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Research Article
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Soil Quality Assessment of Cropping Systems in the Western Highlands of Cameroon
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C.M. Tankou,
G.R. de Snoo,
H.H. de Iongh
and
G. Persoon
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ABSTRACT
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Soil nutrient depletion is a major constraint in agricultural development in sub-Saharan Africa. A study was conducted in the Western Highlands of Cameroon to assess soil nutrient balance and identify household and farm characteristics influencing soil nutrient balance using the procedures outlined in the NUTMON Tool-box. This is based on the assessment of the stocks and flows of nitrogen (N), phosphorus (P) and potassium (K) through the inputs (mineral fertilizers, organic inputs, atmospheric deposition and sedimentation) and outputs (harvested crop products, residues, leaching, denitrification and erosion). The gross margin was estimated as gross return minus variable costs while the net farm income was estimated as total gross margin minus fixed costs. The nutrient budgeting results revealed that nitrogen mining was very common at all levels with the greatest mining carried out by intercropping systems which generally received little or no off-farm inputs. High positive nutrient balances were found on market oriented crops. A general picture of the study site showed that only nitrogen was deficient while there were surplus amounts of potassium and phosphorus. The gross margins of green pepper, leeks and onions were negative while the others were positive. Legume intercrops could significantly modify the nutrient balance and sustainability in this region.
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Received: January 14, 2013;
Accepted: March 22, 2013;
Published: June 04, 2013
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INTRODUCTION
The depletion of soil nutrients is a major constraint to sustainable agriculture
(Tchabi et al., 2008; Stoorvogel
et al., 1993, Smaling et al., 1996).
Oenema et al. (2003) postulated that nutrient
monitoring of agro-ecosystems can be used as a tool to increase the understanding
of nutrient cycling, or as a performance indicator and awareness raiser in nutrient
management and environmental policy. The rural community of Cameroon in general
(Molua, 2002) and the Western Highlands of Cameroon
(WHC) in particular depend nearly entirely on agricultural activities for food,
feed and income. The rising demographic pressure has imposed intensive land
use over space and time which in turn demands high amounts of off-farm inputs.
Though some studies have been done in the forest region of Cameroon (Stoorvogel
and Smaling, 1990; Kanmegne et al., 2006;
Ehabe et al., 2010), no information so far exists
for the WHC to provide guidelines on soil nutrient management for sustainable
production.
Nutrient monitoring is a method that quantifies a systems nutrient inflows
and outflows resulting in nutrient balance which is a useful indication of soil
quality. Soil fertility is determined through the quantification of nutrient
stocks and flows within the production systems (Bationo
et al., 1998; Deugd et al., 1998).
Nutrient balance can be determined at spatial scales ranging from field level
to national level. A nutrient balance determined at the level of individual
activities within a farm serves as a useful indicator to provide insight into
magnitude of losses of nutrients from the system and the causes for such losses,
which ultimately enables target interventions. Understanding the nutrient balance
at each crop activity level at farm level can provide useful guides on agricultural
policy decisions for planning at these levels to sustain the production system.
The importance of this study to elucidate the nutrient dynamics in the breadbasket
of Cameroon (Bergeret and Djoukeng, 1993) where no
such study has been done cannot be overemphasized.
A nutrient balance is the difference between nutrient inputs and outflows (or
losses). Positive balance for a particular nutrient means that nutrient will
accumulate in the soil while negative balance reflects the mining of the nutrient
concerned. Soil depletion is provoked by nutrient loss while pollution is the
result of accumulation of high levels of nutrients, particularly nitrogen (N)
and phosphorus (P). Nutrients are generally taken up by the plant from the solution
phase of the soil, which is replenished through ion exchange, by dissolution
from the solid mineral phase, or by mineralization of organic compounds. While
part of the nutrients is returned to the soil in the form of crop residues,
the rest is removed from the field in the form of harvested products, soil erosion,
water runoff, soil sediments, and leaching (mainly nitrogen and potassium) and
volatilization (mainly nitrogen). The loss of nutrients is countered by biological
N-fixation, atmospheric deposition in rainfall and application of mineral fertilizers,
animal manures, or compost.
Numerous studies have shown that soil nutrient depletion in Africa is extremely
high (Stoorvogel and Smaling, 1990; Van
der Pol, 1992; Smaling, 1993; Smaling
and Braun, 1996; Smaling et al., 1997; Scoones,
2001). This is due to the fact that nutrients taken away in crops or lost
in processes such as leaching and erosion far exceed the nutrient inputs through
fertilisers, deposition and biological fixation (Smaling
and Braun, 1996). Stoorvogel and Smaling (1990) estimated
that 21 kg N, 2 kg P and 13 kg K were lost per ha and per year in southern Cameroon.
The application of nutrients to croplands is critically important for improving
crop yields and productivity of farmland. It has been estimated that approximately
50% of the applied nutrients are integrated into plant mass while the rest accumulate
in soil, or are emitted to the atmosphere (NO, NH3, N2O)
or water bodies as soluble components (NO3, PO4) or as
a component of soil. Agricultural activities are a significant contributor to
the substantial increase of both nitrogen and phosphorus (Smil,
2000; Galloway, 1998) in the environment.
