Accurate estimation of lime requirement (LR) has been a problem since liming practices began. Thus, a field study was done in 2014 and 2015 to determine the LR by using different methods and investigate barley response to lime and phosphorus fertilizer. Shoemaker-McLean-Pratt (SMP) buffer, Ca(OH)2 titration, permissible acid saturation percentage and exchangeable acidity LR testing methods were evaluated with factorial combination of P; 0, 34.5 and 69 kg P2O5 ha-1, arranged in a randomized complete block design with three replications. The results showed that application of lime and P fertilizer had significant (p<0.05) effect on the yield of barley on testing sites where soil pH was <5.0. The highest grain yield, 3.2 t ha-1, was obtained from application lime estimated with SMP method statistically at par with Ca(OH)2 titration method. Application of 69 kg P2O5 ha-1 gave the highest yield statistically at par with 34.5 kg P2O5 ha-1. SMP method estimated lime raised the soil pH from 5.6 to 6.7, 6.2 to 6.8 and 5.6 to 6.2, while Ca(OH)2 titration method estimated lime raised soil pH from 5.6 to 6.5, 6.2 to 6.5 and 5.6 to 6.2. However, the LR estimated with SMP method exceeded the LR estimated with Ca(OH)2 titration method by 44.2%. Thus, Ca(OH)2 titration method was found best LR estimation method among the methods evaluated in this study.

1. Method for Estimation of Lime Requirement to Assess Lime and Phosphorus Application on the Yield of Barley (Hordeum vulgare L.)
Method for Estimation of Lime Requirement to Assess
Lime and Phosphorus Application on the Yield of Barley
(Hordeum vulgare L.)
*1
Abebe Getu Asfaw, 2
Samuel Adissie Gedamu, 3
Tilahun Taye Mekonen, 4
Tadesse Hailu Shibeshi
1,2,3,4Sirinka Agricultural Research Centre (SARC), P.O.Box 74, Woldia, Ethiopia
Accurate estimation of lime requirement (LR) has been a problem since liming practices began.
Thus, a field study was done in 2014 and 2015 to determine the LR by using different methods
and investigate barley response to lime and phosphorus fertilizer. Shoemaker-McLean-Pratt
(SMP) buffer, Ca(OH)2 titration, permissible acid saturation percentage and exchangeable acidity
LR testing methods were evaluated with factorial combination of P; 0, 34.5 and 69 kg P2O5 ha-1
,
arranged in a randomized complete block design with three replications. The results showed that
application of lime and P fertilizer had significant (p<0.05) effect on the yield of barley on testing
sites where soil pH was <5.0. The highest grain yield, 3.2 t ha-1
, was obtained from application
lime estimated with SMP method statistically at par with Ca(OH)2 titration method. Application of
69 kg P2O5 ha-1
gave the highest yield statistically at par with 34.5 kg P2O5 ha-1
. SMP method
estimated lime raised the soil pH from 5.6 to 6.7, 6.2 to 6.8 and 5.6 to 6.2, while Ca(OH)2 titration
method estimated lime raised soil pH from 5.6 to 6.5, 6.2 to 6.5 and 5.6 to 6.2. However, the LR
estimated with SMP method exceeded the LR estimated with Ca(OH)2 titration method by 44.2%.
Thus, Ca(OH)2 titration method was found best LR estimation method among the methods
evaluated in this study.
Key words: Barley, lime, lime requirement, phosphorus, soil acidity.
INTRODUCTION
Soil acidity is rampant in Ethiopia and it is becoming a
serious threat to crop production in the western, southern,
northwestern and central highlands of the country
(Abdenna et. al., 2007; Taye 2007; Behailu, 2015 and
Mesfin, 2007). This is attributed to higher precipitation,
which exceeds evapotranspiration that subsequently
leaches appreciable amounts of exchangeable bases from
the soil surface. As a result, most of the soils have a pH
range of 4.5 - 5.5, low OM content (<20 g/kg) and low
available plant nutrients (Temesgen et al., 2011).
Soil acidification and erosion are the major soil
degradation issues in the humid and highlands areas of
North-eastern escarpment of Ethiopia. Different studies
showed that soils in the highland areas of North Wollo
including the present study area, Wadla district, have
become acidic with the soil acidity level ranging from
slightly to strongly acidic.
