Agriculture, Ecosystems and Environment 79 (2000) 1–8
Diagnostic indicators of soil quality in productive and non-productive
smallholders’ fields of Kenya’s Central Highlands
Evah W. Murage a , Nancy K. Karanja b , Paul C. Smithson c , Paul L. Woomer b,∗
a Kenya Agricultural Research Institute, PO Box 47811, Nairobi, Kenya
Department of Soil Science, University of Nairobi, PO Box 29053, Nairobi, Kenya
c International Centre for Research in Agroforestry, PO Box 30677, Nairobi, Kenya
b
Received 19 February 1999; received in revised form 7 September 1999; accepted 14 October 1999
Abstract
Food security in the East African Highlands is dependent upon the productivity of lands managed by smallholders who
face difficult challenges in maintaining the fertility of their soils. A study was conducted to identify indicators of soil fertility
status that are consistent with farmers’ perceptions of soil fertility. Physical, chemical and biological properties of soils were
measured from paired fields identified as either productive or non-productive by 12 farmers and compared to findings of a
household survey on soil fertility management. Special attention was given to the potential of different soil organic matter
fractions to serve as diagnostic indicators of soil fertility. Farmers’ criteria for distinguishing soil productivity included crop
performance, soil tilth, moisture and colour and presence of weeds and soil invertebrates. All farmers attributed low fertility
to inadequate use of organic and inorganic fertilisers (100%) and removal of crop residues (100%). Other causes included
continuous cropping (83%), lack of crop rotation (66%) and soil erosion (42%). Productive soils had significantly higher
soil pH, effective cation exchange capacity, exchangeable cations, extractable P and total N and P than non-productive soils.
Total organic C and several estimates of soil labile C including particulate organic C (POC), three Ludox density separates of
POC, KMnO4 -oxidizable C and microbial biomass C were significantly greater in productive soils. Soil microbial biomass
N, net N mineralisation and soil respiration were also significantly higher in productive soils. Farmers’ perceptions of soil
quality were substantiated through soil chemical analyses and soil organic matter fractions provided precise information on
these differences. The similarity of soil physical properties in productive and non-productive fields suggests that differences in
chemical and biological indicators may have resulted, in part, from smallholders’ management and are not inherent properties
of the soils. © 2000 Elsevier Science B.V. All rights reserved.
Keywords: East African Highlands; Humic Nitisol; Soil fertility management; Soil organic carbon
1. Introduction
Soil fertility depletion results from an imbalance
between nutrient inputs, harvest removal and other
losses and is reaching critical proportions among
smallholders in the East African Highlands. Depletion
∗ Corresponding author. Tel.: +254-2-631643.
E-mail address: biofix@arcc.or.ke (P.L. Woomer)
of soil organic matter (SOM) is a contributing factor
in this decline (Kapkiyai et al., 1998) and several different approaches toward soil fertility replenishment
are being explored (Buresh et al., 1997; Woomer et al.,
1997a). Smaling et al. (1993) estimate that 112, 2.5
and 70 kg ha−1 per year of N, P and K, respectively
are lost from agricultural soils of Kenya. Input/output
approaches to understanding nutrient dynamics in
East African smallhold farming systems were further
0167-8809/00/$ – see front matter © 2000 Elsevier Science B.V. All rights reserved.
PII: S 0 1 6 7 - 8 8 0 9 ( 9 9 ) 0 0 1 4 2 - 5
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E.W. Murage et al. / Agriculture, Ecosystems and Environment 79 (2000) 1–8
Table 1
A profile of smallhold farming in the Central Kenyan Highlands based of a survey of 50 households in Kiambu District, Kenya (after
Woomer et al., 1998)
Average farm size
Age of family farm
Household members
Principal crops
Reported crop yields
Farm animals
Farm management practices
Apply animal manures
Confine livestock
Feed crop residues to livestock
Apply fertilizers
Combine organic and fertilizer inputs
Produce domestic compost
Sell organic residues
advanced by accounting for internal nutrient flows
(Van den Bosch et al., 1998; Woomer et al., 1998),
farm resource endowment (Shepherd and Soule,
1998) and specific cropping strategies (Wortmann and
Kaizzi, 1998; Elias et al., 1998). Knowledge of these
systems has advanced sufficiently that candidate land
management options may now be assessed within the
wider context of Integrated Nutrient Management, a
more holistic approach to judicious resource use that
better accounts for farmer preference and opportunities (Deugd et al., 1998).
