maintain directly or indirectly
about 4 million Kenyans.
The Kenya smallholder tea sub sector is considered the largest and one of the most successful
smallholder schemes in the world (Lamb and Muller 1982), with over 315,800 growers operating 45
factories and producing 124.1 thousand metric tones of made tea in 1999 (Anon 2000). KTDA is
acknowledged as a successful institution in two fields; smallholder rural development and public
sector enterprise both of which the Africa experience is often fraught with difficulties and disappointing
performance (Lamb & Muller 1982). Although the area under tea in smallholder sub sector has been
higher than that in the estates sub sector over the years (Figure 1.1), and total tea production by the
sub sector surpassed that of the estates in 1988 (Figure 1.2), productivity in the estates sub sector has
always been higher than in the smallholder sub sector (Figure 1.3). For example in 1998, thesmallholders had 84,266 hectares of land under tea while the estates had 33,762, but the smallholder
sub sector produced 175.6 metric tons of tea while the estates produced 118.5 metric tons in the1998 (Anon 1999). This translates to an output level of 2,075 and 3,954 kg made tea per hectare forthe smallholders and estates, respectively.
Although it had been predicted that the tea production rate would slow down with time (Schluter
1984), the growth rate has been sustained. From diverse tea cultivars, including the low yielding tea
planted before 1940’s, the estates produced a national average of 3,954 mt/ha in 1998. It is reckoned
in the sub sector that teas yielding lower than 2500 kg mt/ha per year (which are mostly old seedling

3

ATPS R ESEARCH PAPER 3 (PART II)

Figure 1.2: Tea production by different sectors

180
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Estate production

Metric tons

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KTDA production

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tea) are uneconomical to keep. The smallholders mostly have high yielding relatively young clonalteas capable of yielding much higher. Many experimental research trials tailored to improved
productivity of tea producers have been undertaken and recommendations extended to farmers.
Various fertilizer application trials have been carried out and results disseminated accordingly. Indeed,
the TRFK has released clones to the tea industry, which are yielding in excess of 4000 kilogrammes
made tea per hectare per year (kg mt/ha/year) (Othieno 1992; 1994). However, the national average
yield in the sub sector is relatively low (Figure 1.3). If the Kenya Government objective of producing
350 thousand metric tones by the year 2008 (Anon 2001) is to be attained, the major increase is
expected from the smallholder sub sector in the short run. The disparity in tea production has persisted
over the years (Figure 1.3) and the large gap between the smallholder productivity and estates is amajor source of concern, which needs to be addressed (Rutto 1996).
Smallholder sub sector presents peculiar difficulties for building and sustaining effective
development. Each smallholder is a complex unit within which it is difficult to divorce the production(business) from consumption (way of life) dimensions. The behaviour of the smallholder unit issubject to a wide range of internal and external factors that can be social, cultural, political,
technological as well as economic. It involves a large number of farmers pursuing multiple objectives
and operating in a risky and uncertain environment such that management approaches andorganizational framework in use in the estate sub sector may not be applicable. Nevertheless, thesmallholder tea sub sector has gone through several phases of successful development. In the firstphase it had outstanding record in the initial establishment of itself and of the smallholder tea industry.
This was followed by a phase of rapid expansion and diversification into processing and marketing(Etherington 1973). Phase three hopes to consolidate the earlier gains, assuring continued efficiency
and high returns when expansion is much slower and external environment uncertain (Schluter
1984). The uncertain prices and continued low prices of tea (Anon 1964-2000) (Figure 1.4) implies
that although the future may rely on tea quality, it is more promising to get more profits by improving
productivity per unit area as in the case of the commercial estates.

4

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA

Figure 1.3: Tea production per hactare in different sectors

3,000
2,500
Kg/ha

2,000
1,500
1,000

Estate productivity
KTDA productivity

500

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A problem which has received little attention but faces most researchers and development
agencies is how to improve the speed of adoption of developed technological packages even when
the technologies have immediate obvious and proven advantages. Expectations are that adoption of
improved technology would lead to increased farm productivity. However, experience shows that
immediate and uniform adoptions of innovations in agriculture are quite rare (Feder 1981). Someinnovations have been well received while other improvements have been adopted by only a verysmall group of farms. Improved productivity in the agricultural sector is more difficult when one isdealing with traditional oriented smallholders (Leonard 1977). However, farmers recognizing that
their traditional farming techniques and present level of knowledge impose a limitation on farm
enterprise seem to be on the road to success (Anthony et al 1979). In the long run, farmers canimprove productivity through adopting and using more efficient husbandry technologies which are
made available through development of sufficient technological and organizational innovativeness(Leonard 1977).
Increased agricultural productivity will only come about through revolution in the pattern andmethods of production on the individual farm units. These changes may result from adoption of newtechnologies or due to reallocation of the inputs already available at existing prices (Upton 1978) andmust occur by gradual diffusion of ideas or a radical and rapid transformation. The changes may be
the result of the decisions of the many individuals, indigenous producers or direct government
intervention. Over the past three decades the Kenyan farming community has in general understoodthe benefits of adopting new and/or innovative technologies and farming practices provided that thecost/return relationships are perceived as favourable (Anon 1989). However, a closer look at thetransfer and/or adoption of technological advancement and improved farming practices show that itis the Kenyan large-scale tea farmers/estates who have benefited from the use of these technologies(Othieno 1981; 1991b, 1992, 1994). The small-scale farmers who account for the bulk of agricultural
production have lagged behind in adoption of improved practices (Rutto 1996). Pandey and Anderson

5

ATPS R ESEARCH PAPER 3 (PART II)(1990) remark that a new technology is generally useful only if farmers adopt it. Hence an assessmentof effects at the farm level is at the heart of any evaluation process. The impact at the farm level andthe probability of adoption depend on how well the requirements of the technology fit into the particularniche in which a farmer operates.
Figure 1.4: Mean tea price (US$/kg) over time

US$/kg

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The tea industry in Kenya is facing a mysterious predicament in transfer and adoption of newtechnologies and improved practices by the small-scale tea farmers. At the moment many growers
may know as much about tea as extension workers. However the yields of smallholder tea farmers
are still well below potential probably because their techniques of production are inferior to theestates’ (Othieno 1992, 1994). Smallholder growers tea therefore need high level technicalsophistication particularly research linked questions like the response of different planting varieties todrought, optimal fertilizer use, etc. It has been observed that achievement of these need better qualified
staff, improved farmer extension worker ratio, use of computerized green leaf collection data for
identifying unproductive farmers etc. But smallholder tea productivity remains low probably due to low
adoptability of developed technological packages and under plucking in the sub sector as a result of
labour shortage (Venkata Ram 1981). Although hired labour is necessary in smallholder tea production,
cost of hired labour remains high (Etherington 1973) and this may be a contributory factor to low
productivity. Payment trends should therefore take into account inflation, and payment periods need
to be shortened as delays reduce marginal returns and quantity produced. It has been argued that
opportunity cost of labour in picking tea is determined by returns from major expanding enterprises.
However, no study has been done so far to establish if labour drops occur during months of peaklabour demand for food crops.
Gender relations also affect smallholder tea production negatively and lead to low productivity
and neglected tea fields (Sorensen and von Bulow 1990). Tensions arise as a result of conflicts overthe control of proceeds of tea sales, as the smallholder controls the labour of the household members
only to the extent that they also benefit from production. As women make up large part of the labour
force in smallholder tea schemes, it is vital to consider gender in relation to extension service, transferof skills, choice of technology, effects of subsistence crops (Lamb and Muller 1982; Sorensen and6

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
von Bulow 1990). It is not established whether women are effectively integrated in education andtraining, especially extension service (Anon 1989).
The success of policies for raising agricultural productivity in low income countries depends
upon the quality of decision making by farmers as the efficiency of farmer decision making influences
the design of development strategy in a country (Pachico 1980). If farmers are inefficient in the
management of resources, then simply improving the allocation of resources, without having todevelop new technologies, which usually are relatively expensive can raise agricultural production.
On the other hand, if productive technologies are developed, inefficient decision-making reduces thegains from these technologies, both to the farmers and society as a whole. The factors that contributeto stagnating tea productivity need to be identified and understood to facilitate appropriate decision
making at all levels.

1.2. Research Problem Statement
1.2.1 The need for improving productivity
Tea is planted in the prime lands with very good soils and climate (Othieno 1991a). Thus there is apertinent need to maximize its productivity. Although the objective of the Kenya Government is that thecountry should produce 350 thousand metric tones made tea per annum by the year 2008 (Anon
2001), suitable land for tea expansion is limited and hence this target can only be attained by improving
technical efficiency of production within the existing tea plantations. If the productivity of the smallholder
tea can only increase to about 2500 kg/ha/year, this projection can be realized without allocating
more land to tea enterprise, which when done, substitutes food crop enterprises. Factors responsible
for the low productivity in the sub sector therefore need to be determined and corrective measures
undertaken to ameliorate the situation.
Unlike most research undertakings, tea research in Kenya is highly integrated into the industry.
Both the former TRIEA and TRFK have enjoyed backward linkages with the tea farmers and forward
linkages with tea producers (farmers and factories). The tea industry funds and strengthens its research
activities through cess payments by farmers, which is administered by the Tea Board of Kenya. Thus
tea research scientists do not operate abstractly and in isolation in generating production technologies
but rather concentrate on solving real problems arising from any felt need areas within the tea
industry. The industry therefore consumes most of the technologies developed through research. As
a result of this interaction, the estate sub sector of the Kenya tea industry has undergone improvementin productivity unparalleled by any other tea producing countries (Othieno 1994). However, the adoptionof the technological packages is not very successful in the smallholder tea sub sector, probably due
to use of inappropriate policies to transfer the packages to the sub sector. For both the smallholder
and estate sub sectors of the tea industry, technological packages for improved productivity aredeveloped by the TRFK (Othieno 1981) or adopted from other tea research institutes. The information
is disseminated to the growers through seminars, symposia, courses, annual reports, journal
publications, demonstrations and advisory (extension) visits. Despite these efforts, information may
not be reaching most of the smallholder tea growers, probably leading to low average productivity.
This study examined: (i) The level of adoption of the technological packages available to the Kenya tea industry in thesmallholder tea sub sector;

ATPS R ESEARCH PAPER 3 (PART II)(ii) If the level of adoption of the available technology contributes to low productivity;(iii) If the policies used to transmit the technologies are appropriate to the smallholders.
Adoption success of the developed technologies have been assumed to be easier in the smallholder
sub sector since technical packages KTDA administers in the field and factories are presumed to be
simpler and already tested and proven in the estate sub sector of tea production. The objective of thisstudy was to investigate and explain why technological packages while widely adopted in the estate
sub sector resulting in high productivity, are not being widely adopted in smallholder sub sector. The
findings will help in providing data to create policies to improve smallholder technology adoption.
Whereas, socio-economic factors could be partly responsible, technological package transfer
problems from the researchers could also play a major role. It was therefore important to examine thelevel of technology adoption in tea production by the smallholder and identify the factors that circumvent
and/or circumscribe technological transfer and/or adoption.
1.2.2 Available technologies probably not reaching the smallholder tea farmers
Several technological packages have been developed and made available to the Kenya tea industry
throughvariousTRFKpublicationsliketTea
he Growers’ Handbook (Anon 1986), Annual Reports,
Tea Magazine, Quarterly Bulletin, various international and national journals, symposia, seminars,
courses, demonstrations and advisory visits (Rutto 1995). Summaries of these recommendations
have been given in the Tea growers’ Handbook (Anon 1986) and various recent reviews (Othieno
1988; Owuor 1995, Rutto 1995). The available technological packages for maximizing green leaf
production for the Kenya tea growers include selection of suitable tea growing areas, proper land
preparation and soil conservation methods, procedures for planting vegetatively propagated materials,
general crop husbandry methods and recommendations on necessary farm inputs. Development
and selection of planting materials has been done and high yielding clonal plants released to theindustry. Indeed yields of up to 11,995 kg made tea per hectare have been achieved from clonal tea
under estate management practice (Oyamo 1992). Suitability of planting materials to an area has
been assessed and correct planting density for maximum leaf production suggested for use. Betterways of bringing into bearing, fertilizers for young tea, and weed control methods in young tea havebeen developed to ensure proper establishment of planted tea. Correct fertilizers including rates andtime of application have been recommended and chemical methods of diagnosis for nutrientsavailability or deficiencies on mature plants through leaf and soil chemical analysis developed toadvise the growers on the correct plant nutritional status and effective types and rates of fertilizers to
use to correct possible deficiencies. Plucking methods inclusive of plucking standards, plucking
equipment, and plucking frequencies have been recommended to the growers to ensure high yields
per bush and production of high quality black tea. Pruning technologies have been developed for theindustry to ensure proper timing during the year, heights and types suitable for various geographicalregions. And after pruning, the optimal tipping height has been provided to the growers. The Kenya
tea growers have also been provided with cost effective ways of pests and diseases control based on
biological control methods.
Although an impressive range of technological packages for the improvement of green leaf
production have developed and disseminated in Kenya to tea growers, there has been no study to

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ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
assess the levels of adoption of the technologies. This is more critical in the smallholder sub sector
which relies wholly on the technical advise from the TRFK unlike the estates sub sector with a whole
range of forward interlinked technical departments and a host of advisers or consultants to follow up
and further examine whether the packages availed to the sub sector are correctly implemented.
1.2.3 Possible factors responsible for smallholder low production
Many factors could contribute to the low green leaf production in the smallholder sub sector of the
Kenya tea industry. Some of the factors could be due to lack of adoption of the above technologies forvarious reasons and/or socio-economic or cultural factors. Labour constraints or availability was oneof the reasons impeding tea production in the smallholder sub sector of the Kenya tea industry(Etherington 1973). Possibly, this problem has persisted. It is suspected that some smallholder tea
farms are in the marginal drought susceptible regions while others are in very high altitudes where
low temperatures limit tea growth. While neither of these regions maybe suitable for tea growth, theexistence of tea in them could reduce the national average of smallholder tea production and growing
tea in such areas could be uneconomical. It is not known if such areas are extensive or not andfarmers in such areas are probably better off engaging in alternative farm enterprises. Also, the prices
of Kenya tea have stagnated or have been declining in the last decade (Figure 1.4) and this could bemaking farmers to direct attention to alternative competing farm enterprises.
Although the above technical packages have been produced and made available to the growers,
it is not known if they reach the targeted users. People in smallholder farms include the smallholders,smallholders’ wife/family, and hired worker. It is important to know who in the smallholder tea sub
sector receives the technical information or training and how often each smallholder actually receives
technical advice and uses of it.
1.2.4 Objectives of the study
The general objective of the project was to “assess the level of adoption in the smallholder tea sub
sector of technological packages available to the Kenya tea industry and examine policy factors
responsible for their low adoption leading to the low productivity per unit area”. The specific objectives
were: 1.
to investigate the extent of awareness and /or knowledge of the various recommended tea
production technologies within the smallholder tea sub sector of Kenya and to identify thetechnological packages in use by small scale tea farmers;2.
to investigate the extent of adoption within the smallholder tea sub sector of Kenya of therecommended technological packages available for tea production;3.
to study the effectiveness of the present methods of technology transfer to the smallholder
tea farmers and assess if there is need to change/modify methods of transferring the available
technology to the smallholders;4.
to find out whether there are any differences in tea yields across agro-ecological zones
where technical methods of production are relatively homogeneous,6.
to establish the profitability of the tea enterprise within Kenya’s smallholder tea sub sector;
7.
to determine the break-even price for the tea enterprise in the smallholder tea sub sector of
the Kenya tea industry.

ATPS R ESEARCH PAPER 3 (PART II)
1.2.5. Hypotheses
There are three broad areas on which hypotheses testing was based. These are: a) Effectiveness of extension
It may be possible that only a few smallholder tea farmers have awareness and/or knowledge of thetechnologies identified and available for high tea productivity, hence the packages are not reaching
the smallholders effectively. Alternatively, many smallholders are using hired labour or members of
the family who do not receive the technological packages as training or extension services maybe
directed to the farm owners who do not pass the information on to the personnel doing the actual farmwork. As a result, tea yields remain low because technology transfer is not effective. The following
hypotheses were tested:i)that less than half of the smallholder tea farmers have knowledge of the tea technologies
identified;ii)
that in more than half of tea farms, training in tea and extension services are directed to thefarm owners and not to the personnel doing the real tea work;iii)
that in less than half of tea farms, the farm owners do not have adequate time to train theirworkers after attending tea production training and/or receiving advice from tea extension
staff;
iv)
that more than half of the farmers have no access to credit to purchase the recommended
inputs or where the inputs are available on credit, they do not reach the smallholder on time;b) Socio-economic and/or cultural factors.
Probably many smallholders with awareness and/or knowledge of the identified technologies havenot adopted them. The packages may be reaching the farmers but are not being implemented due
to socio-economic and/or cultural factors. The following hypotheses were tested: i)that there are some recommended technologies which are not culturally acceptable for use
in some regions;ii)that more than half of the smallholder tea farmers have not adopted the recommended
levels for each identified technology;iii)
that there is a significant difference between the recommended level and the applicationlevel on the farm for each identified technology;iv)
that tea production is a profitable farm activity;v)that there is no difference between the computed break-even price and the monthly producer
price paid by KTDAc) Suitability of land for tea growing
It is possible that some smallholder teas are planted in agro-ecological zones not suitable for tea
production. This leads to situations where there are differences in yields of tea across different agroecological zones or regions where technical methods of production are relatively homogeneous. As
a result, the average tea yields in the smallholder tea sub sector would be lower than estate sub sector
tea yields. The most suitable zone for tea in Kenya is Lower Highland Zone I (LH 1). The following
hypotheses were tested: -910

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
that there is a significant difference in tea yield between Lower Highland Zone (LH) andUpper Midland Zone I (UM 1).
1.2.6 Justification of the study
The problem this project investigated was the general failure of available technological developments
and packages to reach the rural farmers for enhanced farm productivity. This scenario translates ahigh yielding prime land with good soils and excellent climate to a low yielding uneconomical
production thus enhancing poverty in rural Kenya despite the high potential. The lack of effective
technology transfer policy and methods is therefore slowing down agro-industrial and economic
development. This makes it very necessary that factors responsible for low adoption of the existing
technologies are identified and proper policies put in place to ameliorate the situation.
The tea industry in Kenya has had an enviable economic performance and growth during the last
decade when compared with other similar industries. Although the smallholder sub sector has
accomplished high level of expansion, productivity has remained low. Comparison of the adoption
level of the technological packages between the sub sector and the estate sub sector offers excellent
opportunity for policy makers to understand the constraints smallholders face in adapting existing
technologies. In all East and Central Africa tea growing countries, the smallholder tea sub sectors areproducing very low yields compared to the estates (Owuor 1999). Results from this project therefore
have wider audience including governments and Tea Boards of the countries who could use thefindings to improve efficiency of their smallholder tea industry and/or production through the use of
appropriate policy of technological transfer.
The projected future development in Kenya is set to be in rural areas where the smallholders aremajor stakeholders (Anon 1997). Kenya’s population is expanding at a fast rate resulting in rampant
poverty and unemployment. Increase in tea production in the smallholder sub sector would therefore
create job opportunities in the rural areas, promote more rural agro-industrialization, improve thesocio-economic development and ultimately reduce poverty.
Tea is the leading foreign exchange earner for Kenya (Anon 1997). Improvement of the smallholder
sub sector will play a major role in sustaining the high in flow of hard currency that the country needs
for industrial development and to sustain servicing of high foreign debts. This project investigatedways of improving the productivity of smallholder tea in Kenya leading to more inflow of foreign
currency earnings. The study would help in developing appropriate methods to alleviate the possible
technological transfer problems to the smallholder tea sub sector which would in turn increase theproductivity of the smallholder tea production thus enhancing the profitability to the growers. This
would help change the policy of technological transfer to the smallholder enterprises and help boththe KTDA and TRFK to identify weak points in the presently used technological transfer mechanisms.
The research is also meant to make it possible to introduce a better technological transfer mechanism
and adoption methodology to smallholder farmers in general. Many lessons could be drawn for othersmallholder enterprises in Africa and this would hopefully have positive effects on both the policy
makers and researchers in Africa.

ATPS R ESEARCH PAPER 3 (PART II)
1.2.7 Organisation of the Report
The subsequent chapters in this report are organised as follows. Chapter two, methodology, describes
the relevant conceptual framework and the analytical procedures adopted. Results and discussions
are presented in chapter three in two parts. Part one presents the frequency statistics results for thesocio-economic characteristics of the extension staff in the study areas, while part two presents thedescriptive statistics results for smallholder tea growers in the study area. It summarises the socioeconomic characteristics of the farm survey respondents i.e. information on the farm operator, adoptionof tea technologies, use of labour in tea enterprise. It also presents the tea enterprise analysis.
Chapter four summarises the conclusions and policy implications of this study.