Accordingly, to reclaim the soil acidity problem in the
highland areas of North Wollo Zone, the North Wollo Zone
Bureau of Agriculture with Dessie Regional Soil Testing
Laboratory had conducted extensive soil acidity survey
and advised different lime recommendations at farmer’s
field level. However, the lime requirement (LR) testing
method i.e permissible acid saturation percentage (PASP)
method as described by Manson and Katusic (1997), used
to determine the LR is not accurate and underestimate the
LR. Some soil testing laboratories in the region have
adopted exchangeable acidity and Shoemaker, McLean,
and Pratt (SMP) (Shoemaker et al., 1961) single buffer as
LR estimation methods. However, indirect lime testing
methods such as SMP buffer method (Shoemaker et al.,
1961), Adams and Evans buffer method (Adams and
Evans, 1962), Mehlich (Mehlich, 1976), need to be
*Corresponding Author: Abebe Getu Asfaw, Sirinka
Agricultural Research Centre (SARC), P.O.Box 74,
Woldia, Ethiopia. Email: abegetu3@gmail.com
Co-Authors 2
Email: Sammy.ab1990@gmail.com, 3
Email:
sarctilahun3@gmail.com, 4
Email: tadessesarc@gmail.com
Research Article
Vol. 7(1), pp. 192-200, February, 2020. © www.premierpublishers.org. ISSN: 2326-3997
World Research Journal of Agricultural Sciences

2. Method for Estimation of Lime Requirement to Assess Lime and Phosphorus Application on the Yield of Barley (Hordeum vulgare L.)
Asfaw et al. 193
calibrated and validated to the Ethiopian soils before
adoption. Because most of the buffer methods were
developed in the United States (US) for American soils by
indirect calibration experiments with the standard
reference methods; soil incubation with CaCO3 and/or
Ca(OH)2 (Dumford and Coronel, 1966; Mehlich A, 1976;
Loynachan, 1979; Barrow and Cox, 1990).
Different studies showed that SMP method (Shoemaker et
al., 1961), based on the average buffer capacity of a broad
group of soils, is reasonably accurate for a wide range in
LR. Recently, McLean et al. (1978) have indicated that the
SMP method is most accurate for soils that have a LR > 4
meq/100 g, pH < 5.8, OM < 10%, and soluble (extractable)
Al in appreciable quantities. However, it was also reported
that SMP method has low correlation on soils with low lime
requirement and it tends to overestimate LR on sandy
soils. The Adams and Evans method (Adams and Evans,
1962) was developed for Red-Yellow Podzolic soils
(Ultisols) where amounts of lime needed may be small,
and the possibility of damage from over-liming exists.
However, this method has shortcomings of
underestimating LR on high CEC soils, not suited for
organic soils or mineral soils high in clay or organic matter,
and also not suited on soils high in montmorillonitic type
clays. Mehlich buffer method (Mehlich A, 1976) is a
relatively new buffer pH method for the rapid estimation of
unbuffered salt-exchangeable acidity and lime
requirement. In view of the importance of exchangeable
acidity, and particularly exchangeable AI, Mehlich
determined that there was a need for a buffer primarily
calibrated against salt-exchangeable acidity for lime
requirement determinations. The method gives a
quantitative measure of exchangeable acidity.
Different rapid LR testing methods can give widely
divergent results (Peech M, 1965), certain methods are
better suited to specific soil conditions (Mehlich et al.,
1976). Incubation in the field would be ideal for determining
LR, but it is prohibitive due to the high cost and time
required. Baker and Chae (1977) reported that the use of
room temperature incubation of incremental mixtures of
CaCO3 and soil tends to overestimate the actual LR.
Because soil acidity increases under room temperature
incubation. Even though the titration method for
determining the soil pH buffering capacity is considered
reliable and is often used as a calibration for 11 buffer
methods, it is not considered for routine measurement of
the LR especially in soil testing laboratories because of the
time required (Follett and Follett, 1980).
Barley (Hordeum Vulgare L.) is one of the most dominant
cereal crops produced and consumed in Wadla district of
North Wollo Zone of Amhara Region. It is a dependable
source of food in the highlands as it is produced during the
main and short rainy seasons as well as under residual
moisture. However, it is considered sensitive to soil acidity
and so as to aluminum (Al) (Stolen and Anderson, 1978).
In addition, highly weathered tropical and acid soils have
strong P sorption capacities, which intensify limitation of
land suitability. Phosphorus (P) fixation by the
predominant Al3+ and Fe2+ ions in strong soil acid
conditions leads to P deficiency for crop growth. Therefore,
lime application along with P fertilization has a paramount
importance to ameliorate soil acidity and achieve
maximum yield. The objectives of this study were,
therefore, to select the most accurate LR estimation
methods suitable for the study area and evaluate the
response of barley to the combined application of lime and
P fertilizer.
