ῐ
J. Jpn. Soc. Soil Phys.
ῐ῎῍ῑῒ῏
No. 3-, p. ,+ῌ-- ῍,**-῎An Evaluation of Co#ee Crop Factor under Di#erent Weed
Managements Using USLE Method in Hilly Humid TropicalArea of Lampung, South Sumatra, Indonesia
AFANDI*, Tumiar Katarina MANIK*, Bustomi ROSADI*, Muhajir UTOMO*,
Masateru SENGE**, Tadashi ADACHI*** and Yoko OKI**** Faculty of Agriculture, University of Lampung,
Jl. Sumantri Brojonegoro +, Bandar Lampung -/+./, Indonesia** Faculty of Agriculture, Gifu University, +ῌ+ Yanagido Gifu /*+ῌ++32, Japan*** Faculty of Environmental Science and Technology, Okayama University,-ῌ+ῌ+ Tsushimanaka Okayama 1**ῌ2/-*, Japan
Abstract
An evaluation of crop management factor (C) for co#ee using USLE method was conducted inhilly humid tropical area of Lampung, Indonesia. The treatments were as follows : co#ee without
cover crop (clean-weeded plot) ; co#ee with Paspalum conjugatum as cover crop (Paspalum plot) ;and co#ee with natural weeds (natural weeds plot). Weed management was done every two
weeks by clearing all the weeds in clean-weeded plot, and cutting the weeds around the co#ee
trees at a diameter of + m for the weedy plots (Paspalum and natural weeds plots). Two methodsof estimating C-factor for co#ee were used : (+) using similar condition with other crops (Ct), and(,) using equivalent method based on the existing value of co#ee-C factor (Ce). The results showedthat the use of Ct gave soil loss prediction 3ῌ,. times higher than that measured, while the use of
Ce gave +*ῌ2+ times higher. The predicted values of soil loss using Ct were 1.1 t/ha/year and +..+
t/ha/year for Paspalum and natural weeds plots respectively. These values were still acceptable
and reasonable to the soil loss tolerance, and very low compared to the other Indonesian studies
which could be hundreds of ton/ha/y. This experiment showed that the measured co#ee C-factor
was *.*./ for clean-weeded plot, *.**0 for Paspalum plot and *.**. for natural weeds plot, whichwere lower than the common value (*.,) usually used in Indonesia. By introducing the e#ect of
weeds as the weeds C-subfactor (Cs) and co#ee C-factor (Cb) obtained from this experimentmeasurement, the co#ee C-factor (Cc) with various weeds coverage could be estimated by theequation CcῌCb Cs.
Key words : soil erosion, co#ee, erodibility, USLE, crop factor+.

Introduction

Of all the empirical erosion models, the USLE
(Wischmeier and Smith, +312) is the mostwidely used all over the world for predicting
erosion loss and guide for conservation planning. However, it is often used without validating or measuring soil speciﬁc properties andrainfall factors, so the information generated

can thus be erroneous, misleading, and counterproductive, which represents the misuse
and abuse of empirical equation (Lal, ,***).
The founding of USLE, Wischmeier (+310) has
warned the misuse of USLE, such as applying
C and P values from the handbook without
considering, and applying the factors too
broad, such as single C value for all cropland.
However, Risse et al. (+33-) showed that from῏  3-

22

Table +
Depth
(cm)

pH
H, O

*ῌ +*
+*ῌ ,*,*ῌ -/-/ῌ 0*
0*ῌ+**

.43,
.423
.43+
.421
.42/

,**-

Initial soil properties prior to planting

Texture (kg/kg)
Total-N Organic-C
CEC(g/kg)(g/kg) (cmol/kg) Sand
Silt
Clay
,40
+40
*43
*41
*40

-.42
+240
243
24,
24,

+-434334241
241

the six parameters in USLE, the crop management and topographic factors had the mostsigniﬁcant e#ect on the overall model e$ciency. These indicated that most of the researchemphasis should continue to be placed on theseparameters.
The equation of USLE is also widely used inIndonesia as a tool for conservation planning,
especially in watershed scale. Unfortunately,
the results were frequently overestimated ; thevalue of hundreds of tons of soil loss per hectare per year predicted by USLE is very easy to
be found in many literatures in Indonesia.
The above problems were arisen because it isvery di$cult to apply the USLE purely in Indonesia, such as how to obtain an exact value ofcrop management factor, especially for treecrop. Because soil erosion experiment was
mainly concentrated on food crops in Java
Island, there are very few Indonesian’s literatures of soil erosion for some popular crops in
Sumatra Island, such as co#ee, sugarcane, andoil palm. The crop management factors for
those tree crops are frequently estimated fromthe table in handbook, which are the results ofexperiments in the other countries with very
di#erent conditions from Indonesia. In case ofco#ee trees, a very limited research was done
concerning soil erosion. Up till now, the valuesof the soil erosion from co#ee trees areas were
mostly predicted by USLE equation using thevalues from the table. So, creating a new crop
factor of co#ee tree from a ﬁeld experiment isvery important.
The objective of this study is to evaluate the

*4,/
*4,/
*4,0
*4,0
*4,2

*4,*4+0*4+*4+*4+/

*4/,
*4/3
*40+
*40+
*4/1

Bulk density(kg/m-)
30*
3-*
33*
3-*


value of crop management factor of co#ee treewith di#erent weeds management using USLE
in a hilly tropical area of Lampung, South Sumatra, Indonesia.
,.

