17-Optimal P fertilization using low-grade phosphate rock-derived fertilizer for rice cultivation

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Optimal P fertilization using low-grade phosphate
rock-derived fertilizer for rice cultivation under
different ground-water conditions in the Central
Plateau of Burkina Faso
Shinya Iwasaki, Monrawee Fukuda, Kenta Ikazaki, Satoshi Nakamura,
Korodjouma Ouattara & Fujio Nagumo
To cite this article: Shinya Iwasaki, Monrawee Fukuda, Kenta Ikazaki, Satoshi Nakamura,
Korodjouma Ouattara & Fujio Nagumo (2021) Optimal P fertilization using low-grade
phosphate rock-derived fertilizer for rice cultivation under different ground-water conditions
in the Central Plateau of Burkina Faso, Soil Science and Plant Nutrition, 67:4, 460-470, DOI:
10.1080/00380768.2021.1932584
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ORIGINAL ARTICLE
Optimal P fertilization using low-grade phosphate rock-derived fertilizer for rice 
cultivation under different ground-water conditions in the Central Plateau of Burkina 
Faso
Shinya Iwasaki a, Monrawee Fukudaa,b, Kenta Ikazakia, Satoshi Nakamuraa, Korodjouma Ouattarac and Fujio Nagumoa
aCrop, Livestock and Environment Division, Japan International Research Center for Agricultural Sciences (JIRCAS), Tsukuba, Ibaraki, Japan; bInstitute 
of Plant Protection, National Agriculture and Food Research Organization (NARO), Tsukuba, Ibaraki, Japan; cDépartement Gestion Des Ressources 
Naturelles/Systèmes De Production, Institut De l’Environnement Et De Recherche Agricole (INERA), Ouagadougou, Burkina Faso
ABSTRACT
Previous studies have reported two major methods of increasing PR solubility; calcination and partial 
acidulation. In addition, soil water condition would influence the solubility of P fertilizers. However, the 
effects of local P fertilizers, namely calcined PR (CPR) and partially acidulated PR (PAPR) on rice yield under 
different soil water conditions have not been explored comprehensively. The aims of the present study 
were to evaluate the effects of local P fertilizers produced from PR in Burkina Faso under different soil 
water conditions and to propose local fertilizers with optimal application rates for different soil water 
conditions. The field experiments were conducted at four farmers’ fields with different ground-water 
levels (GWL). CPR, PAPR, and superphosphate were applied at rates of 0, 7.6, 15.3, and 30.5 kg P ha−1, 
respectively. Superphosphate mostly consists of water-soluble P fraction (WP), PAPR of WP and alkaline 
ammonium citrate-soluble P fraction (SP), and CPR of SP and 2% citric acid-soluble P fraction (CP). The 
solubility is in the order of WP > SP > CP. The GWL was monitored during the growing season, and yield 
components were observed. Results of multiple regression analysis showed that WP influenced grain 
yield under all soil water conditions, whereas SP only influenced grain yied at mean GWL > −24.7 cm. 
Therefore, PAPR with high WP has an advantage over CPR in the field with GWL > −18.7 cm, and both CPR 
and PAPR are effective in fields with GWL > −6.5 cm. The optimal application rate was 14.4 kg P ha−1 as 
WP in the field with low GWL (mean −29.2 cm), 15.2–15.9 kg P ha−1 as WP + SP in the field with middle 
GWL (mean −24.7 to −18.7 cm), and 11.1 kg P ha−1 as WP + SP in the field with high GWL (mean −6.5 cm). 
According to the results, the optimal fertilizer types and application rates differ according to the soil 
water conditions.
ARTICLE HISTORY 
Received 2 February 2021 
Accepted 17 May 2021 
KEY WORDS 
Lixisols; Ground-water level; 
Rice; Local phosphate 
fertilizer; Optimal fertilization
1. Introduction
Rice is the most rapidly expanding food commodity, both in 
production and consumption, in sub-Saharan Africa (SSA) 
(USDA 2018). However, the average rice production in SSA is 
only around 2.1 Mg ha−1, which is far below the potential yield 
(USDA 2018). Low phosphorus (P) content in the highly weath-
ered soils of SSA is a major constraint for rice production 
(Nishigaki et al. 2019; Saito et al. 2001). According to 
(Bouwman, Beusen, and Billen 2009), global soil P balance will 
increase slowly, and soil P depletion may become a major 
problem in agricultural land. Consequently, many studies eval-
uated ways to increase rice production via P fertilizer applica-
tion (Sahrawat et al. 2001; Savini et al. 2016; Vandamme et al. 
2016). However, few farmers can access and utilize imported 
fertilizers, mainly because of the high cost incurred from long- 
distance transportation (Kelly 2006). Thus, local farmers may 
increase fertilizer input only if the fertilizers are available, 
affordable, and profitable for rice production (Tsujimoto et al. 
2019). Nevertheless, global phosphate rock production has 
steadily increased (approximately 6 MMT per year) from 139.3 
MMT in 2000 to 207.5 MMT in 2012 (Chowdhury et al. 2017).
Geological phosphate rock (PR) deposits occur through-
out SSA (FAO 2004). According to the Burkina Faso 
Government, there is 100 MMT of PR in the Kodjari region 
of Burkina Faso (Van Straaten 2002). which could be 
exploited as a source of P as an alternative to expensive, 
imported P fertilizers. However, most PR deposits in SSA have 
been rarely utilized because of their low P content and 
reactivity (FAO 2004). Nakamura et al. (2013) summarized 
the potential utilization of local PR for rice production and 
showed that direct application of local PR could improve rice 
yield in lowland fields. In contrast, other studies have stated 
that the direct application of local PR in SSA is ineffective 
(Fukuda et al. 2013; Sale and Mokwunye 1993). These con-
flicting results indicate that various factors influence the 
fertilization effect of PR, such as PR solubility, climate, and 
environmental conditions (Chien and Menon 1995a; Sale and 
Mokwunye 1993).
