Nutrient Constraints in a Sahel Valley Land For Irrigated Rice Cultivation

Koné et al., / Advances in Applied Agricultural Science 03 (2015), 02: 65-74

65

ARTICLE INFO

ABSTRACT

Article history: Received: August 20, 2014

Revised: December 02, 2014

Accepted: December 05, 2015

Available online February 23, 2015

Missing tool for site specific nutrient management can impaired the sustainability of

rice (Oryza sativa L.) production. To improve knowledge of nutrient constraints in

irrigated plain of the Sahel zone in West Africa, an omission trial was conducted in

2007 and 2008 in Baguenida (Mali). The experiment design was a randomized

complete block consisting of complete fertilizer treatment-Fc (nitrogen [N],

phosphorus [P], potassium [K], calcium [Ca], magnesium [Mg] and zinc [Zn]) and

treatments with specific nutrient excluded from the complete fertilizer treatment (Fc-

N, Fc-P, Fc-K, Fc-Ca, Fc-Mg and Fc-Zn) with four replications. Respective rates of 30

kg N ha-1, 100 kg P ha-1, 50 K kg ha-1, 50 kg Ca ha-1, 50 kg Mg ha-1 and 10 kg Zn ha-1

were applied as basal fertilizer. Rice variety WITA 12 was used and additional rate of

urea was applied at 35 kg N ha-1 at rice tillering and panicle initiation stages excluding

Fc-N and the control (no fertilizer). Results revealed significant (P<0.05) decreasing

effect of N and Ca deficiencies on the grain yield and additional effects of K and Zn

deficiencies occurring occasionally. A synergistic interaction of soil nutrients and the

change of soil pH after flooding were likely to be useful tools for irrigated soil fertility

management in a way of sustainable rice production in the irrigated plain of Sahel in

West Africa.

© 2015 AAAS Journal. All rights reserved.

Keywords:

Fertilizer

Irrigated plain

Rice yield

Sahel

Soil nutrient deficiency

* Corresponding Author; E. Mail: [email protected]

Tel: +225 06546189

n West Africa, the declining rainfall (Barnett

& Schlesinger, 2012) is reinforcing the

suitability of lowlands for crop production due

to preferential drainage of surface water in this ecology

as compared to upland: Lowlands have higher potential

for rice production (6 t ha-1) compared with the

production of the upland (1 t ha-1) though it represents

only about 5% to 10% of the total land surveyed in Africa

(Giertz et al., 2012). Therefore, the restriction of lowland

area can limit rice production. Thus, the use of lowland

areas should be optimized for the needs of the sub-region

(Harsh, 2004). To achieve this, strengthening water, land

and soil fertility management strategies are required.

I

Advances in Applied Agricultural Science

Volume 03 (2015), Issue 02, 65-74

Journal homepage: www.aaasjournal.com

ISSN: 2383-4234

Research Article

Nutrient Constraints in a Sahel Valley Land for Irrigated Rice Cultivation

Brahima Koné 1*, N’guessan Kouamé Antoine 2, Touré Natari 1, Doumbia Yacouba 3, Sié Moussa 4

1 Soil Science department, Earth Science Unit, Felix Houphouet Boigny University, Cocody, 22 BP 582 Abidjan 22, Côte d’Ivoire.

. 2 Biology Science department, Peleforo Gon Coulibaly University, Korhogo, Biology Sciences, BP 1328 Korhogo. Côte d’Ivoire.

. 3 Agronomy department, Institue d’Economie Appliquée-IER, BP 16 CRRA, Sikasso, Mali.

. 4 Lowland rice breeding, Africa Rice Center, 01 BP 2031 Cotonou, Bénin.

.

http://www.aaasjournal.com/


66

Most of the studies conducted in the inland valleys

(including lowland) of West Africa are related to agro-

ecological characterization (Ogban & Babalola, 2009),

impact of irrigation on rice productivity (Kebbeh et al.,

2003) and rice response to fertilizer (Segda et al., 2005).