Materials and Methods,. + Study site
The study site was located at Sumber Jaya
District, Lampung Province, South Sumatra,Indonesia. The study was conducted during
four rainy seasons from +33/ to +333. The slope
gradient was -*ῌ with an elevation of 12* m
above sea level. The selected soil properties areshown in Table +. The soil was classiﬁed as
Inceptisols (Dystrudepts), which was dominated by clay fraction in all depths. The bulk
density was very low indicating that the soil
was friable and porous. The soil reaction wasslightly acid with moderate cation exchange
capacity. The total rainfall during four yearsof experimental period was ./.1.0 mm, with++-0.3 mm per rainy season (usually from October to April).
,. , Treatment plot
The size of erosion plot was ,* m length and/ m width (+** m,). Two collection units were
installed at the lower end of the plot for measuring soil loss. The ﬁrst unit was a ditch withthe capacity of *.+ m-, which was connected tothe second unit by seven pipes. One pipe
which was in the center, was connected by asiphon to a tank and the rests were overﬂowed
to the water reservoir box in which a triangular weir and a water gauge was installed(Afandi et al., ,**,). The sediment and runo#῕῔ : An Evaluation of Co#ee Crop Factor under Di#erent Weed Managements Using USLE Method in Hilly Humid Tropical Area of Lampung, South Sumatra, Indonesia 23

water in the ditch and tank was pulled out into
a drum with a siphon, thoroughly stirring thecontents in the drum and quickly extracting/** ml sample with plastic bottle. The total soil
loss was calculated by measuring the dryweight of sediment sample and the volume ofruno# water stored in the ditch and tank.
The treatments were as follows :(+) Treatment + (clean-weeded plot) : Cleanweeded co#ee. Ground surface was always
kept bare by hand weeding at two weeks interval. This management is a general practice inthis co#ee plantation area was regarded as thecontrol.
(,) Treatment , (Paspalum plot) : Co#ee
with Paspalum conjugatum as cover crop.
Young Paspalum conjugatum was transplantedin the experiment plot in November +33/ andFebruary +330. Paspalum conjugatum is one of
the weed species, gramineous perennial ofSouth Africa origin. Its stalks, hard and long,
are crawled over the ground, putting out anirregular roots from joints. Its growth speed isvery fast and the rhizomes are dense. This
plant was widely used in both private andpublic park areas in Indonesia.
(-) Treatment - (natural weeds plot) :Co#ee with natural weeds as cover crop.
The seedlings of Arabica co#ee were planted
at +./ m by , m spacing on November +33/.
Weed management was done every two weeks
by clearing all the weeds in clean-weeded plot,
and cutting the weeds about + m in diameteraround the co#ee tree for the weedy plots(Paspalum and natural weeds plot). Before andafter rainy season, the Paspalum mats (atPaspalum plot) and natural weeds (at naturalweeds plot) were mowed at +/cm height. Application of fertilizer and pesticides had been adopted according to the standard practice.
,. - Weeds type
Sriyani et al. (+333) reported that a few weeds
named as Ageratum conyzoides appeared inclean-weeded plot. Among the weeds whichappeared in natural weeds plot were Clibadia
surinamense, Clidemia herta, Chromolaena

odorata, Melastoma a$ne, and Imperata cylindrical.
Clibadia surinamense (woody species)
whose mean plant height reaches +-0 cm was
the dominant species in natural weedy plot.
Imperata cylindrica is a type of grass, which
covered about ,*῍ of the soil surface. Six
months after the experiment started, the weeds
in both weedy plots had already covered fully
the soil surface.
,. . Methodology(+) USLE equation
The USLE (Wischmeier and Smith, +312),
which is used as the basis of calculation, has
the following formula :AΐRῌKῌLῌSῌCῌPῌWhere : A : soil loss per unit area per year
R : rainfall and runo# factor
K : soil erodibility factor
L : slope length factor
S : slope steepness factor
C : crop management factor
P : support practice factor(,) Rain erosivity (R)Rain erosivity index was calculated using
the following equation of Wischmeier andSmith (+312).
RΐEῒI-*
῍
Where, R : rainfall erosivity index (MJ · mm ·hῑ+ · haῑ+)E : total rainfall energy (MJ · haῑ+)I-* : the maximum -*-min rainfall intensity (mm · hῑ+)(-) Erodibility factor (K)Soil erodibility factor was calculated using
the equation of Wischmeier, Johnson, andCross (+31+) as follows :Kΐ*.+-,῎,.+M+.+.ῌ+*ῑ.῍ῌ+,ῑa῍ῐ-.,/ῌbῑ,῍ῐ,./ῌcῑ-῍῏῎where, K : erodibility factor (t · h · MJῑ+ ·mmῑ+)M : (῍ silt ῐ ῍ ﬁne sand) ῒ (+** ῑ ῍clay)a : organic matter content (῍)
b : the soil-structure code used insoil classiﬁcationc : the proﬁle-permeability class24  3-  ,**-