CONTACT Monrawee Fukuda monrawee@affrc.go.jp National Agriculture and Food Research Organization (NARO), Institute of Plant Protection, 3-1-3 
Kannondai, Tsukuba, Ibaraki, 305-8604, Japan
AbbreviationsP: phosphorus; SSA: sub-Saharan Africa; PR: phosphate rock; PAPR: partially acidulated phosphate rock; CPR: calcinated phosphate rock; EC: electric 
conductivity; CEC: cation exchange capacity; WP: water-soluble P fraction; SP: alkaline ammonium citrate-soluble P fraction; CP: 2% citric acid-soluble P fraction; RP: 
residual P fraction; RAE: relative agronomic efficiency; CBR: cost-benefit ratio; GWL: ground-water level; AIC: Akaike’s information criterion.
SOIL SCIENCE AND PLANT NUTRITION 
2021, VOL. 67, NO. 4, 460–470 
https://doi.org/10.1080/00380768.2021.1932584
© 2021 Japanese Society of Soil Science and Plant Nutrition
Fertilizers and soil amendments 
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Another approach to improve rice production using local PR 
is to enhance P solubility (Nakamura et al. 2019). Partial acidula-
tion of PR by sulfuric acid has been promoted promoted by the 
International Fertilizer Development Center as a solubilization 
method. Acidulation of PRs with sulfuric acid produces the 
phosphate component monocalcium phosphate, small amounts 
of dicalcium phosphate, and residual apatite in the amount 
dependent on the degrees of acidulation (Mizane and 
Rehamnia 2012). The positive effects of partially acidulated PR 
(PAPR) on rice production have been reported (Chien and 
Menon 1995b; Rahman 2018). The degree of solubility in PAPR 
increases with the addition of more sulfuric acid; however, the 
viscosity and acidity of the product also increase because of 
unbound sulfuric acid (Akiyama, Tsumita, and Wada 1992; 
Frederick and Roth). Therefore, to secure adequate solubility, it 
is necessary to minimize the amount of sulfuric acid added. In 
contrast, Akiyama, Tsumita, and Wada (1992) proposed the 
calcination procedure for PR in a temperature range of >900°C 
with alkaline carbonates to convert fluoride apatite into α- 
tricalcium phosphate and rhenania phosphate. Nakamura et al. 
(2019) applied a modified version of this method to the low- 
grade PR from the Kodjari region and achieved more than 90% 
solubility in 2% citric acid. These authors Nakamura et al. (2019) 
also demonstrated that calcinated PR (CPR) significantly 
increased rice production in pot experiments. However, the 
effects of PAPR and CPR on rice cultivation under different soil 
conditions remain poorly understood, especially in West Africa.
Along with increasing the grain yield on existing lands 
favorable for rice production, it would be necessary to expand 
rice cultivation into surrounding marginal lands to attain rice 
self-sufficiency in many West African countries (Van Oort et al. 
2015). The major problem in these lands is poor soil water 
conditions. Hömberg and Matzner (2018) and King et al. 
(2015) have stated that soil water conditions are closely related 
to the solubilization, transportation, and hence availability of 
P in soil. Despite the negative effect permanent flooding has on 
lowland rice cultivation (De Bauw et al. 2019), P fertilization is 
generally considered to be more effective under flooded con-
ditions than under upland conditions on similar soils 
(Dobermann et al. 1998); consequently, optimal local fertilizer 
application should differ according to soil water conditions.
Thus, this study aims to evaluate the fertilization effects of 
PAPR and CPR under different soil water conditions. We 
hypothesize that P fertilization would be more effective under 
optimal water conditions for rice cultivation. The results could 
facilitate the selection of optimal fertilization methods under 
different soil water conditions. If PAPR and CPR improve rice 
yield in fields with low ground-water level, they could facilitate 
the expansion of rice cultivation areas into more marginal lands 
of the Central Plateau of Burkina Faso.
2. Materials and methods
2.1. Study site
The field experiment was conducted in 2019 in Nassoulou 
Village (12°21′12.0ʺ N 2°07′37.4ʺ W), Central Plateau of 
Burkina Faso, West Africa. The village is located in the 
Sudanian Savanna and characterized by mid-latitude steppe 
and desert climate (BSh) according to the Köppen climate 
classification. In this region, rice cultivation is generally con-
ducted in lowland riverine areas (bas fond in French). Using 
a digital surface model constructed based on ALOS World 3D- 
30 m images (JAXA 2018), a line transect was placed along 
a gentle slope, starting from the river bottom, with an average 
gradient of 0.8% (190 m in length). On the line transect, four 
farmer fields were selected, which were named Middle slope, 
Lower slope (1), Lower slope (2), and Lowland. The Middle 
slope was located 165–190 m from the river bottom, and the 
two fields on the lower slope were located 60–135 m from the 
river bottom. The Lowland was located on the river bottom. 
The Lowland has been used as a paddy field for a long time. 
The two sites on the lower slope were occasionally used for 
rice cultivation. The field on the Middle slope was mainly used 
for upland crop cultivation.
A soil profile survey was conducted in October 2018 in the 
Lowland (Table 1). The soil was classified as Ferric Lixisol (IUSS 
Working Group WRB 2015), which is distributed on the lower 
slopes extending into the river bottom, and has higher produc-
tivity mainly because of the deeper effective soil depth (Ikazaki 
et al. 2018a). The topsoil was characterized by high sand con-
tent and low carbon content, resulting in a weak soil structure. 
Clay content gradually increased with soil depth. The texture 
class changed from sandy loam at the surface to heavy clay at 
the bottom. Available P content was determined by both Bray- 
1 and Bray-2 methods in the profile and ranged from 0.26 to 
1.79 and 1.00 to 3.25 mg P kg−1, respectively. Similar to other 
areas of the Sudan Savanna, the availability of P was quite low 
(Ikazaki et al. 2018b).