The characterization of soil from irrigated plains in West

Africa showed low C, N, P, Ca and Mg contents (Buri et

al., 2010). Apart from Zn deficiency and iron toxicity in

rice production in the valley of Niger River

(Hägnesten,2006), there is scant evidence of soil nutrient

constraints on rice production inland valleys, especially,

for the irrigated plains of the Sahel zone as early

mentioned by Haefele et al. (2002). Indeed, existing data

collected from the temporarily flooded lowlands of the

humid zone in West Africa (Buri et al., 2010; Abe et al.,

2010) cannot be extrapolated to irrigated plains due to

the effect of submersion on soil properties and soil

nutrient flows in rice roots (Le Mer & Roger, 2001):

water displaces oxygen and CO2, affecting redox

conditions in soil with negative consequences for rice

growth (Thein, 2004). Furthermore, difference in climate

effects can be of concern from the humid zone to the

Sahel ecology. The use of soil testing (chemical analysis)

and rice yield for a specific fertilizer treatment can

underline site specific soil nutrient constraints on rice

production as illustrated for upland rice in the derived

savanna zone across the Dahomey gap of West Africa

(Koné et al., 2009; 2011) as well as in the humid forest

zone (Koné et al., 2013; 2014).

The current study was therefore conducted on the

irrigated plain of the Niger River at Baguenida (Mali) to

judge the level of deficiency of some soil major nutrients

(N, P, K, Ca, Mg and Zn) for rice production. The

objective was to identify the required nutrients for

sustainable rice production in an irrigated plain of the

Sahel zone in West Africa.

Materials and Methods

Experimental Site

Baguenida (12º35´05.89´´N; 7º42´05.40´´W; 357 m) is

located 30 km East of Bamako (Mali) on the plain of the

Niger River. It is within the Sahel zone where the

cropping period duration is 90 days with about 800 mm

total annual rainfall amount. The experiment was

conducted in an irrigated plain (2450 ha) along the Niger

River. The experimental site was established 200 m from

the valley fringe. It was preceded by two years fallow

period having vegetation composed exclusively by

annual grasses (Ischaemum rugosum Salisb.,

Echinochloa colona (L.) Link and Oryza barthii A.

Chev.). The soil was a Fluvisol having a loamy sandy

texture (40% sand; 35 % silt and 25 % clay) in the

surface soil depth (0 – 20 cm).

Experiment Layout

In 2007, the land was cleaned, flooded, ploughed and

manually leveled. A randomized complete block design

with four replications and eight treatments was laid out.

Plot size was 3 m × 5 m with spacing of 0.75 m between

plots and a distance of 1.5 m was maintained between

blocks as replications.

Each plot as well as the complete blocks were bunded

(0.30 m high, 0.20 m wide). Irrigation (0.20 m depth) and

drainage (0.20 m depth) canals were also made. A

complete fertilizer treatment (Fc) composed of nitrogen

(N), phosphorus (P), potassium (K), calcium (Ca),

magnesium (Mg) and zinc (Zn) was used. A specific

nutrient was excluded from Fc in each of other

treatments (Fc-N, Fc-P, Fc-K, Fc-Ca, Fc-Mg and Fc-Zn).

A non-fertilized treatment (0) was used as the control.

Fertilizers were applied as basal fertilizer according to


67

Dobermann and Fairhust (2000), at rates of 30 kg N ha-

1 (Urea), 100 kg P ha-1 (Super triple phosphate), 50 kg K

ha-1 (potassium chloride) and 10 kg Zn ha-1 (zinc sulfite).

The rates of 250 kg ha-1 were applied as magnesium

sulfate (20% Mg) and calcium sulfate (23% Ca)

respectively. Each micro-plot was re-ploughed before

the transplanting rice of 21 days old seedling. One of the

popular, locally-adopted rice varieties, WITA 12, was

used. Additional urea was applied at a rate of 35 kg N ha-

1 as top dressing at maximum tillering stage (21 days

after transplanting-DAT) and again at panicle initiation

of rice (40 DAT) respectively excluding the treatments

Fc-N and the control. About 5-15 mm of water depth was

maintained weekly from transplanting to heading, and

the water was drained off field 2 days before applying N-

fertilizer (21 DAT and 40 DAT) and ten days before the

harvest.

Soil Sampling and Analysis

Soil samples were taken at 0 – 20 cm depth using an

auger before (2007) fertilizer application. Five samples

were taken in the four corners and the centre of every plot

for 3 kg of composite sample. A total of 32 composite

samples were taken for analysis of soil pH (water), soil

content in organic carbon (C), total nitrogen (N),

available phosphorus (P) and free iron using the methods

described by the International Institute of Tropical

Agriculture (IITA,1989).