Soil structure code (b) was as follows :(+) very ﬁne granular, (,) ﬁne granular, (-)
medium to coarse granular, and (.) platy,
blocky, or massive.
Permeability class (c) was classiﬁed as follows :(+) rapid (+,./ cm/hr), (,) moderate to rapid(0.,/῔+,./ cm/hr), (-) moderate (,.**῔0.,/ cm/hr),(.) slow to moderate (*./῔,.** cm/hr), (/) slow(*.+,/῔*./ cm/hr), and (0) very slow (*.+,/ cm/
hr).
Soil samples were taken for calculating
erodibility factor before rainy season. Particles
size analysis was determined by sieving andhydrometer methods ; permeability was determined using falling head methods ; soil structure was determined directly in the ﬁeld ; andorganic matter was measured by Walkey andBlack methods.
(.) Topographic factor (LS)The topographic factor was calculated using
Wischmeier and Smith (+312) equation as
follows :LSlῌ,,.+m0/..+ sin,q../0 sinq*.*0/ῌ
where, LS : topographic factor (dimensionless)l : slope length (m)q : angle of slopem : constant, *./ (percent slope/ῌ),*.. (../ῌpercent slope-./ῌ),*.- (-ῌpercent slope+ῌ), *.,(percent slope+ῌ)(/) Co#ee and weeds coveragea. Co#ee coverage
The coverage of co#ee canopy was calculated as the basis for calculating co#ee C-factor.
Ac-.+.Dcῌ,,῍VcAtNAcῌAt+**῎,where, Ac : co#ee canopy area (m )Dc : diameter of co#ee canopy (m)Vc : co#ee coverage (ῌ)
N : number of co#ee trees in experimental plot
At : total area of experimental plot(m,)
The canopy diameters of co#ee trees were
measured every two months, and in this analy-

sis, the average value during measurement
period of each rainy season was used. The
canopy diameter is one of the growth parameters of co#ee trees ; hence it could be used for
C-factor determination during its growth.
b. Weeds coverage
After six months of the experiment, theweeds in both weedy plots had already covered
the soil surface. Before weeds management
was done, the weeds spread under the canopyof the co#ee. So for Paspalum and naturalweeds plots, the following equation was used
to calculate the weeds coverage (Vw) from thesecond to fourth year of experiment.
Vwb+**
῏
VwaAtTawῌAt+**ῐ
Taw -.+.Dwῌ,, N
ῑVwVwbVwaῌ,ΐῒ
Where, Vwb : weeds coverage before cutting (ῌ)
Vwa : weeds coverage after cutting (ῌ)
Dw : diameter of weeded area aroundthe co#ee tree (m)Taw : total area, which has been weededaround the co#ee tree (m,)
Vw : average weed coverage (ῌ)
Because the number of co#ee trees in eachplot (N) was .* and the diameter of weeded area(Dw) was + m, so the value of Vwa was 03ῌ, andaverage value of weeds coverage (Vw) was (+**
03)/,2/ῌ
In clean-weeded plot, a very few weeds
whose heights were less than / cm appeared (e.
g. Ageratum conyzoides). However, they werecleaned as soon as possible they appeared, so
the weeds coverage (Vw) could be estimated to
be zero.
(0) Support practice P-factor
The P-factor was derived using the value
given by Wischmeier and Smith (+312). Because there was no practice management inclean-weeded plot, the P-factor was +. The
P-factor for both weedy plots was also +, for theﬁrst year and second year of measurement.
However, in the third year and fourth year of
measurement, there was a change in micro
slope gradient between the co#ee rows along῕῔ : An Evaluation of Co#ee Crop Factor under Di#erent Weed Managements Using USLE Method in Hilly Humid Tropical Area of Lampung, South Sumatra, Indonesia 25

the slope due to the farmer activities such as
weeds management. A single terrace between
two rows of co#ee trees was developed withslope gradient of -῏2῍, so the P-factor for the
weedy plots was *./ for the third and fourthyear of experiment.
(1) Estimation of crop and management
factorThe crop management factor was calculated
based on the ﬁeld condition, especially co#ee
and weed coverage. Because C-factor is very
critical value, we use two approaches indetermining the C-factor as follows.
a. C-factor derived from similar condition
The combination of ground cover (weeds
coverage) and vegetative canopy (co#ee coverage) was considered in determining the Cfactor. Since there were no information andresults about C-factor of co#ee and weeds combination, the C-factor was derived from similar
condition. The table given by Wischmeier andSmith (+312) for determination of C-factor for
pasture, range, and idle land was matched forthis purpose, because it encounters the percentage of groundcover as well as the percentage ofvegetative canopy. For convenience, the Cfactor derived from this table was called Ct.
b. Equivalent C-factor
Generally, the calculation of C-factor for various combinations of crops was done byweighted average methods. In this method,
every single C-factor was multiplied by the
proportion of the area that every crop
occupied, and then the C-factor was the sum of
every single C-factors. However, this method
could be applied successfully if every single
crop could be clearly deﬁned separately. In
case of co#ee trees, this method is di$cult tobe applied, because the weeds and the co#ee
trees were located side by side from upper
slope to down slope, so erosion from upper
slope will be reduced and entrapped by theweeds. To encounter this problem, new equation is proposed to estimate the C-factor of
weeds and co#ee combination.
C-factor
derived from this equation was designed as Ce.