11

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METHODOLOGY

2.1 Data Sources and Collection
The areas the smallholder tea cover are in regions east and west of the Rift Valley on the foothills of
Abadares and Kenya mountains in the east of the Rift Valley (in Nyeri, Murang’a, Kiambu, Kirinyaga
Districts (in Central Province), Embu, Meru, Nyambene, Tharaka/Nithi Districts (in Eastern Province))and Mau, Nandi, Kisii and Kakamega Hills in the West of the Rift Valley (covering Kericho, Bomet,
Bureti, Nandi, Trans Nzoia, Keiyo, Marakwet, Trans Nzoia, Nakuru, and Narok Districts (in Rift Valley
Province), Nyamira, Kisii, Gucha, Trans Mara and Rachuonyo Districts (in Nyanza Province),
Kakamega, Vihiga, Butere/Mumias and Bungoma Districts (in Western Province). For ease ofadministration, KTDA has subdivided the districts into East covering Central and Eastern Provinces
and West of the Rift Valley covering Rift Valley, Nyanza and Western Provinces. Some of the districts
have been further sub divided to give the above districts, however, during the study period, theadministrative boundaries for KTDA was as outlined in table 2.1. The rainfall pattern in the East of Rift
Valley is unimodal with main rains in September to December, but in the West of the Rift Valley, rainfall
is bimodal with rains in long rains in April to June and short rains in September to December. The
framers in the tea growing areas practised mixed farming of maize, beans, and dairy.
Mainly the Kikuyu, Embu and Meru inhabit the areas of tea under KTDA in the East of the Rift
Valley and Kalenjin, Kisii and Luhya in the West of the Rift Valley. This study covered four districts. Two
districts from the East namely Kirinyaga and Nyambene to represent district with high and low mean
productivity per unit area respectively. These districts also covered different cultures i.e. Kikuyu and
Meru cultures respectively. Nyamira and Nandi districts covered in the West of the Rift Valley torepresent high and low productivity respectively among Kisii and Kalenjin cultures respectively.
This study adopted an exploratory form of research design and data collection was done in
July, August, September, and November 1999 for Kirinyaga, Nyambene, Nandi and Nyamira, respectively.
Cross–sectional data was obtained from a sample of smallholder tea producers in four districts
representing high tea producers and low tea producers in Kenya. These districts were Kirinyaga andNyamira representing high yielding districts and Nyambene and Nandi representing low yielding
districts. A questionnaire instrument targeted to the farmers was developed, pre-tested, adjusted andthen administered to the farmers. The questionnaire sought to obtain information concerning adoption
and application levels of the various recommended tea technologies i.e. site selection, land
preparation, nursery establishment, field management, use of chemical inputs, labour use andextension services.
The altitude of each farm visited was recorded using Thommen Classic altimeter plus
barometer while rainfall data was received from the records of the nearest factories.

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ATPS R ESEARCH PAPER 3 (PART II)
Table 2.1: Administrative districts of the KTDA, area under each district, number of growers per
district and mean production per hectare* during the 1997/98 financial year**
East of Rift
District
KiambuMurang’a II
Murang’a III
Nyeri
Kirinyaga
Embu
Tharaka/Nithi
Meru
NyambeneWest of Rift
KerichoBomet
Nyamira
Kisii
Nandi
KitaleVihigaKakamega
Olenguruone
Total

Area under tea (Ha)No. of growers

Mean production kg

6,809
5,836
5,326
6,314
5,480
3,447
1,380
4,378
3,300

No. of Extension staff
mt/ha)
48
37
35
46
27
24
13
28
12

18,76919,673
21,31824,271
17,112
12,657
5,491
14,96813,070

2,517
3,163
2,899
2,366
3,217
2,317
2,694
1,335
1,861

8,145
6,747
9,500
7,297
2,490
736
1,698
511
1,013
80,407

25
43
41
48
20
7
16
8
1
479

19,558
21,10247,50046,154
6,820
1,012
9,449
2,408
1,346
302,698

1,534
1,775
2,045
1,517
1,028
810
1,284
1,018
404
2,101

*Based on total green leaf production and using a factor of 0.225 (Anon 1986) to convert green leaf into made tea. **Source KTDA
Statistical data; +Tea officers plus assistant tea officers and technical assistants. ++This figure excludes Nyayo Tea Zones
Development Corporation areas.

2.2 Research Design and Survey Methods
In order to better understand the mode of technological package transfer within the smallholder tea
sub sector, proper classification of all institutions involved was made. Grouping the institutions interms of the roles they play in technology transfer gave an impetus for desired analysis. Also, theclassification of the technologies for tea production assisted in the quantitative technical and economic
description and interpretation of the levels of adoption and the existing technological constraints. In
terms of design, the study had both quantitative and qualitative components. The empirical data
generated in various tea farms was quantitatively analysed and compared with each other between
low, and high yielding districts for the purpose of pin-pointing significant differences and/or similarities
that existed and this was used as a basis for recommending improvements to adoption of various
technologies to smallholders.
Diagnostic activities included a set of questionnaire. A formal survey established actual baseline
data for economic relationships. The questionnaire was directed to a representative sample ofsmallholders. It was structured with both coded and open-ended expected responses. Verbal
interviews were conducted for the individual farmer, by the investigating scientists with the help of theKTDA personnel. The information sought was related to the knowledge of existing technologicalpackages for green leaf production, methods and effectiveness of the methods being used todisseminate the information to growers, possible factors causing poor yields in the smallholder sub
sector and suggested ways of overcoming them. Training programmes by KTDA for the farmers were14

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
also assessed in relation to the targeted users, i.e. whether the person involved in day to day operation
were being trained or if the smallholders were trained to train their hired workers or members of thefamily.

2.3 Research Design and Sampling
The smallholder tea growing districts had a total of 84,502 tea growers (Table 2.1). If 50 percent
figure is considered to give the highest sample acceptable and assuming 50% of the growers were
not receiving adequate technological information for high tea production, the desired sample size
(Yamane 1973) was computed as follows:n = z2pqN/(z2pq + Ne2)
(Eq. 1)
Where z = the standard deviate
p = the proportion of the population with the desired characteristic
q=1-p
N = Number of growers in the districts of studye = desired degree of accuracy.
In this study, p was estimated at 50%, z = 1.96 for 95% confidence level and a degree of accuracy of
0.05.
Therefore, substituting in the above equationn = 1,962x0.5x0.5x84502/(1.962x0.5x0.5 + 84502x0.052) = 382(Eq. 2)A slightly high figure of 450 was proposed to be taken to allow for loss of cases. Thus, it wasenvisaged that such a sample size adequately represented the study population and reliable inferences
could be drawn from it. However, at the start of the study, a budget constraint was occasioned by
reduction of the expected research funds by a half. As a result, the expected sample size was reduced
accordingly. When the survey work commenced, KTDA and TRFK decided to lend a hand in terms oftransportation and personnel. Consequently, the sample size was rationalised and adjusted upwards
towards achieving the targeted size. The achieved sample size represented the population adequately
because it was within the large sample size range i.e. above 30 (Lapin 1987), which is approximatedby the normal distribution.
Proportionate sampling was done per district as follows:n = nKirinyaga + nNyambene + nNyamira + nNandi
N = NKirinyaga + NNyambene + NNyamira + NNandi
For every district the sample size wasni = Nixn/N ................ (Eq. 3)
i.e. ni = Ni x 450/84502 as presented in Table 2.2 below.
Where ni was the district sample size and Ni was the total number of farmers in the district.
Table 2.2: Sample size per district.
Target size
Expected size after budget reduction by half
Achieved size After KTDA/TRFK chipped in
Reference population

Kirinyaga
90
45
70
17,112

Nyambene
72
36
44
13,070

Nandi
42
33
39
6,820

Nyamira246
90
106
47,500

Total
450
204
259
84,502

ATPS R ESEARCH PAPER 3 (PART II)
In all tea growing districts, tea factories keep growers records. Each factory is served by a numberof buying centres where farmers deliver tea leaf. The factories keep systematic records for every
buying centre within its jurisdiction. The sampling frame therefore consisted of the factories, buying
centres and the individual farmers. The number of buying centres in each factory was first ascertained.
Then the total number of the buying centres was obtained by summing them in each district. A
number of buying centres were randomly selected proportionately in each factory with reference tothe sample size in each district. From every selected buying centre, one grower was randomly
selected to represent it. Thus, multi-stage random sampling was used to appropriate farmers into thesample size in every district. However, in Nandi District, there was only one tea factory (Chebut) withan expansive tea leaf delivery catchment. As a result, the selection was based on divisions, buying
centres and individual growers and had the same consistency as the rest of the districts. Although thesampling was random, growers were covered from all the tea growing agro ecological zones in thevarious districts.
The interviews of the farmers were focused on the knowledge, adoption and use of the available
technologies in their farms, problems encountered in the adoption of the technologies, factors not
related to tea production but causing reduction in tea productivity and possible suggestions of improving
productivity in their farms. Other factors assessed included provision of extension services, adequacyof farm in-puts from the KTDA, supply of farm in-puts on time and application level by the farmers.

2.4 Analytical Procedures
Three procedures were used to assess the awareness and/or the knowledge of the recommended
technologies, the level of adoption by the smallholders and the factors leading to low adoption,differences in tea yields across agro-ecological zones, profitability of the tea enterprise and the breakeven price. These procedures were: frequency and descriptive statistics, comparison of means andgross margin analysis
2.4.1. Frequency and Descriptive Statistics
This method involves the use of frequency distributions, calculating means, percentages andtabulations of responses for qualitative and quantitative cross sectional data obtained from tea farmers.
The frequency distributions and the percentages obtained were used for testing most of the generalhypotheses related to qualitative data.
Descriptive statistics involved computing frequency distributions, calculating means andtabulations of responses for quantitative cross sectional data obtained from tea farmers. It was used
to analyse the level of technology adoption for each identified agronomic recommendation. It analysedsocio-economic and cultural factors such as: awareness and/or knowledge of the recommended
technologies, the level of technology adoption, methods used in the extension mechanism to transfer
information to tea farmers, factors inhibiting the flow of technological information, whether transfer of
information through “local barazas” reaches the farm workers, availability of credit to farmers, etc.
The mean of each recommendation use level was computed and compared with the research
recommendation level. The test statistic used for comparison was specified as: t = (m -µ )/[s/(n - 1)1/2 ](Eq.4)

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ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
where: µ =Research recommendation level;m = Farm application level;s = Standard Deviation for the samples;n = Farmers sample size.
The computed t statistic was then compared with critical t to find out whether there was a significant
difference between the farm application level and the agronomic recommendation level. The results
were then used to test the hypothesis that there is a significant difference between the research
recommended level and the farm application level for each identified recommendation. The testing
was done for quantifiable recommendations only. These were as follows: - Soil pH, land preparation,nursery establishment, fertilizer rates, etc. The testing was done on district-by-district basis. The null
hypothesis tested was that there was no difference between the research recommendation level andthe farm application level i.e.
Ho :m = µ.
(Eq 5a)This was tested against the alternative hypothesis that there was a difference between the research
recommendation level and the farm application level. i.e.
HA : m ¹ µ...
(Eq 5b)
The testing for significance was done for each quantifiable recommendation and the computed t value was compared with the critical t value at 5 per cent level of two-tailed test of t-distribution. The
null hypothesis was accepted if t < tc or t > tc where t was negative. This would imply that m- µ.= 0 i.e.
m.= µ. This would then mean that the farmers’ application level and the recommendation level are
not different. The null hypothesis could be rejected in favour of the alternative hypothesis if t > tc or t <tc where t was negative. This would imply that m - µ ¹ 0, that is, m ¹ µ. This would mean that the farm
application level of the recommendation and the research recommendation level are significantly
different. Hence the extension knowledge reaching the farmer would be deemed to be inaccurate.
Analysis of socio-economic characteristics of technology adoption helped in diagnosing farm businessweaknesses and strengths. On the strength of these results, recommendations were based on facts
and figures.
2.4.2. Mean Comparison
This method involves the calculation of means for quantitative data in descriptive statistics. The
means were subjected to various statistical methods in order to determine: differences in population
characteristics, variation or even the effect of one variable on another. This method was used toanalyse the differences between research recommendation levels and the farm application level ofthe technologies, yield differentials across agro-ecological zones and to establish whether the use of
the available technologies had an impact on tea production among smallholders. Two statisticalmethods were used. The first one tested the deviation of the application level of the farmers for eachtechnology from the research recommendation level. The test statistic was specified below as: t = (m - l)/[s/(n - 1)1/2](Eq. 6)
Where:
m=sample mean knowledge or application level of therecommended technology;

ATPS R ESEARCH PAPER 3 (PART II)l=s=

Research recommendation level;
standard deviation of knowledge level or application level of thetechnology;n=sample size for tea farmers.
The second method tested whether there were any differences between tea yields in
different agro-ecological zones. The t - statistic was used to test statistical difference in mean
yields using equation 7 below.
t = (X- - Xj-)/ [S21/n1 + S2j/nj]1/2 ....... (Eq. 7)
Where:
X- = mean tea yield per hectare in Lower Highland (LH) zone;
Xj- = mean tea yield in Upper Highland (UH) or Upper Midland (UM)zone;
S21 = variance of tea yield in LH;
S2j = variance of tea yield in UH or UM zone;
n1 = sub-sample size of tea farmers in LH zone;
nj =sub-sample size of tea farmers in UH or UM zone;
The means of yields computed for the agro-ecological zones were compared to find out whether
there were any differences. Thus, the equation was used to compare mean output in kg/ha between
Lower Highland zone and Upper Mid-land zone and between west and east of the Rift Valley. The
hypothesis tested aimed at finding out whether the Upper Midland zone contributed to low tea
productivity. The hypothesis was tested for statistical significance for every UM1 in the districts using
LH as control zone for tea production. The null hypothesis was that there is no difference in tea yields
per hectare between UM1 and LH zones. i.e.
Ho: mI = mj
(Eq.8a)This was tested against the alternative hypothesis that there is a difference between tea yields per
hectare in the UM1 and LH zones i.e.
HA: mI ¹ mj
(Eq. 8b)
The computed t value was then compared with the critical t-value. The null hypothesis was
accepted or rejected depending on whether the computed “t” value was less or greater than thecritical “t” value. If Ho was accepted, that meant that there is no difference in tea yields between UM1
and LH on the other hand. Its rejection indicated that there is a difference between tea yields in UM1
and LH. The same hypothesis was used to find out whether there is any difference in tea yields
between east and west of the Rift Valley.
2.4.3. Gross Margin Analysis
Gross margin (GM) analysis was used to analyse the viability of the tea enterprise and to determine its
profitability. Break-even price analysis was also undertaken using data on gross margin analysis.
Gross margins are widely used in farm planning. They can be used to prepare partial budgets for
marginal changes in the farm programs, or whole farm budgets for major changes in farm programs(Sturrock, 1971). Gross margin involves computing total variable costs (TVC) and total output value(TOV) associated with an enterprise. The difference between total output value and total variable
costs is the gross margin for that enterprise. This in essence, is the return to fixed costs, management

17

18

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
and risk. A number of efficiency measures can be computed from the enterprise analysis and comparedwith the standards to diagnose areas of potential improvement. Possible efficiency measures include:- a) gross margin per unit of enterprise, b) gross margin per unit of a scarce resource and c) grossmargin per unit of investment. In this study, gross margin was done for purposes (a) and (b). The
results of this analysis were used to determine whether tea is a profitable farm activity.
The break-even point is that scale of activity where income equals total costs. A break-even priceis the price necessary to cover the cost of production at a certain yield level (Ronald, 1986). Breakeven price for green leaf was calculated on the basis of total direct costs of production. These are theshort run costs, which were directly applicable and accrued specifically to tea enterprise. There has
been a general complaint by the smallholder tea farmers that the monthly payment of green leaf is too
low to intensify and ultimately increase tea production. In this sub-section, analysis to gauge theprofitability of the tea enterprise and the break-even price of the green leaf in the smallholder tea
sector were reported. Gross margin involves computing total variable costs (TVC) and total output
value (TOV) associated with an enterprise. The difference between total output value and total
variable costs is the gross margin for that enterprise. The break-even point is that scale of activity
where income equals total costs. A break-even price is the price necessary to cover the cost of
production at a certain yield level (Ronald 1986). Break-even price for green leaf was calculated on
the basis of total direct costs of production. These were the short run costs, which were directly
applicable and accrued specifically to tea enterprise. The results of the analysis were therefore used
to test the hypothesis that the computed break-even price was not different from the monthly paymentof KShs. 6.00 per kg in 1998/99 (during the study). The alternative hypothesis was that the computedmonthly break-even price was different from the monthly payment. The null hypothesis could be
accepted if the computed t was less than the critical t (t < tc). The alternative hypothesis could be
accepted if t > tc. The equation used to compute t was: - t = [P-P0 ]/[s/(n-1)1/2] where P is the sample
mean price; P0 is the current monthly payment; s is the sample standard deviation and n is the
sample size. Table 4.7 gives a summary of the results of gross margin analysis based on the 1999/
2000 production systems in the smallholder sub-sector. The prices used to compute revenue andcosts were those that prevailed in the tea industry during the 1998/99 financial year. The calculationsof tea output values, variable costs, interest and total variable costs (TVC) are means of individual
variables, and were not derived from the means of the related variables. For, example, tea output
value was not a product of mean of tea output and mean of producer price, but was a mean of tea
output value variable. The interest was not simply 20% of the mean of variable costs but a mean of
20% of variable costs variable, etc.

3

RESULTS AND DISCUSSION

3.1 Socio-economic Frequency Statistics on the Factors Inhibiting Flow of Tea
Production Technologies to Smallholders
3.1.1. Introduction
All Kenya tea growers pay service cess to the Tea Board of Kenya, partly for the development of tea
industry through research. The TRFK does the research on behalf of the Tea Board. Tea production
technologies produced by the TRFK are therefore intended for and are the properties of the Kenya
tea growers. The produced technologies should reach the tea growers to help them increase tea
productivity and/or production and reduce costs of production. At present, the smallholder tea sub
sector produces over 60% of Kenya tea (Anon 2000). This implies that over 60% of cess money,
generating tea production technologies is contributed by the smallholders. However, productivity of
tea in the smallholder sub sector has remained low compared to what is achieved in the estate sub
sector (See Figure 1.3). This low productivity is possibly due to lack of adequate tea production
technologies reaching the individual farmers or that though available, the technologies are not being
adopted by the farmers in the sub sector. The results of the farmers’ responses to inquiry of theirknowledge, access to and factors impeding access to tea production technologies are reported.
3.1.2 Information on the farm operators.
The number of the farmers in the district surveyed, those interviewed and information on thoseinterviewed are presented in Table 3.1. Most of the farmers interviewed were the owners of the farms.
It was hoped when the smallholder tea sub sector was being established that the family units would
manage their farms (M’Imwere 1997, 1999). This was indeed the case as when the owner was not
managing the farm, a son or daughter or relative did the management. Most of the decisions on thefarms were made by the key members of the family unit (husband and wife). Unlike what used to beon tea previously, when females (wives) never made important decisions on tea production (Sorensen
and von Bulow 1990), the situation has changed. Indeed in many farms, husbands and wives mademost of the decisions jointly. Where this was not done, about equal percentage of females as males
were individually managing the enterprises (Table 3.1).
The mean age of the smallholder farmers interviewed was about 45 years in all the districts.
Although this suggested that most of the farms are managed by mature personnel, there was ageneral complaint from the children of the farmers that the parents are unwilling to subdivide to thempieces of the tea holdings, despite their doing most of the work on the farms. This may be a problem
in tea production as it creates less incentive for the youngsters to work on tea farms since their work
is paid in kind not by cash. As unemployment increases in Kenya, rural industrialisation is being

19

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ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
projected as possible way of overcoming the problem (Anon 1997), smallholder tea production is
likely to be a key player in the rural industrialisation process and there is need to develop a proper
rewarding system for the family labour. Most farmers interviewed indicated their unwillingness to
subdivide the farms in fear of the possibilities of the youngsters selling off their portions if they getalternatives ways of making a living. A proper study should be done to come out with clear policy on
how to deal with this problem.
The majority of the smallholders had either not gone to school or had only reached primary levelof education. Indeed the mean period spent in school ranged from 5 years in Nyambene district to 8
years in Nandi district. The low formal education level of most farmers (Table 3.1) implied that
passing technical information through bulletins is unlikely to help technology diffusion in thesmallholders tea sub sector. Consequently, it is necessary that the technologies are disseminated tothe smallholder farmers through on farm courses based on practical demonstrations in which thefarmers have contact with the trainers. However, this situation is likely to change with time as the oldfarmers are gradually being replaced by younger and better-educated farmers. Both bulletins anddemonstrations should therefore be used for groups, which need them.
Table 3.1: Information on the farm operators interviewed
Kirinyaga

Nyambene

Nandi

NyamiraRegistered farmers
Number interviewed

17,112
70

13,070
44

6,820
40

47,500106

Are you the owner of the farm

89
10
1
3
1
4
3
4
20
23
43
1
13
0
47.97
24
53
19
4
4.9

61
34
5
0
0
18
2
18
23
18
46
2
9
2
44.53
36
48
16
0
8

69
31
0
0
0
15
5
10
28
18
46
0
8
0
46
15
49
28
8
6.89

77
23
0
1
2
8
1
10
13
25
50
1
11
0
48.02
25
40
33
2

Yes
No
Missing
If no, who are you on the farm?
Employed Mgr‘’ relative
Son
DaughterOthersWho make decision on the farm?
HusbandWife
husband & wife
Employed Mgr
OthersMissing
Mean age of farmers
Age (years)
What is your education level?
unschooled
Primary level
Secondary ‘’College
How many years did you spend in school? 6

The mean number of people living in each household ranged from 6 to 9 (Table 3.2). Most ofthese people were members of the core family (parents and children). Large percentage of the family
members lived permanently on the farms and thus derived their livelihood from the tea enterprise.
Except in Nandi district, most smallholders did not have any occupation apart from farming. As had
been intended (M’Imwere 1997, 1999), the smallholder tea enterprises help the immediate family
members make a living. This demonstrates the need to put in place policies that ensure the smallholder
tea production is sustainable. A collapse of the sub sector can lead to high unemployment and loss of

21

ATPS R ESEARCH PAPER 3 (PART II)
livelihood to many Kenyans. Indeed, as at 1995 (Cheruiyot 1995), the smallholder tea sub sector, wascomposed of 289,270 family units supporting about 3 million Kenyans at farm level, over 16,000
KTDA employees plus their families and other sectors (marketing, warehousing, brooking, packaging,etc) of the tea industry. It was estimated to maintain directly or indirectly about 4 million Kenyans. This
number has gone up and by 1999 there were over 315,000 smallholder tea farmers (KTDA Statistics).
It is hoped the other tea sub sectors also increased with tea production since additional new factories
have been built and old ones expanded to cope with additional production.
A reasonable number of the smallholder tea farmers had other jobs in addition to tea growing. If
the sub sector does not do well, a large number of the farmers will continue to seek other methods ofmaking a living and may grow tea as a part time occupation or may abandon it altogether. Since thesmallholder labour is based on family labour, this will further reduce production and productivity in the
sub sector. Clear Government and KTDA policies are crucial to keep the farmers well remunerated
to reduce incentives for moving on to other enterprises. There was no clear relationship between
smallholders having other jobs and tea productivity in all districts.
Table 3.2: Details on households
Mean number in house holdHow many are
Do all of them (%) live on thefarm consistently?
If no, how many have lived
consistently on the farmduring last year?
Do you (%) have any otheroccupation a part from farming?