2.2. Preparation of calcinated and partially acidulated 
phosphate rock
Two types of fertilizers were produced by partial acidulation 
and calcination method using PR from the Kodjari deposit (12° 
1′ N; 1°55′ E) in Burkina Faso. The PR contained 113 g P kg−1, 
and its 2% citric acid solubility was 31.1% of the total P. Total 
P content and solubility were similar to those documented 
previously (Nakamura et al. 2019; Zapata 2004). To prepare 
PAPR, we followed the acidulation method described by 
Frederick and Roth (). The addition rate of sulfuric acid was 
determined based on the mineral composition of PR; 326.8 mL 
H2SO4 was used to 1 kg BPR to produce 100% acidulated 
phospate rock (PAPR100). Therefore, 245.1 mL H2SO4 was 
added to prepare PAPR75. In the present study, we employed 
PAPR75 as PAPR for the experiments. The calcination procedure 
described by Nakamura et al. (2019) was used to prepare CPR. 
Fine powdered PR was mixed well with K2CO3 at a rate of 166 g 
K per kg PR. The components were mixed with distilled water, 
and then pressed to form coin-shaped pellets. The pellets were 
calcinated at 900°C for 10 min using a muffle furnace (FP32; 
Yamato Scientific Co., Ltd., Japan). Commercially available sin-
gle superphosphate (SSP) was used.
The chemical properties of CPR, PAPR, and SSP were ana-
lyzed following the procedure outlined by the Food and 
Agricultural Materials Inspection Center (FAMIC 2013). The 
water-soluble P fraction (WP) corresponded to water solubility. 
The alkaline ammonium citrate soluble P fraction (SP) was 
SOIL SCIENCE AND PLANT NUTRITION 461
defined as alkaline ammonium citrate solubility subtracted by 
water solubility. The 2% citric acid-soluble P fraction (CP) was 
defined as 2% citric acid solubility subtracted by alkaline 
ammonium citrate solubility. The residual P fraction (RP) was 
the P fraction not soluble in 2% citric acid.
2.3. Experimental design
A total of 10 treatments were established, namely P unfertilized 
control (CT) and P fertilized at 7.6, 15.3, and 30.5 kg P ha−1 using 
CPR, PAPR, and SSP, respectively. The application rate was set 
based on the recommendation of INERA (P1: 15.3 kg P ha−1), 
and 7.6 (P0.5) and 30.5 (P2) kg P ha−1 corresponded to a half 
and twice the recommended rate, respectively. Four replicates 
were set up based on a complete randomized block design. The 
experimental subplots measured 16 m2 (4 m × 4 m) in size with 
1-m spacing between neighboring plots. A bund of about 
30 cm height was established around each subplot to avoid 
any contamination by fertilization. For all treatments, 74 kg 
N ha−1 and 16.6 kg K ha−1 (correspond to 40 kg K2O ha−1) 
wereapplied as urea and potassium chloride (KCl), respectively. 
Urea, P fertilizers, and KCl were mixed well and applied about 
one week before seeding by broadcasting. Rice (Oryza sativa) 
was directly seeded on 8 July 2019 with 20 cm × 20 cm planting 
space. We used ‘FKR19,’ an improved variety registered by 
INERA, to adapt to the lowland rice cultivation in West Africa. 
The plants were harvested around the first week of 
October 2019. Total biomass, grain yield, and harvest index 
were measured.
2.4. Ground-water level measurement
Pipes (150 cm) were used for ground-water level (GWL) mea-
surements and holes drilled at 120 cm from the top of the pipe. 
The pipes were then installed to a depth of 120 cm from the 
land surface. The section of the pipe above the ground was 
covered with a cap to protect it from incoming rain. The GWL 
was manually measured inside the pipe using a measuring stick 
on Monday, Wednesday, and Friday mornings each week.
2.5. Soil sampling and analysis
Soil was collected at a depth of 0–20 cm in each subplot before 
rice cultivation to determine initial soil chemical properties. 
Composite samples were air-dried and passed through 
a 2 mm mesh sieve to remove stones, roots, and other plant 
residues. A mixture of soil and distilled water at a ratio of 1:2.5 
was used to measure soil pH (H2O) with a LAQUA pH/ION F-72 
(Horiba, Japan) and electrical conductivity (EC) with a COND 
meter ES-51 (Horiba, Japan). Available P was extracted by Bray- 
1 and Bray-2 extracting solutions (Bray and Kurtz 1945). The 
concentration of P in the filtrate was determined by 
a colorimetric method (Murphy and Riley 1962) using a UV- 
1800 spectrophotometer (Shimadzu, Japan).
2.6. Data processing
2.6.1. Evaluation of the P fertilization effect
The effect of P fertilization was evaluated based on yield rela-
tive to CT and relative agronomic efficiency (RAE) of local 
P fertilizers for SSP (hereafter RAE). RAE was calculated as: 
RAE %ð Þ ¼ Ylocal P fertilizers � YCTð Þ= YSSP � YCTð Þ � 100; (1) 
where Ylocal P fertilizers, YCT, and YSSP indicate rice grain yields (Mg 
ha−1) in the corresponding treatments at P2 application level.
2.6.2. Optimal fertilization rate and required price of local 
P fertilizers
The optimal fertilization rate was considered as the minimum 
P application rate that produced grain yields comparable to 
saturated grain yield. Specifically, the comparable yield was 
defined as YSSP at the P2 level subtracted by one standard devia-
tion (SD) of YSSP at the P2 level. For example, YSSP and SD at the 
P2 level in Lowland were 3.99 and 0.37, respectively, and thus the 
comparable yield was calculated as 3.99 − 0.37. The optimal 
fertilization rate was calculated for each site from the relationship 
between the application rate of the P fraction and grain yield.