Typically, smallhold farming systems contain three
enterprise areas (Woomer et al., 1998); ‘outfields’ cultivated in cereal–legume intercrops mainly intended
for home consumption, ‘infields’ of market crops, and
home sites where livestock are confined, manures and
composts accumulated and kitchen gardens cultivated.
Crop residues from these ‘outfields’ are harvested, fed
to livestock and manures applied to crops intended
for market. The nutrient mining of ‘outfield’ soils
results in characteristic patches, plots and fields of
nutrient-deficient crops. Depletion of soil organic matter exacerbates this condition (Kapkiyai et al., 1998).
Smallholders in East Africa recognize special heterogeneity within fields and adjust land management
practices accordingly (Ugen et al., 1993; Ojiem and
Odendo, 1997), however, past studies have not distinguished between inherent differences of soils and
those that result from past land management. The
Kikuyu Red Clay is the most abundant and important
agricultural soil in the Central Highlands of Kenya and
2.3 ha
26 years
10 (two adult males, two adult females and six children)
maize, beans, potatoes, banana, vegetables, coffee, tea
maize 1420, beans 675, potatoes 3800 kg ha−1
five cattle, three goats, two swine, 15 poultry
96%
92%
92%
82%
72%
32%
14%
its successful management greatly affects the prosperity and food security of Kenya (Siderius and Muchena,
1977). Past studies by researchers at the University
of Nairobi have focused upon smallholder land-use in
the Central Highlands of Kenya (Table 1) and the environmental consequences of their most common land
management practices (Woomer et al., 1997b, 1998;
Kapkiyai et al., 1998). The objective of this study was
to characterise differences between soils from productive and non-productive fields that have resulted from
smallholders’ management practices in order to identify soil quality indicators consistent with perceptions
of land quality with emphasis on SOM fractions (Cambardella and Elliot, 1992; Smith et al., 1993; Blair
et al., 1997) and soil biological processes (Woomer
et al., 1994).
2. Methods
2.1. Site description
Twelve farms on the Kikuyu Red Clay, a Humic
Nitisol (Siderius and Muchena, 1977) were randomly
selected from 18 farms in Kiambu District (Kenya)
identified during an earlier on-farm survey of organic
resource management in the Central Kenyan Highlands (Kapkiyai et al., 1998). The natural vegetation
is afromontane forest and evergreen bushland (White,
1983) that has mostly been cleared for cultivation
in the mild, subhumid climate and fertile soils.
E.W. Murage et al. / Agriculture, Ecosystems and Environment 79 (2000) 1–8
Kiambu District is adjacent to Nairobi, with ready access to its markets. A short (eight questions), formal,
open-ended survey was designed that asked farmers to
distinguish between productive versus non-productive
sites on their farms, which crops are cultivated in
productive and non-productive areas, whether or not
and how crop residues, animal manure, mineral fertilizers and other soil inputs are utilized, which crops
and fields are targeted for inputs, and their opinion on
causes and solutions for soil fertility decline.
2.2. Soil sampling
Soils were collected in October 1996 from 12
farms in Kiambu District, Kenya (0◦ –0.5◦ S latitude
and 36◦ 300 –37◦ E longitude, 1350–2400 m asl). Farmers identified productive and non-productive areas
after which 20 soil samples were recovered from the
0–20 cm depth in both types of fields with a small,
narrow shovel. The samples were spread on a clean
polythene sheet, mixed thoroughly and a 7 kg composite sample recovered. A 2 kg sub-sample was removed
from the composite sample for C fractionation and
biological process measurements and stored under refrigeration at 4◦ C. The remaining soil was air-dried,
sieved to 2 mm and stored at ambient temperature for
use in the various physical and chemical analyses.