MATERIALS AND METHODS
Site Description
The study was conducted in 2014-2015 and 2015-2016
main cropping seasons in Wadla district of North Wollo
zone of the Amhara Region. The study district is situated
with an altitude range of 2000-2800 meters above sea
level and within the geographical coordinates of 11o
49’59.99” N and 38o 49’ 59.99” E. The district receives a
mean annual rainfall of 800-1200 mm with minimum and
maximum temperature of 17 and 22oC, respectively.
Experimental Procedures
Selection of farmers’ fields and lime estimation
methods
Soil samples at a depth of 0-20 cm were collected from ten
farmers' fields prior to starting the experiment for pH
analysis. Based on the soil pH (1:2.5 soil: water
suspension) results, three farmers’ fields with strong to
moderate soil acidity were selected for the experiment.
Four different methods were used for determination of LR
such as, SMP single buffer method (Shoemaker et al.,
1961), Ca(OH)2 direct titration method (Dunn, 1943; Liu et
al., 2004), permissible acid saturation percentage method-
PASP (Manson and Katusic, 1997) and exchangeable
acidity method (multiplied by a correction factor of 1.5 and
it is included in the second year of the study).
Soil testing procedures for LR estimation methods
Shoemaker-McLean-Pratt (SMP) single buffer (SB)
method
Ten milliliter of SMP buffer (pH 7.5) was added to the soil-
water slurry used for pH determination (1:1 soil water
suspension), then, the mixture was closed tightly and
shaken at 250 excursions per minute for 10 minutes and
was settled for 20 minutes. The pH was measured under
stirring to the nearest 0.01 pH unit. Finally, the lime
requirement was determined from soil-buffer pH and
existing calibrated data developed in US.
Ca(OH)2 direct titration method (Dunn, 1943 and Liu et
al., 2004)

3. Method for Estimation of Lime Requirement to Assess Lime and Phosphorus Application on the Yield of Barley (Hordeum vulgare L.)
World Res. J. Agric. Sci. 194
Thirty milliliter distilled water was added to 30 g of air dried
and ground soil sample, which passed through a 2 mm
sieve. The water soil mixture (ratio of 1:1) was carefully
mixed with a glass rod for 30 minutes and left to decant for
30 min. The initial soil pH was measured under stirring by
inserting a pH electrode in to the water soil mixture. Since
titration curves are nearly linear within the pH range of
most agricultural surface soils (4.5 to 6.5), three aliquots of
base (Ca(OH)2) were used to develop the slopes of the
titration curves for each soil. Thus, three time of 3 ml of
Ca(OH)2 solution (0.022M) were added to the above
mixture with 30 minutes interval every time while mixing
thoroughly for 30 min for each addition. The changes in pH
were measured systematically. The pH electrode was
rinsed with distilled water after each pH measurement to
avoid cross contamination. The titration curve was plotted
by taking the pH values (4 pH values including the initial
pH measurement) measured against the volume of
Ca(OH)2 added. A linear regression graph was then fitted
by plotting the base added in the abscissa and the change
in soil pH measured in the ordinate. The LR was calculated
based on the slopes of the linear regression equations and
the pH difference between initial pH (y intercept) and the
desired pH i.e. 6.5 as shown in the equation below;
LR (kg CaCO3 per ha) =
6.5 − Intercept
Slope
Permissible acid saturation percentage method
(PASP) (Manson and Katusic, 1997)
LR (kg CaCO3 per ha) = 1160x [Exchangeable acidity −
1
10
(ECEC)]. Where, ECEC is effective cation exchange
capacity and 1/10 (ECEC) is meant for the assumption that
the permissible acid saturation percentage level for wheat
is 10% (1/10).
Exchangeable acidity method
5.1*
2000
1000*)/(..*10*15.0*/
)/(,
324
3
mMgDBmmsoilofkgcmolEA
hakgCaCOLR =
. Where, EA is exchangeable acidity, B.D is soil bulk
density and a 1.5 multiplication factor was adopted based
on a recommendation by Birhanu et al. (2016).
Liming, fertilizer application and planting
In the field evaluation study, the LRs determined with the
four LR testing methods and control (without lime) were
factorially combined with three levels of P fertilizer (0, half
and full of the recommended P i.e. 69 kg P2O5 ha-1). The
treatments were arranged in the randomized complete
block design with three replications.
Agricultural calcitic lime with fineness factor of 0.52,
moisture content of 1.06%, and Calcium Carbonate
Equivalent (CCE) of 90% (Mekonen et. al., 2014)
produced from Dejen lime factory was spread evenly and
incorporated in to the plow layer (20 cm) three weeks
before planting the test crop. Phosphorus fertilizer was
applied in a row all at planting. While, N fertilizer (46 kg N
ha-1) was applied half at planting and the remaining half at
tillering (40 days after planting).