The derivation of this formula is described inAppendix.
Ceΐ῎ῌ+**ῑVw῍ῌ+**ῒCc+ῌmῐVwῌ+**ῒCw+ῌm῏m῍ῌwhere, Cc : single co#ee crop factor
Cw : single weed crop factor
Ce : equivalent C-factor
m : constant shown in equation (.)
The co#ee and weeds single C-factor used inequation (++) was derived from the research
results in Indonesia. The C-factor for co#ee ingood coverage was *., (Arsyad, +323). Becauseof no information about the co#ee C-factor inbad coverage, we assumed that it was similar
to C-factor for rubber and tea crop with badcoverage. Those C-factor values were *.2 forrubber and *./ for tea as well as mixed-garden
with medium coverage (Hammer, +32+).
The weeds single C-factor for Paspalum conjugatum was assumed to be similar with Bedegrass. There were two values of C-factor for
Bede grass, *.,2 and *.**, (Utomo, +323). The
value *.,2 was applied for the ﬁrst year ofexperiment, because the root system ofPaspalum as well as the coverage was not sodense, and the value of *.**, was applied fromthe second year of experiment.
For natural weeds, the value *.- was used forthe ﬁrst year, assumed to be similar to shrubs(Hammer, +32+) and *.*,+ from the second year
which assumed to be similar to permanentalang-alang (Imperata cylindrica) (Utomo, +323).
(2) Measured C-factor
The measured C-factor was calculated basedon USLE equation as follows :CmΐAῌῌRῌKῌLῌSῌP῍῎ῌwhere, Cm : measured C-factor of each treatment
The value of Cm was calculated yearly and asingle Cm factor for each treatment was foundby averaging four years measurement. The
value of A was obtained from the measurementin each plot ; R, K, L, S values were calculated
based on the observation data, and P was takenfrom table based on the ﬁeld conditions.



26

Table ,

3-,**-

E#ects of di#erent weeds management under co#ee tree on erodibility index

TreatmentYearsiltvery
ﬁne sand(ῌ)

Organic
matter (ῌ)

CodestructureCodepermeabilityK(t · h · MJ+ · mm+)

Cleanweeded
Plot

+st
,nd
-rd
.th
Ave

./
./
./
./

-41
-4-4-40


.
.
.
.


,
+
+
,


*4*+*
*4**1
*4**1
*4*++
*4**3

Paspalum
Plot

+st
,nd
-rd
.th
Ave

....-

04+
.41
.43
04

.
.
.
.


+
+
+
,


*4**/
*4**0
*4**0
*4**3
*4**1

Natural
weeds
Plot

+st
,nd
-rd
.th
Ave

./
./
./
./


/4/
-4*
/4,
.40


.
.
.
.


+
+
+
+


*4**0
*4**2
*4**0
*4**1
*4**1

Table Treatment

Clean-weeded plot
Paspalum plot
Natural weeds plot-.

Co#ee and weeds coverage

Weeds coverage (ῌ)

Co#ee coverage (ῌ)

+st

,nd

-rd

.th

+st

,nd

-rd

.th

+3
,0
,/

*
2/
2/

*
2/
2/

*
2/
2/

+4+4+4-

,-4,
/4*
.4-

+**4*
14+
,41

3,4+
,*42
+141

Results and Discussion-. + Erodibility factor
The result of soil erodibility calculation ispresented in Table ,.
The average value of erodibility factors forclean-weeded plot is *.**3 t · h · MJ+ · mm+followed by natural weeds plot (*.**1 t · h · MJ+
· mm+) and Paspalum plot (*.**1 t · h · MJ+ ·mm+). Comparing with the values of the othersoils in Lampung, these values were smaller.
Using the same method, Susanto (+33,) foundthe values of erodibility between *.*,.ῌ*.*/, t ·h · MJ+ · mm+ in some Red Acid Soils (Ultisol)which were higher than the values found in
this experiment due to lower permeability.
-. , Weeds and Co#ee Coverage

The results of weeds and co#ee coverage arepresented in Table -. After the second year ofexperimental period, the weeds in weedy plots
had already covered the soil surface with anaverage value as much as 2/ῌ coverage.
About +/ῌ of the plots were maintained barefor co#ee areas. In the case of clean-weeded
plot, the weeds were cleared by hand as soon as
they appeared.
In the second year, competition between
weeds and co#ee suppressed the co#ee growthin weedy plots, so the co#ee coverage in bothweedy plots was around /ῌ, whereas in cleanweeded plot was ,-ῌ. The competition was
severe in natural weeds plot due to the existence of Clibadia surinamense whose height
could be , m.

῍ῌ : An Evaluation of Co#ee Crop Factor under Di#erent Weed Managements Using USLE Method in Hilly Humid Tropical Area of Lampung, South Sumatra, Indonesia 27

In the fourth year, the co#ee coverage was,+ῌ in Paspalum plot, which means that co#ee
canopy covered the weeded area (about +/ῌ ofthe total area) and overlapped some part ofweeds area. This situation also occurred innatural weeds plot whose co#ee coverage was+2ῌ. In case of clean-weeded plot, the co#ee
canopy had already covered the erosion plot
since the third year, and in the fourth year theco#ee coverage decreased because the co#eetree had been harvested, and some of the
branches were broken.
-. - Estimation of Crop factor(+) C-factor derived from similar condition
In the ﬁrst year, the co#ee coverage was verysmall since there was no appreciable canopy,
thus the C-factor was mainly determined byweeds coverage. The existing weeds in cleanweeded plot and Paspalum plot were in contact
with the soil surface, covering about +3ῌῌ,0ῌ,
so the C-factor value was *.,*. On the other
hand, the natural weeds which were mostly
herbaceous plants, covered about ,/ῌ, and theC-factor value was *.,.. From the second year
to the fourth year, the weeds coverage in cleanweeded plot was zero, thus the C-factor wasdetermined only by the co#ee coverage. In thesecond year, the height of co#ee tree was less
Table /