3
dissolving 0.1 g NaCO3 in 1 l of distilled water) by
end-to-end shaking for 16 h and then collected on a
53 ␮m mesh by wet sieving (Okalebo et al., 1993).
Density fractionation of organic matter using Ludox
at densities 1.13 and 1.37 Mg m−3 was conducted by
the method of Meijboom et al. (1995). Potassium permanganate oxidizable C was determined in 333 mM
KMnO4 according to Blair et al. (1997), with the exception that readings were taken at 24 hr instead of 1 hr
reaction time. Soil microbial biomass C and N was
determined by the chloroform fumigation–extraction
method (Anderson and Ingram, 1993) in a closed desiccator for 24 h at 25◦ C. Potential anaerobic N mineralization was determined according to Anderson and
Ingram (1993) following incubation of saturated soils
for 7 days at 40◦ C. Soil respiration was determined using the potassium hydroxide trapping method of Franzluebbers et al. (1995) over a period of 24 h followed
by titration with standardised HCl using phenolphthalein indicator after addition of barium chloride.
2.4. Data analysis
Data were entered into a spreadsheet software programme with measurements as columns and the 12
farms as rows. The data were then imported into SYSTAT (Wilkinson, 1990) and pairwise t-tests were conducted between the two soil categories.
2.3. Soil analyses
Soil texture was determined using a Bouyoucos hydrometer after Gee and Bauder (1986). Soil pH was
determined in H2 O (1 : 2.5), exchangeable Ca and Mg
by 1 M KCl extraction, and exchangeable K and available P by 0.5 M NaHCO3 +0.01 M EDTA extraction.
Extractable inorganic N was measured by extraction
in 2M KCl, with ammonium determination after Anderson and Ingram (1993). Nitrate was measured by
Cd reduction after Dorich and Nelson (1984) followed
by colorimetric determination of nitrite (Hilsheimer
and Harwig, 1976). Total organic C was determined
by digesting the soil at 130◦ C for 30 min with concentrated H2 SO4 and K2 Cr2 O7 , after which C was determined colorimetrically (Anderson and Ingram, 1993).
Total N and P were determined by Kjedhal digestion
(Parkinson and Allen, 1975).
Particulate organic matter (POM) was recovered
from soils dispersed in pH 10 water (prepared by
3. Results
3.1. Farmers’ diagnostic criteria of land productivity
Farmers’ criteria for distinguishing productive and
non-productive fields included crop performance,
ease of tillage, soil moisture retention and soil colour
(Fig. 1). Indicator organisms included soil macrofauna and invading plants. The presence of earthworms and beetle larvae were regarded as positive
features. Weed species were also associated with land
quality, particularly Commelina benghalensis (L.) in
productive fields and Digitaria scalarum (Chiov.)
and Rhynchelytrum repens (Willd.) C.E. Hubb in
non-productive fields (data not presented).
Different crops were cultivated in productive and
non-productive fields (Fig. 2). Farmers grew market
annuals such as tomatoes (Lycopersicon esculentum
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E.W. Murage et al. / Agriculture, Ecosystems and Environment 79 (2000) 1–8
and sweet potatoes (Ipomoea batatas L.) were frequently established in the less productive areas.
The main causes of productivity decline identified
by farmers were inadequate fertilization (100%), removal of crop residues (100%), continuous cultivation
(83%), monocropping (67%) and soil erosion (42%).
Solutions proposed by the farmers to overcome this
condition included use of farmyard manure (100%),
increased use of inorganic fertilisers (100%), crop rotation (25%) and establishment of contour strips for
soil conservation (42%) (data not presented). Although
most farmers identified continuous cultivation of land
as being a major cause of low fertility status, only 25%
of the farmers considered crop rotation a feasible solution to restore lost fertility and no farmers mentioned
fallow rotations as feasible, suggesting land scarcity.
