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Effects of Integrating Deficit irrigation and Carbonate Foliar Fertilizers into the System of Rice Intensification on Growth and Yield: A Case study of Mkindo Irrigation Scheme, Tanzania

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Abstract and Figures

Individually, the System of Rice Intensification (SRI), deficit irrigation and foliar fertilizer application have proved to be effective in enhancing rice growth and yield, however, the information on their combined effects is limitedly known. Therefore, a study was conducted to evaluate the effects of integrating deficit irrigation and carbonate foliar fertilizer (Lithovit) application into SRI on rice growth and yield. This study was conducted in Mkindo Irrigation scheme in Mvomero, Morogoro, Tanzania during the dry and wet season (October 2020 to June 2021). The experiment was laid out in a split plot design with three levels of irrigation for main plots which were 100% of the irrigation water requirement (40mm) imitating the SRI alternate wetting and drying pattern and induced deficit irrigation applied at 80% and 50% of the irrigation water requirement as IR100, IR80 and IR50, respectively. Irrigation was carried out at the appearance of soil cracks in IR100. The sub-plot fertilizer treatments were five in number namely: (A) Diammonium Phosphate (DAP) and Urea (normal practice), (B) DAP, Urea and 100% of recommended foliar fertilizer (Lithovit Standard), (C) DAP and 50% (Lithovit and Urea), (D) Lithovit Standard only and (E) no fertilizer. The data was analyzed using IBM SPSS version 20 at 5% probability level in order to ascertain if any significant differences between the various treatment combinations existed. Water application IR80 had the best performance in terms of growth and yield. Among fertilizer applications, the highest yield was attained by treatment B with 11.09 t/ha and 6.74 t/ha in the dry and wet season respectively. Treatment E had the least yield of 7.26 t/ha and 4.10 t/ha in the dry and wet season respectively. Foliar treatments performed considerably well as Lithovit supplies higher concentrations of carbon dioxide thereby aiding photosynthesis hence increasing crop growth and yield.
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26
Full Length Research Paper
Effects of Integrating Deficit irrigation and Carbonate Foliar Fertilizers
into the System of Rice Intensification on Growth and Yield: A Case study
of Mkindo Irrigation Scheme, Tanzania
G Aseru*, A K P R Tarimo, F R Silungwe1 and W Mbungu
Department of Civil and Water Resources Engineering, Sokoine University of Agriculture (SUA), Morogoro, Tanzania,P.O Box
3000.
ARTICLE INFORMATION ABSTRACT
Introduction
Globally, about 26% of the population (2 billion) lack regular access to safe, nutritious and sufficient food (FAO, 2019).
According to United States Department of Agriculture (USDA) (2019), the global population of food insecure people is
expected to fall from 19.3 to 9.2% between 2019 and 2029. On the contrary, Sub-Saharan Africa (SSA) is predicted to be the
epicenter of global food insecurity by 2029 with 22.5% of its population being food insecure (USDA, 2019). This calls for
more food production to meet this global target while curbing the aggravating situation of SSA. Rice, wheat and maize are
the three most essential cereals critical for the survival of a vast population globally (FAO, 2016). According to FAO (2016),
daily consumption of cereals is expected to increase by 390 million tonnes between 2014 and 2024. By 2050, an annual
demand for rice, wheat and maize is predicted to reach 3.3 billion tonnes (FAO, 2016).