Children
Parents
OthersYes
No
On the farm
Outside farm

Kirinyaga
6
4
2
0
72
27
5
1

Nyambene
8
5
2
1
84
16
5
5

Nandi
9
5
2
2
77
23
7
2

Nyamira
7.91
5
2
1
77
23
6
3

Yes
No

33
66

32
68

44
56

26
74

The average tea growing experience of the smallholders was high and ranged from 18 to 23
years (Table 3.3). There was no major difference in age between smallholders in the east and westof the Rift Valley or between the districts with low or high productivity per unit area. Again most of thesmallholders grew tea as a means of living and their main objective was to maximise profits or bothprofits and production (yields) (Table 3.3). This implies that it is in the interest of the smallholder tea
farmers to increase production and/or productivity while reducing costs of production to enhance
the profitability of the enterprise. Farmers would therefore benefit from technologies for achieving
these targets.
The sizes of the total areas of land owned by the smallholders varied considerably. Generally thesmallholders in the east of the Rift Valley owned less land than those in the west of the Rift Valley(Table 3.3). Again in each side of the valley, there was higher productivity per bush where farmers
had smaller pieces of total land areas. This probably was due to absence of competing farm
enterprises, as the available land was too small to support other farm activities. The land pressure is
forcing the smallholders in these areas to concentrate on tea production. This difference was also
noted between east and west of the Rift Valley. Tea production patterns followed the land pressure
pattern such that the lower land holdings in the east dictated higher production per unit area compared22

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
to west of the Rift Valley where mean land holdings were higher. Again since the number of people
living in individual households were about the same in west and east of the Rift Valley (Table 3.2), it
can also be argued that there may be adequate labour to maintain tea in the east of the Rift Valley
while the farms in the west were too large for the family units. They are therefore unable to remove
the entire crop or to manage the farms effectively. However, this needs confirmation in a separate
study.
In Kirinyaga and Nyamira districts, high percentage of the smallholder tea growers did not haveany other farms except where the tea was planted (Table 3.3). These were also the districts withhighest productivity per bush in the east and west of the Rift Valley, respectively. On the other handalmost half of the smallholders in Nandi and Nyambene districts had other farms apart from the tea
gardens. These districts had the lowest tea productivity per bush west and the east of the Rift Valley
respectively. Possibly the smallholder tea farmers in these two districts were spending part of theirtime on other non-tea enterprises in these other farms, consequently lowering tea productivity due todivided loyalties. Indeed, it was noted that most of the smallholder tea growers spent a lot of time on“miraa’ (Kat) than tea in Nyambene, while in Nandi most growers spent a lot of time on maize
production and dairy farming. It is likely that these competing farm activities contributed largely to the
low tea productivities in these districts. Detailed socio-economic study is necessary to evaluate theeconomic advantages of these individual crops so that farmers are encouraged to concentrate on
crops or farm undertakings giving best returns.
In the east of the Rift Valley, despite the farmers in Nyambene district owning more land thanfarmers in Kirinyaga district, less land per farmer was dedicated to tea growing (Table 3.3). Thismight have been due to the farmers in Nyambene district having an alternative crop, (Khat) which
they perceive to give better returns than tea. A proper study is necessary to establish if this perception
is valid. In the west of the Rift Valley, on the average the farmers dedicated almost the same percentageof their land units to tea growing. However, because of the large land units per farmer in Nandi district
compared to Nyamira district the smallholder growers had more land under tea.
Table 3.3: Objectives, experience in tea growing of tea growing and land holdings details
Mean length (years) of tea growing
Why do you grow tea (%)

Main objective of growingtea (%)

Size of whole farm (Ha)Own other farm (%)
If yes how many (ha)Total land owned (ha)Area under tea (ha)Land area (%) under tea

As businessNo employment
As way of life
As inheritance
Maximise yield
Maximise profit
Max. yield & profit
OthersMissing
1.2
Yes
No
Missing
1.5
1.5
0.51
40.7

Kirinyaga
23
87
3
3
7
3
36
50
11
0
1.7477
23
77
0
1.066
2.3
0.30
23.95

Nyambene
23.2
77
9
5
9
7
37
52
2
2
4.970
56
43
1
3.9
7.0
0.73
20

Nandi
18
87
3
3
8
8
41
49
0
2
2.03
46
51
3
1.15
2.27
.33
19.95

Nyamira
21.79
91
3
2
5
4
28
66
1
0
29
75
1

ATPS R ESEARCH PAPER 3 (PART II)
3.1.3. Awareness and application of recommended tea production technologies
3.1.3.1. Soil characteristics
Tea requires specific soil characteristics to grow and produce economic yields (Othieno 1991a).
These include soil depth, slope, pH, texture and free drainage. The majority of the smallholders
interviewed did not know these requirements. The lack of knowledge was higher in the west (94 and
97% in Nandi and Nyamira districts, respectively) than in the east (73 and 84% in Kirinyaga andNyambene districts, respectively) of the Rift Valley. When individual soil characteristics were examined,majority of the farmers did not know the slopes of their tea farms, and recommended soil depths forplanting tea. All the smallholders interviewed did not know the soil texture or pH of their tea farms. Thiswas possibly because most smallholder tea growers plant tea after the districts have been surveyed
and declared tea-growing zones. Farmers therefore grow tea because their lands happen to bewithin the gazetted areas. There is little incentive for the individual farmers to know these requirements.
However, these requirements were not even known to the extension staff (Owuor et al 2001). The
knowledge might not have therefore been available to the individual tea farmers.
Although an area may be gazetted as tea growing zone, there shall always be pockets within thezones not suitable for growing tea. Such areas may be unsuitable due to poor soil texture, high pH,
water logging, very steep slopes, etc. It is important that knowledge on how to avoid bad areas during
tea planting is made available to the tea growers. Since smallholder areas under tea are relatively
small, averaging just about 0.27 hectare per farmer (M’Imwere 1997, 1999), poor choice of a site canlead to total crop failure or very slow and expensive tea establishment. Both are waste of resources tothe smallholders and should be avoided.
Most smallholder tea growers were keen to know how they could learn about the soil requirementsof the tea plant, but did not know how this can be done. This demonstrates the lack of effective
extension system in the sub sector. It is important the smallholders are educated on the sources oftechnical information available to them as this can enhance their tea production. Both the TRFK and
KTDA extension services need to address these problems.
The areas where smallholder teas are growing were assessed and established to have been
receiving adequate rainfall in most years. The altitude range in which tea was growing was within thelimits. All farmers interviewed had farms in Upper Midland zone I and Lower Highland zone (Table
3.4). These areas had been surveyed and are recommended tea-growing areas. On the average
Nyambene district received more rainfall than the other districts. Kirinyaga and Nandi districts received
about the same amount of rainfall, but the farms surveyed in Nandi district had higher altitude thanfarms surveyed in Kirinyaga district. The rainfall in Nyamira district was higher than that of Kirinyaga
district and Nandi districts, but lower than that of Nyambene, while the mean altitudes of the farms
visited in Nyamira and Nandi districts were similar. It is noted that the rainfall received, altitude or zoneof the tea growing could not explain the tea productivity patterns. These results are surprising because
tea yields decrease with rise in altitude. Indeed, Squire et al (1993) and Obaga et al (1988) had
reported yield decrease of 200-300 kg made tea per ha with a rise in altitude of 100 m. Total rainfall
per se is not as useful in tea production as its distribution. For very good tea production, there should
be a minimum of 120 to 150 mm rainfall per month (Othieno 1991, 1994). However, rainfall distribution
data was not obtained in this study.

23

24

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
Table 3.4: Mean rainfall, farm visited altitudes and zone of growing tea
Average rainfall in the area (mm)Mean altitude (m.a.m.s.l.)
Location of farm
Upper Highland zone (UH)
Lower Highland zone (LH)
Upper Midland zone (UM)Kirinyaga

Nyambene

Nandi

Nyamira1654.29
1750
0
44
56

2514
1652
2
30
68

1630.77
1915.63051
49

1804.2453
1923.630
68
32

3.1.3.2. Land preparation
In most smallholder areas, land preparation was done by the most commonly available and used
implements. A Bulldozer was never used probably because of the high costs involved or small sizesof the holdings. The majority of the farmers in the east of the Rift Valley used combination of pangas,
jembes and rakes (Table 3.5). These seemed to be what are commonly used in the areas due toboth sizes of the land holdings and the land terrains. Although these implements were also used byreasonable percentage of smallholders in Nyamira and Nandi districts, it was noted that a sizeable
percentage prepared their lands using tractors, especially in Nandi where the land holdings arelarge (Table 3.5). It is necessary that mechanical machinery suitable for use in smallholder landholdings that are small and most of the times with very steep slopes be introduced in Kenya agricultural
systems. These will alleviate the present difficulty of using pangas, jembes and rakes to cultivate
lands.
In all areas, ripping was done to a depth of about 0.2 m and most farmers removed all roots fromthe prepared lands. The ripping depth was slightly deeper in Nandi district because many farmers
used tractors to prepare their lands. This is important since roots left in the soil are the source of
inoculum for Armillaria root rot infection. Despite the ripping, however, in most farms young plants
dried up, possibly due to poor plant methods and/or planting into bad weather. Most farmers did notknow the causes of death for the young tea plants.
In most farms the lands were cleared then ploughed during preparation before planting. However
in some areas this was not done. Indeed this might not have been necessary as in many smallholder
tea farms, tea growing was started in areas that were previously used to grow food crops (Othieno1994). For those who ploughed, the lands were ploughed more times in the west than in the east of
the Rift Valley (Table 3.5). Most of the farmers then harrowed their fields. Since the harrowing
machines are not suitable for very small farms, most farmers did subsequent ploughing after the firstas a way of harrowing. Harrowing was done more times in the east than west of the Rift Valley. Whenharrowing and ploughing were considered as part of one operation, there was no difference in thenumber the operations were done east and west of the Rift Valley.
In many farms after ploughing and harrowing, the lands were surveyed, and contour terraced toconserve the soil and water. In some farms, however, this was not done. Most farmers planted tea after
this operation. One aspect noted under land preparation was that there were many questions thefarmers did not respond to. This might have been due to the farmers not knowing the history of theirfarms There are many farmers who had inherited or bought the tea farms and were not involved in theoriginal planting exercise. These groups of farmers are unlikely to know how their lands were preparedsince smallholders are poor at keeping records. Also there were farmers who might have forgotten
since they planted the tea on the average almost 18 years ago (see Table 3.3).

25

ATPS R ESEARCH PAPER 3 (PART II)
The mean number of plants the smallholders had varied with districts (Table 3.6). Generally thiswas dependent on the size of the tea enterprises. Farmers with larger areas under tea enterprises had
more plants, but this did not exactly translate to the equivalent of 8611 plants per hectare originally
recommended for the smallholders. If this recommendation was strictly followed, the mean numberof plants per farm should have been 4392, 2583, 6286 and 2842 plants, for Kirinyaga, Nyambene,
Nandi and Nyamira districts, respectively. In Nyambene district, the mean number of tea plants
recorded from the farmers’ records was higher than what it should have been. This may be due tofarmers using closer plant spacing than the 5 x 2.5 ft (1,52 x 0.91 m) recommended by KTDA. Closer
planting leads to higher tea production per unit area (Bore et al 1998; Wanyoko and Owuor 1995).
However, a closer look at the farms did not indicate such planting was being used in Nyambene
district. It is likely most of the smallholders in Nyambene district either did not know the number ofplants in their farms or the exact area under tea. In the other districts, the mean number of tea plants
the farmers indicated they had was less than what was expected This was attributed to lack of infillingfor a long time. The fields had many vacancies in all the districts. It is important that infilling is carriedout urgently as vacancies in the field translate to under use of land resource. Areas where tea plants
had died/dried in the middle of the plantations cannot be used for another useful farm enterprise andare wasted, and lead to low productivity of tea.
Table 3.5: Methods of land preparation by farmers (%)
Tool for clearing/ripping
land for tea growing (%)

Pangas/Jembes/Rakes
TractorOthersDo not know
Length of ripping tool (m)0.21
Were all roots fromYes
previous trees removedNoprior to tea planting (%)
Do not know
Did some of your tea die inYes
the 1st and/or 2nd year afterNo
planting (%)
Do not know
Was land ploughed afterYes
clearing? (%)
No
Do not know
If yes, how many times (mean number)
Did you harrow it? (%)
Yes
No
Do not know
If yes how many times (mean number)
Was field prepared, surveYes
yed & contour terraced forNosoil & water conser.?(%)
Do not know
After contour terracing
Planted tea immediately
what did you do to
Planted oatsprotect the bare soil?
Planted food - maize/beans
Mulched the soil
Left it bare
OthersDo not know

Kirinyaga

Nyambene

Nandi

90
0
3
7
.20
79
9
12
64
19
17
64
20
16
1.67
21
56
23
1.72
79
6
15
51
0
1
11
11
10
14

96
0
0
4
0.28
77
14
9
89
5
6
27
68
5
1.67
23
71
6
1.82
68
23
9
71
0
2
5
5
2
14

33
33
26
8
0.20
67
18
15
80
10
10
72
15
13
2.43
33
56
11
1.37
69
18
13
49
0
31
0
3
8
9

Nyamira
79
11
10
0
60
27
13
81
11
8
67
31
2
2.50
31
60
9
1.67
64
33
3
72
2
13
0
1
7
5

26

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
Table 3.6: Mean number of plant per farmer and recommended planting density
How many tea plants do you haveon the tea enterprise?
Are you aware of the recommended
plant density for tea in this region?
If Yes, what is it per ha.? (number)
If Yes how did you come to know
about it?(%)

Do you apply this recommendation
on your farm when planting tea?(%)

Yes
No
8952
Own expeAgricultural
Tea neigh
TRF
Other (Specify)
Yes
No

Kirinyaga

Nyambene

Nandi

Nyamira

3222

2835

4867

2534

57
43
8755
9
47
1
0
0
49
9

50
50
9564
5
43
5
0
5
48
25

68
32
7799
3
56
3
3
3
62
26

47
53
9
29
6
0
2
41
28

Most of the smallholders did not know the correct plant spacing. This implied that if they were toincrease the areas under tea, they would use incorrect spacing. There is urgent need to educate thetea farmers on the most economical planting densities for increased tea productivity and production.
For those who had the knowledge, it mostly came from the KTDA extension staff. Most of those who
knew the recommendation applied it while some knew it but did not apply the information. They
probably used other planting densities giving higher yields (Bore et al 1998; Wanyoko and Owuor
1995) or learnt it after planting their tea.
3.1.3.3 Nursery techniques
The fast expansion of the smallholder tea sub sector could not have been possible without availabilityof planting materials. Farmers who planted tea initially used seedling materials from either the KTDA
nurseries or estates. However, developing plants from seeds took too long, upto three years from seedplanting to planting in the field (Othieno 1981). Also transporting the seedling plants from the nurseries
was cumbersome and expensive. Indeed it involved transportation of a lot of soil with the plants
making them heavy. When the plants were transported over long distance on poor roads, the survival
rate in the field was low. Again the plants from seeds were not pre-selected for any advantage like highquality or yield. It therefore became necessary that easier methods of availing superior plants to thefarmers be sought. This culminated in the development of vegetative propagation method (Othieno1981). The method was simplified such that even smallholder farmers can use it. Indeed, the fast
expansion of smallholder tea sub sector in Kenya was only made possible by the easy availability ofthe vegetative plants. Unlike seedling plants, vegetatively propagated plants took only between 9 and18 months in the nursery. With vegetative propagation, it became possible to only develop plants withdesirable characteristics like high yields and quality. On annual basis, today smallholder tea in Kenya
has the highest quality and this is attributed to use of high quality clones, especially 6/8 (Othieno1981). Most importantly, vegetative propagation removed the burden of the smallholder transporting
heavy plants over long distance. Farmers chose their own plants to propagate. The extension systemof the KTDA and TRFK (or the TRIEA) trained the farmers to propagate their own planting materials
on site. An assessment was done on present farmers’ knowledge on the nursery techniques.
A large percentage of the farmers established their own nurseries, or received plants from theKTDA nurseries, a few purchased plants from their neighbours, and a reasonable percentage got

27

ATPS R ESEARCH PAPER 3 (PART II)
their plants from multiple sources (Table 3.7). Since not all the farmers interviewed were the original
owners who planted the tea, some farmers did not know the source of their tea plants. Very few
farmers received their planting materials from the estates, while none bought plants from the TRFK
nursery.
Table 3.7: Sources and types of planting materials (%)
How did you get your youngtea plants for transplanting?

Did you choose the plants to buy?
Basis of choosing the plants

Established own nursery
Buy from neighbours
Buy from KTDA Farms
Buy from TRFK
Buy from Estates
Multiple sources
Yes
No
Popular clones
High yielding clones
High quality clones
Drought resistant clones
Highly adaptable clones
Any other (Specify)
Whatever was available

Kirinyaga

Nyambene

Nandi

Nyamira

39
9
29
0
0
14
27
73
0
12
2
0
1
13
72

39
9
21
0
2
23
30
70
2
9
0
2
5
11
71

36
13
23
0
8
15
51
49
10
36
0
0
0
5
49

36
8
28
0
2
24
34
66
0
24
0
1
0
13
62

Most of the smallholder tea farmers did not choose the plants to grow. However, about 50% of
farmers in Nandi district selected plants to grow. For those who received their plants from KTDA
nurseries, pre-selection had been done and further selection was not necessary. Indeed, as a policy
KTDA only gave farmers mixed clones with proven yields and quality traits. Most of the farmers who
prepared their own nurseries obtained cuttings from the KTDA nurseries, and these were also frompre-selected clones. The farmers did not therefore have selection criteria. However, those who madeselections from either earlier planted tea on their farms or their neighbours’ teas, made selection
using high yields, popularity and adaptability as main criteria (Table 3.7).
The success of establishing the plants in the nursery depends on the vigour of the planted cuttingsand how the plants are tendered while in the nursery. It is therefore necessary that the mother bushes
be well taken care of so that by the time of obtaining the cuttings, the shoots are in active growing
phase. Most farmers, except in Nyambene district indicated they knew how to treat mother bushes inreadiness for obtaining cuttings (Table 3.8). Their detailed knowledge was not however assessed.
But it was noted that a large number of the farmers did not know how to treat mother bushes inreadiness for obtaining cuttings.
Most of the smallholders indicated the mean age of the cuttings to be obtained for propagation
ranged from 3 to 5 months (Table 3.8). Ideally this should be about 6 months. Again most smallholders
did not know the recommended age of shots from which to prepare cuttings. A few who knew indicatedthis should be less than 6 months.
After deciding the plants to make mother bushes, the normal practice is to prepare them so thatthey can grow vigorously. This is usually done by pruning the plants, keeping the bushes weed free
and after they recover from prune, applying fertilizer. Most farmers who indicated they knew how thisis done actually knew (Table 3.8). They learnt this mainly from the KTDA extension staff, althoughmany of them seem to have experimented and developed their own experience.