Fig. 1. Frequency of criteria cited by smallholders in their assignment of land quality status as productive or non-productive in
Kiambu District, Kenya.
L.), potatoes (Solanum tuberosum L.) and green vegetables in rotation with maize (Zea mays L.) in the
fields they considered productive. Maize and bean
(Phaseolus vulgaris L.) intercrops were cultivated in
both soil categories but more so in the productive areas. Fodder crops such as napier grass (Pennisetum
purpureum Schumach.), lucerne (Medicago sativa L.),
3.2. Soil properties in productive and non-productive
soils
Soil physical and chemical properties are presented
in Table 2. Mean clay and sand contents for the two
soil fertility categories were not significantly different
but silt content was significantly higher in productive
soils compared to non-productive soils (p < 0.001).
Productive soils contained more exchangeable cations
and had higher pH than non-productive soils.
Several soil organic matter fractions were significantly greater in the productive soils than in
non-productive soils (Table 3). Carbon fractions in
productive versus non-productive soils were significantly greater in particulate organic C, Ludox heavy,
medium and light C separates and KMnO4 oxidizable
C but not in non-labile C. Soil microbial biomass C
and N, potential anaerobic mineralizable nitrogen and
24 h soil respiration were significantly higher in productive soils than in non-productive soils (Table 4).
4. Discussion
4.1. Soil management decision-making by
smallholders
Fig. 2. Frequency of cropping activities by smallholders in fields
they regard as either productive or non-productive in Kiambu
District, Kenya.
Smallholders in the Central Kenyan Highlands recognized various categories of soil fertility upon which
subsequent management decisions were made. Other
studies demonstrate similar ability of East African
E.W. Murage et al. / Agriculture, Ecosystems and Environment 79 (2000) 1–8
5
Table 2
Soil physical and chemical properties for a Humic Nitisol from productive and non-productive soils (0–20 cm) in 12 farms in Kiambu
District, Kenya
Soil property
(g kg−1 )
Clay
Sand (g kg−1 )
Silt (g kg−1 )
Exchangeable K (cmolc kg−1 )
Exchangeable Ca (cmolc kg−1 )
Exchangeable Mg (cmolc kg−1 )
Extractable NO3 − (mg kg−1 )
Extractable P (Olsen) (mg kg−1 )
Effective CEC (cmolc kg−1 )
Soil pH (1 : 2.5 H2 O)
a
b
Farmers’ category of soil quality
Productive
Non-productive
350
320
330
1.9
13.0
3.4
27.0
55.2
18.3
6.29
380
350
270
1.1
8.3
2.4
17.2
17.1
11.9
5.56
Probabilitya
nsb
ns
<0.001
<0.001
<0.001
<0.001
<0.05
<0.001
<0.001
<0.001
Comparison by Tukey t-test.
ns = not significant.
Table 3
Mean organic carbon content in the different organic matter pools for soils from productive and non-productive sites in selected farms in
Kiambu District, Kenya
Carbon pool
Particulate Organic C (POC, >53 ␮m)
Heavy POC separate (>1.37 Mg m−3 )
Medium POC separate (1.13–1.37 Mg m−3 )
Light POC separate (<1.13 Mg m−3 )
Sum of POC separates
KMnO4 -oxidizable C
Non-KMnO4 -oxidizable Cc
Total soil organic C
Soil fertility status (mg kg−1 )
Productive
Non-productive
5753
222
453
560
1236
19594
4554
24148
3829
103
252
420
801
14848
4420
19268
Probabilitya
<0.01
<0.05
<0.01
<0.05
<0.01
<0.001
nsb
<0.001
a
Comparison by Tukey t-test.
ns = not significant.
c An estimate of non-labile soil C.
b
farmers to assess soil fertility status. Irungu et al.