Rice (Oryza sativa L) is the primary staple food for over half of the world’s population while sustaining livelihoods of more
than 100 million people in Sub-Saharan Africa (SSA) (FAO, 2013). Globally, rice ranks third after wheat and maize in terms
Vol. 11. No.2. 2022
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Contents available at:
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International Journal of Basic and Applied Sciences (ISSN: 2277-1921) (CIF:3.658 ; SJIF: 6.823)
(A Peer Reviewed Quarterly Journal)
Corresponding Author:
G Aseru
Article history:
Received: 01-06-2022
Revised: 08-06-2022
Accepted: 18-06-2022
Published: 21-06-2022
Key words:
System of Rice
Intensification (SRI),
deficit irrigation,
carbonate foliar fertilizer,
growth, yield
Individually, the System of Rice Intensification (SRI), deficit irrigation and foliar fertilizer
application have proved to be effective in enhancing rice growth and yield, however, the
information on their combined effects is limitedly known. Therefore, a study was conducted
to evaluate the effects of integrating deficit irrigation and carbonate foliar fertilizer (Lithovit)
application into SRI on rice growth and yield. This study was conducted in Mkindo Irrigation
scheme in Mvomero, Morogoro, Tanzania during the dry and wet season (October 2020 to
June 2021). The experiment was laid out in a split plot design with three levels of irrigation for
main plots which were 100% of the irrigation water requirement (40mm) imitating the SRI
alternate wetting and drying pattern and induced deficit irrigation applied at 80% and 50% of
the irrigation water requirement as IR100, IR80 and IR50, respectively. Irrigation was carried out
at the appearance of soil cracks in IR100. The sub-plot fertilizer treatments were five in number
namely: (A) Diammonium Phosphate (DAP) and Urea (normal practice), (B) DAP, Urea and
100% of recommended foliar fertilizer (Lithovit Standard), (C) DAP and 50% (Lithovit and
Urea), (D) Lithovit Standard only and (E) no fertilizer. The data was analyzed using IBM SPSS
version 20 at 5% probability level in order to ascertain if any significant differences between
the various treatment combinations existed. Water application IR80 had the best performance
in terms of growth and yield. Among fertilizer applications, the highest yield was attained by
treatment B with 11.09 t/ha and 6.74 t/ha in the dry and wet season respectively. Treatment
E had the least yield of 7.26 t/ha and 4.10 t/ha in the dry and wet season respectively. Foliar
treatments performed considerably well as Lithovit supplies higher concentrations of carbon
dioxide thereby aiding photosynthesis hence increasing crop growth and yield.
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27
of production with a daily consumption of more than three billion people (GRiSP, 2013). Nearly 11% of the world’s
cultivated land is occupied by rice covering an area of about 158 million hectares with over 527 million tonnes as annual
production (FAO, 2019). As the world population is projected to increase to 8.27 billion in 2030 (UN, 2015),
correspondingly, there will be increase in rice demand. The global rice demand is projected to increase from 439 - 555
million tonnes (milled rice) between 2010 and 2035 (GRiSP, 2013). Other studies such as Shamshiri et al. (2018); Dinesh et
al. (2019); Raut et al. (2019); are all promoting increase in rice production following the increase in rice demand.
In Tanzania, rice is the third most important food crop after maize and cassava consumed by about 30% of the households
(FAO, 2015). About 20% of farmers are involved in rice production (Mtaki, 2018) with 80% of these being small scale
farmers (Katambara et al., 2016). Tanzania is also the lead rice producer in Eastern and Southern Africa while accounting for
about 9% of the total 30.8 million tonnes of African rice production (FAO, 2014). However, the rice yield gap for Tanzania is
over 87% (Senthilkumar et al., 2018). This is attributed to the generally low rice yields ranging from 1.1 t/ha under rainfed
lowland conditions to 3.5 t/ha under irrigated conditions (SRI-Rice, 2020) which is below the world’s average yield of 4.31
t/ha (FAO, 2015). Despite its central role in food security and economic development, rice production in Tanzania is faced
with a number of constraints such as low rice yielding varieties, weed infestation, prevalence of pests and diseases with water
scarcity and poor/low fertilizer application being of major concern.
Various studies have been carried out to assess the capacity of the System of Rice Intensification (SRI) as a means to curb
rice production constraints and improve the yields in Tanzania (Katambara et al., 2013; Reuben et al., 2016; Kangile et al.,
2018; Materu et al., 2018; Gowele et al., 2020). SRI has been profound in boosting yields between 6-8 t/ha and water
productivity by saving water of up to 25% as compared to conventional flood irrigation (Katambara et al., 2013). Despite SRI
success, the potential rice yields have not been achieved in Tanzania. Another study by Nhamo et al. (2014) reported that the
use of fertilizers could avail a relative yield gain of 52%, equivalent to 948 kg /ha of rice grain in Eastern and Southern
Africa. This highlights the inadequacy of nutrients availability (fertilization) to the plants that limits more production per unit
area to consequently close the yield gap (Khan and Iqbal, 2018; Hashem, 2019; Kumar et al., 2019). Evidently, rice requires
sufficient nutrients to produce ample yields (Kumar et al., 2019). Senthilvalavan and Ravichandran (2019) reported that
integration of organic and inorganic fertilizers is essential in enhancing the growth and physiological attributes of rice.
