The problem of declining soil fertility is becoming one of the major challenges
for sustainable agriculture production in sub Sahara African countries (Stoorvogel
and Smaling, 1998). Agricultural productivity per unit area of land is declining
through time and food production could not keep pace with population growth
(Roy et al., 2003). In order to feed the growing
population, agricultural production has to grow at least by 3-4% per annum (Greenland
and Nabhan, 2001). This can be achieved either by bringing more land under
cultivation (i.e., area expansion) or by increasing productivity per unit area
of land (i.e., intensification). The first option has been less feasible due
to land shortage. The remaining feasible option to increase productivity per
unit area through improved soil fertility management accompanied with the use
of improved crop varieties and better agronomic practices (Sanchez
et al., 1997). However, in many place, farmers continue mining soil
nutrients without adequate replenishment and soil and water conservation (Ryan
and Spencer, 2001).
Ethiopia is one of the countries that are affected by soil nutrient depletion
(Elias et al., 1998; Haileslassie
et al., 2005). As a result, productivity per hectare has been declining
over the past several decades (Elias, 2002). It is less
likely that increasing food production without employing integrated soil fertility
management practices allied with adoption of improved crop verities (Sanchez
et al., 1997; Julius Ayodele and Solomon Olusegun,
2008; Ayeni, 2011).
In Jimma Zone, decreasing agricultural productivity per unit area due to soil fertility depletion is becoming a challenge for smallholder farmers. Therefore, this investigation was conducted to determine the effects of current soil fertility management practice on soil nutrients status through nutrient balance analysis via nutrient in and out flow monitoring and to examine the role of farmers resource endowment in maintaining and improving soil nutrients balance.
MATERIALS AND METHODS
Description of the study area: The study was conducted in two locations
(high altitude and low altitude) of Gligel Gibe catchment, Jimma zone, Southwestern
Ethiopia. The catchment covers an area of 4225 km2, lied between
7°22' 72" to 7° 34' 84" N and 37° 21' 05" to 37° 28' 80" E and
has an altitude range of 1609-3018 m above sea level (m.a.s.l) (Aticho,
2011). The dominant soil groups of the region were Nitisols, Ferralsol and
Planosol (FAO, 1994). Rainfall of the area is bimodal
type. The heavy rainy season (main crop growing) is begin in the mid June and
ceased in mid September. The moderate rain (harvesting and planting short cycle
crop) is from February to May (USDA, 2003). The mean
annual rainfall of high and low altitude is 1592 and 1275 mm, respectively (Aticho,
2011). Hypothetically, an altitude more than 2000 m.a.s.l is taken as high
and less than 2000 m.a.s.l low altitude because the land escapes, cropping systems,
amount of rainfall, temperature, land and soil fertility management practices
are quite different between these altitudes.
Integration of livestock with crops is the common farming system. However,
type of crops integrated with livestock is varied with an altitude range. Integrating
livestock with Ensete (Ensete ventricosum), Wheat (Triticum spp.),
Oat (Avena sativa), Tef (Eragrostis tef) and Barley (Hordeum
vulgare) is common in the high altitude. Whereas in the low altitudes livestock
is integrated with Tef (Eragrostis tef), maize (Zea mays) and
sorghum bicolour (Aticho, 2011).
Data collection: Participatory Rural Appraisal (PRA) exercise was conducted
in six villages of the catchment. This activity is used as tool to; select representative
study villages, identify major cropping systems, capture local wealth ranking
criteria, identify crop production problems (FAO, 1996).
Then, the number of villages were minimized in to two based on altitude, cropping
system, amount of rainfall, temperature, soil fertility management, vegetation
and landscape similarity. Gesheluchine and Kejelo villages were selected to
represent the high and low altitude areas, respectively.
Number of livestock and landholding size are the major criteria to classify farmers in to different wealth classes. Accordingly, three (rich, medium and poor) resource group farmers are identified.
Eighteen case study farms were randomly selected (three farms from each wealth
classes of both locations i.e., 3x3x2 = 18) and nutrient flow monitoring activity
was done for a year. NUTMON (nutrient monitoring) model was used to analyze
the N, P and K (kg ha-1 year -1) balance. It was obtained
by subtracting the quantity of N, P and K removed from soil through crop products
(OUT1), crop residues (OUT2), leaching (OUT3), gaseous lose (OUT4) and erosion
(OUT5) from the total amount of N, P and K added to the soil with mineral fertilizer
(IN1), manures (IN2), biological nitrogen fixation (IN3), wet deposition (IN4)
subtracted from the (Stoorvogel and Smaling, 1998).