(1996) conducted an on-farm survey among 30 households in the semi-arid area of Tharaka Nithi District
to assess soil fertility as perceived by farmers and re-
ported that farmers’ opinions considered crop vigour,
invading plants, presence of earthworms and soil
colour. These indicators are very similar to those identified in this study despite being derived from a semi-
Table 4
Biological properties of a Humic Nitisol from productive and infertile soils in 12 selected farms of Kiambu District, Kenya
Carbon pool
Soil fertility status (mg kg−1 )
Productive
Non-productive
Soil microbial biomass C (mg kg−1 )
Soil microbial biomass N (mg kg−1 )
Soil microbial biomass P (mg kg−1 )
N-mineralization (mg N kg−1 per day)
Respiration (CO2 ) (mg C kg−1 per day)
145
64
12
6.1
61.4
103
46
10
3.8
43.7
a
b
Comparison by Tukey t-test.
ns = not significant.
Probabilitya
<0.01
<0.01
nsb
<0.01
<0.05
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E.W. Murage et al. / Agriculture, Ecosystems and Environment 79 (2000) 1–8
arid, midland agroecosystem. Ugen et al. (1993) also
found that small scale farmers’ judgement of soil fertility status in Mpigi District of Uganda was based on
readily observed visible and tactile soil characteristics.
Farmers in Kiambu District manage productive
and non-productive soils differently. Productive sites
were used for production of high value crops, often
due to expectations of more favourable soil moisture
conditions into the dry season. These crops included
tomatoes, bananas, potatoes and green vegetables.
Because of their importance to household diets, beans
and maize were cultivated as intercrops in both productive and non-productive areas of the farm but more
so in productive areas. Plants cultivated in poorer
soils were primarily intended for livestock feed but
most farmers also recognized their importance in the
restoration of soil fertility. Lucerne (M. sativa) fixes
atmospheric nitrogen, sweet potato (I. batatas) protects soil from erosion and napier grass (P. purpureum)
is an indigenous plant used for soil regeneration by
native farmers prior to European contact (Boonman,
1993). This survey and that conducted by Ugen
et al. (1993) among smallholders in Uganda show
that farmers’ preference to grow high value crops
on certain portions of their farm is governed by soil
fertility status but the selection of those crops also
considers social and economic factors.
Our findings reveal that farmers are more likely to
allocate their limited organic resources and fertilizers
to higher value crops in more productive areas of the
farm than to attempt amelioration of fertility-depleted
field areas. Farm ‘outfields’ thereby become mined of
soil nutrients (Smaling et al., 1993) due to a conscious
decision by land managers. Fertilizer application
rates by farmers in Kiambu District are considerably
less than that recommended by agricultural extension
(FURP, 1994; Woomer et al., 1997b). Increased population density has led to land scarcity and necessitated
continuous cultivation of ‘outfields’ by households,
greatly restricting opportunity for fallowing and
resulting in accelerated nutrient depletion (Woomer
et al., 1998) and soil organic matter loss (Kapkiyai
et al., 1998).
4.2. Diagnostic criteria of soil quality
Clay and sand contents did not vary between soil
categories, suggesting that differences in soil prop-
erties result from past soil management rather than
inherent soil properties. Silt, on the other hand, varied between soil categories (Table 2) and differences
were greatest where farmers identified soil erosion as
a cause of soil fertility depletion (data not presented).
This observation is consistent with the general principle described by Brady (1984) that silt is usually the
first mineral component of soil washed away by soil
erosion.
The effective cation exchange capacity (ECEC) for
productive soils was significantly greater than that of
non-productive soils (p < 0.001). If soil ECEC and pH
are mainly determined by soil organic matter content
and the type and amount of clay and the clay content
is not different between the soil categories, then differences in soil pH and nutrient holding capacity (Table
2) mainly arose from changes in the soil organic matter content (Table 3). In contrast, Irungu et al. (1996)
failed to detect significant differences in soil pH between good and poor soils in Tharaka Nithi District,
Kenya, suggesting that soil pH may not be a reliable
indicator of soil fertility status in all smallhold, upland conditions. The similarity of soil physical properties in productive and non-productive fields observed
in this study (Table 1) indicates that differences in
chemical and biological properties (Tables 2 and 3)
have resulted, in part, from land management and not
inherent differences in soil.