28

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
Table 3.8: Assessment of how smallholders prepare mother bushes and/or obtain cuttings.
Do you know how to prepareYes
cuttings from the motherNobushes? (%)
If Yes, what is the age of the shoots fromwhich you prepare cuttings? (Mean age in months)
Are you aware of the recommYes
ended age of tea shoots fromNo
which to preparre cuttings?(%)
If yes, what is it? (Mean
4.23
months) (<6)
Are you also aware of how toYestreat the mother bushes
No
before taking cuttings? (%)
If Yes, how do you treat them?
Prune & water
Prune & spray
Prune & fertilise
Peg & fertilise
Other (Specify)
If Yes how did you come to know
Own experience
about these methods? (%)
Agric extension staff
Tea neighbours
TRF
Other (Specify)

Kirinyaga

Nyambene

Nandi

Nyamira

69
31

48
52

59
41

55
31

4.69

5

3.36

5.35

31
69

25
75

28
72

31
69

5

2.6

4.56

39
61

21
79

28
72

32
68

3
0
23
0
10
10
20
5
0
1

0
0
15
0
5
9
9
2
0
2

0
3
33
0
8
8
21
5
0
8

0
0
28
0
6
11
19
4
0
1

In the preparation of the cuttings for planting, most farmers knew that the shoots are immersed inwater after being removed from the mother bushes. Generally the farmers knew the recommended
stem length of the cuttings and the duration they are supposed to be immersed in water (Table 3.9).
However, about 30% of the farmers in all districts did not have this knowledge. After the cuttings areplanted and the nursery beds are made, it is important that they are continuously monitored andadjustments made to ensure the plants are growing properly. Most farmers regularly checked thenursery beds (Table 3.9). When the plants have formed roots they are prepared by way of making
them acclimatise to the conditions they will be subjected to in the field before transplanting. The
polythene sheet is removed gradually as abrupt removal leads to the plants drying since they were notused to such environment. However, the shade remains and is also only removed slowly (gradually).
Plants do not remain under shade until the time of transplanting. Generally the smallholder farmers
noted that it took at least 6 months before the shade was completely removed and then left to harden
for at least 3 months (Table 3.9).
Most of the farmers knew that it is mandatory to water the plants in the nursery (Table 3.10), andindicated this is done either once or twice a week. In practice, this should be done as dictated byprevailing weather conditions, but it must be ensured the plants have adequate moisture to growfreely. Over watering must be avoided as it leads to water logging and plants death and encourages
development of some diseases. Again, most farmers applied fertilizer to nursery plants mostly as
NPKS 25:5:5:5. The application was done as a spray in water as is recommended, but few farmers
broadcast the fertilizer. Broadcasting the fertilizer is not recommended, as the amount put is usually
very small doses at a time. If it is broadcast, it is very difficult to apply it uniformly. A lot of fertilizer put ina single dose causes plasmolysis leading to plants death. Most smallholder tea farmers were applying
fertilizer to the nursery plants once a month.

29

ATPS R ESEARCH PAPER 3 (PART II)
The period the plants take in the nurseries vary from 9 to 18 months depending on the altitude atwhich propagation is done. At very high altitude where growth rate is slow, it takes longer than at low
altitudes where growth is faster. Most farmers knew the recommended period the tea plants shouldtake in the nursery (Table3.10). Indeed the mean age they gave was correct and this knowledge wasmainly acquired from the extension staff of KTDA.
Table 3.9: Assessment of how smallholder tea growers prepare cuttings for nursery planting.
Kirinyaga
Leave in sunlight0
Put in water
67
Plant directly in sleeves
1
Other (specify)
7
Do not know (Missing)25
Are you aware of theYes64
recommended stemNo
36
length and the duration they are supposed to be immersed in clean water? (%)
If Yes, what are they?
Mean
3.43
(lenght, Cm)
If Yes, what are they?
Minutes40(duration, Minutes)
If Yes how did you comeOwn experience10
to know about them? (%)
Agricultural extension staff
47
Tea neighbours
1
Tea Research Foundation
0
Other(Specify)
3
Do not know (Missing)39
Do you apply theseYes
59
Do not know (Missing)51
Do you check the beds
Yes
76
No
6
Do not know (Missing)18
If Yes, how many times
2
3
Do you prepare your rooted
Yes
71
cuttings for transplanting? (%) No
1
Missing
28
When the roots of the roots of Nothing0
the cuttings have reached
Remove sheeting abruptly
3
the bottom of the sleeves,Remove sheeting gradually69
what do you do? (%)
Transplant the cuttings
0
Other (specify)
Do not know (Missing)28
What do you do withthe cuttings after removing them from themother bushes? (%)

Nyambene
2
59
2
5
32
61
39

Nandi
3
56
0
3
28
56
44

Nyamira
8
63
2
4
23
64
36

4

4.34

4.884

47

110

62.62

14
39
5
0
29
40
59
41
59
14
27
4
39
23
38
0
7
59
0

8
36
10
0
8
38
59
41
59
3
38
3
41
18
41
0
5
59
0

15
35
11
0
5
34
70
30
76
5
19

34

46

28

41
39
20
0
5
67
0

Under nursery techniques, the knowledge of the farmers was about the same in all districts. About
30% of the farmers did not know the techniques across the board. The percentages given in Tables
3.7 to 3.10, therefore do not add up to 100%. The differences were those farmers who were unawareof the techniques. This percentage is very high and it is necessary that awareness be created. Even
those farmers who indicated knowledge of nursery techniques did not know all of them. The diffusionof nursery techniques to the farmers is therefore not complete. There are farmers who need awarenessof all techniques and those who only need refresher courses. Effort should be made to accomplish
this.

30

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
Table 3.10: Assessment of nursery management techniques.
Do you shade the cuttings

Yes
No
Do not know (Missing)If No, at what age of the cuttings do you remove
the shade? (Months)
How long do the cuttings remain in the nursery after
the shade is removed? (Months)
What is the purpose of removing the shadesometime before transplanting the cuttings? (Hardening%)
Do you water your nursery
Yes
No
Do not know (Missing)If yes, how often do you water
Daily
nursery plants? (%)
Once a week
Two times a week
Monthly
Any other (specify)
Do not know (Missing)
What fertilizer do you apply
NPKS
to your nursery plants?
DAP(%)
NPKS + DAP
SSP
TSP
Urea
CAN
Any other (Specify
Do not know (Missing)How do you apply fertilizer
Broadcast (Bc)
to nursery plants? (%)
As spray in water
Bc and spray in water
Any other (Specify)
Do not know (Missing)How often do you apply
Daily
fertilizer to your nursery
Once a weekplants? (%)
Monthly
Once in six months
Once in a year
Any other (Specify)
Do not know (Missing)

Kirinyaga
31
46
23
6.56

Nyambene
39
30
31
8

Nandi
41
28
31
7.14

Nyamira
42
34
24
7

4.11

3

2.41

3.4

61

55

56

50

76
1
23
1
33
17
4
20
25
51
9
0
1
0
0
4
3
33
4
57
1
6
32
0
13
16
7
9
24
31

64
7
29
0
18
18
2
25
37
43
2
18
0
0
0
2
0
35
16
39
0
9
36
0
7
30
5
2
30
26

64
0
36
10
15
21
8
13
33
56
3
15
0
0
0
0
0
26
0
56
0
21
23
5
0
26
5
8
33
23

76
3
21
4
17
36
2
18
23
24
16
1
0
0
0
0
30
39
11
27
0
23
39
0
6
14
6
3
30
41

The demand for planting materials in the smallholder tea sub sector out strips supply. Most
farmers who want to either make new planting, or do infilling or expand their tea holdings must
therefore increasingly propagate their own planting materials. This can only be achieved if the farmers
have the technologies to propagate the plants. Indeed, for farmers with tea, it was observed (see sub
section 3.1; 3.5) that there were vacancies, which reduce the productivity of most tea farms andrender high potential agricultural lands to no use, as other crops cannot grow effectively in thesepatches. Beneficial use of these sections can only be from tea. Farmers therefore urgently need thesources of planting materials. The continued expansion of the smallholder tea sub sector requires all
farmers to be taught all nursery techniques. Indeed with knowledge of preparing mother bushes,
individual tea growers stand a better chance of making their own selections for expansion and/or
infilling their farms.

31

ATPS R ESEARCH PAPER 3 (PART II)
3.1.3.4 Field planting and bringing into bearing
For successful plant establishment, tea planting should be done after the field is well prepared andduring the correct season. Planting must be done during rainy season to ensure high rate of survival
and fast establishment. Planting during drought leads to high plant mortality and should be avoided.
Most smallholder tea farmers (Table 3.11) were aware that transplanting into the field is done during
rainy season, but 14, 7, and 1% of the farmers in Kirinyaga, Nyambene and Nyamira districts,
respectively, thought planting should be done in dry season.
The recommended holes for planting should be 15 to 20 cm deeper than the length of thesleeves and double the sleeve diameter. For a standard sleeve 25 cm long and 6.25 cm diameter,
commonly used in the smallholder sub sector, the holes should be 40 cm deep and 25 cm indiameter. The average depths and diameters given by the farmers are presented in Table 3.11.
There were no large differences in the hole sizes in various districts and they were on the averagesmaller than recommended.
Table 3.11: Assessment of field planting methods and in puts by smallholder tea growers.
At what season do you
transplant the cuttings? (%)
How wide and deep are
your holes for planting tea
cuttings? (%)
Do you apply fertilizer in the
cuttings? (%)

Dry season
Rain season
Do not know
Width (cm)Depth (cm)YesNo
Do not know
If Yes, what type of fertilizer
DAP
do you apply in the holes?
CAN
(%)
SSP
Other (Specify)
No and do not know
If Yes, how much fertilizer do you apply per hole?
(gm/hole)

Kirinyaga

Nyambene

Nandi

Nyamira

14
79
7
21.2
32.5

7
93
0
23
39

0
95
5
23
29

1
93
6
17.1
30.62

39
50
7
20
0
7
11
62
14.05

31
61
8
21
2
2
5
70
10

64
33
3
59
0
3
8
30
10

39
55
6
22
1
2
17
58
18.21

During planting, it is recommended that fertilizer rich in phosphorous is used. Usually 30 gm ofsingle super phosphate is mixed with the soil removed from the hole before planting. However, DAP
can also be used at the same rate. In the east of the Rift Valley and Nyamira district, most farmers did
not plant tea with fertilizers, while in Nandi district, most farmers used fertilizers in the planting hole.
Those who knew fertilizer should be used in the planting hole were applying very low rates. Either way,a large percentage of the farmers were not using fertilizer for planting tea. Possibly this was due to thefact that the majority of the smallholders planting tea for the first time had not registered with KTDA
and did not have fertilizer credit facility. Some farmers, however, did not have the information that it isnecessary to use fertilizer in the planting holes. Efforts should be made to ensure that use of fertilizer
in the planting hole is made known to all farmers, and especially prospective new farmers. Planting
with phosphatic fertilizer ensures that the young tea plants develop good rooting system and start
growing vigorously. This helps the plants to establish faster and withstand drought. The majority of the
farmers who used fertilizer in the planting holes used DAP, while others used SSP and a small number

32

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
used CAN (Table 3.11). But despite the use, in all districts the mean amount of fertilizer used per
planting hole was too low. However, the relationship between fertilizer used in the planting hole andyields were not apparent in the study. This is because use of fertilizer only helped the plants toestablish faster and better in the early years of planting and had no relationship with yields of maturetea.
In the establishment phase of tea, there is a period when financial returns may depend on the
speed and efficiency with which the young tea plants are brought into bearing. The method ofbringing tea into bearing should therefore result in economic production of an even stand of healthy
bushes attaining their optimum yield potential as soon as possible and maintaining this optimum
yield. The lower part of the branch of the bush will form a permanent frame that will remain largely
unaltered throughout the life of the bush or until the bush is down pruned to rejuvenate it. The frame
must therefore be low, strong and have good spread. A system of bringing tea into bearing whichenables plucking to start very early may first seem satisfactory but prove poor in the long run if thesystem restricts root development or encourages more shoot and less root growth as that makes theplants susceptible to drought or results in narrow framed bushes which cover the ground slowly andgive low yields when pruned next. Operations designed to help the plant form permanent branchsystem from the time the plants are in the nursery to the time they are tipped-in to form a plucking table
are collectively called “bringing into bearing”.
When a shoot of tea is removed, axillary buds are stimulated to develop about 10 to 12 cm below
the cut. Young tea can be brought into bearing by pruning or by pegging. When bringing into bearing
by pruning, the shoots are first pruned at 15 cm. Most farmers gave an average first pruning height
ranging from 18 to 25 cm (Table 3.12), which is a little high. This should be done when the plants are
30 cm tall, but most farmers thought it should be done when the heights of the plants ranged from 34
to 50 cm. These answers indicated that farmers started bringing their tea into bearing late. Thisdelayed the period the farmers could start harvesting their tea plants economically. However, thedelayed pruning ensures plants develop deeper rooting system to withstand drought better.
Table 3.12: Bringing young tea into bearing by smallholder tea growers
At what height do you prune the young tea for the
first time (decentring)? (cm)
What is the approximate length of the central stems
at the point of first pruning? (cm)After decentring, indicate the
1st pruning
the heights at which you
2 nd pruning
prune your young tea
3 rd pruning
sequentially. (Pruning Height (cm))
At what length of the lateral shoots do you startpegging them? (cm)At what height of the central stems Height (cm)and length of the lateral shoots do
Length (cm)you establish plucking table for your tea plants?

Kirinyaga

Nyambene

Nandi

Nyamira

18.16

21.7

24.9

18.88

34.15

50

45

48.08

35.61
48.25
57.oo

39
49
51

27.3
34.7
41.3

19.87
27.22
40.25

49.83

59.6

37.2

39.28

48.71
59.10

48
59

41.1
52.6

48.17
48.20

Subsequent prunings are done at 28, 40, and 50 cm respectively. Farmers in the east of the Rift
Valley gave high average height at which they did the subsequent prunings, while farmers in the west

ATPS R ESEARCH PAPER 3 (PART II)
of the Rift Valley gave lower heights (Table 3.12). Either may, the means given indicated lack ofknowledge of the recommendation.
However, if plants are brought into bearing by pegging, after the plants are decentred at 15 cm
when they are 30 cm high, the first pegging is done when the lateral shoots are not less than 50 cm
and not more than 65 cm high. While most farmers in the east of the Rift Valley knew the correctheight, the farmers in the west of the Rift Valley were pegging when the plants were too short (Table
3.12). The first plucking table is normally established at 50 cm height. Farmers from the east of the
Rift Valley indicated a higher height while farmers from the west of the Rift Valley were establishing
their plucking tables at the correct height (Table 3.12).
3.1.3.5 Field management
Plucking and leaf collection
The economic part of the tea bush is the young tender shoots which are harvested to process various
tea beverages. Efficiency of harvesting the shoots can dictate whether tea enterprise is profitable ornot. If plucking is done at very long intervals, yields (Odhiambo 1988, Owuor et al 1997) and quality(Owuor 1997, Owuor et al 1997, 2000) decline. Plucking rounds in Kenya vary from 7 to 10 days
during favourable growing seasons and 12 to 15 days during dry or very cold seasons. On the average,
the farmers interviewed were plucking on 10 or 11 days plucking rounds (Table 3.13). However,examination of individual farms and/or factory deliveries records showed that many farmers still pluck
after very long rounds, while there are farmers who are over plucking at very short intervals. The
plucking rounds indicated did not vary much with the districts.
For plucking to be efficiently done, it is necessary that the plucking table is kept flat and uniform.
When the table is not uniform, plucking rates become slow and plucking is made more difficult.
Farmers find it more difficult to keep set plucking standard and a lot of leaf that is ready for harvestingis left on the bush. Again it leads to farmers harvesting immature leaf. It is recommended that whenplucking, pluckers should use plucking wands (long sticks) to ensure the table is maintained. Althoughmost farmers knew the recommendation, in all districts, the farmers did not use the wands (Table
3.13). Consequently in most farms, the plucking tables were uneven which makes plucking very
inefficient. Most farmers believed that use of plucking wand slowed down their plucking speeds andhence plucker productivity. It is important to educate the farmers on the benefits of using plucking
wands.
Most of the smallholder tea farmers started plucking between 7 and 8 am, although a few, especiallyin the west of the Rift Valley started plucking at 6 am (Table 3.14). In Nyambene, Nandi and Nyamira
districts, plucking in most farms ended between 12 noon and 1 pm. This duration is too short for all
leaf to be removed from the fields. In Kirinyaga district, however, farmers plucked for longer durations
upto 4 pm. Indeed, where plucking stopped early, farmers indicated that they did not have enoughtime to remove all crop. In the west of the Rift Valley more farmers plucked for longer duration in
Nyamira district than in Nandi district. Again in the east of the Rift Valley, productivity per bush was
higher in Kirinyaga district where plucking duration was longer than in Nyambene district. Indeed, inthe overall Kirinyaga district where farmers were plucking for longest period per day had the highest
productivity per bush. For farmers to have adequate time to harvest all the available leaf, it is necessarythat plucking is started early in the morning. These results demonstrated that it is important to work

33

34

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
out for farmers plucking schedules, which enable them to spend more time plucking. Ways should befound to increase plucking time to between 3 and 5 pm in all districts.
Most farmers did not have adequate plucking time because the leaf collection lorry came too
early (Table 3.13). Through discussion with the farmers, it was noted that in the west of the Rift valley,
the leaf collection lorry collected leaf only once in a day from most buying centres. This was unlike
Kirinyaga district where the leaf collection lorry collected leaf at least two times a day. This arrangement
must have been made between the farmers’ representatives, tea officers, leaf collection managers
and factory managers. Other districts should copy this system that is working well in Kirinyaga district.
The earliest time most farmers delivered their leaf to buying centres was between 10 am and 12
noon in the east of the Rift valley and 10 am and 11am in the west of the Rift Valley (Table 3.14).
However, it was noted that a large percentage of farmers in Nyamira and Nandi districts indicated thatthey delivered their leaf at any time, i.e. there was no timing. This is because the lorry came only oncea day, at times that were not regular, and farmers rushed to the buying centres whenever it arrived.
Although early delivery of leaf to buying centres especially where it is collected at least two times a day
is beneficial as it helps factory personnel to handle and process leaf more efficiently, most farmers
could not deliver their leaf early to give them enough time to pluck. However, a reasonable percentage
of farmers could not do early delivery because the leaf clerks did not come to buying centre earlyenough. In many centres this is because one leaf clerk is in charge of more than one buying centre,
but in some cases, this was attributed to lack of discipline and/or supervision.
Table 3.13: Plucking arrangements in the smallholder tea farms
What is your plucking round for tea? (Days)
How do you maintain aExperienceplucking table for yourLong straight sticktea? (%)
Other (specify)
When does plucking start in
6 amyour farm? (%)
7 am
8 am
9 am
Other (specify)
Missing (not timed)
When does plucking stop in
10 amyour farm? (%)
11 am
12 noon
1 pm
2 pm
3 pm
4 pm
Missing (not timed)
Do you feel you normallyYes
have enough time toNopluck your tea? (%)
If No, why is the time
Buying centre too far
inadequate? (%)
Lorry comes too early
Pluckers not willing topluck for long hours
Busy with other entrps.
Any other (Specify)

Kirinyaga

Nyambene

Nandi

Nyamira

11
91
6
3
16
34
39
6
5
0
1
1
10
14
13
22
39
0
69
31

11
77
23
0
9
50
36
5
0
0
2
9
11
32
46
0
0
0
55
45

10
82
8
10
31
56
12
0
0
1
18
39
28
15
0
0
0
0
20
80

10.5
88
11
0
37
47
14
0
0
2
14
14
43
20
7
0
1
1
36
64

1
14
3

2
25
5

3
62
0

2
52
1

9
0

14
0

0
8

0
3

35

ATPS R ESEARCH PAPER 3 (PART II)
Whereas most farmers in the east of the Rift Valley had 4 pm as the latest time to deliver leaf tobuying centres, in the west of the Rift Valley, this was a bit early and was mostly determined by the time
the leaf lorry arrived. Farmers were unable to deliver leaf later due to the last delivery time being set by
the buying centre committee and/or because the leaf buying clerk left the centre too early (Table
3.14). The arrangement of leaf buying centre committee setting the last leaf delivery time brings orderin the operation and should be encouraged. However, the data presented here showed that leaf
collection arrangement in the west and east of the Rift valley were not the same. Farmers in the westof the Rift Valley have shorter plucking duration (Table 3.13) and earlier time for leaf delivery to buying
centres (Table 3.14) than farmers in the east of the Rift Valley. This may be one factor reducing leaf
productivity and production in the west of the Rift Valley compared to the east of the Rift Valley. Efforts
should be made so that more plucking and leaf delivery durations are created, especially in the westof the Rift Valley. Farmers need to be educated to start plucking early to create extra harvesting
duration, while policies should also be made to ensure leaf is collected at least two times a day andthat leaf clerks spend longer durations at the buying centres. In every district, it is necessary that
farmers and KTDA staff (extension, leaf collection and factory staff), work out a system that ensures
farmers harvest all the available leaf and that whatever is harvested is collected on time for processing.
Kirinyaga district seemed to have been in the forefront in such arrangements.
Table 3.14: Timing leaf delivery to buying centres by smallholder tea farmers (%)
What is the approximate
earliest time in a day you
can deliver leaf to buying
centre?