Moreover, micronutrients are also very essential in the production of rice (Khan and Iqbal, 2018; Raut et al., 2019; Gowele et
al., 2020). However, the use of low or excess amount of fertilizers compromises the soil quality and crop yield in addition to
high production costs (Raut et al., 2019).
In addition, the methods of fertilizer application have a significant impact on the growth and yield attributes (Raut et al.,
2019). Rice fields require slow release of fertilizers (Tarigan et al., 2019) yet large volumes of fertilizers are lost through
leaching and fixation following basal fertilizer application (Raut et al., 2019). Foliar application, the technique of spraying
liquid fertilizers (macro or micro nutrients) directly onto the leaves of crops is considered key in attaining maximum and
quality yields (Khalil and Hussein, 2015; Buczek, 2017; Jakab-gábor and Komarek, 2017; Kaleri et al., 2019; Kumar and
Nagesh, 2019; Aljutheri et al., 2020) while alleviating inhibition due to water stress (Badawi et al., 2013).
Foliar fertilizers are reported to have significant impact on the growth and yield of paddy rice ( Badawi et al., 2013;
Toromanova and Georgieva, 2017; Hashem, 2019; Raut et al., 2019). Hashem (2019) recommended the use of foliar fertilizer
application together with the conventional fertilizers at the various growth stages in order to enhance rice productivity.
Badawi et al. (2013) affirmed that the interaction between foliar fertilizer application and deficit irrigation had significant
impact on the yield of rice. Toromanova and Georgieva (2017) reported that foliar fertilizer application played a positive
effect on rice productivity with a 13.1% increase in productive tillering capacity following application of Lithovit fertilizer
which was the highest among other foliar treatments used. Lithovit is a natural 100% organic calcite carbonate fertilizer
extracted from natural limestone deposits suitable for organic farming (Nassef et al., 2013; Morsy et al., 2018; Zorovski et
al., 2021). Lithovit consists of nano-particles that are directly absorbed through the stomata and can considerably increase the
photosynthesis rate, reduce crop water requirement and increase crop yield (Farouk, 2015). Deficit irrigation, SRI and foliar
fertilizer application have proved to be effective in enhancing rice growth and yield individually. However, the information
on their combined effects is limitedly known.
Therefore, this study evaluates the effects of integrating deficit irrigation and carbonate foliar fertilizer application into SRI
on rice growth and yield.
Materials and Methods
Description of the Study Area
The study was conducted at Mkindo farmer managed irrigation scheme in Morogoro, Tanzania given that the scheme is
among the few farmer-based schemes which practice SRI. Small scale irrigation schemes are considered essential in
improving the livelihoods of majority of small scale farmers in Tanzania (Fundi and Kinemo, 2018). Mkindo irrigation
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scheme is located in Mkindo village, Mvomero District, Morogoro Region in eastern Tanzania between latitude 6016’ and
6018’ South, and longitude 37032’ and 37036’ East as shown in Fig. 1. Its altitude ranges between 345 m and 365 m above
mean sea level and is about 85 km from Morogoro Municipality (Kahimba et al., 2014). The major crop grown in the area is
rice under surface irrigation supplied by Mkindo Perennial River.
Fig 1: Location of the Study area
The study area is characterized by an average annual temperature of 24.95˚C, with a minimum temperature of 15.8˚C in July
and a maximum temperature of 33.8˚C in February as shown in Fig. 2. The study area has a bimodal rainfall regime which
determines the two rice growing seasons- dry season (vuli) with short rains starting in October to December and wet season
(masika) with long rains starting from March to May. Rainfall in Mkindo usually starts in October with an increased trend
until May with peak rainfall in April. The trend then decreases from May until July where the least rainfall is attained. The
average annual total rainfall ranges between 700 and 1600 mm.