To evaluate the availability of local P fertilizers to local farm-
ers, the required price of local P fertilizers to achieve a cost 
Table 1. Physico-chemical properties of lowland soils.
Horizon
Depth
Soil texture
Total carbon Total nitrogen
Available P pH
Sand Silt Clay Bray-1 Bray-2 H2O KCl
(cm) (%) (g C kg−1) (g N kg−1) (mg P kg−1)
Apg 0–6 77.0 11.1 11.9 4.40 0.39 1.79 3.25 5.1 4.1
ABg 6–24 50.8 14.3 34.9 4.93 0.48 0.63 2.00 6.0 4.6
Bg1 24–35 43.2 12.9 43.9 4.06 0.49 0.26 1.00 6.2 4.7
Bg2 35–50 39.2 11.5 49.3 2.84 0.36 0.31 1.75 6.4 5.0
BCg 50–70 39.5 10.5 50.0 2.39 0.31 0.44 1.75 6.5 5.2
Cg 70–80+ - - 2.85 0.35 0.59 4.75 - -
Horizon Depth EC Exchangeable cations CEC Base saturation
Na+ K+ Ca2+ Mg2+ Al3+
(cm) (S m−1) (cmolc kg−1) (%)
Apg 0–6 5.7 0.04 0.12 1.42 0.57 0.42 3.8 56.2
ABg 6–24 2.2 0.09 0.17 5.29 2.05 0.08 10.1 75.0
Bg1 24–35 1.9 0.09 0.18 5.67 2.11 0.07 11.2 72.0
Bg2 35–50 2.2 0.12 0.28 6.43 2.70 0.07 17.6 54.2
BCg 50–70 2.4 0.12 0.34 6.90 3.05 0.07 16.3 64.0
Cg 70–80+ - 0.16 0.50 7.99 3.71 - 18.0 68.5
Soil horizons were classified according to WRB (IUSS Working Group WRB 2015). EC: electrical conductivity; CEC: cation exchange capacity.
462 S. IWASAKI ET AL.
benefit ratio (CBR) of 1 and 2 under optimal fertilization rate 
conditions was estimated. CBR was calculated as: 
CBR ¼ ΔY � Priceð Þ � Curea þ CKClð Þ½ �= Pfertilizer � ARopt
� �
; (2) 
where ΔY is the expected increase in grain yield under optimal 
fertilization compared with the expected increase without fertili-
zation (Mg ha–1), Price is the farm gate price of rice (€258.2 Mg–1 
according to Dr. Koide [personal communication]), Curea and CKCl 
are the costs of urea and KCl, respectively (€ ha–1), Pfertilizer is the 
required price of P fertilizers (€ 100 kg–1) to achieve a certain 
value of CBR, ARopt is the optimal fertilization rate of three types 
of fertilizers (kg ha–1). Curea and CKCl were calculated by multi-
plying the market price of urea and KCl (€45.7 and €160.1 100 kg– 
1, respectively) by the application rate (74 kg N ha–1 and 16.6 kg 
K ha–1, respectively). Net benefit (€ ha–1) was estimated as: 
Net benefitðha� 1Þ ¼ ΔY � Priceð Þ � Curea þ CKCl þ CP� fertilizer½ �
(3) 
where ΔY is the expected increase in grain yield under optimal 
fertilization compared with the expected increase without fer-
tilization (Mg ha–1), Price is the farm gate price of rice, Curea, CKCl, 
and CP-fertilizer are the costs of urea, KCl and P fertilizer applica-
tion, respectively (€ ha–1). CP-fertilizer was calculated using the 
optimal fertilization rate of three types of P fertilizers and the 
required price of P fertilizers to achieve a CBR = 2.
2.7. Statistical analysis
Statistical analysis was performed using R version 4.0.0 (R 
Core Team 2020). The difference in the soil chemical proper-
ties between the sites were analyzed by Tukey HSD method. 
The effects of the site, fertilizer type, P application rate, and 
their interactions were analyzed by the three-way analysis of 
variance (ANOVA), followed by multiple comparisons using 
Shaffer’s modified sequentially rejective Bonferroni proce-
dure. The effect size of the source was evaluated by eta 
squared (η2). The difference in the RAE between the PAPR 
and CPR was analyzed by paired t-test. Factors controlling 
grain yield and yield relative to CT were analyzed at each 
site using a stepwise multiple regression analysis. The appli-
cation rate of the P fractions (WP, SP, CP, and RP) and water- 
soluble sulfur were used as explanatory variables. Mean 
GWL, soil pH (H2O), EC, soil available P content, and the 
application rate of P fractions were used as variables to 
analyze yield relative to CT. Standardized partial regression 
coefficients were estimated. The selection of explanatory 
variables was based on the Akaike’s information criterion 
(AIC). A simple regression analysis was conducted using the 
explanatory variables that significantly contributed to grain 
yield to simplify the contribution. The alpha level was set 
to 0.05.
3. Results
3.1. Chemical properties of fertilizers
Chemical properties of P fertilizers are provided in Table 2. The 
partial acidulation and calcination methods increased the solu-
bility compared with raw PR. The residual P fraction (RP), which 
is not soluble in the 2% citric acid, decreased from 68.9% in PR 
to 25.8% and 32.7% in CPR and PAPR, respectively. SSP included 
a high water-soluble P fraction (WP) and contained a small 
quantity of alkaline ammonium citrate-soluble P fraction (SP). 
PAPR mainly consisted of WP and SP, whereas CPR contained 
almost equal amounts of SP and 2% citric acid-soluble 
P fraction (CP). The pH (H2O) at the solid:liquid extraction of 
1:10 for CPR, PAPR, and SSP was 12.3, 2.8, and 3.0, respectively.