The plot sizes had an area of 12 m2 (3 m * 4 m) with a
spacing of 1 m between experimental plots and
replications. The food barley variety with local name
Agegnehu was used, planted by drilling in a row with 20
cm spacing and a seeding rate of 120 kg ha-1. There was
a total of 20 rows of plants in each plot out of which the
inner most 18 rows were harvested and used for data
collection and analysis.
Soil sampling
Three composite surface (0-20 cm) soil samples were
collected from the three testing sites before the lime
application for pH analysis (H2O and 0.01 M CaCl2),
texture, exchangeable acidity, exchangeable aluminum,
available P, exchangeable Ca, Mg, K and Na. Surface (0-
20 cm) soil samples were also collected plot wise after
harvesting to investigate the effects of each lime rates
applied on soil pH, exchangeable acidity and
exchangeable Al3+. The soil sampling depth i.e. 20 cm was
selected as the lime was incorporated to the 20 cm surface
layer of the soil.
Soil analysis
Particle size distribution (soil texture) was determined
following the modified Bouyoucous hydrometer method
(Bouyoucous, 1962). Soil textural class names were then
assigned based on the relative contents of the percent
sand, silt, and clay separates using the soil textural triangle
of the USDA. Soil pH was measured potentiometrically
using a combined glass electrode pH meter in water and
0.01M CaCl2 solution at 1:2.5 soil to water ratio (Van
Reeuwijk, 1992). Exchangeable acidity was determined by
saturating the soil samples with 1M KCl solution and
titrating with 0.01M NaOH as described by Mclean EO
(1965) and Rowell (1994). Exchangeable Al was
determined from aqueous solutions extracted by 1M KCl
and NaF and titrated with 0.01M HCl. Exchangeable bases
(Ca, Mg, Na and K) were extracted with 1M NH4OAc at pH
7 and then Ca and Mg were determined by EDTA titration,
while K and Na were determined using flame photometry.
Effective cation exchange capacity was calculated as the
sum of exchangeable basic cations and Al (United States
Department of Agriculture Soil Survey Information
Laboratory Manual, 1995). While, organic carbon (OC)
was determined by wet digestion method through chromic
acid digestion method as described by Walkley A and
Black A (1934) and available P was determined
colorimetrically using Olsen’s method (Olsen, 1952).
Data collected
Grain yield was measured at maturity from the inner most
18 rows and was adjusted to a 12.5% moisture content.

4. Method for Estimation of Lime Requirement to Assess Lime and Phosphorus Application on the Yield of Barley (Hordeum vulgare L.)
Asfaw et al. 195
Fresh biomass weight was measured by weighing the
fresh total above ground biomass of the harvestable rows.
While, the dry biomass weight was measured by taking
straw sample with the seed spikes, drying in an oven at
105 oC for 12 hours and adjusting the fresh biomass weight
in to dry biomass by using the moisture content measured
after an oven dry. Plant height was measured at maturity
from random five plant samples of the harvestable rows,
from ground level to the tip of the spike including the awns.
Thousand seed weight was also randomly measured on a
sensitive balance.
Data analysis
The data recorded were subjected to analysis of variance
(GLM procedure) using SAS software version 9.00 (SAS
Institute, 2004). The LSD and DMRT mean separation
methods at 5% probability level were used to separate
treatment means. Statistical analysis result of plant height
and 1000 seed weight data are not included in the report
as grain and dry matter yield can show the effect of liming
and application of P with better magnitude.
RESULTS AND DISCUSSION
Soil Acidity and Some Soil Physico-chemical
Properties of Study Sites before Liming
The soil acidity levels and some other selected soil
physico-chemical properties of the three experimental
farmers’ fields in the two experimental years are shown in
the Tables below (Table 1, 2). The soil acidity levels of the
farmers’ fields selected for the study in the first
experimental year, based on the ratings by Jones (2003),
were very strongly and moderately acidic (Table 1). While,
the soil acidity level of the farmer’s selected in the second
experimental year was very strongly acidic (Table 2).