Why can you not deliverleaf earlier?

What is the approximate
time in a day you candeliver leaf to buying
centreWhy can you not deliverleaf later?

9 am
10 am
11 am
12 noon
1 pm
2 pm
3 pm
4 pm
Not timed
Clerks come lateTime to pluck more leaf
No labour to deliver leaf
Any other (Specify)
Missing
1 pm
2 pm
3 pm
4 pm
5 pm
6 pm
Not timed
Clerks come early
Leaf clerk leaves early
No labour to deliver leaf
Official time
Any other (Specify)
Missing

Kirinyaga
0
14
44
24
4
6
2
3
4
30
43
1
19
7
3
4
17
66
0
0
10
4
23
1
56
13
3

Nyambene
5
30
27
39
0
0
0
0
0
21
55
5
18
1
9
11
23
41
0
0
16
5
16
0
61
14
9

Nandi
3
37
40
0
0
0
0
0
22
18
64
15
0
3
13
10
10
5
0
0
62
5
59
3
33
0
9

Nyamira
22
26
20
0
7
1
18
32
25
21
59
1
11
8
20
18
11
12
0
29
10
4
27
2
51
9
7

36

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
As noted earlier, the arrival of the leaf collection lorry is crucial to leaf delivery and collection. In theeast of the Rift Valley, the first lorry arrived between 10 am and 12 noon which was about the same as
10 am and 1 pm the first lorry arrived in the west of the Rift Valley. However, whereas in the east of the
Rift Valley there would be another delivery, in the west of the Rift Valley to many farmers the first lorry
was also the last lorry. Again its timing was more irregular in the west of the Rift Valley with most
farmers indicating they could not time it (Table 3.15). This is because the lorry most of the timecollected the leaf only once in a day and most of the time the first lorry did not arrive until late in theafternoon or even in the night. Generally, the arrival time in the west of the Rift Valley tended to be more
irregular than that in the east of the Rift Valley. Efforts should be made especially in the west of the Rift
Valley to improve leaf collection by making the lorries collect the leaf more times a day and also tomake the collecting time more regular.
In Kirinyaga, most of the time the last lorry arrived by 11 pm. This is unlike the other districts where
the arrival of the late lorry was not regularly timed. This is because in some districts the last lorry was
also the first lorry. But generally when there was too much leaf that could not be all carried by thescheduled one trip in the districts where collection was done once the leaf could stay in the buying
centres until the next day or longer.
Most farmers were usually spending at most only one hour at the buying centres (Table 3.15).
However, the longest time farmers had spent in the buying centres was long, being more than 12hours in most districts except in Nandi district. The reason for the long stay is that the leaf clerk avoids
buying too much leaf he/she cannot keep it good condition. The farmers are therefore left with theirleaf to look after until the time the leaf collection lorry arrives. Again if there is too much leaf, the leaf
clerk and the lorry driver alone cannot load it into the lorry. Farmers wait at the buying centres to help
load the leaf. A mechanism should be found so that farmers avoid spending too much time in thebuying centres as this denies them a chance to do other farm and personal duties. In some districts
farmers have now hired leaf loaders to take care of the leaf after it has been purchased but before it
is collected by the leaf collection lorries and to load the leaf into the lorries. This coupled with the leaf
clerk arriving at the buying centre on time will help reduce the durations farmers spend at the buying
centres.
The reason given in most cases for poor leaf collection programme is the poor state of the roads.
Farmers now pay cess to improve and maintain the roads. Tea roads are therefore being maintainedby funds contributed by the farmers. Most farmers, especially in the west of the Rift Valley and Nyambene
district observed that the tea roads were in very poor states (Table 3.15). Indeed, this was impacting
negatively on tea production. Again in the districts where the state of the roads was noted to be poor,
leaf collection programme was also poor. It is therefore not possible to correct the poor leaf collection
problem without improving the state of the roads. These two problems must be solved concurrently.
Due to the fact that the tea farmers are now paying substantial amount of money to ensure the roads
are in a fair state, accountability should be enhanced so that the money collected is used for theintended purposes only.
Pruning and in-filling
For tea in production, the table rises at a rate of about 20 cm per year (Mwakha 1997). After three tofour years, the table reaches a height of about 120 to 150 cm, which is too high for efficient management,

37

ATPS R ESEARCH PAPER 3 (PART II)
particularly plucking, which becomes very difficult or unmanageable. It becomes necessary to prune
the plants to a lower height. This is normally done from 45 cm, rising to 70 cm each time the pruning
height is increased by 5 cm above the previous pruning height. After reaching the 70 cm pruning
height, it is again brought down to 45 cm. The common type of pruning in the smallholder tea sub
sector is the cut across method, and pruning is done using pruning knives. It is recommended that theprunings (the cut leaves and branches) are left in situ in the field to return nutrients, reduce soil
erosion and conserve moisture as the prunings also act as mulch.
Table 3.15: Assesment of problems of leaf collection and state of roads (%)
When does the first leaf
lorry arrive to collect leaf
from your buying centre?

When does the last leaf
lorry arrive to collect leaf
from your buying centre?

How long do you normally
stay at the buying centre?

What is the longest time you
have spent at the buying
centre?

How do you rate the stateof tea roads in your area?

Does the state of tea roads
affect your green leaf
production?

10 am
11 am
12 noon
1 pm
2 pm
3 pm
Not timed
6 pm
7 pm
8 pm
9 pm
10 pm
11 PM
Not timed
Less than one Hour
1 Hour2 Hours
3 Hours
4 hours
Not timed
3 hours
4 Hours
5 Hours
6 Hours
8 hour10 hours
11 hours
12 hours> 12 hours
Not timed
Very good
Good
Fair
Poor
Not decided
Yes
No

Kirinyaga

Nyambene

Nandi

Nyamira

20
43
19
7
0
1
10
3
0
6
1
17
70
0
71
13
6
1
0
9
20
6
3
14
4
0
0
4
47
2
0
14
37
49
0
71
29

32
23
25
9
0
2
9
0
2
0
11
11
0
76
71
14
9
2
0
4
9
4
0
0
2
0
0
2
80
4
5
5
27
64
4
86
14

15
23
10
13
5
0
34
3
3
0
0
0
0
94
85
15
0
0
0
0
41
0
3
15
0
0
0
0
36
5
0
3
18
73
6
92
8

30
21
9
7
3
2
28
7
0
0
2
4
5
82
78
9
3
1
1
7
20
6
1
6
0
1
0
12
56
8
0
5
9
86
0
96
4

Most of the smallholders were pruning after three years as recommended (Table 3.16). Some,
especially in the west of the Rift Valley were pruning after four years. Since plucking has been intensified
and many farmers now pluck on 10 to 11 days plucking rounds (Table 3.13), it is justifiable for farmers

38

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
to increase pruning cycles lengths to four years. Indeed farmers should not prune as a routine but asa means of keeping the plucking table at manageable heights. There were farmers who were pruning
when the plucking tables had not even reached 50 cm, but just because it is three years since they
last pruned. This needs to be avoided. The average pruning heights as given by the farmers areshown in Table 3.16. However, examination of the farmers’ fields indicated that pruning heights were
not measured in the smallholder tea sub sector. Indeed, most farmers never pruned themselves, but
used hired pruners. The hired pruners were not supervised as they pretended to be specialists who
know more about pruning than the farmers. The farmers treat them as experts. These pruners
generally pruned the tea plants at very low heights, sometimes even below the formative pruning
height level at which the plucking table was established. They do so that during pruning they have
only few branches to cut, thus facilitating fast completion of the task since pruners are paid on task
basis.
Table 3.16: Information on pruning technology and vacancies in the field.
After how long do you prune
you tea? (%)

One year
Two years
Three years
Four years
Five years
Six years
Seven years
Do not know (Missing)
The mean pruning heights
First cycle
in five successive pruning
Second cycle
cycles (cm)Third cycle
Fourth cycle
Fifth cycle
Sixth
After how long do you do down or height reduction
pruning? (mean years)
What type of pruning do
Cut acrossyou do on your tea farm?
Rim lung(%)
Any other (specify)
What pruning implements
Pangas (a)do you use in your farm?
Saws(%)
Pruning knives (b)Other knives
Combination of a & b
Others (specify)
Do you remove yourYes
prunings from the pruned
Nofield? (%)
Mean vacancies in farms. (%)
5.2
Mean in filling periods. (Every years)2

Kirinyaga
0
1
93
3
2
0
1
0
43
47
52
52
48
11

Nyambene
2
9
61
5
5
0
16
2
47
54
59
61
50
9.2

Nandi
0
10
51
26
0
0
10
3
48.14
54.09
55.23
56.06
58.08
61
13.29

Nyamira
0
3
56
23
9
1
8
0
47.8
53.4
58.3
62.8
53.1
47
9.5

97
3
0
56
0
41
0
3
0
26
74

98
0
2
48
0
50
0
0
2
25
75

100
0
0
10
0
90
0
0
0
15
85

96
4
0
0
2
94
2
0
2
21
79

13
1

14.33
1.17

9.1
2

The low pruning has several disadvantages. When it is done below the initial formative pruning,
farmers need to bring tea into bearing again. The tea plants therefore take a long time to recover fromprune, which delays the time the plants come back into production. Apart from long recovery time, low

ATPS R ESEARCH PAPER 3 (PART II)
pruning reduces yields (Kaptich 1985, Njuguna and Magambo 1990) as it reduces the plucking tablesize. The low pruned fields take long to cover the ground and this raises the costs of production since
the fields must be weeded more times. Also low pruning causes large wounds on the tea bushes atvery low heights. The height and size of the wounds make it easier for Hypoxylon Serpens inoculum
to infect the tea bushes (Otieno 1997). Many farms visited had heavy Hypoxylon wood rot infections
making the future of tea on the farms more uncertain. Again the low pruning height means thatpluckers must bend most of the time to harvest the tea. This makes them tired faster, thus reducing
their productivity. In the long run, this constant bending while plucking causes backache to thepluckers. Low pruning therefore hurts both the tea plant and the farmers and must be avoided.
Although the pruning height should be increased by 5 cm most farmers did not know how it should bedone (Table 3.16). But since it did not appear as though the farmers were actually monitoring thepruning height, this knowledge, although poor, was not being put to use.
Most smallholder tea farmers especially in the west of the Rift Valley used pruning knives to prune
their tea plants as recommended. However, large percentage of the smallholder tea farmers in theeast of the Rift Valley were using pangas to prune tea (Table 3.16). They argued, using pangas madepruning faster. However, this creates a problem, as the pangas usually caused cracks on the tea
bushes making the cutting wounds even larger/bigger and the plant more predisposed to Hypoxylon
wood rot infection. Indeed in several tea farms, many plants are already dying because of hypoxylon
wood rot. Again maintaining uniform pruning height is more difficult to achieve with the use of a panga
for pruning. Farmers should be educated to prune correctly and to use appropriate implements. In all
the districts, most farmers leave the prunings in the field (Table 3.16), but in many areas farmers arestill removing the prunings for use as firewood. This needs to be discouraged.
As a result of disease, pests and other natural calamities, some plants are lost causing large
vacancies in the farmers’ fields. There were vacancies in the fields visited with means ranging from
5 to 14% (Table 3.16). Tea production or productivity per bush in various districts did not follow thepattern of vacancies means. For the dead tea plants it is only possible to infill during the year of prune.
However, farmers gave infilling frequencies of 1 or 2 years (Table 3.16). If this was done, it is unlikely
the plants survived. However, most farmers were not infilling their farms. Since no other crop can growviably in these vacancies, the lack of infilling programme implied that large areas of prime lands arebeing under utilised as no crop is grown on them. There should be a continuous infilling programme
to increase tea production in the farms.
3.1.3.6. Adoption and use of chemical inputs on tea
Fertilizers and manures
Tea in regular production has to get nutrients supplemented in form of fertilizers and/or manures tocontinue to give high yields. In the smallholder sub sector of the Kenya tea industry, the recommended
fertilizers for tea (Othieno 1988) and supplied by KTDA on credit is the NPKS 25:5:5:5. Most farmers(Table 3.17) used fertilizers on tea and knew they were receiving NPKS 25:5:5:5 or simply called it“fertilizer for tea”. However, there were farmers in Nyambene, Nandi and Nyamira districts who were
not applying fertilizers. These farmers were either not applying to get fertilizers from KTDA on credit orsold whatever they received to their neighbours or used the fertilizers they received on other farm
enterprises.

39

40

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
The fertilizer use per unit area varied largely from district to district. This followed the same pattern
as productivity such that areas, which applied more fertilizers, realised higher production per bush
(Table 3.17). Kirinyaga district that had applied the highest rate of fertilizer had the highest productivity
per bush, followed by Nyamira district. The rates of fertilizer applied and productivity per bush achievedin Nyambene and Nandi districts were the same and low. Fertilizer application is therefore one
technology whose use ensures farmers get higher green leaf production.
Table 3.17: Assessment of fertilizers and manures use on tea.
Do you apply fertilizers on
your tea? (%)
If Yes, what type(s)? (%)

If Yes, what rates do you
apply on mature tea?
Indicate the fertilizer rates
you apply/applied yearly on
your immature tea.
(Bags/ha/year)
Month fertilizer received foryour tea last year? (%)

Yes
NoMissing
DAP
NPKS 25:5:5:5
Urea
Other (specify
Do not apply
Bags/hectare/year
Kg/hectare/year
KgN/ hectare/year
1st year from planting
2nd year from planting
3rd year from planting
4th year from planting
May
June
July
Aug
Sep
Oct
Nov
Dec
Did not receive

How many bags did you get? (bags)
How many bags did you buy directly from themarket or your neighbour? (bags)
How many bags did you apply to your tea? (bags)
Do you apply organic on
Yes
your tea? (%)
No
Missing
If Yes, what type? (number)Cow dung
Goat manure
Pig manure
Maize stalks
Others (specify)

Kirinyaga

Nyambene

Nandi

Nyamira

100
0
0
3
90
0
7
0
23.16
1157.81
290
1.4
2.6
3.1
5.1
0
0
0
30
53
7
1
0
9
8.9
7

98
2
0
0
96
0
0
4
12.43
631.5
155
.9
1.3
1.4
1.8
0
0
2
4
46
16
2
1
32
5.5
0.7

95
5
0
0
95
0
0
5
12.68
634
159
1.7
2.7
3.2
4.0
3
3
0
8
33
18
10
25
0
10.03
2.1

97
2
1
1
91
1
5
2
16.95
847.5
212
6.86
8.3
9.73
11.01
0
0
2
4
43
16
2
1
32
4
1

9
34
64
2
0
0
0
1
0

5.6
41
59
0
21
2
2
5
11

9.1
5
92
3
3
0
0
3
0

5
14
85
1
4
1
1
4
1

For young tea, farmers used increasing and progressive rates of fertilizers with time (Table 3.17).
Although the bags per hectare are given in Table 3.17, the data is suspect because most farmers did
not plant all their tea in the same year. They had increased areas under tea gradually, but the calculation
was based on the areas under tea for each farmer. The only important observation is that farmers
knew when the tea is still young it receives less fertilizer, which is increased in progression upto when
the tea is mature at which point it starts receiving a full dose.

ATPS R ESEARCH PAPER 3 (PART II)
It is deduced from Table 3.17 that a very high percentage of the farmers have access to fertilizer
credit. However, there seems to be a problem of timely distribution of the input to the farmers. Generally
farmers should receive fertilizers in July, August and latest in September for application when the rainscome in October. In 1998, in Kirinyaga district, most farmers received fertilizer in August and September,while in Nyambene and Nyamira districts, most farmers received fertilizer in September, and October,but in Nandi district most farmers received fertilizers in September, October, November and December(Table 3.17). Thus except in Kirinyaga district where the fertilizer supply was timely, in other districts
supply was generally late. This resulted in late application of the fertilizer and it is unlikely the applied
fertilizer benefited tea production during the season as it was applied after the rains had ended. This
led to low yields in these districts during the period. Inputs supply needs to be made on time in allareas for farmers to be able to use them to increase production.
The mean amount of fertilizer obtained by the farmers on credit (Table 3.17) was proportional tothe mean areas under tea (Table 3.3). However, most farmers believed that the amount of fertilizers
they were obtaining on credit was inadequate, and therefore purchased additional fertilizer for tea
from the market or their neighbours (Table 3.17). In Kirinyaga district the extra amount of fertilizer
bought was large leading to mean higher application than that envisaged by KTDA. This was followed
by Nandi, Nyamira, and Nyambene districts, in that order. Use of higher rates of nitrogen thanrecommended raises the tea costs of production without reasonable economic benefits (Owuor andOthieno 1996, Owuor and Wanyoko 1996), reduces black tea quality (Owuor et al 1997, 2000) andcauses other soil management problems (Owuor 1997). However, in this study the mean rate was not
more than recommended rates, except in Kirinyaga district. But it is likely there are individual farmers
who may be using over 300 kgN/ha/year. These need to be identified and advised. Similarly in theother areas, there were producers not using fertilizers or using very low rates. These farmers need tobe identified and urged to use fertilizers to boost their production.
In the west of the Rift Valley, farmers did not use organic manures on tea, while in the east of the Rift
Valley considerable number of farmers use organic manures (Table 3.17). The common type oforganic manure used was cow dung, goat manure, pig manure and maize stalks. There is nothing
wrong in the use of the organic manures provided it supplies the necessary nutrients and it is used at
the correct rates.
Weeds, pests and diseases control
Weeds in tea production cause yield reduction/losses as applied fertilizers mostly go to feed theweeds. It is therefore necessary that tea plantations are kept weed free. Generally this is done manuallyusing “jembes” or hoes, or chemically using herbicides. However, manual weeding destroys feeder
roots system of the plants thus impeding the ability of the plants to absorb nutrients from the soil
(Othieno 1981). Herbicide weeding is therefore recommended in tea production. However, 93%,93%, 85% and 96% of the farmers in Kirinyaga, Nyambene, Nandi and Nyamira districts, respectively
used manual weeding. Indeed, most of the farmers did not know the herbicides for controlling weeds
in tea and those who knew did not know appropriate rates to use. Education of the farmers on
herbicides weeding is necessary in all tea growing districts.
There are several pests, which attack tea in Kenya (Owuor et al 2001). The pests which could be
identified by most farmers was mole rats which occurred in 41%, 21%, 28% and 26% of the farms

41

42

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
belonging to farmers in Kirinyaga, Nyambene, Nandi and Nyamira districts, respectively (Table 3.18).
Few farmers also noted the occurrence of mites, scales and aphids in their farms. But it is noted that
35%, 56%, 40% and 42% of farmers in Kirinyaga, Nyambene, Nandi and Nyamira districts, respectively(Table 3.18) could not identify any pests. Thus they did not know even if there were pests in their tea
fields.
If pests existed in their farms they left it to laws of nature to control them (Table 3.18) However, few
farmers believed that they could control the pests using field management practices, while fewer
farmers in the East of the Rift Valley use pesticides. Most farmers did not know the pesticides to use
and when they knew, they did not know the recommended/correct rates and safe use of the pesticides.
The problem of mole rats was most prevalent in many farms (Table 3.18) and they were controlled bymanual trapping.
Table 3.18: Tea pests and diseases and their control by smallholder (%) tea growers:
Name tea pests, which
occur in your tea farm.

How do you control pests
and diseases in tea?
Do you experienceproblem with mole rats?
If Yes, how do you control
them?

Name tea diseases you
know.

Which ones can you
identify?
Name tea diseases in your
farm.

Mites
AphidsMole rats
ScalesOthers (specify
Do not know
Chemicals
Field management
Laws of nature
Other (specify)
Yes
No
Manual trapping
Poison bating
Fumigation with smokefrom Kirinyaga mole machine
Other (specify)
Armillaria root rot
Hypoxylon wood rot
Phomopsis canker
Leaf spots
Others (specify)
None
Armillaria root rot
Hypoxylon wood rot
Others (specify)
None
Armillaria root rot
Hypoxylon wood rot
Do not know

Kirinyaga

Nyambene

Nandi

Nyamira

0
3
41
0
21
35
9
16
75
0
71
29
40
9
9

7
5
21
11
14
56
2
9
89
0
57
43
55
2
0

3
8
28
0
21
40
0
5
87
8
62
38
49
5
8

3
2
26
1
26
42
0
24
75
1
60
40
57
2
0

6
37
1
0
0
1
61
31
1
1
66
36
1
63

5
39
2
0
0
0
59
36
0
0
64
32
0
68

3
8
3
0
0
3
86
5
3
3
87
3
0
97

2
2
1
0
0
3
94
4
0
2
94
6
0
94

Several diseases attack Kenyan tea (Owuor et al 2001). Reasonable percentage of the smallholder
growers in the east of the Rift Valley and only few in the west of the Rift Valley could identify Armillaria
root rot while very few farmers could identify Hypoxylon wood rot of tea (Table 3.18). The majority of
the farmers could not identify any disease of tea. Again a reasonable number of farmers from the eastof the Rift Valley and very few farmers from the west of the Rift Valley reckoned the presence ofArmillaria root rot in their farms. Most farmers did not know if they had any diseases in their farms.