3.2. Seasonal variation in ground-water level
During the growing season, GWL ranged from +9 cm (in the 
Lowland on September 16) to −120 cm (in the Middle slope on 
July 5) (Figure 1). The mean GWL in the Middle slope, Lower 
slope (1), Lower slope (2), and Lowland were −29.2 ± 32.8, 
−24.7 ± 18.5, −18.7 ± 23.2, −6.5 ± 21.1 cm (mean ± SD), respec-
tively. GWL in the Lowland was significantlyhigher than that on 
the Middle slope and Lower slope (1) (p < 0.01, respectively).
3.3. Soil chemical properties
The results of the soil chemical analysis are shown in Table 3. 
A significant difference (p < 0.01) between sites was observed 
for soil pH (H2O) and available P, but not for EC. Soil pH (H2O) 
was highest in the Middle slope (7.10), followed by Lower slope 
(2), Lower slope (1) (7.07 and 6.21, respectively), and Lowland 
(5.95). Available P ranged from 0.49 mg P kg−1 in the Lower 
slope (2) to 1.21 mg P kg−1 in the Middle slope.
3.4. Grain yield, biomass, and harvest index
Both biomass and harvest index highly correlated with the 
grain yield (Table A1). Table 4 shows the results of the three- 
way ANOVA for the grain yield, biomass, and harvest index. 
The main effects of site, fertilizer type, and P application rate 
on grain yield were strongly significant (p < 0.001). Grain 
yield corresponded well to the site position on the slope. 
Grain yield was lowest in the Middle slope (2.12 Mg ha−1) 
and highest in the Lowland (2.81 Mg ha−1). Among the 
fertilizer types, grain yield was significantly higher for SSP 
(2.78 Mg ha−1), followed by PAPR (2.43 Mg ha−1) and CPR 
(2.15 Mg ha−1). Higher P application rates significantly 
improved grain yield until the P2 level. However, 
Table 2. Chemical properties of phosphate rock and fertilizers used in this study.
Solubility BPR CPR PAPR SSP
(a): Water solubility % of TP 0.2 2.4 28.9 91.6
(b): Alkaline ammonium citrate solubility % of TP 2.5 36.8 56.9 96.8
(c): 2% citric acid solubility % of TP 31.1 74.2 67.3 96.8
P-fractions BPR CPR PAPR SSP
WP [= (a)] % of TP 0.2 2.4 28.9 91.6
SP [= (b) – (a)] % of TP 2.3 34.4 28.0 5.3
CP [= (c) – (b)] % of TP 28.6 37.4 10.4 0.0
RP [=100 – (c)] % of TP 68.9 25.8 32.7 3.2
TP (g P kg−1) 11.6 6.8 9.2 8.3
pH (H2O) 7.4 12.3 2.8 3.0
BPR: Burkina Faso phosphate rock from the Kodjari deposit, CPR: calcinated 
phosphate rock, PAPR: partially acidulated phosphate rock; SSP: single super 
phosphate; WP: water-soluble P fraction; SP: alkaline ammonium citrate-soluble 
P fraction; CP: 2% citric acid-soluble P fraction; RP: residual P fraction; TP: total 
P. The pH (H2O) was measured in the 1:10 solid: liquid extraction.
SOIL SCIENCE AND PLANT NUTRITION 463
a significant interaction between the site and P application 
rate was observed, which indicated diverse P fertilization 
effects depending on site-specific conditions. Therefore, 
grain yield was examined under different P application rates 
at each site [Figure 2 (a)]. For PAPR and SSP, grain yield 
increased with increasing application rate. Maximum grain 
yield was recorded at the P2 level in all sites. In contrast, 
the trend for CPR differed depending on site. The maximum 
grain yield was obtained at P2 in the Middle slope and 
Lowland; however, grain yield peaked at P1 in the Lower 
slopes (not statistically significant).
RAE was low in the Middle slope for CPR and PAPR (62.8% and 
62.8%, respectively), and markedly high in the Lowland for CPR 
and PAPR (97.3% and 99.8%, respectively). In the Lower slopes, 
PAPR had higher RAE (86.2% and 93.8% in Lower slope (1) and 
Lower slope (2), respectively), whereas CPR did not (24.3% and 
43.1% in the Lower slope (1) and Lower slope (2), respectively).
Both biomass and harvest index were highly correlated with 
grain yield (Table A1; p < 0.01). Site did not affect biomass but 
significantly changed the harvest index (Table 4; p < 0.001). In 
contrast, fertilizer type significantly affected biomass (p < 0.001) 
but not the harvest index. The P application rate significantly 
affected both the biomass and harvest index (p < 0.001, 
respectively).
3.5. Factors controlling grain yield and fertilization effect
Table 5 presents the results of multiple regression analysis. 
Regression equations were significant at all sites (p < 0.05 in 
the Middle slope and p < 0.01 for all other sites). The adjusted 
coefficient of determination (R2) was lowest in the Middle slope 
(R2 = 0.45) and highest in the Lower slope (2) (R2 = 0.81). WP 
persistently and strongly contributed to grain yield (p < 0.01). 
However, the contribution of SP was site-dependent. SP was 
rejected in the Middle slope, but weakly contributed to the 
Lower slope (1) (p < 0.1), and significantly contributed to the 
Lower slope (2) and Lowland (p < 0.05 and p < 0.01, respec-
tively). Mean GWL and pH (H2O) negatively contributed, 
whereas, available P (AP), WP, and SP positively contributed 
to yield relative to CT. A regression equation with high R2 (0.85, 
p < 0.01) was obtained; in this equation, the variance inflation 
factor of variables was >1.63, suggesting no multicollinearity 
problem in the multiple regression analysis.