Fig 2: Average Monthly Rainfall, Maximum and Minimum temperature from 2000-2020 (Source: Mtibwa Sugar Estate
Meteorological Station)
The soils of the study area are sandy clay loam (69.12%, 23.6% and 7.28%) with pH of 5.54 (medium acidic soils), electrical
conductivity (EC) of 87.7 µS/cm (acceptable range), total nitrogen (N) and organic carbon of 0.09% (very low) and 1.26%
(medium) respectively. Other properties include: available phosphorus (P) of 7.11 mg/kg (medium) with Cation Exchange
Capacity (CEC) of 8.0 Cmol/kg (low) and exchangeable Ca, Mg, K, Na of 3.29 (medium), 1.44 (medium), 0.16 (medium)
and 0.21 (low) Cmol/kg respectively. These soils are deemed suitable for rice cultivation according to Msanya (2012) and
Shamshiri et al. (2018) as they facilitate root proliferation, aeration, water infiltration and water holding capacity, soil
nutrients retention and drainage.
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Experimental design
The experiment was laid out in a split plot design with three levels of irrigation for main plots which were 100% of the
irrigation water requirement (40mm) imitating the SRI alternate wetting and drying pattern and induced deficit irrigation
applied at 80% and 50% of the irrigation water requirement as IR100, IR80 and IR50, respectively. Irrigation was carried out at
the appearance of soil cracks in IR100. The sub-plot fertilizer treatments were five in number namely: (A) Diammonium
Phosphate (DAP) and Urea (normal practice), (B) DAP, Urea and 100% of recommended foliar fertilizer (Lithovit Standard),
(C) DAP, 50% (Lithovit and Urea), (D) Lithovit Standard only and (E) no fertilizer. The combined irrigation and fertilizer
treatments tested were IR100A, IR100B, IR100C, IR100D, IR100E, IR80A, IR80B, IR80C, IR80D, IR80E, IR50A, IR50B, IR50C, IR50D
and IR50E.
All the treatments were randomly allocated and replicated three times. An individual plot size was 4 m × 2 m (8 m2) each
separated from the other by 0.5 m buffer zone to prevent lateral movement of water from one plot to another as shown in Fig.
3.
Fig 3: Set up of the experiment
Agronomic practices
The agronomic practices that were carried out include nursery and field preparation, transplanting, fertilizer application and
weeding. During land preparation, the field was properly turned using a power tiller. Levelling was also carried out to aid
uniform wetting of the soil. Proper drainage was maintained to facilitate water discharge especially during the rainy period.
The SARO (TXD 306) rice variety was used as it is well suited to the conditions of Mkindo and was recommended by the
Ministry of Agriculture, Tanzania (Kahimba et al., 2014).
During nursery preparation, only viable seeds were used and were identified by submerging all the seeds in a salty solution in
which an egg would float. All the seeds that floated were considered inferior and were discarded. Seed priming was then
done by soaking the seeds in clean water to enhance the rate of seedling emergence and germination.
One seedling per hill was transplanted at the age of 10 days using 25 cm × 25 cm spacing (Reuben et al., 2016). While
considering particular sub-plots with their respective treatments, DAP was applied only once on the second day after
transplanting (DAT), Urea was applied at two different times (30 and 60) DAT while all foliar fertilizers were applied at 30,
60 and 81 DAT. Urea and DAP were applied at a rate of 125kg/ha while all foliar treatments at 1kg/ha in 100 litres of water.
The fertilizer compositions are as shown in Table 1.
Block 1
L1 - IR100 (40mm)
L2 - IR80 (32mm)
L3 - IR50 (20mm)
All dimensions in meters
Block 2
Block 3
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Table 1: Fertilizer composition for the various treatments (Source: Lithovit)
Fertilizers
Composition
DAP
Nitrogen, N (18%)
Phosphate, PO4 (46%)
Urea
Nitrogen (46%)
Lithovit Standard
Calcium carbonate, CaCO3 (60%)
Calcium oxide, CaO (35%)
Silicon dioxide, SiO2 (12%)
Magnesia, Mg (2%)
Iron, Fe (1%)
Manganese, Mn (0.02%)
Lithovit and Urea (50%)
Calcium Carbonate (33%)
Nitrogen (21%)
Calcium oxide (18.5%)
Silicon dioxide (6.5%)
Magnesia (1.2%)
Iron (0.5%)
Manganese (0.01%)
Weeding and spraying of pesticides against white fly infestation was carried out four and two times in the dry and wet season
respectively. Before harvesting, a 14 days dry period was observed to allow for maximum transfer of nutrients to the grains.