43

ATPS R ESEARCH PAPER 3 (PART II)
Without knowledge of pests and teadisease, it is unlikely farmers can control them. Farmers’ education
on identification and control of pests and disease is urgently required.
3.1.4. Labour use in tea
The main use of labour in tea production is in plucking (harvesting). Although at the inception ofsmallholder tea sub sector in Kenya, it was hoped that the smallholder tea would only be tendered by
the family (husband, wife and children) (M’Imwere 1997, 1999), the production has grown to an
extent that in most farms the family alone cannot cope. Again most children go to school and are notavailable for plucking. Child labour is also discouraged by Kenya laws.
Most smallholder tea producers used hired labour in their farms (Table 3.19). The percentage of
hired labour use in Nyamira district was lower than other districts, which were using about the same
percentage. Most smallholder tea farmers used male and female workers, however, there was alarge percentage of farms in Kirinyaga, Nyambene and Nyamira districts only hiring females. They
reckoned female workers were easier to control than male counterparts. This observation underscoresthe vital role females play in tea production in Kenya. But in Nandi district, there was no farm employing
only females, although 18% of the farms hired only males. This was due to presence of many
immigrant workers from other districts and in most instances the immigrant workers were either only
males or were couples. However, the data from all districts put together demonstrate that the dominant
hired labour in smallholder tea sub sector are females.
Table 3.19: Smallholder tea growers labour use(%) and tea output
Do you hire people to workon your tea enterprise?
If Yes, what sexes are they?
Do you hire children to workon tea enterprise also?
Are there some family
members who work on thetea enterprise?
If Yes, what sexes are they?
Do some of your children
work on the tea enterprisealso?
Who are the dominant tea
workers in this region?
How much tea leaf did you
produce from your farm lastyear?

Kirinyaga

Nyambene

Nandi

Nyamira

Yes
No
Male
Female
Both
Yes
No
Yes
No

77
23
2
23
53
29
71
91
9

73
27
0
14
64
30
70
91
9

71
39
18
0
44
8
92
72
28

55
45
0
14
43
6
94
93
7

Male
Female
Both
Yes
No

10
30
60
49
51

5
21
74
39
61

8
13
79
38
62

7
28
65
51
49

Males
Females
Both
Mean output (kg green
Mean producer price
Plucking cost/kg gl

190
94410.96
25.10
2.77

2
91
7
1979.80
23.28
2.77

56
13
31
2678.33
21.33
2.82

9
70
21
1706.82
21.33
2.48

High percentage of the smallholder farms used family labour either exclusively or in addition to
the hired labour (Table 3.19). Like hired labour, females were the dominant source of family labour.
The data put together show that most smallholder tea is produced by females. The use of children topluck tea was more dominant in Nandi district where 50% of the farmers used their children to pluck

44

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
tea (Table 3.19). In other districts fewer farmers used children. Indeed some farmers noted they were
not using children because they spoiled tea plant and lowered plucking standards.
The tea output varied with districts (Table 3.19) in a similar pattern to the areas under tea. The
mean producer prices also varied in the different districts. This mainly depended on prices realised
at international markets. Generally areas east of the Rift Valley received high producer prices thanareas west of the Rift Valley. Areas that received better producer prices produced better quality blackteas (Owuor and Othieno 1991, Owuor et al 1987, 1988, 1993). Quality is therefore an important
determinant of producer prices. Although quality is affected by many factors including geographicalconditions (Owuor 1995), it is important that efforts are made to improve agronomic and processing
techniques to ensure production of high quality teas.
Plucking costs were highest in Nandi district, followed by Kirinyaga and Nyambene districts andlowest in Nyamira district (Table 3.19). It seems where most farmers used hired pluckers, the cost ofplucking was higher. The plucking cost was therefore demand driven.
3.1.5. Extension services and training
The success in farmers knowing, adopting and adapting recommended tea production technologies
is largely dependent on the extension system reaching the farmers and educating them on ways of
improving tea production and productivity. An assessment of the KTDA extension system was done tounderstand its weaknesses which maybe impeding effectiveness in technology diffusion. Many farmers
noted most of the extension staff visited their farms (Table 3.20). However, in Nandi district more thanhalf of the farms were not visited by extension staff and in Nyambene and Nyamira districts about 37%of the farms were not visited, while in Kirinyaga district 23% of the farms had not been visited. Even in
Kirinyaga district where most farms had been visited, the percentage of farmers not visited during theyear was substantial. Indeed there were farmers who had never, ever been visited by any extension
staff before. There were more farmers visited in Kirinyaga district followed by Nyamira district. The
visits to farms in Nandi and Nyambene districts were about equal (Table 3.20). It is noted that wherethe visits were more, tea productivity was also higher. This lack of adequate technology transfer
through extension staff visits is an aspect impeding tea production in the smallholder tea sub sector.
During the visits in Kirinyaga, Nyambene and Nyamira districts, the extension staff advised the growers
on best methods of growing tea, especially the current technologies applied (Table 3.20). Most of thevisits to the farmers were for undisclosed reasons. It is necessary that extension visits are planned andmade such that they are beneficial to both the farmers and extension staff, and are intended fortechnology transfer purposes.
Apart from attending tea ‘barazas’(public meetings), most farmers had never attended any formal
course on tea production (Table 3.21). The percentage of those who had not attended any course
varied slightly between the districts. Whenever there was a baraza to educate farmers on tea production
technologies, it is mostly the owners of the farms, interpreted to mean the “man of the home” whoattended the meetings. But in several cases both spouses attended. In Nyambene and Nandi districts,
in most cases the person who attended the meetings never passed information learnt to the farmworker. These new knowledge were therefore a waste as the wrong persons were trained and theinformation never reached the farm operators. The training techniques should be changed so thatthe correct personnel are trained to ensure technologies are reaching the intended group who caneffect change in production patterns.

45

ATPS R ESEARCH PAPER 3 (PART II)
Table 3.20: Assessment of extension services and training
Do agricultural extension
Yes
officers visit your farm? (%)
No
If Yes, how many times do
Monththey visit you per (Number)Year
Number of visits last year. (number) 9
Do they advise you on theYesbest methods of growingNotea? (%)
Do they advise you on theYescurrent technologies e.g.
Nofertilizer application, plucking methods etc for this area? (%)

Kirinyaga

Nyambene

Nandi

Nyamira

77
23
2
12
3
77
23

64
36
1
4
5
57
43

49
51
1
5
7
41
59

62
38
2
7

77
23

57
43

41
59

54
46

55
45

Whenever the extension staff visited the tea farms, they usually met the owner of the farm “readhusband” or both husband and wife. However, in many farms, they were met by the wives, except in
Nandi district (Table 3.21). It is likely that the people meeting the extension staff at the farm level were
not the farm operators and were not imparting any technologies leant through the visits to the farmoperators. Most of the technologies therefore do not reach those who can profitably use them toimprove tea productivity and production. It is important that a policy is developed and put into practicethat facilitates the farm operators to easily receive information on tea production technologies. Thisshould be done fast as most farmers do not want their workers to have more knowledge than them.
However, although the farmers would like to monopolise knowledge, their knowledge does nottransform to tea production.
Table 3.21: Assessment of smallholder tea growers training (%) on tea production technologies
Have you ever been trainedon tea production?
If there is a baraza to
educate farmers on better
technologies concerningtea production who
attends it?

YesNo
Owner of the farm
Spouse (wife)
Employed manager
One of the workers
One of the children
Both husband & wife
No oneYes
No
No oneIs the person who attends
tea educational barazas ortraining the same one who
manages the farm?
Does the person who
Yesattends the training pass on
No
new ideas learnt at training to the rest of tea workers?
When the agricultural
Owner of the farmextension officers comeSpouse (wife)around on the farm to give
Employed manager
advice on tea production
One of the children
matters, whom do they
Both husband & wife
advise?
Not visited
Does the person pass onYes
the information to the rest ofNo
the tea workers?

Kirinyaga

Nyambene

Nandi

Nyamira

26
74
51
14
2
0
6
20
7
83
10
7

9
91
64
9
2
0
0
14
11
68
23
9

18
82
64
8
0
0
8
8
12
67
26
7

5
95
13
21
2
1
7
23
33
81
15
4

84
16

50
50

58
42

62
38

31
22
1
2
27
17
74
1

27
16
0
5
27
25
61
14

33
8
0
5
21
33
49
18

25
21
1
4
31
18
63
13

46

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
Some farmers voiced concern that when the farm operators became more aware of the tea
production technologies, they became more marketable and difficult to maintain. Thus the individual
farmers looked at training farm workers as an undertaking that benefits their neighbours/competitors
rather than themselves.
Few farmers noted that there were different tea production technologies not favoured by theworkers (Table 3.22). However, most tea farmers felt that all tea recommended production technologies
were useful. The basket for carrying plucked green leaf is one implement that many farmers, especiallyin Nandi district felt the male farm operators did not like carrying on their heads or back. This arises
from cultural beliefs that a man should not carry such things on their heads. It is advisable to develop
some farm operator/user friendly carrying equipment for the use.
Table 3.22: An assessment of acceptability (%) of production technologies
Kirinyaga
Are there some tea
Yes34
recommendations notNo46
favoured by tea farmers and the workers in general?
If Yes, which tea
Fertilizer recommendationss 2
recommendations don’t
Weed control recommendation 0
augur well with the
Plucking methods
6
community here?
Plucking equipment e.g. baskets
Other specify
14
Do male workers here haveYes
33
a problem of carrying tea
No67baskets on their heads or back?

Nyambene

Nandi

Nyamira

23
77

46
54

16
84

0
0
0
20
0
41
59

0
0
0
27
5
64
36

0
1
8
46
9
23
77

1

3.1.6. Tea production and extension policies
The success of tea production in the smallholder tea sub sector is heavily dependent on appropriate
production technologies reaching the farmers, especially the farm operators. This can only happen
if correct production and technology transfer policies are put in place. Farmers were assessed on
their perception of the tea production and extension policies of the KTDA. The extension staff visited
most farms using their own schedules and rarely on invitation (Table 3.23). This probably is because
the farmers’ knowledge on technology and even how to acquire the technology is so low that most ofthem do not know when they have problems in their farms. Alternatively the extension staff are too few
so they do not honour invitations. As an alternative since the extension staff were not directly under
KTDA management they adopted negative attitudes and the farmers could not do anything to change
the situation. Consequently the farmers described the system as long, slow, with too few staff,
inadequate and needing overhaul (Table 3.23). Policy makers need to take note of this and makenecessary adjustment.
Most farmers in Nyambene and Nyamira districts felt that getting technical information fromTRFK directly could be useful (Table 3.24). While this is necessary to be done to complement what
KTDA extension service is doing, as it will ensure farmers get their problems solved faster, it is also
necessary that TRFK strengthens its advisory system to meet farmers expectations. Indeed it wasobserved under sources of technologies the farmers use that no farmer indicated he/she ever learnt
any of the techniques from TRFK.

47

ATPS R ESEARCH PAPER 3 (PART II)
The results on the response to TRFK reveals other problems. First it shows that the farmers are
not feeling the effectiveness of the TRFK extension services. It is necessary that the TRFK changes
its present approach to the farmers. At present farmers are visited on recommendation of the KTDA
extension staff. In this study however, farmers were randomly selected. It is likely that when extension
staff select farmers to be visited, visits are made only to farmers who are either doing very well as ashow of the extension staff effectiveness or farmers are selected who are close to the main road. Boththese techniques do not allow visits to farmers who are in real need of tea production technologies.
It is necessary that apart from visiting farmers with problems as identified by the extension service of
KTDA, TRFK extension service needs to make its own regular visits in which the farmers are selected
randomly. Again, the staffing of the TRFK extension services has been lean over the years. Most of thevisits are therefore made by scientists who go out to solve specific problems, at the invitation of KTDA
extension services staff. The TRFK extension staff service needs to be strengthened so that its
effectiveness is felt.
Table 3.23: Views of smallholders (%) on the KTDA extension system.
Kirinyaga
How do you get field extension staff to visit your farm?

By inviting them
6
Using own schedule94
No response0
How would you describe the existing extension structure in tea industry?
i) It is:
Long
59
Short
41
ii) It is:
Quick
39
Slow
61
Iii) Has:
Too many officers
9
Too few officers
91
Current extension system: Adequate for farmers
16
Inadequate for farmers
84
Current extension system: Needs to be continued
33
Needs to be overhauled
61

Nyambene

Nandi

Nyamira

5
77
18

8
64
28

1
81
18

86
14
18
82
11
89
11
89
21
79

74
26
18
82
15
85
3
97
10
90

74
26
23
77
10
90
3
97
15
85

The TRFK sources its finances from the farmers through cess paid to Tea Board of Kenya. But isnoted that very few farmers actually knew they were contributing money to do research (Table 3.24).
This implies they either thought the research technologies being developed for the Kenya tea industry
was being financed by the government or by some donors. The lack of information that they owned
the technologies might have made most farmers feel that it was a privilege getting the technologies
from TRFK. It is necessary to change this view, as it shall make the farmers search for available
technologies as nobody wants to spend money for nothing.
Most farmers recognised the need to have technologies that could help them improve their tea
production and productivity. This they realise can be done through either courses or seminars. The
majority of farmers need courses/seminars on tea production at least once in a year (Table 3.24). For
effectiveness and ease of reaching the farmers they recommended group-training approach. Again
for effectiveness, the farmers suggested a need to transfer the extension staff to be under the factories.
This has since been done and it is hoped the extension services will be more effective as the staff will
now be answerable to the farmers. Thus the new system has increased accountability of the extension
staff to the farmers.

48

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
Table 3.24: Views smallholders (%) on additional sources of technology and methods of transfer.
Should you get direct advice
from TRFK without passing
through KTDA?
Are you aware you arecontributing money to TRFK
to give you advice?
How often should tea
production training be done
for farmers?

Which method of extension
is most effective for you?
Do you think there is need toestablish tea extension
office and staff in each factory?

Kirinyaga

Nyambene

Nandi

Nyamira

Yes
No

50
50

64
36

46
54

67
33

Yes
No

36
64

45
55

21
79

27
73

Once a month
Two time a year

17
26

17
30

8
39

8
27

Thrice a year
Once a year
Once in two years
Once in three years
Once in four years
Other (specify)
Single farmer approach
Group approach
Baraza approach
Other (specify)
Yes
No

10
37
7
0
2
1
26
64
9
1
84
16

5
30
9
0
7
2
21
61
18
0
96
4

5
31
8
5
3
1
26
59
15

22
20
13
0
0
10
12
69
17
2
75
25

51
49

Adequate and timely payment to the farmers is the key to any commercial agricultural production.
Most farmers felt that the payment during the study of Kshs 6 per kg green leaf as minimum guaranteed
payment on monthly basis followed by a second payment (“bonus”) after the tea has been sold to givea full value at the end of financial year was not adequate. The first (monthly) payment was too low to
run their tea business. They suggested monthly payment of KShs 11 to 12 per kg green leaf (Table
3.25). This payment mode has since been adjusted to KShs 7.50 and it is likely the amount may still
be inadequate to run the tea farms. It is necessary that the rate of payment to farmers be objectively
worked out to enable the farmers to produce tea more effectively.
Generally, farmers in the west of the Rift Valley and in Nyambene recommended that second
payment should be done once at the end of the financial year, while only 26% of farmers in Kirinyaga
district preferred this mode of payment. The farmers liking this system observed that it helped them tosave money (Table 3.25). Most of the farmers who did not like this mode of payment because the firstpayment was too low and therefore they wanted more regular payment of part of the bonus to meet therecurrent costs of running the tea farms. Consequently most farmers wanted a payment mode withhigher first (monthly) payment followed by second (bonus) payment at six months intervals (Table
3.25). KTDA has been making this mode of payment lately.

49

ATPS R ESEARCH PAPER 3 (PART II)
Table 3.25: Views of smallholders on green leaf payment policy.
Kirinyaga
Is the current first green leaf
Yes
10
payment adequate to run
No90
your tea farm? (%)
If No, how much first green
KSh /kg green leaf.
11.84
leaf payment do you think will be adequate?
Should KTDA wait until end
Yes
26of the financial year to makeNo
74
second payment to tea farmers? (%)
If Yes, why? (%)
Help farmers save3
Help farmers earn interest0
Any other (specify)
21
If No, why? (%)
First payment is too low
61
Farmers to save their3
money themselves
Farmers have little
3
confidence in KTDA
Any other (specify)
0
Give suggestion for yourMonthly payment of10
preferred mode of green
total proceeds
1st payment then one
86
2nd payment
1st payment then two
0
2nd payments at six months intervals
1st payment then 2nd
1
payment as soon as net sales are realised
Others (specify)
1Missing (Undecided)
2

Nyambene

Nandi

Nyamira

16
84

10
90

3
97

12.2

11.09

11.16

71
29

62
38

72
28

66
2
0
32
0

56
0
3
28
8

68
0
1
15
3

0

5

2

0
0

0
3

7
1

32

49

47

64

46

41

2

2

10

0
2

0
0

0
0

3.1.7 Causes of low tea production.
Factors which the farmers believed contributed to low green leaf production in the small holder
tea sub sector (Table 3.26) were mainly poor crop husbandry, late supply of farm inputs (fertilizers),
inadequate plucking funds, poor leaf collection programmes, drought, excessive rainfall, cold weather,hail storms, and inadequate factory capacity. Except drought, cold weather, hail storms and too muchrain, most of the other factors were man made and could be minimised by correct policy intervention.
Indeed, the farmers suggested that tea production could be enhanced through extension services
if the number of extension staff was increased (Table 3.26). Also green leaf production in thesmallholder sub sector could be improved by improving first payment, intensifying extension, training
the tea farmers, creating incentives for farmers doing well and improving tea roads (Table 3.26).

50

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
Table 3.26: Assessment of factors contributing and method to overcome low green leaf production andproductivity (%)
What do you thinkcontributes to low leaf
production in smallholder
tea production?

Suggest possible ways of
improving tea extension toenhance leaf production
among smallholders

Suggest possible ways ofenhancing leaf production
in smallholder tea sub-sector

Kirinyaga

Nyambene

Nandi

NyamiraHail storms
Cold weather
Poor leaf collection
programme
Poor crop husbandry
Inadequate extension
services
Late inputs supply(fertilizers)
Inadequate funds forplucking
Drought
Too much rain
Inadequate factory
capacity
Others (specify)
More extension staff
Intensify supervision ofextension staff

4
20
6

0
7
32

18
8
49

57
8
62

37
9

66
34

77
56

53
47

46

39

51

42

41

27

26

36

14
11
3

25
5
2

10
3
3

42
2
2

4
53
20

21
46
5

0
26
35

2
53
10

Transfer extension
officers to KTDA
Others (specify)
Missing (No suggestions)Improve first payment
Intensify extension
services
Hold more regularseminars
Avail farm inputs readily
Avail farm inputs tofarmers based on tea area
Create incentives forfarmers doing well
Expand tea factories
Improve tea roads
Others (specify)

23

11

10

16

0
4
73
26

36
2
77
64

28
0
72
69

18
0
71
64

33

46

62

63

54
24

41
16

46
10

52
7

20

30

33

25

1
33
3

7
43
9

3
74
10

5
76
8

3.1.8. Frequency statistics on technical knowledge of farmers. Testing of hypotheses
The results of frequency statistics for the smallholder tea farmers were used to test the
hypotheses that: (i)less than half of the smallholder tea farmers have knowledge of tea production technologies
identified.
(ii)
in more than half of the smallholder tea farms, training on tea husbandry and extension
services are directed to the farm owners and not to the personnel doing actual tea work.
(iii)
in less than half of the smallholder tea farms, the farm owners do not have adequate time totrain their workers after attending tea production trainings.
(iv)
that there are some recommended technologies which are not culturally acceptable foruse in some regions;

ATPS R ESEARCH PAPER 3 (PART II)v)

that more than half of the smallholder tea farmers have no access to credit to purchase therecommended inputs or where the inputs are available on credit, they do not reach thesmallholder on time;
Table 3.27 shows the quantifiable technologies considered in each district, the respective
responses and percent responses. Figure 3.1 shows the summary of the percentage of research
recommendations below/above 50% responses. The results show that amongst the technologies
identified, 46, 58, 52 and 65% in Kirinyaga, Nyambene, Nandi and Nyamira Districts respectively, had
responses, which were less than half of the farmers interviewed. Therefore, the hypothesis that lessthan half of the farmers have adequate knowledge of tea production technologies identified was
accepted except for Kirinyaga District, which had 46%. Nevertheless, it was very close to half of theidentified tea production technologies where the farmers responded. The general observation wasthat the percentage of the technologies in which less than half the farmers responded was over 50%
in three of the four districts hence the hypothesis was accepted. Thus, a high percentage of farmers
do not have adequate knowledge of tea production technologies.
The second hypothesis tested was that in more than half of the tea farms, training on tea
technologies and extension services are directed to the farm owners and not to the personnel doing
the actual tea work. The results (Table 3.21) show that 83, 68, 67 and 81% of farms in Kirinyaga,
Nyambene, Nandi and Nyamira districts respectively, the person who attends “barazas” and tea
training is the same person who manages the farm. Table 3.1 shows that more than 50% of the farms
are owned and managed by the owners. The inference drawn from the results is that in more thanhalf of the farms, training on tea production technologies and extension services are directed to thefarm owners and not to the farm workers. Hence the hypothesis was accepted.
The results in Table 3.21 show that 84, 50, 58 and 62% of farms in Kirinyaga, Nyambene,
Nandi and Nyamira districts, respectively, the person who attends the training passes on the newideas learnt at the training or extension services sessions to the rest of the tea workers. The hypothesisthat most of the owners of the tea farms do not have enough time to educate their workers after
attending tea production training was rejected.
The results of the frequency analysis were also used to test the hypothesis that there aresome recommended technologies, which are not culturally acceptable in some tea growing regions.
From the results, (Table 3.22) it was inferred that there is no technological recommendation, which
is significantly unacceptable. However, 64% of male workers in Nyamira District have a problem ofcarrying tea baskets on their heads or backs. It is necessary to develop more user-friendly tea carrying
equipment for these workers.
The frequency statistics results were also used to test the hypothesis that more than half ofthe farmers have no access to credit to purchase the recommended inputs or where the inputs areavailable on credit, they do not reach the smallholder on time. It was deduced from Table 3.17 that avery high percentage of the farmers have access to fertilizer credit. The results further showed thatexcept in Kirinyaga district where the fertilizer supply was timely, in other districts supply was generally
late. This resulted in late application of the fertilizer and it is unlikely the applied fertilizer benefited tea
production during the season as it was applied after the rains had ended. Hence contributing to low
yields in these districts.