Figure 1. Precipitation (a) and seasonal variation in ground-water level (b). Panel (a) shows the monthly precipitation and mean temperature
Table 3. Soil chemical properties before the experiment.
pH (H2O) EC Available P (Bray-1)
n (S m−1) (mg P kg−1)
Middle slope 45 7.10 ± 0.85 c 4.64 ± 4.20 ns 1.21 ± 0.58 c
Lower slope (1) 48 6.21 ± 0.47 b 4.52 ± 9.81 0.71 ± 0.27 b
Lower slope (2) 48 7.07 ± 0.30 c 4.07 ± 0.88 0.49 ± 0.23 a
Lowland 48 5.95 ± 0.23 a 3.97 ± 1.48 1.12 ± 0.22 c
Mean values with different letters are significantly different (p < 0.05). ns: not 
significant. Values indicate mean ± standard deviation.
464 S. IWASAKI ET AL.
3.6. Determination of optimal fertilization rate and 
expected increase in grain yield
Simple regression analysis showed an evident relationship 
between the application rate of P fractions and grain yield 
(Figure 3). The optimal application rate of the P fractions was 
14.4 kg P ha−1 of WP in the Middle slope, and 15.9, 15.2, and 
11.0 kg P ha−1 of WP + SP in the Lower slope (1), Lower slope 
(2), and Lowland, respectively. The optimal fertilization rate for 
each fertilizer, expected increase in grain yield, the required 
price of local P fertilizers, and net benefit at CBR = 2 are 
summarized in Table 6. Under optimal fertilization, grain yield 
was expected to increase by 1.08–2.00 Mg ha−1. The required 
price to achieve CBR = 1 or 2 were lowest in the Middle slope 
and highest in the Lowland. Net benefit was estimated to range 
from 59.3 in the Middle slope to 177.8 in the Lowland.
4. Discussion
4.1. Effects of PAPR and CPR on grain yield under 
different GWL
Grain yield was significantly affected by the site, fertilizer type, 
and application rate (Table 4). Based on η2, P application rate 
explained 46% of the variance in grain yield. Grain yield 
increased by 168%, 204%, and 251% under P0.5, P1, and P2, 
respectively. Thus, the limited plant growth due to low P in soils 
in this region (Gebrekidan and Seyoum 2006) can be success-
fully mitigated with P fertilizer application to significantly 
improve rice grain yield.
However, the effects of P fertilization differed across sites 
(Figure 2). RAE variation closely reflected the contribution of 
the P fractions [Figure 2 (b) and Table 5]. In the Middle slope 
with low GWL (Figure 1), only WP contributed to grain yield; 
consequently, PAPR and CPR had a disadvantage over SSP with 
high WP. In comparison, in the Lowland with high GWL (Figure 
1), WP and SP had an almost equal contribution (Table 5), with 
both PAPR and CPR performing well (Figure 2). At the other two 
sites with middle GWL, both WP and SP contributed to grain 
yield, as observed in the Lowland (Table 5). However, more WP 
+ SP was required to reach comparable yields (15.2–15.9 kg 
P ha−1) than that required for the Lowland (11.0 kg P ha−1) 
(Figure 3). Therefore, PAPR with higher total P content (9.2 g 
P kg−1) and WP + SP (56.9% of total P) showed an advantage 
over CPR (6.8 g P kg−1 and 36.8% of the total P, respectively). 
Thus, PAPR is useful in fields with a mean GWL > −24.7 cm, and 
both CPR and PAPR are effective in fields with mean GWL of – 
6.5 cm.
Site and fertilizer type also significantly affected grain yield 
(Table 4). Site mainly reflected differencesin GWL in the 
current study (Figure 1), while fertilizer type reflected differ-
ences in P solubility (Table 2). The post-hoc test showed that 
GWL contributed to grain yield by increasing the harvest 
index. Emam et al. (2014) also reported that the harvest 
index significantly decreased in fields subjected to water 
stress compared with the well-watered conditions in Egypt. 
In contrast, fertilizer type (i.e., only SSP) contributed to grain 
yield by increasing biomass. Song et al. (2019) reported that 
application of SSP with high WP significantly enhanced root 
biomass and structure, thereby allowing plants to access and Ta
bl
e 
4.
 E
ffe
ct
s 
of
 t
he
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re
at
m
en
ts
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n 
gr
ai
n 
yi
el
d,
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io
m
as
s,
 a
nd
 h
ar
ve
st
 in
de
x.
Si
te
Ty
pe
 o
f f
er
til
iz
er
P 
ap
pl
ic
at
io
n 
le
ve
l
G
ra
in
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ie
ld
Bi
om
as
s
H
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ve
st
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de
x
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ra
in
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ld
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as
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ve
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de
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de
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(M
g 
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lo
pe
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 w
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re
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ig
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tly
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iff
er
en
t (
p 
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.0
5)
. d
f: 
de
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ee
 o
f f
re
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om
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: s
ite
; F
: t
yp
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 P
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 p
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PR
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al
ci
ne
d 
ph
os
ph
at
e 
ro
ck
; P
AP
R:
 
pa
rt
ia
lly
 a
ci
du
la
te
d 
ph
os
ph
at
e 
ro
ck
; S
SP
: s
in
gl
e 
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pe
r 
ph
os
ph
at
e;
 P
0:
 n
on
-f
er
til
iz
ed
 (c
on
tr
ol
); 
P0
.5
: 7
.6
 k
g 
P 
ha
−
1 ; P
1:
 1
5.
3 
kg
 P
 h
a−
1 ; P
2:
 3
0.
5 
kg
 P
 h
a−
1 .
SOIL SCIENCE AND PLANT NUTRITION 465
solubilize P sources in the soil and increase above-ground 
biomass. Our results demonstrate that WP is essential for 
enhancement of biomass compared with SP and CP. CPR 
showed a low performance at the P2 application level in the 
two sites on a lower slope. We were not able to explain this 
phenomenon, which requires further research.
4.2. Effect of GWL and soil pH on fertilization effect
Multiple regression equations for yield relative to CT revealed 
that soil water condition as well as soil chemical properties 
affected the fertilization effect (Table 5; Figure A1). In particular, 
the mean GWL and soil pH (H2O) had a large contribution. 