Table 1. Acidity levels and some physico-chemical properties of surface soils (0-20 cm) of the study fields in 2014
Testing site pH (H2O) pH (CaCl2)
Exch. H+
Exch. Al3+
Exch. acid
Acid saturation (%)meq/100 g
Site 1 4.97 4.50 0.580 1.06 1.632 17.1
Site 2 6.00 4.75 0.096 - 0.096 1.70
Exch. H+: exchangeable hydrogen, Exch. Al3+ : exchangeable aluminum, Exch. Acid: exchangeable acidity
Testing site
Exch. Ca+Mg Exch. Na Exch. K ECEC Sand Silt Clay
Textural classmeq/100 g %
Site 1 7.50 0.195 0.205 9.5321 16 40 44 Silt clay
Site 2 5.05 0.087 0.397 5.6296 22 50 28 Clay loam
Exch. Ca+Mg: exchangeable calcium plus magnesium, Exch. Na : exchangeable sodium, Exch. K: exchangeable
potassium, ECEC: Effective cation exchange capacity.
Table 2. Acidity levels and some physico-chemical properties of surface soil (0-20 cm) of the testing site in 2015
Testing site pH (H2O) Exch. acidity (meq/100g) Organic Carbon (%) Available P (mg kg-1
) Textural class
Site 3 4.70 0.576 2.38-2.57 4.84-6.76 Sandy clay loam
Exch. Acidity: exchangeable acidity, available P: available phosphorus
Lime Requirement based on the Four Methods
The LR (t ha-1 CaCO3) for the experimental farmers’ fields
estimated based on different methods such as SMP buffer
method, Ca(OH)2 titration method, PASP and
exchangeable acidity method (included in year II only) is
shown below (Table 3, 4).
Table 3. Lime requirement (t ha-1 CaCO3) of the testing
sites based on the three methods in 2014
Testing sites SMP buffer Ca(OH)2 titration PASP
Site 1 15.1 9.3 0.8
Site 2 9.0 4.2 NL*
Mean 12.05 6.75 0.8
*NL: No lime is required based on the method, i.e. PASP
Table 4. Lime requirement (t ha-1 CaCO3) of the testing
sites based on the four methods in 2015
Testing
site
SMP
buffer
Ca(OH)2
titration
Exch.
Acidity PASP
Site 3 4.00 2.17 0.97 NL*
*NL: No lime is required based on the method, i.e. PASP
Effect of Application Lime and P Fertilizer on the
Barley Yields
In the first experimental year, the agronomic data analysis
results showed that there was no significant interaction
effect of the application of lime and P fertilizer on the barley
yield at both testing sites (Table 5). However, the grain and
dry biomass barley yields at site 1 were significantly
affected by the main effects of the lime application and the
P fertilizer. This indicated that the lime application
significantly ameliorated the initial soil acidity level (pH
4.97) of testing site 1, which eventually resulted in a
significant yield improvement as compared to the control
(No lime) treatment and limed treatment with PASP
method. A number of authors reported a positive effect of
liming on barley growth and grain yield (Tang et al., 2003
and Kovacevic et al., 2006). Ito et al. (2009) also reported
the positive responses of barley root growth and yield
improvements on acidic Andosols due to liming. The
significant yield response to the applied P fertilizer might
also be attributed to the supply of P in the treated plots as

5. Method for Estimation of Lime Requirement to Assess Lime and Phosphorus Application on the Yield of Barley (Hordeum vulgare L.)
World Res. J. Agric. Sci. 196
Table 5. Main effects of lime and P fertilizer on the barley yields (kg ha-1) at both study sites (1 and 2) in 2014
Lime rates*
(CaCO3 t ha-1
)
Grain yield Dry biomass Lime rates*
(CaCO3 t ha-1
)
Grain yield Dry biomass
Site 1 Site 2
Control (0) 1229.8c 4045.3c 0 2976.8 7689.9b
SMP buffer (15.1) 2054.9a 6401.2a 9.0 3235.0 8111.1a
Ca(OH)2 titration (9.3) 1655.8b 5446.5b 4.2 3314.5 8332.2a
PASP (0.8) 952.7c 3671.2c 0 - -
Grand mean 1512.4 4936.8 Grand mean 3175.5 8044.4
CV (%) 18.0 13.4 CV (%) 12.4 5.0
LSD (5%) 290.34 684.12 LSD (5%) NS 379.5
P rates*
(kg P2O5 ha-1
)
P rates*
(kg P2O5 ha-1
)
Control (0) 1011.9c 3838.2b 0 2811.5b 7435.2b
Half of rec. (34.5) 1645.4b 5356.9a 34.5 3337.5a 8261.8a
Full rec. (69) 1916.6a 5615.4a 69 3377.4a 8436.2a
Grand mean 1512.4 4936.8 Grand mean 3175.5 8044.4
CV (%) 18.0 13.4 CV (%) 12.4 5.0
LSD (5%) 248.27 591.69 LSD (5%) 393.2 379.5
*Means with in a column followed by the same letter are not significantly different at 5% probability level. NS: Non-
significant at 5% probability level.
compared to the untreated ones, where indigenous soil P
was most likely fixed in unavailable form due to the very
strong soil acidity.