Nutrient inflow analysis: As reported by the participants of PRA program and survey, currently mineral fertilizer (IN1) application is not practiced in Gesheluchine village because of urea and DAP addition to Wheat (Triticum spp.) crop in the last decade caused logging of the crop. Consequently, commercial fertilizer extension was failed and the soil is considered as inherently fertile. Nutrient applied with IN1 was considered to be zero. However, in the Kejelo village urea and DAP fertilizers are used for maize cultivation. The amount of N and P supplied calculated by multiplying the amount of urea and DAP applied with their N and P content.
In both sites fresh manure (IN2) is transported to farm regularly by locally
made materials. The amount applied was determined by physically weighing the
fresh weight per local material of each wealth groups and then daily record
the numbers to four months (November, February, May and August). N, P and K
content was determined in laboratory by following standard procedures (AOAC,
1990). The quantity of N, P and K added to farm was obtained by multiplying
dry weight of manure with its nutrient content.
N, P and K added to the soil with wet deposition (IN3) were estimated with
reassign equation developed by Stoorvogel and Smaling (1998)
which is a function of mean annual rainfall (mm year-1). The mean
annual rainfall (p) was obtained from eighteen year rainfall data of the nearby
Studies conducted in different parts of Ethiopia shows that 60% of legume plant
N requirement is meet by symbiotic nitrogen fixation (Elias
et al., 1998; Haileslassiea et al., 2005).
So, in this study the amount of N fixed symbiotically (IN4b) was assumed to
be 60%. Similar with IN3, N input from non-symbiotic fixation and N fixing trees
that are left on the field was estimated through transfer function (Stoorvogel
and Smaling, 1998).
Nutrient outflow analysis: Crop biomass removal is one of the causes for nutrient flow out of crop land. The amount of crop (grain, tuber and root) products (OUT1) and residues (OUT2) exported from farm section was determined by randomly demarcating ten sample plots per hectare (each plot had 16 m2 area). At crop maturity, crops in the sample plots were harvested, sun dried, trashed and weighed with hand held balance and composite samples were taken for laboratory analysis.
The amount of N, P and K exported by OUT1 and OUT2 were calculated by multiplying
the total amount of crop product and residue exported from farm with their respective
N, P and K content (Stoorvogel and Smaling, 1990).
Substantial amounts of N and K are lost with leaching effect but, P is not
because, it is highly bind with soil particle (Roy et
al., 2003; Ahmed et al., 2006). It is
difficult to measure N and K lost (kg ha-1 year-1) by
leaching in field transfer function developed by Stoorvogel
and Smaling (1990) was used to estimate lose. Accordingly:
where, p: mean annual rainfall, F: soil fertility class (1= low; 2 = moderate; 3 = high), IN1+IN2: mineral fertilizer and manure applied (kg ha-1 year-1) and TNU, TKU: total N and K uptake (kg ha-1 year-1), respectively.
Nitrogen lost from agricultural soils in the form of dentrification and volatilization
is considered as gaseous loss (Stoorvogel and Smaling, 1990).
Similar with leaching, direct measurement of N loss in gaseous form is difficult
(Stoorvogel and Smaling, 1990) thus it was estimated by
regression equation (FAO, 2001).
where, p= mean annual rainfall; IN1 + IN2: mineral fertilizer and manure applied (kg ha-1 year-1), respectively.
Soil lost with water erosion (OUT5) was estimated by Revised Universal Soil
Loss Equation (RUSLE) for Ethiopia (Hurni, 1985). The
quantity of N, P and K lost with erosion was quantified, the amount of soil
lost with erosion multiplied with N, P and K enrichment factor (Roy
et al., 2003).
Laboratory analysis: Soil samples were air-dried, sieved by 2mm sieve
and analyzed by following standard laboratory procedures. pH was determined
in 1:2.5 (soil: water suspension) by using glass electrode at 25°C (at room
temperature), organic carbon by wet oxidation method (Walkley
and Black, 1934) and available P was extracted by Bray method (Bray
and Kurtz, 1945) and P in the extract was determined colorimetrically by
spectrophotometer. Total N was determined by Kjeldahl method (Houba
et al., 1989). Available K was extracted by Morgans solution
and K in the extract measured by flame photometer. Cation Exchange Capacity
(CEC) was determined at pH 7 using ammonium acetate as exchanger.
Plant samples were washed with 0.25% detergent solution followed rinsing in distilled water to remove dusts and other contaminants. Then, the samples were dried in oven at 105°C for 24 h, grounded, sieved by 2 mm sieve and again dry at 65°C to obtain a constant weight upon which to base the analysis. Finally, N, P and K compositions of the samples were analyzed in laboratory by wet oxidation.
Plant samples for nitrogen determination were digested in sulphuric acid at a temperature 400°C and determined by Kjeldahl method. K in acid digest was determined colorimetrically by flame photometer and P by spectrophotometer.