Among soil organic carbon pools and fractions, total
organic C was the most sensitive soil quality indicator suggesting that within a narrow range of soil, total
soil organic C may serve as a suitable indicator of soil
quality. Irungu et al. (1996) also reported similar differences between good and poor soils. Other studies in
Africa report that soil organic matter fractionation may
offer further insight into soil fertility changes and the
sustainability of past management history (Woomer
et al., 1994; Barrios et al., 1996; Kapkiyai et al., 1998).
In this study, soils from productive areas contained
significantly greater particulate organic C and its density separates compared to those from less productive
areas. This observation agrees with Kapkiyai et al.
(1998) who compared C fraction changes in different
soil management strategies after 18 years of continuous cultivation in a long-term, on-station experiment
also located on the Kikuyu Red Clay. It is inferred that
C fractionation may provide more precise differentiation of soils and management histories under some
E.W. Murage et al. / Agriculture, Ecosystems and Environment 79 (2000) 1–8
conditions, but the additional time and expense of conducting these procedures compared to analysis of total organic C may not be warranted in assessment of
smallholds in the Central Kenyan Highlands.
Measuring differences in soil C fractions is not as
useful as understanding how these differences have
occurred. In our case, uncertainties of past crop and
soil management histories by smallholders and past
colonial estates and the paucity of soils continuing
under natural vegetation (Woomer et al., 1998) provide
insufficient information with which to compare these
various C fractions. For example, in this study it was
not possible to generate a Carbon Management Index
to compare farms and soils as described by Blair et al.
(1997) for lack of a suitable control condition.
The KMnO4 oxidizable C was significantly different between soil categories, but the recalcitrant,
non-oxidizable C was not. Blair et al. (1997) reported
that labile C as estimated by the KMnO4 oxidation
technique was extremely sensitive to soil management
in Australia. Among the different labile C pools compared in this study, the KMnO4 technique emerged as
one of the most convenient and reliable but serious
disadvantage rests in its destructive nature, not allowing for recovery of a fraction for further characterization. Fractions inferred through KMnO4 oxidation
were consistently much larger than those recovered
through physical procedures, suggesting that these estimates of lability are based upon different soil organic
constituents and are not interchangeable.
7
important, but preliminary, steps in the development
of new solutions appropriate to farmers’ needs and resources. Many adjustments by land managers are under way, particularly in shifting toward less intensive
cultivation of areas undergoing decline but additional
products and technologies that specifically address
land rehabilitation without withdrawing lands from
food production are urgently required. Several simple
field indicators and soil measurements offer potential
in assessing the impacts of candidate interventions as
these are developed for, and adopted by, the smallhold
farming sector in the Central Highlands of Kenya,
particularly those cultivating the Kikuyu Red Clay, a
Humic Nitisol.
Acknowledgements
We are indebted to the 12 smallholders in Kiambu District for their cooperation during soil sampling and household survey. We are grateful to V.
Mbugua, W. Ngului and V. Karari for laboratory
assistance and to P. Mugane for help in sampling
farmers’ fields. Financial support to this research
project was provided by Rockefeller Foundation Forum on Agricultural Resource Husbandry. Additional
funding was provided through a graduate scholarship
to the first author from the German Exchange Service (DAAD). This research was conducted by Ms.
Murage in partial fulfilment of a M.Sc. programme
in the Department of Soil Science, University of
Nairobi.
5. Conclusions
Smallholders in the Central Highlands of Kenya
are aware of the root causes of productivity decline
but are often unable to devote sufficient resources to
lands undergoing degradation. The internal flow of
resources within the farm and allocation of scarce
fertilizers are focused upon improving returns in
areas viewed as having greatest potential productivity, rather than attempting to ameliorate those areas
undergoing decline. This situation results in an intensification of human-induced spatial heterogeneity
characterizable through several physical, chemical and
biological process attributes of soil. The recognition
of land management difficulties by smallholders and
the documentation of consequences by scientists are
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