Multicollinearity was not found in the multiple regression ana-
lysis. Therefore, it could be inferred that the GWL and the soil 
pH independently affected the yield relative to CT. Moreover, 
the high R2 (0.85) indicated that the variables selected in this 
equation well explained the variability at the four study sites 
and the small effect of the other soil environmental factors.
Soil water condition is generally related to the accessibility 
and solubility of P fertilizer in the soil. Consistent with previous 
studies (Fukuda et al. 2013; Balasubramanian et al. 2007), the 
effect of P fertilization was more substantial at the site with 
high GWL, because it increased solubilization, transportation, 
and subsequent availability of P in the soil (Hömberg and 
Matzner 2018; King et al. 2015).
The mechanisms of the effects of pH on P availability are 
diverse (Haynes 1982). Robinson and Syers (1990) evaluated 
how pH affected the solubilizing rate of PR using the incubation 
method, and showed that P solubility in water increased under 
low-pH conditions because dissolution of the apatite relies on 
the net supply of protons. However, lowering soil pH also 
increases the P fixation and Al toxicity (Margenot et al. 2016). 
Haynes (1982) has shown that the availability of P in soil gen-
erally increases as pH rises from 4.0 to 7.0 because of the 
Figure 2. Comparison of grain yield (a) and relative agronomic efficiency (RAE) (b) of local P fertilizers between treatments. Error bars in (a) and (b) indicate the standard 
deviation and standard error, respectively (n = 4). CPR: calcinated phosphate rock; PAPR: partially acidulated phosphate rock; SSP: single superphosphate;*: p> 0.05.
Table 5. Factors controlling grain yield and yield relative to the control.
Site Equation p-value R2 SE AIC
Middle slope Grain yield = 0.882 WP** + 0.338 CP + 1.665** < 0.05 0.452 0.46 −12.23
Lower slope (1) 0.765 WP** + 0.742 SP* – 0.594 CP + 2.031** < 0.01 0.735 0.441 −13.48
Lower slope (2) 0.814 WP** + 0.820 SP* – 0.427 CP + 1.763** < 0.01 0.806 0.275 −22.94
Lowland 0.731 WP** + 0.698 SP** + 2.053** < 0.01 0.705 0.471 −12.64
All sites Relative yield for CT = (b): −0.506 GWL** −0.352 pH** + 0.170 AP** + 0.538 WP** + 0.156 SP** + 543.9** < 0.01 0.852 29.03 247.96
Equations were obtained by stepwise multiple regression analysis. WP: water-soluble P fraction; SP: alkaline ammonium citrate-soluble P fraction; CP: 2% citric acid- 
soluble P fraction; GWL: mean groundwater level; AP: soil available P; SE: standard error; AIC: Akaike’s information criterion; +: p < 0.1; *: p < 0.05; **: p < 0.01; ***: 
p < 0.001.
466 S. IWASAKI ET AL.
stimulation of mineralization of soil organic phosphorus. Carbon 
content and exchangeable Al were low in the current study 
(Table 1), while the minimum pH was relatively high (Table 3). 
Therefore, Al toxicity was not a problem, and the direct effect of 
low soil pH on P solubility would be greater than the other 
effects.
4.3. Optimal fertilization and expansion of rice 
cultivation area
The availability and profitability of fertilizers influence local farm-
ers’ decisions to increase fertilizer inputs (Tsujimoto et al. 2019; 
Yanggen et al. 1998). Although local P fertilizers were inferior to 
SSP in terms of solubility and optimal application rate (Table 6), 
their availability and profitability would be superior to that of 
imported commercial fertilizers. The use of local PR deposits 
could reduce transportation costs and might significantly reduce 
the price of P fertilizers in SSA (Kelly 2006). The reduced price of 
local P fertilizers would increase cost benefits and profitability. 
Buah and Mwinkaara (2009) emphasized the importance of 
economic analyses to calculate the net benefit to farmers.
Guèdègbé and Doukkali (2018) showed that the local price 
of P fertilizer in the African market considerablyexceeded that 
in the international market because of high transportation 
costs, which represented 43% of the local P fertilizer price. 
The authors estimated that, by increasing domestic fertilizer 
Figure 3. Relationship between the application rate of P fractions and grain yield. The Sum of effective P fractions that were significantly selected in Table 5 was 
employed as X-axis. The horizontal and vertical lines indicate the grain yield of SSP treatment with an application rate of 30.5 kg P ha−1 subtracted by its standard 
deviation and optimal fertilization rate. Error bars are standard deviation (n = 4). The gray areas represent the 95% confidence interval. CPR: calcinated phosphate rock; 
PAPR: partially acidulated phosphate rock; SSP: single superphosphate; WP: water-soluble P fraction; SP; alkaline ammonium citratesoluble P fraction.
Table 6. Optimal P fertilization rate and expected increase in grain yield.
Site
Optimal rate
Optimal fertiliza-
tion rate Expected grain yield
Expected increase
Required price to 
achieve CBR = 1
Required price to 
achieve CBR = 2
Net benefitCPR PAPR SSP Without P Optimal P CPR PAPR SSP CPR PAPR SSP
(kg P ha−1) (kg P ha−1) (Mg ha−1) (Mg ha−1) (€ 100 kg fertilizer−1) (€ 100 kg fertilizer−1) (€ ha−1)
Middle slope 14.4 as WP 600 50.0 15.7 1.78 2.86 1.08 1.30 21.6 61.7 0.70 10.8 30.9 59.3
Lower slope (1) 15.9 as WP ＋ SP 43.2 27.9 16.4 1.55 3.51 1.96 54.3 114.4 176.2 27.2 57.2 88.1 172.9
Lower slope (2) 15.2 as WP ＋ SP 41.3 26.7 15.7 1.57 2.98 1.41 33.3 70.0 108.1 16.6 35.0 54.1 101.9
Lowland 11.0 as WP ＋ SP 29.9 19.3 11.4 1.62 3.62 2.00 80.7 170.2 262.3 40.4 85.1 131.2 177.8
Optimal fertilization rate is defined as the minimum P application rate that produced grain yields comparable to those under saturated ones. Values are estimated in 
Figure 3. CPR: calcinated phosphate rock; PAPR: partially acidulated phosphate rock; SSP: single super phosphate; WP: water-soluble P fraction; SP: alkaline 
ammonium citrate-soluble P fraction; CBR: cost benefit ratio. €1 = 655.957 FCFA (fixed rate).