However, at testing site 2, the yield was not significantly
affected by the application of lime. This might be explained
by the slight soil acidity level (pH 6.0), which as a result
had no significant adverse effect on the yield of barley, but,
was rather affected significantly by the main effect of the P
application due to the low soil fertility status and less
availability of soil P in the study district (World Bank, 1983
and FAO, 1986).
The highest grain and dry biomass yields of 2.05 and 6.4 t
ha-1, respectively, were obtained by the lime application
estimated with SMP buffer method followed with significant
difference by the grain and dry biomass yields of 1.65 and
5.45 t ha-1, respectively obtained by lime application
estimated with Ca(OH)2 titration method. Regarding to P
response, the highest yield was measured from application
of 69 kg P2O5 ha-1 followed by 34.5 kg P2O5 ha-1 with
significant difference., at testing site 2, the highest grain
and dry biomass yields of (3.38 and 8.43 t ha-1,
respectively)were measured from application of 69 kg
P2O5 ha-1 followed with insignificant difference by the
yields obtained from application of 34.5 kg P2O5 ha-1. As
shown in table 5, at site 2, where the soil pH was
conducive for barley growth, the yield collected was about
100% higher than the yield obtained at site 1, where the
soil was very strongly acidic (pH 4.97). This indicated the
gradual effect of liming on improving soil acidity and overall
soil properties beneficial for plant growth.
The combined analysis pooled over the two testing sites
revealed significant effect of lime and P fertilizer on the
yield of barley (Table 6). The lime application with SMP
and Ca(OH)2 titration methods and application of 69 and
34.5 kg P2O5 ha-1 resulted in the highest grain and dry
biomass yields with statistically insignificant difference
between each of the treatments. While, the lowest yields
were recorded from the plots where lime and P fertilizer
were not applied (Table 6).
Table 6. Effects of lime and P fertilizer on the yields of
barley at testing sites (pooled over two sites)
Lime rates*
(CaCO3 t ha-1
)
Grain yield
(kg ha-1
)
Dry biomass
(kg ha-1
)
Plant
height (cm)
Control (0) 2278.0b 5974.8b 101.9b
SMP buffer
(12.05) 2644.9a 7256.2a 112.4a
Ca(OH)2 titration
(6.75) 2485.2ab 6974.2a 110.5a
Grand mean 2480.6 6745.1 108.4
CV (%) 13.9 8.1 7.2
LSD (5%) 243.7 377.85 5.35
P rates*
(kg P2O5 ha-1
)
Control (0) 2058.0b 5975.4b 103.1b
Half (34.5) 2657.4a 7197.4a 112.5a
Full (69) 2726.5a 7044.8a 109.8a
Grand mean 2480.6 6745.1 108.4
CV (%) 13.9 8.1 7.2
LSD (5%) 242.8 377.85 5.35
P rates x site NS NS NS
Lime rates x site NS ** *
*Means with in a column followed by the same letter are
not significantly different at 5% probability level. NS: Non-
significant at 5% probability level.
In the second experimental year, yield of barley was
significant affected by both the main effects of lime and P
fertilizer rates. The significant yield response to the
addition of lime was attributed to the very strong soil acidity
(pH 4.7) of the testing site (site 3) and the sensitivity of
barley to soil acidity. The increase in the agronomic yields
of barley due to liming might be attributed to the
improvement in soil pH, reduction in the ion toxicity of H+,

6. Method for Estimation of Lime Requirement to Assess Lime and Phosphorus Application on the Yield of Barley (Hordeum vulgare L.)
Asfaw et al. 197
Al3+ or Mn2+, release and availability nutrients like Ca, P,
or Mo as well as due to indirect effect of better physical
condition of the soil (Haynes, 1984 and Kettering et al.,
2005).
Similarly, the significant yield response to the application
of P fertilizer was most likely due to the supply of additional
P to the crop as indigenous soil P was exposed to fixation.
The highest grain and dry biomass yields (3.2 and 9.8 t ha-
1, respectively) were obtained from the lime application
with SMP method followed by Ca(OH)2 titration method
(Table 7).