Data Collection

At 30 DAT, the total number of tillers was counted

within in one square meter (1 m2) of each plot. Plant

height and panicle number were also collected at rice

maturity. The plot size harvested was 8 m2, with two

border lines eliminated from each side of the plot in order

to avoid a border effect. The rice was threshed and the

grains were sun dried and weighed. The moisture content

of the grain was measured and grain yield (GY) was

determined at 14% of moisture content.

Statistical Analysis

General linear model (GLM) analysis was used to

generate effect of the treatment on the grain yield and to

generate the mean values of grain yield obtained in each

treatment per year. The average mean of grain yield of

the two years experiment was also generated through

analysis of variance. In the same manner, means plant

height, tiller and panicle numbers per square meter were

determined. The least significant difference (LSD.05) was

used to separate the mean values. Existing synergistic or

antagonistic relationships between rice grain yield

production and the native soil contents of C, N, P and Fe

as well as with soil pH were explored in each treatment.

For this purpose, Pearson correlation analysis was used.

SAS software (SAS, 2001) was used for all statistical

analyses.

Results

Treatment Effects on Rice growth and Yield

No significant difference was observed between the

mean values of plant height (1.10 to 1.20 m) per

treatment meanwhile, the rice height was almost twice

higher in the treatments Fc-Zn and Fc-N than Fc-Ca, Fc-

Mg and the control plots as illustrated by a sharp

decreasing trend observed in Figure 1. But, there was

significant difference in treatment effects during the

tillering stage as noticed in Figure 2: Extreme values of

tiller numbers accounted for treatments Fc-Zn and the

control as highest and lowest values respectively while,

moderate effects were observed for treatments Fc-Ca and


68

Table 1. The grain yields per treatment in 2007 and 2008 and the average mean grain yield for the year’s

period. Grain yields (t ha-1)

Treatments 2007 2008 Mean

Fc-Zn 3.55aA 3.46bA 3.50ab

Fc-Mg 3.29aA 3.66abA 3.47ab

Fc 3.28aA 3.49abA 3.39abc

Fc-Ca 3.24aA 2.84cA 3.04c

Fc-K 3.18aA 3.44bA 3.31abc

Fc-P 3.10aB 3.99aA 3.54a

Fc-N 2.43bB 3.73abA 3.08bc

Control 2.20bA 1.78dA 2.00d

GM (t ha-1)

LSD.05

P>F

3.03A

0.521

0.0003

3.30A

0.519

<0.0001

3.16

0.432

<0.0001

a, b, c and d: significant different mean values according to the LSD value in column as A and B in the line

between the two years.

Table 2. Chemical characterization of soil (0 – 20 cm depth) in each treatment plot

Plots pHw C

(g kg-1)

N

(g kg-1)

P

(mg kg-1)

Fe

(cmol kg-1)

Fc Mean 5.1 4.2 0.3 23.2 77

SE (4) 0.34 2.04 0.04 5.32 19.25

Fc-Ca Mean 5.1 4.9 0.3 18.7 49.2

SE (4) 0.37 0.92 0.07 5.37 14.27

Fc-K Mean 5.3 4.5 0.2 20.5 48.7

SE (4) 0.25 1.79 0.04 3.28 17.3

Fc-Mg Mean 5.3 4.3 0.2 17.5 43.2

SE (4) 0.36 1.33 0.02 1.55 15.52

Fc-N Mean 5.1 5.5 0.3 25.0 67.5

SE (4) 0.25 1.07 0.04 4.02 17.58

Fc-P Mean 5.3 5.0 0.27 22.5 66

SE (4) 0.22 0.81 0.02 4.25 18.94

Fc-Zn Mean 5.2 5.0 0.3 23.0 60.2

SE (4) 0.20 0.54 0.04 4.02 16.03

Control Mean 5.2 3.9 0.3 16.0 60.7

SE (4) 0.25 1.07 0.04 1.73 7.53

SE : Standard error; (4): sample size

Fig 1. Across years mean values of plant height per treatment (Letter “a”

is indicating no significant different between mean values).


69

Fc-Mg and the number of tillers was reduced in treatment

Fc-P close to that of the control plot. Similar trend was

observed for panicle numbers as induced by treatments

with major difference in treatment Fc-P which induced

moderate panicle number (Figure 3) contrasting with the

tiller number previously presented.

Treatment Fc-Zn presented the highest effect on rice

vegetative development among the studied treatments

indifferently to the parameters (height, tillers and

panicles) considered.