SOIL SCIENCE AND PLANT NUTRITION 467
production and by reducing transportation costs, it would be 
possible to reduce the price of P fertilizers from €74.6 to €42.5. 
The required price of CPR and PAPR to achieve CBR = 1 was 
comparable or higher than €42.5 in fields with mean GWL > 
−24.7 cm (Lower slope (1), Lower slope (2), and Lowland). 
Therefore, the net income of farmers could be enhanced by 
using local P fertilizers. Moreover, the required price of PAPR to 
achieve CBR = 2 could be realized.
In this region of the Central Plateau of Burkina Faso, most 
areas of rice cultivation are distributed in lowland riverine sites. 
Our result indicated that PAPR could help expand rice cultiva-
tion to the lower slopes with GWL > −24.7 cm (~135 m from the 
river bottom in the line transect), while SSP could even facilitate 
rice cultivation on middle slopes with GWL > – 29.2 (~190 m 
from the river bottom in the line transect).
5. Conclusions
This study demonstrated the effectiveness of two types of local 
P fertilizers made from low-grade PR products in Burkina Faso. 
Only WP contributed to grain yield in fields with low GWL, but 
showed an equivalent contribution in fields with high GWL, WP, 
and SP. Therefore, PAPR with high water-solubility has an advan-
tage over CPR in fields with low GWL. Both PAPR and CPR 
performed well at sites with high GWL. The optimal application 
rate was determined to be 14.4 kg P ha−1 as WP in the field with 
low GWL (mean −29.2 cm), 15.2–15.9 kg P ha−1 as WP + SP in the 
field with middle GWL (mean −24.7 to −18.7 cm), and 11.1 kg 
P ha−1 as WP + SP in the field with high GWL (mean −6.5 cm). 
Optimal fertilizer type and application rate differed according to 
the water condition. Our results provided the basic information 
toward expansion of the rice cultivation area into the surround-
ing land on the Central Plateau of Burkina Faso.
Acknowledgments
The authors thank local farmers and technical staff members (Mr. Mohamed 
Ouedraogo and Mr. Kafando Serge Placide) for supporting our field trials, as 
well as JIRCAS’s Soil Team for soil chemical analysis. Soil sample was 
imported with plant phytosanitary certificate of Ministry of Agriculture, 
Forestry and Fisheries.
Disclosure of potential conflicts of interest
The authors declare that they have no known competing financial interests 
or personal relationships that could have appeared to influence the work 
reported in this paper.
Funding
This work was financially supported by the Science and Technology 
Research Partnership for Sustainable Development (SATREPS), Japan 
Science and Technology Agency (JST)/Japan International Cooperation 
Agency (JICA) (Project on establishment of the model for fertilizing cultiva-
tion promotion using Burkina Faso phosphate rock).
ORCID
Shinya Iwasaki http://orcid.org/0000-0002-5015-7837
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Table A1 Pearson’s correlation matrix of grain yield, biomass, harvest index, and yield components.
Grain yield Biomass Harvest index Number of panicle Number of grain 100 grain weight
(Mg ha−1) n (Mg ha−1) n (%) n (panicle ha−1) n (grain panicle−1) n (g) n
Grain yield 1
Biomass 0.809 *** 171 1
Harvest index 0.598 *** 171 0.049 0.528 171 1
Number of panicle 0.302 *** 189 0.396 *** 171 0.080 0.298 171 1
Number of grain 0.778 *** 186 0.544 *** 171 0.526 *** 171 −0.221 *** 186 1
100 grain weight 0.285 *** 189 0.296 *** 171 0.128 0.096 171 0.168 * 189 0.117 0.112 186 1
*: p < 0.05; **: p < 0.01; ***: p < 0.001
Figure A1. Effect of ground-water level (a) and soil pH (H2O) (b) on the yield relative to the control. Error bars indicate standard deviation (n = 4). Gray shading 
corresponds to the points of other fertilizers. CPR: calcined phosphate rock; PAPR: partially acidulated phosphate rock; SSP: single superphosphate; P0: nonfertilized 
(control). P0.5: 7.6 kg P ha-1; P1: 15.3 kg P ha-1; P2: 30.5 kg P ha−1
470 S. IWASAKI ET AL.
	Abstract
	1. Introduction
	2. Materials and methods
	2.1. Study site
	2.2. Preparation of calcinated and partially acidulated phosphate rock
	2.3. Experimental design
	2.4. Ground-water level measurement
	2.5. Soil sampling and analysis
	2.6. Data processing
	2.6.1. Evaluation of the P fertilization effect
	2.6.2. Optimal fertilization rate and required price of local P fertilizers
	2.7. Statistical analysis
	3. Results
	3.1. Chemical properties of fertilizers
	3.2. Seasonal variation in ground-water level
	3.3. Soil chemical properties
	3.4. Grain yield, biomass, and harvest index
	3.5. Factors controlling grain yield and fertilization effect
	3.6. Determination of optimal fertilization rate and expected increase in grain yield
	4. Discussion
	4.1. Effects of PAPR and CPR on grain yield under different GWL
	4.2. Effect of GWL and soil pH on fertilization effect
	4.3. Optimal fertilization and expansion of rice cultivation area
	5. Conclusions
	Acknowledgments
	Disclosure of potential conflicts of interest
	Funding
	ORCID
	References