Statistical analysis: Laboratory results of soil samples were analyzed
by Statistical Analysis Software (SAS version 12) and their means were separated
by Least Significant Difference (LSD 0.05 test). Nutrient balance was calculated
by employing Nutmon model and means of the depletion rate between wealth groups
and nutrients were compared by Duncan multiple test (p = 0.05). Also, 2-tailed
t-test correlation analysis was used to determine the relationship between rate
of nutrient depletion and locations.
RESULTS AND DISCUSSION
Selected soil chemical properties: Mean comparisons for the selected
soil chemical properties attested high value was observed in the high altitude
(Table 1). According to Elias et al.
(1998) vegetation coverage, conservation measure, farming system and soil
nutrient management practices determines soil chemical properties.
Farms belong to rich and medium resource classes had similar chemical properties
except for CEC and OC. The higher concentration was observed at resource higher
classes than the poor. Soil total N and organic carbon has direct relationship,
the higher concentration of organic carbon was observed due to organic matter
addition to the soil. This is agreed with the findings of Fallahzade
and Hajabbasi (2011).
Nutrient balance at farm level: The mean values for nutrient balance
at farm scale were negative among wealth groups in both locations (Table
2). This implies that, the subsistence farming systems of smallholder farmers
in the area is depleting soil nutrient stock. Due to high P fixation within
the study area, P depletion was lower than N and K in both locations for all
wealth groups. This, result is agreed with Surendran and
Murugappan (2007). According to Stoorvogel et al.
(1993) soil nutrient depletion rating in sub Sahara African countries; the
depletion rate in the high altitude was very high for N, P and K but, high N
and very high P and K in the low altitude. None significant difference (p<0.05)
was observed between wealth classes owing to inadequate nutrient addition via
commercial and organic fertilizer at farm scale.
|| Mean comparison soil chemical properties between location
and wealth groups
|Same latter refers not any difference between the means (p
|| Mean comparison of nutrient depletion rate between wealth
|NS: Non significant difference (p<0.05), same latter superscript
refers not any difference between the means at p = 0.05
|| Mean comparison of nutrient depletion rate within nutrients
|*** Highly significant (p = 0.01), same latter superscript
refers to none significant (p<0.05) difference between means
|| Correlation of N, P and K (kg ha-1 year-1)
depletion rate with locations
|NS: Not significant difference (p<0.05), *** highly significant
(p = 0.001)
Small quantity of nutrient added to a portion of large farm by resource rich
or medium group had no longer significant contribution to maintain or improve
soil nutrient stock at farm scale. In the Jimma Zone soil nutrient depletion
caused reduction of agricultural productivity, household food insecurity, unemployment,
decreasing household income and overdependence on chat (Catha edulis)
(mild stimulants) chewing. Recognizing that, Agricultural and Rural Development
Bureau of the region attempted different activities (soil and water conservation
practices, chemical fertilizers (DAP and urea) use, compost preparation and
sustainable land management extension services) to set up the possible solutions.
The measures taken by the government to address the problem were not successfully bring real solutions to the expected level because of the following constraints; farmers inability to afford for chemical fertilizer (due to high price), limited availability of organic fertilizer and its inefficient utilization, absence of experiment based area (soil chemical property, climate, etc..,) and crop specific fertilizer recommendation and farmers late technology adoption.
Rate of depletion within N, P and K nutrients, there was highly significant (p = 0.001) difference was observed in both locations (Table 3). The mean comparison revealed that; the depletion rate of N weighed against P and K, it was higher than P and K. But, K compared with N and P, none significant difference was observed within N and P. This variation was happened due to, the amounts of N, P and K withdraw from soil by harvest was varied, the quantity of N, P and K added to soil (through fertilizer, wet deposition, biological fixation and other inputs) differ and their susceptibility to remove through leached and erosion.
High degree of correlation was observed for location and N and K depletion but, negligible for P (Table 4). This implies, the quantity of nutrient depletion is positively related with locations.
CONCLUSION AND RECOMMENDATION
This study found that, N, P and K added to crop lands were much more less than nutrients removed out of the system. Poor integrated soil nutrient management practices, ineffective use of locally available nutrient resources, inadequate soil conservation practices and high cost of commercial fertilizers became the cause for unsustainable agricultural production and food insecurity in the study area. To tackle soil nutrient depletion and boost agricultural productivity, adequate nutrient replenishment practices through nutrient addition via chemical and organic fertilizer, nutrient retention or harvesting by soil and water conservation were obligatory. Beside, the existing blanket fertilizer application exercise should be replaced with field experiment based rate for each crop. To achieve this, the government should subsidize the farmers for fertilizers and allocate adequate facility for area and crop specific fertilizers recommendation researches.
I would like to express my sincere thanks to Gesheluchine and Kejelo Village farmers for their active participation in PRA program, the villages' administrative bodies and development agents for coordinating the farmers in the PRA. In addition, my special thanks go to the case study farm owners for allowing me to conduct the study on their farm.