The rice was harvested manually with serrated edged sickles at 112 days when about 90% of the panicles had ripened
spikelets and threshed using wooden sticks.
Measurement of plant attributes
Growth attributes
Areas (one square meter) with average uniformly growing representative plants were randomly selected and labelled from
each field plot for measurements of five plants that were carried out after every two weeks. The variables that were measured
after every two weeks include; plant height, number of leaves and total number of tillers. Plant height was measured using a
tape measure while number of leaves and total number of tillers were measured manually by counting.
Yield attributes
At harvest, the number of productive tillers, length of panicles, biomass, yield and dry weight of 1000 grains were measured.
Length of panicles was measured using a tape measure while the number of productive tillers was measured manually by
counting. Dry weight of 1000 grains was measured by randomly picking two grain panicles from 10 plant samples within
each sub plot excluding the boundary crops. The panicles were then air dried and 100 grains were manually counted off and
weighed using a digital electronic balance. The weight was then projected to 1000 grains. Biomass and grain yield were
measured by randomly harvesting one square meter of rice from each plot. Thereafter the grains were separated from the
straw by manual threshing. The weight of the grains was determined after winnowing and one kilogram of straw was also
measured off for further drying. Air drying was then carried out until constant weight was attained for both the straw and
grains. A digital electronic balance was used to measure the grain and straw weights.
Data analysis
Analysis of Variance (ANOVA) was used (p<0.05) to determine the existence of any differences between both the main and
sub plot treatments for the growth and yield attributes. Data was analyzed using IBM SPSS version 20 which is best
recommended for split plot nature of experiments. Duncan’s multiple range test was used to d etermine if any significant
difference existed between the various treatment combinations.
Results and Discussion
Seasonal trend of growth
There was rapid increase in plant height and total number of leaves in the vegetative (28-56 DAT) and reproductive phases
(84 DAT) which became constant during maturity stage (112 DAT). The trend of growth of plant height and total number of
leaves throughout the entire dry and wet season under IR100, IR80 and IR50 for fertilizer treatments A, B, C, D and E at 28, 56,
84 and 112 DAT is as shown in Fig. 4. There was also slight variation in plant height and total number of leaves at the
different growth stages among the different water and fertilizer treatments. At every growth stage, either treatment A or B
had the highest plant height or number of leaves followed by C, D while the no fertilizer treatment E had the least
performance. Growth and panicle initiation occurs during the vegetative and reproductive phases. In addition, all fertilizer
applications were carried out before the reproductive phase hence the rapid increase in growth is due to ample supply of
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nutrients during these phases. A similar trend was also observed by Thakur et al. (2014); Hidayati et al. (2016); Materu et al.
(2018) and Yoga et al. (2020). The variations in plant height and total number of leaves among the different water
applications is attributed to the variation in water depth as also observed by Materu et al. (2018). The variations between the
conventional and foliar fertilizer treatments is due to the impact of Lithovit foliar fertilizers. Lithovit is a nano-fertilizer
which contains Calcium carbonate (CaCO3) and Magnesium carbonate (MgCO3) that rapidly penetrates into plant tissues and
aids in biological and physiological processes. In addition, other macronutrients are availed which increase enzymatic activity
and growth. This is in agreement with Nassef et al. (2013); Morsy et al. (2018) and Zorovski et al. (2021).