Table 7. Effects of lime and P fertilizer on the yields of
barley at testing site 3 in 2015
Lime rates*
(CaCO3 t ha-1
)
Grain
yield
(kg ha-1
)
Dry
biomass
(kg ha-1
)
Plant
height
(cm)
Control (0) 2429.9c 7860.1c 104.4b
Exch. acidity (0.97) 2803.3bc 8847.7b 105.3b
SMP buffer (4.00) 3193.7a 9835.4a 113.2a
Ca(OH)2 titration
(2.17) 2941.0ab 9218.1ab 113.1a
Grand mean 2841.9 8940.3 109.0
CV (%) 13.7 10.5 5.3
LSD (5%) 381.8 913.9 5.6
P rates*
(kg P2O5 ha-1
)
Control (0) 2378.0b 8101.9b 101.9b
Half of rec. (34.5) 2991.6a 9058.6a 111.5a
Full rec. (69) 3156.4a 9660.5a 113.7a
Grand mean 2841.9 8940.3 109.0
CV (%) 13.7 10.5 5.3
LSD (5%) 330.7 791.5 4.9
*Means with in a column followed by the same letter are
not significantly different at 5% probability level.
Likewise, the pooled analysis of testing sites and
experimental years revealed significant response of barley
yields to the main effects of lime and P fertilizer (Table 8).
The highest grain and dry biomass yields were obtained
from the lime estimated by SMP buffer method followed
with insignificant difference by Ca(OH)2 titration method.
Also, application of 69 kg of P2O5 ha-1 gave the highest
yields followed with insignificant difference by 34.5 kg
(P2O5) ha-1. The lime application estimated with SMP
buffer and Ca(OH)2 titration methods increased the barley
grain yield by an average of 19.96 and 16.22%,
respectively as compared to the control treatment.
Similarly, grain yield advantages of 27.3 and 24.9% over
the treatment where P was not applied were obtained from
application of 69 and 34.5 kg P2O5 ha-1, respectively.
Table 8. Effect of lime and P fertilizer rates on barley yields
(pooled over testing sites 1 and 2 and over years 2014 and
2015)
Lime rate*
(CaCO3 t ha-1
)
Grain
yield
(kg ha-1
)
Dry
biomass
(kg ha-1
)
Plant
height
(cm)
Control (0) 2679.5b 7757.2a 108.1b
SMP buffer (9.37) 3214.4a 8960.9a 114.1a
Ca(OH)2 titration
(5.22) 3114.2a 8770.6a 113.7a
Grand mean 3002.7 8496.2 111.9
CV (%) 17.6 14.8 5.9
LSD (5%) 357.9 852.4 4.4
P rates*
(kg P2O5 ha-1
)
Control (0) 2557.6b 7772.6b 107.1b
Half of rec. (34.5) 3194.6a 8755.1a 114.4a
Full rec. (69) 3255.9a 8960.9a 114.3a
Grand mean 3002.7 8496.2 111.9
CV (%) 17.6 14.8 5.9
LSD (5%) 357.9 852.4 4.4
*Means with in a column followed by the same letter are
not significantly different at 5% probability level.
Effect of Lime Application on Soil Acidity
As shown in the table below (Table 9 and 10), addition of
the lime estimated with SMP buffer and Ca(OH)2 titration
methods raised the soil pH level significantly to an
optimum level for barley growth in all testing sites and
experimental years. The average lime rate (5.22 CaCO3 t
per ha) estimated with Ca(OH)2 titration method was by
44.2% lower than the average lime rate (9.37 CaCO3 t ha-
1) estimated with SMP buffer method. So the average raise
in the surface soil pHs measured at harvesting from lime-
treated plots, where LRs were determined by SMP buffer
and Ca(OH)2 titration methods, were statistically similar.
The similar results are supported by Liu et. al., (2004) who
found that the 3-points prediction from the direct titration
with 30 minute interval time between additions of 0.022M
Ca(OH)2 estimated approximately 80% of the soil acidity
and lime requirement determined by the widely accepted
standard procedure for lime determination i.e., 3-day
incubation of the soils with Ca(OH)2. Mclean et al. (1978)
also reported that titration of acidic soils with Ca(OH)2 in
l:5 (w:v) soil: water suspensions (though the titration
method differs from the method used in this study) yielded
lime requirements that were similar to those obtained by
the standard incubation with CaCO3 to pH 6.5 over a 20
months period. This result is also in accordance with the
recommendation by Geremew et al. (2020) who concluded
that for areas covered with Nitisols modified Mehilich
buffer method and Ca(OH)2 direct titration methods can be
recommended to amend soil acidity.

7. Method for Estimation of Lime Requirement to Assess Lime and Phosphorus Application on the Yield of Barley (Hordeum vulgare L.)