51

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
Table 3.27: Percentage responses for the various recommendations in Kirinyaga, Nyambene, Nandi andNyamira Districts.
Knowledge of soil depth (m)Length of ripping tool (m)Plant density per ha.
Age of shoots for cuttings (months)
Period of stay in nursery (months)
Stem length of cuttings? (cm)Period cuttings should remain in water (minutes)
Width of planting holes (cm)Depth of planting holes (cm)Fertilizer amount put in holes (gm)Height of pruning young tea first time (cm)Length of central stems at first pruning (cm)Height at 1st pruning (cm)Height at 2nd pruning (cm)Height at 3rd pruning (cm)Length of lateral shoots when pegging (cm)Height of central stems when establishingplucking table (cm)Length of lateral shoots when establishingplucking table (cm)
Plucking rounds (Days)
1st pruning height (cm)
2nd pruning height (cm)
3rd pruning height (cm)
4th pruning height (cm)
5th pruning height (cm)
6th pruning height (cm)Fertilizer rates for mature tea (bags/ha)

Kirinyaga

Nyambene

Nandi

N=70

%

N=45

%

N=35

%

NyamiraN

responses

N

responses

N

responses N

responses

8
58
38
41
48
44
30
58
58
21
49
23
14
10
9
47

11
83
54
59
69
63
43
83
83
30
70
33
20
14
13
67

41
21
16
23
28
20
38
38
10
29
10
6
2
2
26

91
51
36
51
62
44
84
84
22
64
22
13
4
4
58

5
33
26
18
25
24
16
35
35
22
30
23
15
13
11
14

13
85
67
46
64
62
41
90
90
56
77
59
38
33
28
36

8
77
49
49
74
76
58
98
97
33
78
52
15
9
8
38

8
73
46
46
70
72
55
92
92
31
74
49
14
8
8
36

41

59

22

49

17

44

40

38

36
70
37
34
30
27
26
6
70

51
100
53
49
43
39
37
9
100

17
44
9
6
6
4
2

38
98
20
13
13
9
4

15
39
20
17
13
9
5

38
100
51
44
33
23
13

43

96

35

90

37
103
34
31
27
10
5
2
104

35
97
32
29
25
9
5
2
98

N=106

%

Figure 3.1: Percentage of research recommedations below/above 50% response by
farmers
65
60

Below 50%
Above 50%

55
50
45

%

52

40
35
30
25
20
Kirinyaga

Nyambene

Nandi

Nyamira53

ATPS R ESEARCH PAPER 3 (PART II)

3.2 Descriptive Statistics on the Level of Farmers’ Application of Agronomic
Recommendations
The results of descriptive statistics are summarized in Tables 3.28 to3.32. The technologicalrecommendations considered for the various districts were: - 26 in Kirinyaga, 24 in Nyambene, 25 inNandi and 26 in Nyamira district. The overall comparative results were shown in Figure 3.2. The
results showed that in the east of the Rift Valley region represented by Kirinyaga and Nyamira Districts,
42 percent and 29 percent of the technological recommendations had an application level which
was significantly different from the research recommendation level. In the west of the Rift Valley
region represented by Nandi District and Nyamira District, 54 percent and 62 percent of thetechnological recommendations had an application level which was significantly different from theresearch recommendation level. Thus, in the east of the Rift Valley 58 percent and 71 percent of thetechnological recommendations in Kirinyaga and Nyambene District respectively, were not significantly
different from the agronomic recommendations. These results imply that in the east of the Rift Valley,
farmers have fairly accurate agronomic information about tea husbandry.
Table 3.28: Testing recommendation level aganist farmers practice level in Kirinyaga District
Knowledge of soil depth (m)Length of ripping tool (m)Plant density per ha.
Age of shoots for cuttings (months)
Period of stay in nursery (months)
Stem length of cuttings? (cm)Period cuttings should remain in water (minutes)
Width of planting holes (cm)Depth of planting holes (cm)Fertilizer amount put in holes (gm)Height of pruning young tea first time (cm)Length of central stems at first pruning (cm)Height at 1st pruning (cm)Height at 2nd pruning (cm)Height at 3rd pruning (cm)Length of lateral shoots when pegging (cm)Height of central stems when establishingplucking table (cm)Length of lateral shoots when establishingplucking table (cm)
Plucking rounds (Days)
1st pruning height (cm)
2nd pruning height (cm)
3rd pruning height (cm)
4th pruning height (cm)
5th pruning height (cm)
6th pruning height (cm)Fertilizer rates for mature tea (bags/ha)

N=70
n

m

s

8
58
38
41
48
44
30
58
58
21
49
23
14
10
9
47

1.206
0.214
8952.24.690
10.9803.428
40.12021.19732.35314.05018.16334.15235.60748.25057.00049.830

41
36
70
37
34
30
27
26
6
70

u

Cal
T

Criticaltc

Test

Decision

0.845 2.00.110
0.6
1727.240 11000
2.120
6.0
2.250
10.5
2.846
3.25
61.980 30.0
6.620
25.0
14.641 45.0
13.150 15.0
7.320
15.0
16.537 30.0
15.569 28.0
17.323 40.0
24.668 50.0
16.714 57.5

-1.766 -2.306-26.39 -2.010-7.212 -2.023-3.908 2.021
1.463 2.012
0.409 2.019
0.879 2.042-4.371 -2.004-6.519 2.004-0.323 2.080
2.994 2.011
1.178 2.069
1.762 2.145
1.429 2.228
0.803 2.262-3.112 2.014

t>-tc
t<-tc
t<tc
t<tc
t<tc
t<tc
t<tc
t<-tc
t<-tc
t<-tc
t<tc
t<tc
t<tc
t<tc
t<tc
t<-tc

Not Diff.
Different
Different
Different
Not Diff.
Not Diff.
Not Diff.
Different
Different
Not Diff.
Different
Not Diff.
Not Diff.
Not Diff.
Not Diff.
Different

48.70719.913

50.0

0.411

2.021

t<tc

Not Diff.

59.097
10.94043.32447.27249.24252.18551.96247.91723.15517.5081.910
12.68413.60015.24517.37018.441
20.27416.393

57.5
8.0
45.0
50.0
55.0
60.0
65.0
70.0
14.0

0.540 2.029
12.786 1.997-0.793 2.031-1.152 2.038-2.034 2.042-2.294 2.052-3.535 2.056-2.436 2.447-4.639 1.997

t<tc
t<tc
t<-tc
t<-tc
t<-tc
t<-tc
t<-tc
t<-tc
t<-tc

Not Diff.
Different
Not Diff.
Not Diff.
Not Diff.
Different
Different
Not Diff.
Different

54

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEAIn the west of the Rift Valley however, 54 percent and 62 percent of the technologicalrecommendations in Nandi and Nyamira respectively had an application level, which was significantly
different from the agronomic research recommendation level. Thus, only 46 percent and 38 percentof the technological recommendations in Nandi and Nyamira Districts respectively were notsignificantly different from the agronomic recommendations. These results imply that the level ofaccurate technology adoption among smallholder farmers in west of the Rift Valley region is relatively
low.
For the whole sample, 62 percent of the technological recommendations had applicationlevels, which were significantly different from the research recommendation levels in the four districts.
As a result, low productivity of the green leaf in the smallholder sector is inevitable if only 38 percentof the agronomic research recommendations are fairly applied accurately on the farm. These
results were used to test the hypothesis that more than half of the smallholder tea farmers have not
adopted the recommended levels for each identified technology. The results revealed that 62 percentof the technologies were applied inaccurately. Therefore, the hypothesis was accepted.
Table 3.29: Testing recommendation level against farmers’ practice level in Nyambene District

Length of ripping tool (m)Plant density per ha.
Age of shoots for cuttings (months)
Period of stay in nursery (months)
Stem length of cuttings? (cm)Period cuttings should remain in water (minutes)
Width of planting holes (cm)Depth of planting holes (cm)Fertilizer amount put in holes (gm)Height of pruning young tea first time (cm)Length of central stems at first pruning (cm)Height at 1st pruning (cm)Height at 2nd pruning (cm)Height at 3rd pruning (cm)Length of lateral shoots when pegging (cm)Height of central stems when establishingplucking table (cm)Length of lateral shoots when establishingplucking table (cm)
Plucking rounds (Days)
1st pruning height (cm)
2nd pruning height (cm)
3rd pruning height (cm)
4th pruning height (cm)
5th pruning height (cm)Fertilizer rates for mature tea (bags/ha)

N=45 M
n

S

41
21
16
23
28
20
38
38
10
29
10
6
2
2
26

0.201
8755.19
5.25
14.6504.256347.15023.34239.342
9.200
21.69350.00037.83348.50051.00059.596

22
17
44
9
6
6
4
2
43

µ

Cal
T

Criticaltc

Test

Decision

0.122
0.6
1606.310 11000
1.440
6.0
5.560
10.5
1.986
3.25
47.290 30.0
10.733 25.0
19.250 45.0
9.390
15.0
9.332
15.0
19.978 30.0
14.247 28.0
4.950
40.0
8.485
50.0
21.129 57.5

-20.619-6.2500-2.017
3.501
2.633
1.581
-0.940-1.788-1.853
3.795
3.003
1.543
1.717
0.118
0.496

2.019
2.080
2.120
2.069
2.048
2.086
2.023
2.023
2.228
2.045
2.228
2.447
4.303
4.303
2.056

t<-tc
t<-tc
t>-tc
t>-tc
t>tc
t<tc
t>-tc
t>-tc
t>-tc
t>tc
t>tc
t<tc
t<tc
t<tc
t<tc

Different
Different
Not Diff.
Different
Different
Not Diff.
Not Diff.
Not Diff.
Not Diff.
Different
Different
Not Diff.
Not Diff.
Not Diff.
Not Diff.

47.95515.32050.0-0.612

2.074

t>-tc

Not Diff.

59.35310.98046.94453.66758.75061.25050.00016.57312.262
3.020
8.582
7.394
7.374
13.76914.142
11.830

57.5
8.0
45.0
50.0
55.0
60.0
65.0
14.0

0.604
6.471
0.476
1.109
1.137
0.157
0.131
1.410

2.110
2.017
2.262
2.447
2.447
2.776
4.303
2.018

t<tc
t>tc
t<tc
t<tc
t<tc
t<tc
t<tc
t<tc

Not Diff.
Different
Not Diff.
Not Diff.
Not Diff.
Not Diff.
Not Diff.
Not Diff.

55

ATPS R ESEARCH PAPER 3 (PART II)
Table 3.30: Testing recommendation level against farmers’ practice level in Nandi District
N=39

m

s

µ

n

Knowledge of soil depth (m)Length of ripping tool (m)Plant density per ha.
Age of shoots for cuttings (months)
Period of stay in nursery (months)
Stem length of cuttings? (cm)Period cuttings should remain in water (minutes)
Width of planting holes (cm)Depth of planting holes (cm)Fertilizer amount put in holes (gm)Height of pruning young tea first time (cm)Length of central stems at first pruning (cm)Height at 1st pruning (cm)Height at 2nd pruning (cm)Height at 3rd pruning (cm)Length of lateral shoots when pegging (cm)Height of central stems when establishingplucking table (cm)Length of lateral shoots when establishingplucking table (cm)
Plucking rounds (Days)
1st pruning height (cm)
2nd pruning height (cm)
3rd pruning height (cm)
4th pruning height (cm)
5th pruning height (cm)Fertilizer rates for mature tea (bags/ha)Cal

Critical

T

tc

Test

Decision

5
33
26
18
25
24
16
35
35
22
30
23
15
13
11
14

18.4500.279
9564.08
3.360
10.8804.335
110.0023.00
28.97010.14024.86445.12727.28034.65041.28037.20026.4580.126
1630.53
1.490
3.440
1.401
174.36
9.850
13.00
9.640
17.78515.528
7.440
6.450
7.890
12.930

2.0
0.6
11000
6.0
10.5
3.25
30
25
45
15
15
30
28
40
50
57.5

16.45 2.776-14.478 2.017-4.403 2.060-7.305 2.110
0.541 2.064
3.714 2.069
1.777 2.131-1.184 2.034-7.190 2.034-2.310 2.080
29.867 2.045
4.569 2.074-0.362 2.145-2.873 2.179-3.495 2.228-5.661 2.160

t>tc
t<-tc
t<-tc
t<-tc
t<tc
t>tc
t<tc
t>-tc
t<-tc
t<-tc
t>tc
t>tc
t>-tc
t<-tc
t<-tc
t<-tc

Different
Different
Different
Different
Not Diff.
Different
Not Diff.
Not Diff.
Different
Different
Different
Different
Not Diff.
Different
Different
Different

17

41.14011.90050.0-2.978 2.120

t<-tc

Different

15
39
20
17
13
9
5
35

52.58010.03048.14054.09055.23056.06058.08012.68616.8002.440
11.86011.630
7.010
8.870
7.840
5.439

57.5
8
45
50
55
60
65
14

-1.096 2.145
5.129 2.025
1.154 2.093
1.407 2.120
0.114 2.179-1.256 2.306-1.765 2.776-1.409 2.034

t>-tc
t>tc
t<tc
t<tc
t<tc
t>-tc
t>tc
t>-tc

Not Diff.
Different
Not Diff.
Not Diff.
Not Diff.
Not Diff.
Not Diff.
Not Diff.

Figure 3.2: Percent numberof technological recommendations different/not different
from farm application level
75

Different65

Not different

Percent

55
45
35
25
15
Kirinyaga

Nyambene

Nandi

NyamiraAll districts

56

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
Table 3.31: Testing recommendation level against farmers’ practice level in Nyamira District
N=106

m

s

µ

n
Knowledge of soil depth (m)Length of ripping tool (m)Plant density per ha.
Age of shoots for cuttings (months)
Period of stay in nursery (months)
Stem length of cuttings? (cm)Period cuttings should remain in water (minutes)
Width of planting holes (cm)Depth of planting holes (cm)Fertilizer amount put in holes (gm)Height of pruning young tea first time (cm)Length of central stems at first pruning (cm)Height at 1st pruning (cm)Height at 2nd pruning (cm)Height at 3rd pruning (cm)Length of lateral shoots when pegging (cm)Height of central stems when establishingplucking table (cm)Length of lateral shoots when establishingplucking table (cm)
Plucking rounds (Days)
1st pruning height (cm)
2nd pruning height (cm)
3rd pruning height (cm)
4th pruning height (cm)
5th pruning height (cm)
6th pruning height (cm)Fertilizer rates for mature tea (bags/ha)Cal

Critical

T

tc

Test

Decision

8
77
49
49
74
76
58
98
97
33
78
52
15
9
8
38

1.950
0.202
7798.86
5.350
11.3204.884
62.62017.10130.61618.21
18.88348.07719.87027.22040.25039.276

0.923
2
0.053
0.6
3230.81 11000
2.710
6
2.910
10.5
4.997
3.25
101.89 30
7.018
25
11.356 45
18.250 15
11.375 1519.419 30
6.650
28
8.900
40
14.750 50
16.563 57.5

-0.143 2.306-65.113 1.994-6.860 2.016-1.662 2.016
2.408 1.995
2.832 1.995
2.417 1.981-11.086 1.987-12.411 1.988
0.995 2.036
2.995 1.994
6.648 1.987-4.574 2.145-4.061 2.306-1.749 2.365-6.693 2.027

t>tc
t<-tc
t<-tc
t>tc
t>tc
t>tc
t>tc
t<-tc
t<-tc
t<tc
t>tc
t>tc
t<-tc
t<-tc
t>-tc
t<-tc

Not Diff.
Different
Different
Not Diff.
Different
Different
Different
Different
Different
Not Diff.
Different
Different
Different
Different
Not Diff.
Different

40

48.17517.49950-0.651 2.021

t>-tc

Not Diff.

37
103
34
31
27
10
5
2
104

48.203
10.52047.80953.37158.31562.75053.10047.00016.94917.6252.870
18.53915.26416.11016.420
9.489
4.240
8.263

57.5
8
45
50
55
60
65
70
14

-3.165 2.027
8.868 1.986
0.870 2.034
1.210 2.042
1.049 2.052
2.750 2.062-2.508 2.776-5.424 12.706
3.623 1.986

t<-tc
t>tc
t<tc
t<tc
t<tc
t>tc
t>-tc
t>-tc
t>tc

Different
Different
Not Diff.
Not Diff.
Not Diff.
Different
Not Diff.
Not Diff.
Different

The policy implication is that tea technology transfer and adoption among farmers be
intensified through farmers’ training, demonstrations and field visits in order to give farmers accurateagronomic research recommendations to be applied on the farm. In general, TRFK and KTDA
should create and/or strengthen “Tea Economics and Extension Departments” to co-ordinate anddeal with the problems of technology transfer and adoption in the smallholder sub-sector. The two
departments should conduct tea research in the areas of socio-economics, extension, technology
transfer and adoption, production economics, market and prices, inputs and socio-cultural aspectsof tea. They should also develop modern extension materials to reach farmers more effectively e.g.
small extension pamphlets, send to farmers through green leaf delivery centres, video programs,
television and radio programs to enhance current train and visit, demonstrations and field days
methods of extension.

57

ATPS R ESEARCH PAPER 3 (PART II)
Table 3.32: Recommendation level aganist farmers’ practice level for the four districts
N=259

m

s

µ

n
Knowledge of soil depth (m)Length of ripping tool (m)Plant density per ha.
Age of shoots for cuttings (months)
Period of stay in nursery (months)
Stem length of cuttings? (cm)Period cuttings should remain in water (minutes)
Width of planting holes (cm)Depth of planting holes (cm)Fertilizer amount put in holes (gm)Height of pruning young tea first time (cm)Length of central stems at first pruning (cm)Height at 1st pruning (cm)Height at 2nd pruning (cm)Height at 3rd pruning (cm)Length of lateral shoots when pegging (cm)Height of central stems when establishingplucking table (cm)Length of lateral shoots when establishingplucking table (cm)
Plucking rounds (Days)
1st pruning height (cm)
2nd pruning height (cm)
3rd pruning height (cm)
4th pruning height (cm)
5th pruning height (cm)
6th pruning height (cm)Fertilizer rates for mature tea (bags/ha)Cal

Critical

T

tc

Test

Decision

19
198
134
124
170
172
124
229
228
86
186
108
50
34
30
125

1045
0.19768618.31
4.83
11.61
4.333
60.79
20.07632.25914.08020.09644.66128.65537.50046.36947.238

0.919
0.045
0.102
2437.60
2.310
3.500
3.771
101.100
8.502
14.32814.55011.67118.741
12.722
13.83017.352

2.0
0.6
11000
6.0
10.5
3.25
30.0
25.0
45.0
15.0
15.0
30.0
28.0
40.0
50.0
57.5

2.538 2.093-124.40 1.967-11.263 1.978-5.617 1.979
4.123 1.972
3.753 1.971
3.378 1.979-8.745 1.962-15.067 1.962-0.583 1.991
5.939 1.969
6.648 1.984-4.574 2.016-4.061 2.039-1.749 2.042-6.693 1.979

t>tc
t<-tc
t<-tc
t<-tc
t>tc
t>tc
t>tc
t<-tc
t<-tc
t>-tc
t>tc
t>tc
t<tc
t>-tc
t>-tc
t<-tc

Different
Different
Different
Different
Different
Different
Different
Different
Different
Not Diff.
Different
Different
Not Diff.
Not Diff.
Not Diff.
Different

120

47.32018.93250.0-0.651 1.980

t>-tc

Not Diff.