Treatments Effects on the Yields

In 2007, the results (Table 1) showed significantly (P =

0.0003) similar lower yields in the treatment Fc-N (2.43

t ha-1) and the control treatment (2.20 t ha-1). The highest

yields were observed in the range of 3.10 t ha-1 (Fc-P) to

3.55 t ha-1 (Fc-Zn) contrasting with the results observed

in 2008 for treatments Fc-Zn (3.46 t ha-1) and Fc-K (3.44

t ha-1) characterized by yield reduction. Lowest yields

were obtained in the control treatment (1.78 t ha-1)

followed by treatment Fc-Ca (2.84 t ha-1). The yield

observed in treatment Fc-P (3.99 t ha-1) still remained

high in 2008 while treatment Fc-N (3.73 t ha-1) did not

induce significant yield decrease as observed in 2007:

The yields were significantly increased in both

treatments (Fc-P and Fc-N) from 2007 to 2007. Despite

of this increasing trend of grain yield in treatment Fc-N,

its overall grain yield (3.08 t ha-1) accounted among the

lowest similarly with the treatment Fc-Ca (3.04 t ha-1)

when excluding the control treatment (2.00 tha-1).

Indeed, the initial soil pH was low (< 5.5) indifferently

to the plots of which, Fc-N and Fc-Ca showed the lowest

values (5.1). In contrast, soil contents of available P (>

10 mg kg-1) and C (> 1 g kg-1) were ranging in acceptable

ranges for most of the crop growing (Table 2). There was

also interaction between soil nutrients with consequence

on rice grain yield: Significantly (P<0.10) higher

positive coefficients of Pearson correlation are observed

in the plots Fc (0.92) and Fc-N (0.93) between soil pH

and the grain yield in 2007 (Table 3). Similar

observations can be made in the treatment Fc-Mg for soil

contents of N (0.96) and P (0.94) as well as in treatment

Fc-N for soil content of N (0.93).

Discussion

Treatment Effects on Rice Growth as Affected by Sahel

Ecology

No significant difference was observed between the

mean values of plant height meanwhile, it has been

reported leaf chlorosis and plant height reduction should

have occurred in N-deficient (Fc-N) condition

(Dingkuhn et al., 1992). This was not the case, however,

in Sahelian conditions studied. The intensity of daylight

and/or photoperiodism characterizing this ecology

(Seaquist & Olsson, 1999) may have contributed to this.

Indeed, environment factors affect plant mineral

nutrition requirement as well as the symptoms of nutrient

deficiency (Ames & Johnson, 2013). However, these

processes are not well documented enough for rice

cultivation, especially in West Africa.

Despite the high content of P (22.5 mg kg-1) in the soil of

treatment Fc-P, a significant reduction of the plant tillers

number was observed as compared to Fc-Zn (Figure 2).

This is a typical symptom of P-deficiency as described

by Dobermann and Fairhust (2000) allowing the

suspicion of a certain level of P-deficiency in the studied

soil. However, this observation was not reflected by the

grain yield.

The highest significant tiller (Figure 2) and panicle


70

(Figure 3) numbers that were observed in the Fc-Zn

treatment were contrasting with the work done by

Dobermann & Fairhust (2000) in Philippines. Ecological

differences may have contributed to the differences

observed.

These results are supported by the study done by Makino

(2011) showing the effect of climate on photosynthesis

of rice. Furthermore, Lawlor (2002) stated that

environmental conditions can affect the growth

characteristics and nitrogen response of a crop. Our study

highlighted some differences in N and Zn effects on rice

growth in the Sahel zone of West Africa compared with

existing knowledge of studies performed in Asia.

Nevertheless, S released by fertilizer materials including

magnesium sulphate and calcium sulphate could have

interacted with the indigenous-N for mitigating N

deficiency as reported by Choudhury et al. (2009).

Flooding as Key Practice in Rice Production

There was yield increasing for treatments Fc-P and Fc-N

Fig 2. Across years mean values of tiller number in a square meter per

treatment (a, b and c are indicating mean values with significant

difference).

Fig 3. Across years mean values of rice panicle number in a square meter

per treatment (different letters (a and b) are related significant different

mean values).