The concern for soil nutrient depletion and low soil fertility has led to the
development of several integrated soil fertility management technologies that
offer potential for improving soil fertility management in Africa (Scoones
and Toulmin, 1999). The soil fertility management technologies are focused
on improved soil erosion control, inoculation of grain legumes for improved
nitrogen fixation, efficient use of manure and other locally available organic
materials, use of green manure and cover crops (Delve and
Jama, 2002) and use of low levels of N and P fertilisers on maize and beans
intercropping systems (Wortmann et al., 1998;
Wortmann and Kaizzi, 1998). A holistic approach to
tackle the soil fertility problem through integration of biophysical, socio-economic,
institutional and policy factors has been proposed (CGIAR,
2002). High input costs, inadequate knowledge on soil fertility management
practices and cropping systems design exacerbated by pests and disease problems,
global policies on input-out market and institutional failures are amongst the
determinants hampering the efforts of smallholder farmers (Van
Reuler and Prins, 1993; Hart and Voster, 2006).
To address the importance of the problems faced by smallholder farmers of the
WHC, the present study was undertaken by employing the NUTMON-Toolbox to assess
the nutrient balance at field (crop activity) level in the WHC. In addition,
the study attempted to identify household socio-economic and biophysical factors
influencing soil quality, agro-economic performance and the profitability of
cropping practices.
MATERIALS AND METHODS
Site description: The study was carried out during the first and second
cropping seasons (March to August and September to November) in 2010 and 2011
in three villages: Bafou, Baleveng and Fongo-Tongo located in the WHC found
between the geographical coordinates of 05° 27′-05° 37.62′N and 09°
57.502′-10° 09.544′ E (Fig. 1). The soil is characterized
by granite and gneisses in the southern lower altitudes and basaltic plateau
at northern higher altitudes (Fotsing, 1992).
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Fig. 1: |
Geographical location of study site |
Table 1: |
Household and farm characteristics of the study area |
 |
*Adult equivalence scale = people age 18 or over assigned
a weight of 1, children below 18 assigned a weight of 0.5 |
The natural vegetation is dominated by grass with spotted shrubs and trees.
Many households have planted Eucalyptus trees (most often for border demarcation)
which are commonly used as timber and fuel wood. Cool season vegetable crop
production is dominant at higher altitudes and agricultural activities are also
very common in inland valley swamps and on steep slopes due to land scarcity.
Cropping systems vary with altitude with intercropping predominant at lower
altitudes while at higher altitudes, sole cropping is more practiced and the
crops (predominantly cool season vegetables) grown are more for the market.
Fallowing is less common in the highly populated Bafou village while it lasts
for between 2 and 5 years in some parts of Fongo-Tongo and Baleveng villages.
The general characteristics of the farm plot studied are given in Table
1. Soil samples were collected from the 17 farm plots included in the study
and analysed using standard procedures.
Model description: NUTMON-Toolbox is software for monitoring nutrient
flows and stock especially in tropical soils (Vlaming et
al., 2001). The toolbox enables the assessment of trends based on the
local knowledge on soil fertility management and the calculation of nutrient
balances. The tool is made up of a structured questionnaire, a database and
two models (for calculating nutrient flows and economic parameters). The tool
calculates flows and balances of the macronutrients-N, P and K through independent
assessment of major inputs and outputs using the following equation:
Net soil nutrient balance = Σ(nutrient input)-Σ(nutrient
output) |
The components of the nutrient balance are:
• |
Nutrient inputs denoted as IN 1, IN2, IN3, IN4, IN5 and IN6
and representing, mineral fertilizer, organic inputs, atmospheric deposition,
biological nitrogen fixation, sedimentation and deep capture, respectively |
• |
Nutrient outputs denoted as OUT 1, OUT2, OUT3, OUT4, OUT5 and OUT6 and
representing, farm products, other organic outputs, leaching, gaseous losses,
erosion and human excreta, respectively |
• |
Internal flows, which are consumption of external feeds, household waste,
crop residues, grazing, animal manure and home consumption of farm products
as shown in Fig. 2 |
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Fig. 2: |
Typical nutrient flow within a farm in the Western Highlands
of Cameroon |
Farmers interviews: The semi-structured questionnaire developed
by Van-den-Bosch et al. (1998) was adapted to
collect data from heads of households of the selected farm plots. Biophysical,
socio-economic and farming system data were collected through a household interview.
Farmers gave information on the different production compartments, the different
land uses and their major farm products and destinations. Nutrient flows directly
related to their way of farming were quantified through information from farmers
and through direct measurements on the farm or in the household. The inflows
investigated by asking farmers were: the quantities of mineral fertilizers (IN
1), organic input such as manure (IN 2a) and organic fertilizers (IN 2b), entering
the farm annually. The outflows included the quantity of crops (OUT 1a) and
animal products (OUT 1b) leaving the farm as gifts or sales. Outflows measured
were crop residue (OUT 2a) and animal manure (OUT 2b) leaving the farm. Farmers
generally gave quantities in their own units, such as bundles, bags and buckets,
which were converted to standard metric amounts. For each farmer, a field survey
allowed us to identify the different land uses, the number of plots under each
land use. Areas under different land use systems were measured using a hand-held
GPS (Global Positioning System).