105
256
100
88
76
50
38
9
241

54.36810.64
46.13851.17354.24055.72152.81449.16716.28517.3362.610
14.51913.721
14.46015.92316.00816.703
7.257

57.5
8.0
45.0
50.0
55.0
60.0
65.0
70.0
14.0

-3.165 1.985
8.868 1.961
0.870 1.987
1.210 1.991
1.049 1.995
2.750 2.016-2.508 2.036-5.424 2.262
3.623 1.961

t>-tc
t>tc
t<tc
t<tc
t<tc
t>-tc
t>-tc
t>-tc
t>tc

Not Diff.
Different
Not Diff.
Not Diff.
Not Diff.
Not Diff.
Different
Different
Different

3.2.1. Mean comparison for the Agro-Ecological zones and regions
The results of mean comparison for the Agro-Ecological zones and regions are presented inTable 3.33, revealed that in east of the Rift Valley tea yields were greater in UM1 zones than in LH
zones. However, the results were not significant at 5 per cent level. In west of Rift Valley, tea yields are
greater in LH zones than in UM1 zones, but the results were also not significant at 5 per cent level.
Therefore, the hypothesis that some smallholder tea is planted in agro-ecological zones not suitable
for tea production resulting in low average yield in the sector was not accepted. This was because no
farmers were found producing tea neither in Upper Highland zone nor below UM1 zone. All farmers
were producing tea either in LH or in UM1 zones and there was no significant difference in tea yields.

58

ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
Table 3.33: Comparison of LH and UM1 tea yields/ha and west and East Rift regions
District
Kirinyaga:
LH
UM1
Nyambene:
LH
UM1
Nandi:
LH
UM1
Nyamira:
LH
UM1
West Rift
East Rift

Mean

Std

N

t

tc

Test

Decision

Results

3898.1944818.536

3720.348
5383.783

31
39-0.844

1.671

t<tc

Non rejection

Not different

6031.536
6144.407

5443.280
6382.189

1430-0.061

1.684

t<tc

Non rejection

Not different

3604.818
2995.213

3503.396
3063.687

20
19

0.579

1.697

t<tc

Non rejection

Not different

7030.096
5682.812
5713.00
8986.00

5819.088
10389.76
6832.702
6969.071

72
34
145
114

0.706

1.657

t<tc

Non rejection

Not different

3.784

1.654

t>tc

Rejection

Different

The comparison between east and west of Rift Valley showed that there was a significant difference in tea yields in kilograms/ha. This meant that East of Rift Valley produces more tea yield per
hectare than west of Rift Valley. The differences could be accounted for by differences in soils,
climate, cultural attitudes and different levels of input utilization. These inputs were: - fertilizer, hiredlabour, family labour, and the number of bushes/hectare on the farm. The comparisons in input use
intensities between east and west of the Rift Valley were shown in Figures 3.3 to 3.6 below. Figure
3.3, shows average fertilizer use intensity in terms of N kg/ha between the two regions

Figure 3.3 Comparison of nitrogen fertilzer use between east and west of the Rift Valley

270
250
230
N 210
k
g
/
h
a

190
170
150
130
110
90
70
East

West
Rift Valley

ATPS R ESEARCH PAPER 3 (PART II)
Different ecological zones and cultural practices require different fertilizer rates. For high yielding
tea, growers are advised to test yield/fertilizer rates under their ecological and cultural practices.
Generally in Kenya, the recommended fertilizer rates range between 100 to 250 kg nitrogen perhectare per year depending on yield performance of a field (Othieno 1988). For smallholder tea,
KTDA/TRFK fertilizer demonstration plots at divisional level in all tea growing areas have shown that
NPKS 25:5:5:5 or NPK 20:10:10 fertilizer rates of up to 150 kg nitrogen per hectare per year are
profitable (Othieno et al 1981, 1983, 1984, Owuor et al 1984). The results revealed that 260.75 N kg/
ha were used in the east of the Rift Valley while 199.13 N kg /ha were used in the west of the Rift Valley.
Fertilizer use in east of the Rift Valley was outside the recommended range while that of the west of
the Rift Valley was within the recommended range but still above the recommended average.
Tea is a labour intensive crop. The tea crop needs both hired labour and family labour. Hiredlabour is necessary in smallholder tea production since it is easier to control and to manage than thefamily labour. Figure 3.4 shows the intensity of labour use between the east and the west of the Rift
Valley. The results showed that almost double amount of hired labour (3770.75 Mhrs/ha) was usedin east of Rift Valley as compared to the west of the Rift Valley (1913.93 Mhrs/ha). Also east of the Rift
Valley smallholders used less family labour (3592.64 Mhrs/ha) than west of Rift Valley (4222.82
Mhrs/ha) smallholders. In total, the east of the Rift Valley tea growers used more labour (7363.47
Mhrs/ha) than west of the Rift Valley (6136.75 Mhrs/ha) growers. Thus production intensity is higher
in the east than in the west of the Rift Valley
The number of tea bushes per hectare was relatively lower in east than in the west of the Rift
Valley (Figure 3.4). The average number of tea bushes/ha in the east of the Rift Valley wasapproximately 8010 while that in the west of the Rift Valley was 8460. These physical efficiency
measures indicate that east of the Rift Valley is better than west of the Rift Valley in terms of technicalefficiency of resource use. Ultimately, east of the Rift Valley realised greater output of green leaf per
hectare as shown in Figure 3.6. Thus with greater use of fertilizer and hired labour which is easier tosupervise than family labour, east of the Rift Valley had higher output/ha of tea than west of the Rift
Valley. It is therefore recommended that farmers in the west of the Rift Valley should improve on theirresource use intensities in order to enhance efficiency and increase green leaf productivity. Most of
the husbandry activities should be geared towards increasing green leaf output per hectare or per
bush.

59

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ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
Figure 3.4: Labour use (man hours/ha/year) in the East and West of the Rift Valley.

(

7000

)

m h
L a a
a n /
b h y
o o e
u u a
r r r
s
/

East

6000

West

5000
4000
3000
2000
1000

Hired

FamilyTotal

Labour category

Figure 3.5: Average number of bushes per hectare in the east and west of the Rift
Valley8500
B 8400u 8300s
h 8200e 8100s 8000/h 7900a 7800
7700
East

West
Rift Valley

ATPS R ESEARCH PAPER 3 (PART II)
Figure 3.6: Average green leaf output (kg gl/ha/year) in the East and West of the Rift
Valley

9000
8500
8000
k 7500g

7000

g
l 6500/h 6000
a

5500
5000
4500
4000
East

West
Rift Valley

3.2.2. Gross margin and break-even price analyses of the tea enterprise
The results of gross margins (Table 3.34) and break-even price analyses of the tea enterprise showedthat in the short run, smallholder tea production under the current production system is economically
viable.
The tea enterprise is able to cover all the variable costs and has a positive return to depreciation,
management and risk. The gross margin per hectare, per man-day and per bush can be assessed in
the presence of other figures for comparison e.g. from other countries or for competing enterprises.
For example, small-scale dairy keeping is one of the main competing enterprises in the tea growing
zones in the east of the Rift valley region. The gross margin per man-day of the average dairy farm in
Kiambu District in east of the Rift valley region was found to be KShs. 68.20 (Kilungo 1998). The
average tea enterprise gross margin per man-day for the east of the Rift valley region was found to be
KShs. 210.11. Hence the tea enterprise earns more return per man-day than in the dairy enterprise.
On the basis of this comparison, a decision can be made on how much labour to allocate to the tea
enterprise and the dairy enterprise so as to maximize profits.
The results further revealed that there was a noticeable difference between east and west of the
Rift Valley regions. For the four measures of efficiency considered, east of the Rift Valley region was
better than the west of the Rift Valley region. This could be explained by the differential resource use
intensities between the two regions as shown in Table 3.35.

61

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ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
Table 3.34: Gross margins for smallholder tea sub-sector in Kenya.
Items

Districts/regions
Kirinyaga Nyambene Nandi

Area under tea(ha)0.51Labour-man-days/yr
253.03
Average tea bushes/farm3222
Tea income
Tea output (Kg)4410.96
Producer Price (KShs)
25.10
Tea output value (KShs)
110709.29
Variable costs (KShs)
Fertilizer
10024.70
Weed control
38.14
Pest control
113.40
Disease control
11.43
Plucking cost
12160.30
Variable Costs (VC)
23193.60
Interest (20% VC)
4638.72
Total Variable Costs (TVC)
27286.60
Gross margin/year (KShs)(GM=TOV-TVC)
83422.70
Gross margin per hectare/yr 164574.30
Gross margin per man day/yr 329.70
Gross margin per bush/year 25.90

NyamiraEast Rift

West Rift

All Farms

0.40
366.812835

0.73
381.954867

0.33
265.312534

0.47
298.133063

0.44
295.923156

0.45
296.893115

1979.8023.30
46091.61

2678.36
21.33
57121.36

1706.9321.33
36414.02

3472.6124.40
84721.36

1968.2121.33
41983.97

2630.3822.70
59659.70

6368.80
13.64
32.73
1.59
5483.73
11900.51
2380.1014280.61

10357.55
92.42
2.86
0.00
7631.99
19591.21
3918.24
22003.10

5377.61
9.62
94.71
0.02
4190.709710.30
1942.06
11614.68

8613.64
28.68
82.24
7.63
9583.36
18834.85
3766.9722082.52

6631.55
29.56
71.58
0.01
5116.27
12090.36
2418.07
14267.05

7524.67
29.16
76.38
3.43
7082.4815153.60
3030.72
17746.84

31810.99
79726.80
86.73
11.22

35118.30
48173.25
91.94
7.22

24799.34
74696.80
93.50
9.80

62638.84
134707.20
210.1120.45

27716.92
62136.50
93.66
8.78

41912.8692933.16
141.17
13.46

Table 3.35: Resource use intensities between East Rift Valley and West Rift Valley.
RegionEast Rift Valley
West Rift Valley

Fertilizer(Bags/ha)
20.86
15.93

Hired Labour(Man-days/ha)
471.35239.24

Input use per hectare
Family Labour
Total Labour(Man-days/ha)(Man-days/ha)
449.08920.43527.85767.09Tea Bushes/farm(No. of Bushes/ha)
8010
8460

The results showed that smallholder tea farmers in the East of the Rift Valley use resources more
intensively than those in the Western of the Rift Valley. The farmers from the East of the Rift Valley used
more fertilizer bags per hectare than farmers from the West of the Rift Valley. They also used more ofhired labour; which is easier to control than family labour, thus enhancing labour use efficiency. The
numbers of tea bushes were fewer in Eastern region than in the Western region. As a result of greater
resource use intensity and efficiency in the Eastern region, total production and productivity was
higher than in the Western region. It is therefore recommended that West of the Rift Valley smallholder
tea farmers should improve on resource use efficiency in order to increase tea productivity. The
response by the farmers in the East of the Rift Valley can be improved by increasing the number ofbushes per hectare through intensive in filling programme.
Table 3.36 shows the results of break-even analysis. The break-even price was calculated forevery individual farm by dividing total variable costs by the total tea output delivered per year. A mean
price for all the farms was then computed. A histogram with normal curve was plotted for the breakeven price variable for each district and region. The outliers were knocked out of the sample before
computing the mean break-even price. This reduced the sample sizes. The results indicated that,the break-even price of tea for all farms in 1998/99 is approximately KShs. 7.50.

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ATPS R ESEARCH PAPER 3 (PART II)
The results of the break-even analysis were used to find out if there was any significant difference
between the computed break-even price and the current monthly payment of green leaf. The test
results showed that the computed t was greater than the critical t in all the districts and regions. There
was a significant difference between the computed break-even price and the monthly payment ofgreen leaf in the smallholder sector. This means that the 1998/99 monthly payment of Kshs 6.00 per
kg green leaf did not adequately meet the recurrent costs of tea production and could be contributing
to low green leaf output. Although this price has been adjusted to Kshs 7.50 per kg green leaf for the
1999/2000 crop, the adjustment has been accompanied by rise in production costs. Thus this levelof payment may still be lower than break-even point. Frequent farm surveys should therefore be done
to determine tea production costs and returns. The break-even price computed from the surveys andthe subsequent tea enterprise analysis shall enable policy makers in the industry to make pricedecisions based on facts taking into account the various dynamic changes in the industry. Indeed,adequate payment of the farmers will improve green leaf output.
Table 3.36: Break-even analysis results
Items

Kirinyaga

District/Region
Nyambene Nandi
NyamiraEast Rift

West Rift

All Farm

Monthly Price
Break-even price
N
T
tc
Test
Decision
Result

6.00
7.11
66
2.830
1.998
t > tcRejectDifferent

6.00
7.61
39
3.141
2.025
t > tcRejectDifferent

6.00
7.20
105
4.062
1.985
t > tcRejectDifferent

6.00
7.88
113
6.480
1.981
t > tcRejectDifferent

6.00
7.47
218
7.475
1.977
t > tcRejectDifferent

6.00
8.22
24
4.000
2.064
t > tcRejectDifferent

6.00
7.41
89
4.854
1.991
t > tcRejectDifferent

4

CONCLUSIONS & RECOMMENDATIONSThis chapter gives a summary of the objectives, methodology, results the conclusions and the policy
inference from this study. The policy interventions proposed could if implemented enhance tea
production, productivity and incomes in the study areas and other tea producing districts with similar
conditions and potentialities.

4.1. Conclusions and Recommendations
Several conclusions and recommendations on the assessment of technological adoption and policy
factors impeding the production of green leaf in the smallholder tea farms in the Kenya tea industry
were arrived at. These were as given below: 4.1.1. Assessment of Technological Adoption and Application Levels by the Smallholder
Tea Farmers
1. Most of the smallholder tea farms are managed owners or members of the family, as was hoped
when the smallholder tea sub sector was being established. Generally the key members of thefamily unit (husband and wife) made the decisions on the farms. Unlike what used to be on tea
previously, when females (wives) never made important decisions on tea production, the situation
has changed. Gender sensitivity is therefore high in smallholder tea unit and this should be
encouraged.
2. Large percentage of the family members lived permanently on the farms and thus derived theirlivelihood from the tea enterprise. The government must put in place policies that ensure thesmallholder tea production is sustainable as the collapse of the sub sector can lead to highunemployment and loss of livelihood to many Kenyans.
3. Most smallholders were relatively old and were unwilling to subdivide the tea holdings to theirchildren, despite the children doing most of the work on the farms. This creates less incentive forthe youngsters to work on tea farms since their work is paid in kind not by cash and may lower tea
production. A proper study should be done to come out with clear policy on how to deal with thisproblem.
4. The majority of the smallholders had no or low level of education. Passing technical information
through bulletins is unlikely to help technology diffusion in the smallholders tea sub sector. It is
recommended the technologies be disseminated to the smallholder farmers through on farmcourses based on practical demonstrations in which the farmers have contact with the trainers.
This situation is likely to change with time as younger and better-educated farmers are graduallyreplacing the old farmers.

64

ATPS R ESEARCH PAPER 3 (PART II)
5. In each side of the valley, there was higher productivity per bush where farmers had smaller
pieces of total land areas possibly due to absence of competing farm enterprises, as the available
land was too small to support other farm activities and the land forcing the smallholders in theseareas to concentrate on tea production. Where the tea holdings were too large, labour to maintaintea seemed inadequate and farmers possibly were unable to remove the entire crop or to manage
the farms effectively. It is recommended that this be confirmed in a separate study.
6. Productivity was low in districts where farmers had other farm competing enterprises e.g. “miraa’(Kat) in Nyambene, or maize production and dairy farming in Nandi. Detailed socio-economic
study is necessary to evaluate the economic advantages of these individual crops so that farmers
are encouraged to concentrate on crops or farm undertakings giving best returns.
7. The application levels of the technological recommendations were significantly different fromthe research recommendation levels, particularly in the West of the Rift Valley. This implies that
East of the Rift Valley, farmers have fairly accurate agronomic information about tea husbandry.
This should lead to higher production per unit area. Indeed, Kirinyaga district leads in tea
production per unit area in all smallholder tea districts. The relatively low productivity in Nyambene
district is surprising considering the high level of awareness of the technical recommendations
for producing tea. Tea extension services must therefore be intensified in the West of the Rift
Valley. Factors causing low productivity in Nyambene District also should be ascertained.
8. Tea production/productivity was higher in districts where farmers had longer plucking duration
per day as transport schedules are optimised. Leaf collection schedules needs to be drawn in amanner that ensures farmers are plucking for longer durations. KTDA management not the lorry/tractors drivers should decide these schedules. It was noted that in some districts the leaf collection
lorry collected leaf only once in a day from most buying centres, and in some buying centres thiswas done by 11 am.
9. The poor leaf collection programme is mainly due the poor state of the roads. Due to the fact thatthe tea farmers are now paying substantial amount of money to ensure the roads are in a fairstate, accountability should be enhanced so that the money collected is used for the intended
purposes only. Again as tea is a major contributor to the Kenya economy, the government needs
to inject further money to maintain tea roads. Tea roads must be in fair conditions to improvesmallholder tea production/productivity.
10. In some districts extension staff had not not visited more than half of the farms. There is therefore
inadequate technology transfer through extension staff visits. This is an aspect impeding tea
production in the smallholder tea sub sector. It is necessary that an extension service is developedthat ensures that farmers are visited regularly.
11. Apart from attending tea “barazas”(public meetings), most farmers had never attended any formal
course on tea production. Again, whenever there was a baraza to educate farmers on tea
production technologies, it is mostly the owners of the farms who attended the meetings. In mostcases the person who attended the meetings never passed information learnt to the farm worker.
These new knowledge were therefore a waste as the wrong persons were trained and theinformation never reached the farm operators. The training techniques should be changed sothat the correct personnel are trained to ensure technologies are reaching the intended group
who can effect change in production patterns.

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ASSESSMENT OF CONSTRAINTS IN TECHNOLOGY TRANSFER... AN EMPIRICAL ANALYSIS OF ECONOMIC EFFICIENCY AND SUPPLY OF TEA
12. Whenever the extension staff visited the tea farms, they usually met the owners of the farm who
were not necessarily the farm operators. It is likely that the people meeting the extension staff at
the farm level were not the farm operators and were not imparting any technologies learnt
through the visits to the farm operators. Most of the technologies therefore do not reach those
who can profitably use them to improve tea productivity and production. It is important that apolicy is developed and put into practice that facilitates the farm operators to easily receive
information on tea production technologies.
13. The mean comparison for the Agro-Ecological zones revealed that in east of the Rift Valley tea
yields were slightly higher in UM1 zones than in LH zones. In west of Rift Valley, tea yields areslightly higher in LH zones than in UM1 zones. All smallholder tea is planted in agro-ecologicalzones suitable for tea production. The differences in productivity cannot be attributed to agro
ecological zones.
14. The mean comparison between east and west of Rift Valley showed that East of Rift Valley
produces more tea yield per hectare than west of Rift Valley. The differences could be accounted
for by differences in soils, climate, cultural attitudes and different levels of input utilization likefertilizer, labour use and the number of bushes/hectare on the farm. Indeed both fertilizer andlabour use were more intense in the East than West of the Rift Valley. It is therefore recommended
that farmers in the west of the Rift Valley should improve on their resource use intensities in orderto enhance efficiency and increase green leaf productivity. There should be concerted efforts tointensify labour and fertilizer use in the West of the Rift Valley.
4.1.2. Gross Margin and Break-Even Price Analyses
1. The average tea enterprise gross margin per man-day for the east of the Rift valley region higher
than that of dairy enterprise. Farmers can therefore maximise their earnings through tea production
rather than dairy farming. It is necessary that similar gross margins be established for otherenterprises competing with tea in different regions and agro ecological zones.
2. The break-even analysis showed that there was a significant difference between the computed
break-even price and the monthly payment of green leaf in the smallholder sector. This meansthat the 1998/99 monthly payment of Kshs 6.00 per kg green leaf did not adequately meet therecurrent costs of tea production and could be contributing to low green leaf output. Although thisprice has been adjusted to Kshs 7.50 per kg green leaf for the 1999/2000 crop, the adjustment
has been accompanied by rise in production costs. Thus this level of payment may still be lower
than break-even point. Frequent farm surveys must be done to determine tea production costs
and returns. The break-even price computed from the surveys and the subsequent tea enterpriseanalysis shall enable policy makers in the industry to make price decisions based on facts taking
into account the various dynamic changes in the industry. Indeed, adequate payment of the
farmers will improve green leaf output.

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