71

from 2007 to 2008 as probable consequence of the

improvement of bunds consistency in 2008, reducing the

loss of water and nutrients (Touré et al., 2009). In fact,

N loss can be minimized by maintaining soil

continuously flooded (Khind & Ponnamperuma, 1981)

coupled with more availability of soil P for crop uptake

(Lindsay, 1979). However, the effect of flooding could

reduce Zn availability, affecting the rice yield

(Veldkamp et al., 1991) as observed in treatment Fc-Zn

(in 2008). Furthermore, cations (K+, Ca2+, and Mg2+) can

be displaced from clay exchangeable site by Fe2+, Mn2+

and NH4+ under conditions of soil submersion (Sahrawat,

2012). Therefore, flooding can reduce soil supplying

capacity of K+, Ca2+, and Mg2+ to crop, affecting yields

as observed for Fc-Ca and Fc-K in 2008. The yield

decrease was not, however, significant in treatment Fc-

Mg compared with the highest yield of Fc-P in 2008.

Hence, there is opportunity to assert mitigated effect of

flooding in Mg2+ nutrition of rice compared to that of

other cations (K+ and Ca2+) in soil. Other process than

those related to soil inherent fertility may explain this

result: The high yields observed for Fc-P and Fc-Mg

may be due to the high soil P inherent content (Table 2)

and to a synergistic effect observed in treatment Fc-Mg

(Table 3) respectively. In fact, soil P content was high

(22.5 mg kg-1) despite the relatively low pH (5.3) of the

soil. The relatively high C (organic carbon) content (3.9

– 5.5 g kg-1) in the soil may explain this result according

to isomorphic exchange between HCO2- and P2O5

2- . This

process can induce P release from hydroxide iron

fixation, increasing soil available P content and blocking

iron components during the experiment (Olk et al., 1996;

Bennani et al., 2005; Seng et al., 2006).

In the light of these analyses, we assert the possibility to

increase the yield of rice variety WITA12 in Mg-

deficient soil when applying N or P, while applying N or

raising soil pH can do so, in N-deficient soil. In fact, long

term flooding (2 to 4 weeks) can help to increase the pH

in acidic soil resulting from redox process

(Ponnamperuma, 1972; 1985) and contributing to yield

increase by 0.8 to 1 tha-1 as observed in treatment Fc-N

characterized by 1.3 tha-1 of yield increase in 2008 close

to that of Fc because of bounds and flooding effect

improvement. However, these synergistic effects could

be observed only for specific nutrient deficient condition

(Table 3) of which K and Zn were concerned and the use

of flooding can be cited as a nutrient management

strategy in the Baguenida irrigated plain.

The current study confirmed soil Zn-deficient as early

reported by Hägnesten (2006) in a plain of “Office du

Niger” and underline this occurrence as a consequence

of inadequate duration of soil submersion according to

our interpretations of the results obtained in 2008. To

avoid such constraints, there is a need to generate

knowledge of the effects of flooding duration on tropical

soil contents of K, Ca and Zn in rice cultivation,

particularly, for K which has been neglected in this agro-

ecology (Greenland & De Data, 1985).

The Fluvisols of irrigated plains in Sahel can be

characterized by N and Ca deficiencies’ effects on rice

grain yield without any symptomatic effect on rice


72

growth. Furthermore, K and Zn deficiencies can be

observed under certain conditions that were probably

related to water management. Additional knowledge

concerning the effects of flooding duration on K and Zn

is required for improving fertilizer and water

management in this agro-ecology.

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Table 3. Pearson correlation coefficients (R) and its probabilities (P) showing relationship between soil characteristic

and the grain yield obtained in 2007.

Coefficient of Pearson correlation

pH water C N P Fe

R P R P R P R P R P

Fc 0.92 0.08 0.29 0.70 0.79 0.21 -0.29 0.71 0.65 0.35

Fc-Ca 0.50 0.41 0.32 0.67 0.48 0.52 0.12 0.67 0.34 0.43

Fc-K 0.14 0.85 0.58 0.42 0.42 0.58 0.56 0.44 0.58 0.49

Fc-Mg 0.63 0.47 -0.02 0.98 0.96 0.04 0.94 0.06 0.08 0.94

Fc-N 0.93 0.07 0.51 0.49 0.93 0.07 0.82 0.17 -0.42 0.58

Fc-P 0.42 0.57 0.37 0.63 -0.55 0.43 0.82 0.18 0.83 0.16

Fc-Zn -0.16 0.84 0.24 0.76 -0.24 0.76 0.11 0.89 -0.29 0.70

Control 0.89 0.10 0.92 0.26 0.84 0.15 0.71 0.29 -0.56 0.42

R: Pearson coefficient of correlation; P: Probability of correlation


73

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Nutrient Constraints in a Sahel Valley Land For Irrigated Rice Cultivation

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