Use of transfer functions: In this study the choice of the functions
was based on studies conducted by Stoorvogel and Smaling (1990)
on nutrient balances for sub-Saharan Africa. Wet atmospheric deposition was
calculated from mean annual precipitation as follows:
where, p is the mean annual precipitation.
Biological nitrogen fixation (IN4) in production systems was estimated from
the general equation:
IN4a is the symbiotically fixed and IN4b the non-symbiotically fixed nitrogen.
It was assumed that 60% of the total N demand of leguminous crop (soybeans,
groundnut and pulses) is supplied through symbiotic nitrogen fixation (Stoorvogel
and Smaling, 1990):
OUT1 (N) is the N exported in the leguminous crop and FL3a, the quantity of
N accumulated in crop residues.
The non-symbiotic nitrogen fixation was estimated from the function:
Sedimentation (IN5) takes place in naturally flooded irrigated areas, where
salinisation and iodisation naturally occur. No crop was registered on flooded
or irrigated areas in the study site. This input was thus considered negligible.
Deep capture (IN6) occurs in the presence of trees that exploit the soil layers
below the normal root zone of crops. Intensive cultivation has eliminated such
components in the system and trees and shrubs are virtually absent in the farm
plots. This input was thus not considered in this study area.
Estimation of nutrient outflows not managed by farmers: Leaching below
the root zone (OUT3). In tropical soils phosphorus is tightly bound to soil
particles, and leaching involves only nitrogen and potassium. The quantity of
N and K annually lost (kg ha-1 yr-1) was estimated from
the transfer functions developed by Stoorvogel et al.
(1993).
For N leaching the (Smaling, 1993) model was used:
Where: |
Ns |
= |
Amount of mineralized N in the upper 20 cm of the soil; the mineralization
rate of the site was estimated at 3% (Nye and Greenland,
1960) |
Nf |
= |
Amount of N applied with mineral and organic fertilizers |
p |
= |
Annual precipitation (mm year-1) |
c |
= |
Clay content of the topsoil (percent).For K leaching, the Smaling
1993 model was also used |
Where: |
Ke |
= |
Exchangeable K (cmol kg-1) |
Kf |
= |
Amount of K applied with mineral and organic fertilizers |
p |
= |
Annual precipitation (mm year-1) |
c |
= |
Clay content of the topsoil (percent).OUT4 (gaseous losses) consists of
two parts: gaseous N losses from the soil and gaseous N losses related with
storage of organic inputs. Gaseous N losses from the soil are calculated
as a function of the clay percentage and the precipitation |
Where: |
Ns |
= |
Mineralized N in the rootable zone (kg ha-1) |
Nf |
= |
N applied with mineral and organic fertilizer (kg ha-1) |
c |
= |
Clay content (percent) |
P |
= |
mean annual precipitation (mm year-1).Gaseous losses for N
were calculated as |
Where: |
N |
= |
Faseous losses (kg/ha/yr) |
Soil N |
= |
Mineralizable N in the upper 20cm of the soil profile |
Fert N |
= |
Mineral or organic fertilizer |
Clay% |
= |
The clay content of the upper 20 cm of the soil profile |
p |
= |
The mean annual precipitation |
Gaseous losses from animal dejections: (OUT 4b).
None of the farmers in the study area depended on animal production. As such
animal dejections were not significant in the system. Gaseous losses from animal
dejections were therefore, assumed negligible.
OUT5 (erosion) was calculated using the USLE. A hypothetical soil loss per
Farm Section Unit (FSU) was calculated based on slope, slope length, rainfall,
soil characteristics and the presence of soil conservation measures. For each
Primary Production Unit (PPU) or crop activity, the hypothetical soil loss (in
kilograms per hectare per year) was multiplied by a crop cover factor, the nutrient
content of the soil and an enrichment factor.
OUT 6 represents human faeces. It was not considered in the evaluation owing
to its absence in the production system as a source of nutrients.
Nutrient balance: The NUTMON software quantifies nutrient flows in three
ways: through the use of primary data, estimates and assumptions. Nutrient balances
were quantified using the in-built transfer functions, equations and assumed
values.
To distinguish between primary data and estimates, two different balances were
calculated:- the partial balance at farm level (IN1+IN2)-(OUT1+OUT2) made up
solely of primary data and the full balance (ALL IN-ALL OUT) made up of a combination
of the partial balance and the immissions (atmospheric deposition and nitrogen
fixation) and emissions (leaching, gaseous losses, erosion losses and human
excreta) from and to the environment.