Calculation of
combination

than *.3+ m with coverage ,-ῌ, so the C-factor
was *.-0. The C-factors for the third and fourthyear were *.,2.
For Paspalum plot, the C-factor from thesecond to the fourth year was *.*+- because theweeds coverage reached 2/ῌ and the co#ee
coverage was less than ,/ῌ. So the C-factor
was mainly determined by the weeds coverage.
Using the same way explained above, the Cfactor for natural weeds plot was *.*.+ from thesecond to the fourth year. The value of Cfactor derived from table given by Wischmeierand Smith are listed in Table ..
(,) Equivalent C-factor method
The values of some single C-factors for co#ee
and weeds used in this analysis are listed inTable /. The best C-factor for co#ee with goodcoverage was *.,, and the maximum value of
C-factor was *.2 for co#ee with poor coverage.

Table . Combination C-factor (Ct) for co#ee
and weeds based on table given by Wischmeierand Smith (+312)
Treatment

+st

,nd

-rd

.th

Clean-weeded plot
Paspalum plot
Natural weeds plot

*4,*
*4,*
*4,.

*4-0
*4*+*4*.+*4,2*4*+*4*.+*4,2*4*+*4*.+equivalentC-factor(Ce)

C-factor
for co#ee
Cc

C-factor for
weeds
Cw

for

co#ee

Coverageof weeds
Vw (ῌ)

andweeds

Treatment

Year

EquivalentC-factor
Ce

Clean-weeded
Plot

+st
,nd
-rd
.th

*42
*4/
*4,
*4,

*4,2
*
*
*

+3
*
*
*

*41-*
*4/**
*4,**
*4,**

Paspalum
Plot

+st
,nd
-rd
.th

*42
*4/
*4*4,

*4,2
*4**,
*4**,
*4**,

,0
2/
2/
2/

*41**4+3.
*4++0
*4*11

Natural weeds
Plot

+st
,nd
-rd
.th

*42
*4/
*4/
*4,

*4*4*,+
*4*,+
*4*,+

,/
2/
2/
2/

*41*3
*4+3/
*4+3/
*4*2*

  3-

28

Table 0,**-

Soil losses measured and predicted by USLE
Soil loss from each treatment (ton/ha)

No

+
,
.

Year

+st
,nd
-rd
.th
Ave.

Rain
Erosivity(MJ · mm ·ha+ · h+)
-12/*+3+/+2.
3*./

Clean-weeded plot
Measu
Ctrement factor

Cefactor

242,,41++4.+
.413
++43.

+/24*
+*+42
+,-4,
+*.42
+,,4*

.-41-4+1,4/
+.042
+*243

The value of *., was applied if the co#ee area
was totally covered by co#ee canopy. Thisvalue was achieved in clean-weeded plot in thethird and fourth year. And in case of weedy
plots, it was in the fourth year due to the factthat the weeded area (+/ῌ of total area) in bothweedy plots was totally covered by co#ee
canopy. The maximum value *.2 was applied
when the canopy coverage of co#ee was lessthan ,/ῌ. The results of equivalent C-factor
calculated using equation (++) are presented inTable /.
In the ﬁrst year of experiment, the C-factor
value was almost the same in all treatment,
about *.1. The lowest C-factor was achieved inco#ee covered by Paspalum, *.*11 that wasreached in the fourth year of experiment.
-. . Soil loss prediction by USLE method
and soil loss measurement
Soil loss prediction using the USLE methodwith two values of C-factor is presented inTable 0. The average soil loss predicted by
USLE using Ct was lower than using Ce. UsingCt, the average of predicted soil loss was +*2.3
t/ha, 1.1 t/ha and +..+t/ha for clean-weeded
plot, Paspalum plot and natural weeds plot,
respectively, and were 3ῌ,. times higher thanthe measured soil loss. Using Ce, the averagesoil loss predicted were +,, t/ha, -3./ t/ha and.2.2 t/ha for clean-weeded plot, Paspalum plot
and natural weeds plot, respectively, whichwere also +*ῌ2+ times higher than that measured.
The problem related to the using of C-factor

Paspalum plot
Measu
Ctrement factor,41*4**
*
*403

,,4/
,4,
-4,42
141

Natural weeds plot

Cefactor
134*--4+,34+04.
-34/

Measu
Ctrement factor
+4/.
*4+0
*403
*
*40*

-*4,
240
+*42
042
+.4+

Cefactor
234.
.+4+
/+4/
+-4.
.242

in equivalent method is the limitation of available C-factor value. For a particular crop, thevalue of C-factor must be constant. However,there is a big di#erence among values of Cfactor for particular crop from hundreds oferosion plot experiments in Indonesia. For
example, the range of C-factor values, *.-3 to*.3. and *.+0 to *.3-* were found for soybean
and mungbean respectively, and for alangalang grass (imperata cylindrica) which relatively has the same growth performance, theC-factor ranged from *.+* to *.2. (Utomo, +323).
Although the USLE estimation using Ctvalues at Paspalum and natural weeds plots
are ++ and ,. times greater than the soil loss
measurement, the predicted values are still acceptable because its average value was lower
than the soil loss tolerance in Indonesia, which
was ,,.. t/ha/year according to Utomo (+33.)
and ,/ῌ-1 t/ha/year according to Manik et al.
(+331).
The average value of the soil loss estimation
using USLE in each treatment was not as highas it has been found in some Indonesian literatures. Soil loss estimation using USLE in Indonesia was usually applied on watershed scale,
not in a plot scale. In Lampung, Susanto (+33,)
found soil loss of about 2-ῌ,0* t/ha/year forrain-fed agriculture/garden in Way Kandis watershed. Alkohozie et al. (+33,) found -/. and-+. t/ha/year for garden and rain-fed agriculture in upper Way Seputih watershed.
Nugroho et al. (+33+) found the average soil lossof -**ῌ3** t/ha/year for upper Tulang Bawang῍ῌ : An Evaluation of Co#ee Crop Factor under Di#erent Weed Managements Using USLE Method in Hilly Humid Tropical Area of Lampung, South Sumatra, Indonesia 29