World Res. J. Agric. Sci. 198
The acidity and exchangeable Al3+ exchangeable
measured from the soil samples collected at harvesting
was zero due to the significant rise in the soil pH >5.5 as a
result of liming. The increase in the soil pH measured at
harvesting from the control plot as compared to the pH
measured before planting might be due to the dynamic
property of soil pH, which was raised as a result of the dry
season period during harvesting (Olojugba and Fatubarin,
2015). On top of that, despite the lime was spread by
broadcasting with much care to the lime treatment plots
due to its fineness, there was a possibility of movement of
dusts of lime to the control plots by wind. This might also
lead to elevated soil pH of the control plot measured at
harvesting.
Table 9. Effects of addition of lime estimated with different
testing methods on soil pH at harvesting in 2014
Lime rate*
(CaCO3 t ha-1
)
Soil pH
Site 1
Lime rate
(CaCO3 t ha-1
)
Soil pH
Site 2 Combined
Control (0) 5.6b 0 6.2b 5.9c
SMP buffer
(15.1)
6.7a 9.0 6.8a 6.8a
Ca(OH)2
titration (9.3)
6.5a 4.2 6.5ab 6.5a
PASP (0.8) 5.4b 0 - 5.4b
Grand mean 6.1 Grand mean 6.5 6.3
CV (%) 6.4 CV (%) 6.7 6.4
LSD (5%) 0.38 LSD (5%) 0.43 0.30
*Means with in a column followed by the same letter are
not significantly different at 5% probability level.
Table 10. Effects of lime rates with different testing
methods on soil pH of testing site 3 at harvesting in 2015
Lime rate (CaCO3 t ha-1
) pH (H2O)
Control (0) 5.62b
Exch. acidity (0.97) 5.86ab
SMP buffer (4.00) 6.21a
Ca(OH)2 titration (2.17) 6.16
Grand mean 5.97
CV (%) 5.82
LSD (5%) 0.346
CONCLUSION AND RECOMMENDATION
The accuracy of different lime estimation methods varies
depending on the type of soil and its characteristics.
Therefore, the lime estimation methods should be
calibrated and validated based on the target soil
characteristics and agro-ecology. Taking this background
in to consideration, this study was conducted to evaluate
the accuracy of different lime testing methods (Permissible
acid saturation method, Exchangeable acidity method,
SMP buffer method and Ca(OH)2 titration method) on
estimating the right amount of lime requirement to raise the
soil pH level to the desired level.
Accordingly, the result revealed that different lime testing
methods generate different lime requirement to raise the
soil pH level to the desired level. Shoemaker-McLean-
Pratt buffer method and 3-point Ca(OH)2 titration methods
were found to equally and effectively raise the surface soil
pH level to the desired level with in a period of about six
months. However, the average lime rate (5.22 CaCO3 t ha-
1) estimated with Ca(OH)2 titration method was by 44.2%
lower than the average lime rate (9.37 CaCO3 t ha-1)
estimated with SMP buffer method. Thus, SMP buffer
method was found to overestimate the lime requirement.
On the other hand, Ca(OH)2 titration method was found to
be the most accurate lime estimation method among the
methods evaluated in this study.
Despite 3-point Ca(OH)2 titration method was found to
consume a little more time than SMP buffer method for
routine use in soil testing, it is recommended as the best
LR estimation method for acid soils of the study district and
other similar areas as it can save 44.2% of extra lime
expenses estimated by SMP buffer method. As the buffer
methods such as SMP buffer methods are rapid methods
for routine use in soil testing laboratories, a conversion
factor can be developed based on the above
recommended method to accelerate the soil testing
process while maintaining the accuracy.
Moreover, further study on 1-point and 2-point Ca(OH)2
titration evaluations on soil:0.01 M CaCl2 instead of soil:
water mixture is recommended to shorten the time elapsed
for the soil testing.
CONFLICT OF INTERESTS
The authors declare that there is no conflict of interests
regarding the publication of this paper.
ACKNOWLEDGMENTS
We would like to thank Sirinka Agricultural Research
Center (SARC) for funding the research and providing
vehicles and other logistic support. We want also to
express our sincere appreciation to Wadla District Office
of Agriculture for their cooperation during study site
selection and other support they offered during the course
of the research.
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Accepted 5 December 2019
Citation: Asfaw AG, Gedamu SA, Mekonen TT, Shibeshi
TH (2020). Method for Estimation of Lime Requirement to
Assess Lime and Phosphorus Application on the Yield of
Barley (Hordeum vulgare L.). World Research Journal of
Agricultural Sciences, 7(1): 192-200.
Copyright: © 2020 Asfaw et al. This is an open-access
article distributed under the terms of the Creative
Commons Attribution License, which permits unrestricted
use, distribution, and reproduction in any medium,
provided the original author and source are cited.