The quantified economic flows reveal the profitability of farming activities
(Vlaming et al., 2001). Economic performance indicators
were calculated at both activity level (crop) and farm household levels. The
main indicators at activity level were gross margins (gross return minus variable
costs) and net cash flows (cash receipts minus cash payments) per unit area.
At farm household level, net farm income (total gross margin minus fixed costs)
and family earnings (net farm income plus off-farm income) were the important
indicators.
Statistical analysis: Correlation analysis, means, standard deviations
and standard errors were calculated using the SPSS version 13.
RESULTS
Description of the cropping system of sampled farmers based on interviews:
The primary production units (PPUs) were comprised of sole cropping of vegetable
crops and intercropping systems. The principal vegetable crops were cultivated
on fields generally between one and five kilometers from the homestead. The
crops included potato (Solanum tuberosum), cabbage (Brassica sp.),
carrot Daucus carota), leeks (Allium porrum), onions (Allium
cepa) and beetroot (Beta vulgaris). The intercropping systems were
practised around the homes and a few kilometers from the homestead with different
combinations of maize (Zea mays), beans (Phaseolus vulgaris),
potato (Solanum tuberosum), yams (Dioscorea sp.), aroids (Xanthosoma
sp. and Colocasia sp.) bananas and plantains (Musa sp). The intercropping
systems identified from the sample of farmers were:
• |
Beans+maize+potato (BMP) |
• |
Beans+maize (BM) |
• |
Beans+maize+potato+yam (BMPY) |
• |
Maize+potato (MP) |
Livestock or Secondary Production Unit (SPU) activities were uncommon with
the farmers included in the nutrient balance study.
The identified nutrient flows into the farms in the study site were mineral
fertilizers mostly 20.10.10 and urea (IN 1), off-farm chicken dung (IN 2), atmospheric
deposition (IN 3), biological nitrogen fixation (IN 4a) and non-symbiotic nitrogen
fixation (IN 4b). The only source of on-farm organic input were crop residue
left after harvest which were directly recycled into the farm by incorporation
during land preparation. A few farmers made compost around their homes which
was used in home-gardens. In some cases the crop residues were burned and the
ash exploited as organic input. Outflows from the farm included, crop uptake
(OUT 1), removal in crop residue (OUT 2), gaseous loss (OUT 4), and erosion
losses (OUT 5).
Nutrient balance at crop activity (PPU) level: The quantified nutrient
balance at crop activity level (PPUs) using NUTMON-Toolbox are presented in
Table 2 for nitrogen, phosphorus and potassium, respectively.
The only positive full balances for nitrogen were observed with leeks (PPU
3) with a value of 151.95 kg/ha/yr, carrot (PPU 5) with a value of 552.56 kg/ha/yr
and tomato (PPU 8) with a value of 382.54 kg/ha/yr. The highest negative full
balance for nitrogen was observed with mixed intercropping of bean, maize and
potato (PPU 9) with a value of -697.57 kg/ha/yr. All the intercropping systems
showed high negative full balances for nitrogen ranging from -697.57 to -509.78
kg/ha/yr. For phosphorus, the highest positive full balance was observed with
carrot (PPU 5) with a value of 256.87 kg/ha/yr and the lowest positive was observed
with beetroot (PPU 11) with a value of 7.49 kg/ha/yr. The highest negative full
balance for phosphorus was observed for green pepper (PPU 2) with a value of
-42.23 kg/ha/yr. For potassium, the highest positive full balance of 124.15
kg/ha/yr was observed with tomato (PPU 8) and lowest positive full balance of
was observed with the intercropping of beans, maize, potato and yams (PPU 11)
with a value of 1.16 kg/ha/yr. The highest negative full balance of -138.68
kg/ha/yr was observed with cabbage (PPU 4). With the partial NPK balances, except
for the mixed intercropping system of beans, maize, potato and yams, all the
others were positive for nitrogen while the partial balances for phosphorus
and potassium followed similar trends as the respective full balances except
PPU 11 with respect to potassium.
Nutrient balance for the study area: With regards to the average results
of the study site, the full balances were positive for potassium (30.80 kg/ha/yr)
and phosphorus (28.61 kg/ha/yr) and negative for nitrogen (-183.71 kg/ha/yr)
while the partial balances were positive for all three (Table
3).
Table 4 shows the yield and gross margin of the principal
vegetable cash crops of the WHC.
There were great variations in the yield and gross margin data and three of
the crops cultivated showed negative gross margin values namely green pepper
(-5617.82 US$ ha-1), leeks (-3631.30 US$ ha-1) and onions
(-2910.39 US$ ha-1).
Table 5 shows the statistical significant relationships between
household economic and farm characteristics.
Farm N and K balances were negatively correlated with the farm slope and the
farm P balance was negatively correlated with the net farm income. The only
positive correlation recorded was between the farm K balance and the total farm
area (Table 5).