watershed.
However, some researches in Indonesia
showed that the soil loss from co#ee areas wasvery low. Gintings (+32,) reported that the soil
loss from +-year old Robusta co#ee with /3ῌ
0-ῌ slope gradient was +.3. t/ha (measured
from May to October) and the soil loss from -years old co#ee with slope gradient of 0,ῌ00ῌ
measured from May to October was +./1 t/ha.
Soil loss from +0-years old co#ee with slope of.0ῌ.3ῌ measured during almost one year
(January-October) was ,../ t/ha. Studies weremade from December +320 to June +321 by
Pudjiharta and Pramono (+322) under +/-yr-old
co#ee, corresponding results were *.*, t/ha ona slope of ,*ῌ,-ῌ with undergrowth, and *.+,
t/ha on a slope of ..+ῌ without undergrowth.
Gintings (+32,) also found that the soil loss
from virgin forest with //ῌ0/ῌ slope gradientin Sumber Jaya from January to October +32*
was *./3 t/ha. Since the soil loss from co#ee
areas in Indonesia was very small, a little bit
higher than soil loss from virgin forest areas(Gintings, +32,), the co#ee C-factor should be alittle bit higher than forest C-factor.
The above discussion has proved that theaccuracy of soil loss prediction by USLE ismostly determined by the selection of appropriate value of C-factor. Since there was noexact information of co#ee C-factor in Indonesia, approximation value using similar crop (asit was done in equivalent C-factor) or similar
condition might be done with various results.
-. / Measured C-factor
The measured C-factor (Cm) of each treatment is shown in Table 1. The values of Cm
were very low compared to the existing Cfactor used in Indonesia which usually considered as *.,. The average value of Cm in eachtreatment was *.*./ for co#ee in clean weeded
treatment, *.**0 for co#ee with Paspalum and*.**. for co#ee in natural weeds. The co#ee
C-factor found in this experiment was almost
same with the C-factor for Brachiara grass (*.*,
ῌ*.**,), primary forest (*.**+ῌ*.**/) (Sinukaban,+32/), and undisturbed forest (*.***+ῌ*.**3)(Wischmeier and Smith, +312). The value of *.,usually used in Indonesia was adopted fromthe values of co#ee C-factor with cover crop in
West Africa as compiled by Roose (+311), wherethe value of co#ee C-factor ranged from *.+ to*.-. The low value of C-co#ee factor found in
this experiment was supported by the fact inprevious discussion that the soil loss fromco#ee areas in Indonesia was very low. Probably, the di#erent managements in co#ee plantation had caused that the values of C-factor
found in this experiment were di#erent from
C-factor values of “text book”. In Indonesia,
several researchers had found the di#erent
values of C-factor for certain plant. Utomo(+323) showed that there were four C-factor
values for soybean which were resulted fromsoil erosion plot experiment : *.+0, *..1, *.3-, and*.03*, due to di#erent managements. In case ofco#ee tree in this experiment, weeding wasdone by taking the weeds using hand for cleanweeded co#ee.
As a result, the soil was
minimally destroyed, hence the soil erosion
became small. In addition to this, the litter
originated from the co#ee leaves was nevertaken out from the plot.
As shown in Table -, the percentage of
weeds coverage in clean-weeded co#ee plot
was zero from the second until the fourth yearof experiment, hence the C-factor was totally
determined by the coverage of the co#ee. For
clean weeded co#ee (as shown in Table 1), themaximum value of Cm was *.+++1 when theco#ee coverage reached ,-ῌ, and the minimum value was *.**3+ when the coveragereached 3,ῌ. Since the C-value for bare soil is+, and the minimum value of C-factor is *.**3+,
a graph could be made for estimating the co#ee
C-value for various co#ee coverage with cleanweeded management, using the measured
co#ee C-factors as listed in Table 1. The resultis shown in Fig. +.
The estimation of the C-factor for co#ee withground coverage could be made by introducing
the concept of C-subfactor. The concept ofC-subfactor which had been discussed by

30

Table 1

3-,**-

Measured C-factor

Treatment

+st

,nd

-rd

.th

Average

Clean-weeded plot
Paspalum plot
Natural weeds plot

*4*.*2*4*,.*4*+,,*4+++1*4***,*4***2*4*+2/*4*****4**,0*4**3+*4*****4*****4*./**4**0+*4**-3