Table 2: |
NUTMON-Toolbox generated results for the study area. Average
nutrient balance for Nitrogen, Phosphorus and Potassium for the different
principal production units (PPUs) in the study area |
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a IN1, IN2, IN3 and IN4 represent mineral fertilizer,
organic inputs, atmospheric deposition, and biological nitrogen fixation,
respectively, bOUT1, OUT2, OUT3, OUT4 and OUT5 represent farm
products, other organic outputs, leaching, gaseous losses and erosion, respectively |
Table 3: |
NUTMON-Toolbox generated average farm-level nutrient budget
(kg/ha/yr) for the study area |
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Table 4: |
Yield and gross margin of the principal vegetable cash crops
in the study area |
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11US$ (United States Dollar) is approximately 500
CFA (Colonies françaises d'Afrique ("French colonies of Africa")
which is the local currency of the study area |
Table 5: |
Main significant correlations (Pearson) of household economic
and farm characteristics in the study area |
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DISCUSSIONS
The nutrient balance results showed that adequate attention was given by the
farmers in nutrient management of vegetable cash crops of the area. Similar
results on market oriented crops were also noted by Surendran
et al. (2005). However, De-Jager et al.
(1998) found a more negative N and K balances for higher market oriented
crops in Kenya. Negative full balances for all three nutrients were seen with
green pepper, implying that the amount of nutrients applied in this system was
sub-optimal. All three nutrients had positive balances with leek, carrot and
tomato production. Such a situation needs to be checked because of the risk
of environmental pollution, habitat destruction and risk to human health and
welfare since excess nutrients are pollutants.
As the yield-determining nutrient in most farming systems, adequate, but not
excessive, amounts of N are needed to sustain yields and contribute to the maintenance
of soil organic matter (Goulding et al.,2008).
The net negative nitrogen balance for the study site could be attributed to
the high outflow of N through harvested products, crop residues, losses from
manure, leaching and gaseous loses as reported by Kroeze
et al. (2003). Similar results were observed by Ehabe
et al. (2010) and Kanmegne et al. (2006)
in the southern part of Cameroon on perennial and annual crops. Vos
and van Der Putten (2000) proposed that negative N balance could be mitigated
by increasing the N fertilizer rates for crops grown, use of slow N release
fertilizers, and incorporation of organic manure to recycle nutrients. Nitrogen
Use Efficiency can also be improved by applying the necessary nutrients in the
correct amounts at the correct times (Krupnik et al.,
2004). The nitrogen uptake of beans intercropping systems (BMP, BM, BMPY)
was greatly influenced by atmospheric nitrogen fixation (IN4) of the beans component.
Traditionally, legumes have been viewed as excellent sources of N in agriculture
(Kinzig and Socolow, 1994).
Nitrogen and potassium balances were found to be negatively influenced by the
steepness of the farm slope similar to the findings of Schwab
et al. (1993). Increasing population has provoked farming on vulnerable
areas like steep slopes in the WHC. Practices like terraces and contour ploughing
can help remedy the situation.
Full and partial balances of P were positive. Similar results were found in
the humid forest of Cameroon by Ehabe et al. (2010)
while Kanmegne et al. (2006) found partial and
total negative balances for P in the humid forest zone of southern Cameroon.
This positive balance was mainly due to the optimal use of P fertilizers and
absence of pathways of losses of P other than crop uptake (OUT 1) and loss in
crop residues (OUT 2). Use of P solubilizing (Phospho-bacteria) and mobilizing
Vesicular Abruscular Mycorrhizae (VAM) microorganisms as biofertilizers could
improve the utilization of native soil P in such situations of P fertility buildup
in soil (Debnath and Basak, 1986). The popular view
that P is strongly held in soils has resulted in the build-up of excessive P
levels in some soils, resulting in enhanced leaching (Heckrath
et al., 1995). Even where soil P levels are at the optimum, the loss
by erosion of small amounts of P adsorbed on sediments or in solution can trigger
the eutrophication of freshwaters (Leinweber et al.,
2002).
In this study, the household net farm income was negatively related to the
soil phosphorus balance. This result is different from those of De-Jager
et al. 1998 who found that household net farm income showed no relation
with the nutrient balance in three districts in Kenya.
Full and partial balances for K were also positive indicating absence of deficiency
in the study area. Similar results were found in the humid forest of Cameroon
by Ehabe et al. (2010) while Kanmegne
et al. (2006) found partial and total negative balances for K in
their study of smallholder production systems in the humid forest zone of southern
Cameroon. Crop uptake of K is usually as much as N uptake and sometimes higher,
as in the case of roots and tubers. There appear to be no health or environmental
problems associated with K leaching and there are no gaseous emissions (Goulding
et al. 2008). However, over fertilization with potassium can induce
a magnesium deficiency and also cause a loss of soil structure (Goulding
and Annis, 1998). While the total farm area cultivated was positively correlated
with the K balance in this study, De-Jager et al.
(1998) found in their study that the cultivated area had a negative correlation
with the level of nutrients leaving the farm through agricultural products sold.
The yields of the principal vegetable cash crops of the study area showed very
high variations and the negative gross margins of green pepper, leeks and onions
indicated that either they were not profitable or the cropping practices were
not adequate. The negative gross margin of green pepper could be linked to the
fact the cropping practices resulted to negative balances in all the three nutrients
studied. Generally one of the causes of low profit obtained by the farmers is
due to widespread market imperfections and improving the relationship between
farmers and buyers could contribute to a better economic situation of the farmers
(Schipmann and Qaim, 2011).
CONCLUSION AND RECOMMENDATIONS
Resource flows and nutrient balances from this study show that soil nitrogen
depletion is a major problem in the study area. Nutrient mining is more intense
in the intercropping production system of the smallholder farmers in WHC but
the inclusion of legume crops in the intercropping system alleviates the situation.
Harvesting of crops for food and for sale and soil erosion are the most important
sources of nutrient mining in the crop production systems. Therefore attempts
to correct the imbalance need to address these and other socio-economic factors.
Given the high costs of fertilizers, the recycling of kitchen residues, animal
dejections and/or human faeces, and intensified use of legume as intercrops
could significantly modify the nutrient balance and the sustainability of the
systems. There exist findings that support the fact that intercropping enhances
sustainable plant production (Ledgard, 2001; Aggarwal
et al., 1992). There is also good evidence that adding organic matter
and fertilizers together improves NUE, as nutrients are held by the microbial
biomass (Turner and Haygarth, 2001). In a study conducted
by Olesen et al. (2004), cover crops reduced fertilizer
N requirement by 27 kg ha-1 and increased NUE from 42 to 52%; however,
nitrate leaching increased by 14 kg ha-1.
The magnitude of nutrient mining as a result of crop harvests in Africa is
huge. It has been shown that about 100 kg P and 450 kg K per hectare have been
lost during the past years from approximately 100 million ha of cultivated land
in Africa which is the fundamental biophysical reason for the declining food
production in smallholder farms (Sanchez, 1976, 1995;
Stoorvogel et al.,1993). Studies have shown that
leguminous trees in alley cropping systems can produce up to 20 t/ha/yr dry
matter of prunings, containing as much as 358 kg N, 28 kg P, 232 kg K, 144 kg
Ca, and 60 kg Mg (Young, 1989; Szott
et al., 1991; Bowen, 1984), more than enough
to meet most crop requirements. There exist many types of soil enriching species
in the WHC such as Tithonia diversifolia, Arachis glabrata, Cajanus
cajans, Tephrosia sp, Sesbania sp, Leucaena sp, Calliandra
sp and Crotalaria sp which can be used as organic inputs and also
to improve the structure of the soil.
This study is one of the first attempts to create a database on nutrient balance
studies in the WHC which is a useful guide to policy makers, researchers, extension
specialists and farmers alike in dealing with nutrient management.
ACKNOWLEDGMENTS
This study was made possible by funding from Volkswagen foundation. The authors
wish to thank Maarten vant Zelfde
of the Institute for Environmental Sciences (CML), Leiden, for producing the
map of the research site. We are very grateful to the extension workers of the
Menoua Division who participated in the data collection and the household members
who provided the useful data for the study.
|
REFERENCES |
1: Aggarwal, P.K., D.P. Garrity, S.P. Liboon and R.A. Morris, 1992. Resource use and plant interaction in rice-mungbean intercrop. Agron. J., 75: 71-78.
2: Bationo, A., F. Lompo and S. Koala, 1998. Research on nutrient flows and balances in west Africa: State-of-the-art. Agric. Ecosyst. Environ., 71: 19-35. CrossRef |
3: Bergeret, P. and V. Djoukeng, 1993. Economic evaluation of cropping systems in the Bamileke region (West Cameroun). Cahiers Agric., 2: 187-196.
4: Bowen, G.D., 1984. Tree Roots and the Use of Soil Nutrients. In: Nutrition of Plantation Forests, Bowen, G.D. and E.K.S. Nambiar (Eds.). Academic Press, London, UK., pp: 147-179.
5: CGIAR, 2002. Combating soil degradation in Africa. Proceedings of the International Agricultural Research Annual General Meeting, October 30-31, 2002, Washington DC., USA -.
6: Debnath, N.C. and R.K. Basak, 1986. Effect of rock phosphate and basic slag on available P in acid soils in relation to soil characteristics, seasons and moisture regimes. J. Ind. Soc. Soil Sci., 34: 464-470.
7: De-Jager, A., I. Kariuki, F.M. Matiri, M. Odendo and J.M. Wanyama, 1998. Monitoring nutrient flows and economic performance in African farming systems (NUTMON). IV. Linking nutrient balances and economic performance in three Districts in Kenya. Agric. Ecosyst. Environ., 71: 81-92.
8: Delve, R. J. and B. Jama, 2002. Developing organic resource management options with farmers in eastern Uganda. Proceedings of the 17th World Congress of Soil Science, August 14-21, 2002, Bangkok, Thailand -.