Wischmeier and Simth (+312) as well as
Dissmeyer and Foster (+32+) could be appliedby considering the e#ect of weeds as the subfactor. So, the co#ee C-factor (Cc) for various
ground covers can be estimated as following
equation :CcCbCs῍ῌCc : co#ee C-factor with ground coverageCs : subfactor
Cb : co#ee C-factor without groundcoverage
In clean-weeded co#ee, the Cc will be only
inﬂuenced by Cb, so the value of subfactor Cs
will be + or in other word the ground (weeds)
coverage is *ῌ. On the other hand, if theground (weeds) coverage is +**ῌ, the Cc will be* because the soil loss is *, so the Cs factor willbe *. Based on equation (+-), the value of Cs
subfactor in this experiment could be calculated by the following equation :CsCwῌCb῎ῌwhere, Cs : weeds C-subfactor
Cb : measuring co#ee C-factor at cleanweeded plot (co#ee in bare condition)
Cw : measuring co#ee C-factor at boththe Paspalum and natural weeds
plots
Based on the values in Table 1 (Cw value),
Table - (weeds coverage value), and Fig. + (Cbvalue), the Cs value for Paspalum and naturalweeds could be calculated for various coverageof co#ee tree using equation (+.) and theresults were tabulated in Table 2.
Table 2 showed that with weeds coverage of,/ῌ, the C-subfactor was very low, less than*.*-, and the C-subfactor value was almost zero
when the weeds coverage became 2/ῌ. In

Fig. +

Relationship between co#ee C-factor(Cb) and co#ee coverage.

conclusion, applying ,/ῌ of ground coverage
is enough for controlling soil loss in co#ee
areas, so it is not necessary for covering thewhole soil surface with weeds.
..

Conclusion

Evaluation of co#ee crop factor (C) as a partof USLE was done on erosion plot with gradient -*ῌ in humid tropical areas of Indonesia.
The co#ee C-factors for USLE calculation were
estimated by deriving from the available tablegiven by Wischmeier and Smith (+312) andusing new concept of equivalent C-factor. The
results showed that the values of estimatedco#ee C-factor derived from the table were*.*+-῏*.,2, while the values of equivalent Cfactor were in the range of *.*11῏*.1-, and as aresult, the soil loss estimated was higher whenequivalent C-factor was used. Using Ct, theaverage soil loss was +*2.3, 1.1 and +..+ t/ha/
year for clean-weeded plot, Paspalum plot andnatural weeds plot respectively, which was 3῏,. times greater than the soil loss measure-ῐ῏ : An Evaluation of Co#ee Crop Factor under Di#erent Weed Managements Using USLE Method in Hilly Humid Tropical Area of Lampung, South Sumatra, Indonesia 31

Table 2The estimated value of weed subfactor (Cs) in co#ee garden

Weeds type

Year

Paspalumconjugatum

+
,
.

,0
2/
2/
2/

Natural
weeds

+
,
.

,/
2/
2/
2/

Cc

C b *ῌ

Cs

+4/4*
14+
,*42

*4*,.*4***,*4*****4****

*433
*43.
*40*
*4+-

*4*,./*4***,*4*****4****+4.4,41+141*4*+,,*4***2*4**,0*4****

*433
*411
*431
*4+3

*4*+,*4**+**4**,1*4****

Coverage
Coverageof weeds (ῌ) of co#ee (ῌ)*ῌ The value of Cb is taken from Fig. + with each coverage of co#ee tree.

ment. However, the predicted value was still
acceptable and reasonable, because it was
lower than the soil loss tolerance.
The measured value of co#ee C-factor was*.*./, *.**0, and *.**. for clean- weeded co#ee,
Paspalum plot and natural weeds plot, respectively which were lower than the value (*.,)
usually used in Indonesia. By considering thee#ect of weeds as the subfactor (Cs), the valueof co#ee C-factor (Cc) with various coverage of
weed can be estimated using the following
equation :Cc῎Cb῍Cs
Where Cb could be estimated from the graphwhich was derived from this experiment.
Acknoledgments
Appreciation is extended to Ministry of Education, Culture, and Sport of Japan, for funding
this research.
Reference
Abujamin, S., Adi, A. and Kurnia, U. (+32-) : Permanent grass strip as one of soil conservation
methods, Soil and Fertilizer Research News,
Center for Soil Research, Ministry of Agriculture, Indonesia, + : +0ῌ,* (in Indonesian).
Afandi, Manik, T.K., Rosadi, B., Utomo, M., Senge,
M., Adachi, T. and Oki, Y. (,**,) : Soil erosion
under co#ee trees with di#erent weed management in humid tropical hilly area of
Lampung, South Sumatra, Indonesia, J. of Japanese Society of Soil Physics, 3+ : -ῌ+..
Alkhozie, Manik, K.E.S. and Afandi (+33,) : Soil loss
estimation using USLE, Experimental Journalof Faculty of Agiculture of Lampung University V (.) : ,/,-ῌ,/-- (in Indonesian).
Arsyad, S. (+323) : Soil and water conservation, IPB
Press, Bogor. (in Indonesian).
Dissmeyer, G.E. and Foster, G.R. (+32+) : Estimating
the cover management factor (C) in the Universal Soil Loss Equation for forest condition,
J. of Soil and Water Conservation, -0 (.) : ,-/ῌ,.*.
Foster, G.R., McCool, D.K., Renard, K.G. andMoldenhauer. W.C. (+32+) : Conversion of theuniversal soil loss equation to SI metric units.
J. of Soil and Water Conservation, -0 (0) : -//ῌ-/3.
Gintings, A.G. (+32,) : Surface runo# and soil erosion under co#ee plantation and natural forest
at Sumber Jaya-North Lampung, Forest Research Institute, Ministry of Agriculture Indonesia, Report No.-33 (in Indonesian).
Hammer, W.I. (+32+) : Second Soil Conservation
Consultant Report, Note No. +*, Centre for Soil
Research, Bogor, Indonesia : 32.
Lal, R. (,***) : Physical management of the tropics,
Soil Science, +0/ (-) : +3+ῌ,*1.
Manik, K.E.S., Susanto, K.S. and Afandi (+331) : Estimation of allowable soil loss in two dominantsoil in Lampung, J. of Tropical Soils II (.) : 33ῌ
+*0. (in Indonesian).
Nugroho, S.G., Utomo, M., Haryono, N., Damai, A.A.,
Muludi, K., Bakri, S. and Andi. (+33+) : Estimation of runo#, erosion, and sedimentation of
Tulang Bawang watershed, A Database,
Report of Research Institute of Lampung University : ,/ (in Indonesian).
Pudjiharta, A.G. and Pramono, I.B. (+322) : Runo#and soil erosion under natural forest stands
and co#ee plantations at Tabanan, West Bali,
Forest Research Bulletin .32 : +ῌ2. (in Indone-