9: Deugd, M., N. Roling and E.M.A. Smaling, 1998. A new praxeology for integrated nutrient management, facilitating innovation with and by farmers. Agric. Ecosyst. Environ., 71: 269-283. CrossRef |
10: Ehabe, E.E., N.L. Bidzanga, C.M. Mba, J.N. Njukeng, I. de Barros and F. Enjalric, 2010. Nutrient flows in perennial crop-based farming systems in the humid forests of Cameroon. Am. J. Plant Sci., 1: 38-46. Direct Link |
11: Fotsing, J.M., 1992. Peasants strategies of land management in the Bamileke region West Cameroon. Bull. Reseau Erosion, 12: 241-254.
12: Galloway, J.N., 1998. The global nitrogen cycle: Changes and consequences. J. Environ. Pollut., 102: 15-24. Direct Link |
13: Goulding, K.W.T. and B.E. Annis, 1998. Lime, Liming and the Management of Soil Acidity. International Fertiliser Society, UK., ISBN-13: 9780853100447, Pages: 36.
14: Goulding, K., S. Jarvis and A. Whitmore, 2008. Optimizing nutrient management for farm systems. Philos Trans. R. Soc. Lond B Biol. Sci., 363: 667-680. Direct Link |
15: Hart, T. and I. Voster, 2006. Indigenous Knowledge on South African Landscape: Potential for African Development. Human Sciences Rsearch Council (HSRC) Press, Cape Town, South Africa.
16: Heckrath, G., P.C. Brookes, P.R. Poulton and K.W.T. Goulding, 1995. Phosphorus leaching from soils containing different phosphorus concentrations in the broadbalk experiment. J. Environ. Qual., 24: 904-910. CrossRef | Direct Link |
17: Kanmegne, J., E.M.A. Smaling, L. Brussaard, A. Gansop-Kouomegne and A. Boukong, 2006. Nutrient flows in smallholder production systems in the humid forest zone of southern Cameroon. Nutr. Cycl. Agroecosyst., 76: 233-248. CrossRef |
18: Kinzig, A.P. and R.H. Socolow, 1994. Human impacts on the nitrogen cycle. Phys. Today, 47: 24-31.
19: Kroeze, C., R. Aerts, N. van Breemen, D. van Dam and P. Hofschreuder et al., 2003. Uncertainties in the fate of nitrogen I: An overview of sources of uncertainty illustrated with a Dutch case study. Nutrient Cycling Agroecosyst., 66: 43-69. CrossRef |
20: Krupnik, T.J., J. Six, J.K. Ladha, M.J. Paine and C. Van Kessel, 2004. An Assessment of Fertilizer Nitrogen Recovery Efficiency by Grain Crops. In: Agriculture And The Nitrogen Cycle: Assessing The Impacts of Fertilizer Use on Food Production and the Environment, Mosier, A.R. and J.J.K. Syers (Eds.). Island Press, Washington, DC., USA., pp: 193-207.
21: Ledgard, S.F., 2001. Nitrogen cycling in low input legume-based agriculture, with emphasis on legume/grass pastures. Plant Soil, 228: 43-59. CrossRef |
22: Leinweber, P., B.L. Turner and R. Meissner, 2002. Phosphorus. In: Agriculture, Hydrology and Water Quality, Haygarth, P.M. and S.C. Jarvis (Eds.). CABI Publ., Wallingford, UK., ISBN: 0851995454, pp: 29-55.
23: Molua, L.E., 2002. Climate variability, vulnerability and effectiveness of farm-level adaptation options: The challenges and implications for food security in Southwestern Cameroon. Environ. Dev. Econ., 7: 529-545. Direct Link |
24: Nye, P.H. and D. Greenland, 1960. The Soil under Shifting Cultivation. Harpenden, England: Commonwealth Bureau of SoUs.
25: Oenema, O., H. Kros and W. de Vries, 2003. Approaches and uncertainties in nutrient budgets: Implications for nutrient management and environmental policies. Eur. J. Agron., 20: 3-16. CrossRef |
26: Olesen, J.E., P. Sorensen, I.K. Thomsen, J. Eriksen, A.G. Thomsen and J. Berntsen, 2004. Integrated Nitrogen Input Systems in Denmark. In: Agriculture and the Nitrogen Cycle: Assessing the Impacts of Fertilizer use on Food Production and the Environment, Mosier, A.R. and J.J.K. Syers (Eds.). Ch. 9. Island Press, Washington, DC., pp: 129-140.
27: Sanchez, P.A., 1976. Properties and Management of Soils on the Tropics. John Wiley and Sons, New York, pp: 618.
28: Sanchez, P.A., 1995. Science in agroforestry. Agrofor. Syst., 30: 5-55. CrossRef | Direct Link |
29: Schipmann, C. and M. Qaim, 2011. Supply chain differentiation, contract agriculture and farmers marketing preferences: The case of sweet pepper in Thailand. Food Policy, 36: 667-677. CrossRef |
30: Schwab, G.O., D.D. Fangmeier, W.J. Elliot and R.K. Frvert, 1993. Soil and Water Conservation Engineering. 4th Edn., Wiley, New York, pp: 41-42.
31: Scoones, I., 2001. Dynamics and Diversity: Soil Fertility and Farming Livelihoods in Africa: Case Studies from Ethiopia, Mali and Zimbabwe. Earthscan Publications, London, ISBN: 9781853838194, Pages: 244.