32

sian).
Risse, L.M., Nearing, M.A., Nicks, A.D. and Laﬂen, J.
M. (+33-) : Error measurement in the Universal
Soil Loss Equation. Soil Sci. Am. J., /1 : 2,/ῌ2--.
Roose, E. (+311) : Use of the universal soil loss equation to predict erosion in West Africa, Proc. of
the National Conference, Soil Erosion,
Predicrion, and Control, Soil Conservation Society of America, Ankeney, Iowa : +.-ῌ+/+.
Sinukaban, N. (+32/) : Soil and water conservationin transmigration areas, Main Manual, Ministry of Transmigration, Indonesia. (in Indonesian).
Sriyani, N., Suprapto, H., Susanto, H., Lubis, A.T.
and Oki, Y. (+333) : Weeds population dynamics in co#ee plantation managed by di#erent
soil conservation techniques. Proc. of International Seminar, Toward Sustainable Agriculture in Humid Tropics Facing ,+st Century,
Bandar Lampung, Indonesia, September ,1ῌ,2: /+-ῌ/,*.
Susanto, K.S. (+33,) : Characteristic of Way Kandis
sub-catchment in South Lampung and
Lampung city, Thesis Post Graduate Program,
Bogor Agricultural University. Bogor. (in Indonesian).
Utomo, W.H. (+323) : Soil conservation in Indonesia, A Record and Analysis, Rajawali Press,
Jakarta. (in Indonesian).
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IKIP Malang Press, Malang (in Indonesian).
Wischmeier, W.H., Johnson, C.B. and Cross, B.V.
(+31+) : A soil erodibility nomograph for farmland and construction sites, J. of Soil andWater Conservation, ,* : +/*ῌ+/+.
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No./-1 : /1.

Appendix
Consider the equivalent C-factor of the slope
as shown in Fig. ,. This slope consists of threesub-slopes where only the crop management
factors are di#erent. And soil loss from eachsub-slope could be estimated by USLE equation.
Soil loss (A) is expressed in the following
equation as the function of slope length (L) and3-  ,**-

Fig. ,

Equivalent C-factor of the slope.

crop management factor (C) by combining theequations (+) and (.).
AaῌCῌLmaRῌKῌPῌ+ῌ,,.+m0/..+ sin,q
../0 sinq*.*0/
If equivalent C-factor of slope I and II is
designed as Ce,, soil loss from these slopes (A,)
is expressed by the following equation.
A,aCe,L,m
And soil loss from slope I (A+) is expressed asfollows.
A+aῌC+ῌl+m
If the slope I has the same C-factor of slope II(C,), soil loss (A+) is expressed by following
equation.
A+aῌC,ῌl+῍m
In this case, the length of slope I must bechanged to l+῍ calculated by the following equation.
l+῍C+ῌC,+ῌml+
Soil loss from slope II (A,) is expressed by thefollowing equation.
A,aῌC,ῌL,῍maῌC,ῌl,l+῍maῌC,l,C+ῌC,+ῌml+maῌCe,L,m
Equivalent C-factor (Ce,) is expressed asfollows.
Ce,C,l,ῌL,C+ῌC,+ῌml+ῌL,m
C,+ῌml,ῌL,C++ῌml+ῌL,m
By the same procedure, equivalent C-factor of
the slope I to II (Ce-) can be derived as follows.
Ce-C-+ῌml-ῌL-Ce,+ῌmL,ῌL-m
C- +ῌm l- ῌ L-C, +ῌm l, ῌ L-C+ +ῌm l+ ῌL-mhere, the coverage of the crop of slope I (V+)

¼ : An Evaluation of Co#ee Crop Factor under Di#erent Weed Managements Using USLE Method in Hilly Humid Tropical Area of Lampung, South Sumatra, Indonesia 33

could be expressed as follows.
V+l+ῌLFinally, equivalent C-factor of slope I to III (Ce-)
can be expressed by the function of single crop

factor of each slope and the coverage of eachcrop.
Ce-C-+ῌmV-C,+ῌmV,C++ῌmV+m
USLE   ῌ !"#ῌ#$%&'()*+,-./*ῌ 
*ῌ  *ῌ !"#**ῌ$%&***ῌ' (****ῌ* )*+,-,.
** /0+,-,.
*** 12+,345,.

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