32: Scoones, I. and C. Toulmin, 1999. Policies for Soil Fertility Management in Africa. International Institute for Environment and Development, London, Pages: 128.
33: Smaling, E., 1993. An agro-ecological framework for integrating nutrient management with special reference to Kenya. Ph.D. Thesis, Agricultural University of Wageningen, The Netherlands.
34: Smaling, E.M.A., L.O. Fresco and A. de Jager, 1996. Classifying monitoring and improving soil nutrient stocks and flows in Africa agriculture. AMBIO: J. Human Environ., 25: 492-496. Direct Link |
35: Stoorvogel, J.J., E.M.A. Smaling and B.H. Janssen, 1993. Calculating soil nutrient balances in Africa at different scales. I. Supra-national scale. Nutr. Cycl. Agroecosyst., 35: 227-235. CrossRef | Direct Link |
36: Smalling, E.M.A. and A.R. Braun, 1996. Soil fertility research in sub-Saharan Africa: New dimensions, new challenges. Commun. Soil Sci. Anal., 24: 365-386. Direct Link |
37: Smaling, E.M.A., S.M. Nandwa and B.H. Janssen, 1997. Soil Fertility in Africa is at Stake. In: Replenishing Soil Fertility in Africa, Buresh, R.J., P.A. Sanchez and F.G. Calhoun (Eds.). Soil Science Society of America, Wisconsin, USA., pp: 47-61.
38: Smil, V., 2000. Phosphorus in the environment: Natural flows and human interferences. Ann. Rev. Energy Environ., 25: 53-88. CrossRef | Direct Link |
39: Stoorvogel, J.J. and E.M.A. Smaling, 1990. Assessment of soil nutrient depletion in sub-Saharan Africa: 1983-2000. Report 28, DLO Win and Staring Center for Intagrated Land, Soil and Water Research (SC-DLO), Wageningen, Netherlands.
40: Surendran, U., V. Murugappan, A. Bhaskaran and R. Jagadeeswaran, 2005. Nutrient budgeting using NUTMON - Toolbox in an irrigated farm of semi arid tropical region in India: A micro and meso level modeling study. World J. Agric. Sci., 1: 89-97. Direct Link |
41: Szott, L.T., E.C.M. Fernandes and P.A. Sanchez, 1991. Soil-plant interactions in agroforestry systems. For. Ecol. Manage., 45: 127-152. CrossRef |
42: Tchabi, A., D. Coyne, F. Hountondji, L. Lawouin, A. Wiemken and F. Oehl, 2008. Arbuscular mycorrhizal fungal communities in sub-Saharan savannas of Benin West Africa as affected by agricultural land use intensity and ecological zone. Mycorrhiza, 18: 181-195. CrossRef | PubMed | Direct Link |
43: Turner, B.L. and P.M. Haygarth, 2001. Biogeochemistry: Phosphorus solubilization in rewetted soils. Nature, 411: 258-258. CrossRef |
44: Van-den-Bosch, H., A. Dejager and J. Vlaming, 1998. Monitoring nutrient flows and economic performance in African farming systems (NUTMON) II. Tool development. Agric. Ecosyst. Environ., 71: 54-64. Direct Link |
45: Van der Pol, F., 1992. Soil Mining. An Unseen Contributor to Farm Income in Southern Mali. Bulletin Royal Tropical Institute, Amsterdam, Pages: 48.
46: Van Reuler, H. and W.H. Prins, 1993. The role of plant nutrients for sustainable food crop production in Sub-Saharan Africa. Dutch Association of Fertiliser Producers (VKP), AK Leidschendam, The Netherlands.
47: Vlaming, J., H. van den Bosch, M.S. van Wijk, A. De Jager, A. Bannink and H. van Keulen, 2001. Monitoring Nutrient Flows and Economic Performance in Tropical Forming Systems (Nutmon). Alterra, Green World Research and Agricultural Economics Research Institute, The Netherlands.
48: Vos, J. and P.E.L. van Der Putten, 2000. Nutrient cycling in a cropping system with potato, spring wheat sugar beet oats and nitrogen catch crops. I. Input and off take of nitrogen phosphorus and potassium. Nutr. Cycling Agroecosyst., 56: 87-97. CrossRef | Direct Link |
49: Wortmann, C.S., M. Fischler, F. Alifugani and C.K. Kaizzi, 1998. Accomplishments of participatory research for systems improvement in Iganga district Uganda 1993 to 1997. Network on Bean Research in Africa, Occasional Publications Series, No. 27, CIAT, Kampala, Uganda. http://ciat-library.ciat.cgiar.org/articulos_ciat/op27_part_research.pdf.
50: Wortmann, C.S. and C.K. Kaizzi, 1998. Nutrient balances and expected effects of alternative practices in the farming systems of Uganda. Agric. Ecosyst. Environ., 71: 115-129.
51: Young, A., 1989. Agroforestry for Soil Conservation. CAB International, Wallingford, England.
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