Fig 4: Plant height at 28, 56, 84 and 112 days after transplanting (DAT) for (1) IR100, (2) IR80 and (3) IR50 respectively. Total
number of leaves at 28, 56, 84 and 112 DAT for (4) IR100, (5) IR80 and (6) IR50 respectively
Effect of water application levels
There was no significant difference (p>0.05) among the different water applications for plant height, leaves, total and
effective tillers, panicle length and straw for both the dry and wet season in addition to dry season 1000 grain weight and
yield. However, there was significant difference among the different water applications (p<0.05) for 1000 grain weight (dry
season) and yield (wet season). The effect of the different water levels, IR100, IR80 and IR50 on plant height, number of
leaves, total and effective tillers, panicle length, dry weight of 1000 grains, straw and yield for both the dry and wet seasons
is as shown in Table 2.
Table 2: Water regimes dry and wet season analysis for growth and yield attributes
Season
Water
level
Plant
Height
(cm)
Leaves
Total
tillers
Effective
tillers
Panicle
length
(mm)
1000
grain
weight
(g)
Straw
(g)
Yield
(t/ha)
Dry
season
IR100
109.1a
112a
15a
14a
261.5a
31.01a
0.51a
9.02a
IR80
109.2a
110a
14a
14a
262.6a
31.16a
0.53a
8.75a
IR50
107.2a
112a
15a
14a
268.0a
32.21b
0.52a
8.22a
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Wet
season
IR100
89.3b
101b
14b
13b
228.9b
30.08c
0.51b
5.76b
IR80
89.4b
98b
15b
14b
230.7b
30.26c
0.50b
5.41bc
IR50
89.1b
98b
14b
13b
228.9b
30.63c
0.49b
5.13c
(Mean values followed by different letters within similar columns differ significantly at p< 0.05 according to Duncan’s
Multiple-range test)
The highest 1000 grain weight for the dry season was recorded under IR50 followed by IR80 and IR100 with 32.21, 31.16 and
31.01g respectively but with no significant difference between IR80 and IR100. While considering yield for the wet season,
there was a significant difference between IR100 and IR50 with a 12% difference in yield while IR100 had 6.5% more yield than
IR80.
Dry season 1000 grain weight is contrary to Zoundou et al. (2019) who recorded the highest 1000 grain weight with IR100 and
the least with IR50 but with no significant difference (p>0.05). The plant heights recorded are higher than in Materu et al.
(2018) who observed mean values of 44.0, 40.0 and 30.0 cm for IR100, IR80 and IR50 respectively. The total and productive
tillers for the dry and wet seasons fall within the range of Kissou and Wang (2017) whose range was between 16 and 18
tillers. The panicle lengths are in agreement with Ndiiri et al. (2017) and Kissou and Wang (2017) who observed panicle
length between 213 - 252 mm and 194.2 - 271.5 mm respectively. The panicle lengths for both the dry and wet seasons were
higher than those observed by Zoundou et al. (2019) who recorded 197.5, 195.0 and 177.5 mm as the highest panicle length
under IR50, IR80 and IR100 respectively.
The yield falls within the range of Materu et al. (2018) who recorded yield of (11.5-7.5 t/ha) and (6.0-5.0 t/ha) for the dry and
wet seasons respectively. However, less yield than attained in this study of 6.3 t/ha and 8.5 t/ha was reported for the same
area location by Kombe (2012) and Reuben et al. (2016) respectively indicating the impact of foliar fertilizers in enhancing
yield performance. The no significant difference in growth and yield attributes among the water regimes was due to heavy
rainfall during the second month (November 2020) and first month (March 2021) of the vegetative phase for both the dry and
wet seasons respectively which disrupted water regimes. This was also reported by Materu et al. (2018).
Effect of fertilizer applications
There was significant difference (p<0.05) among the different fertilizer applications for all growth and yield attributes except
for dry season panicle length and straw weight. The effect of the various fertilizer treatments A, B, C, D and E on plant
height, leaves, total and effective tillers, panicle length, 1000 grains weight, straw and yield for both the dry and wet seasons
is as shown in Table 3.
Table 3: Subplot (fertilizer treatment) analysis
Season
TRT
Plant
Height
(cm)
Leaves
Total
tillers
Effective
tillers
Panicle
length
(mm)
1000 grain
weight (g)
Straw
(g)
Yield
(t/ha)
Dry
Season
A
110.0a
118a
16a
15a
263.8a
32.08a
0.52a
9.41a
B
109.4ab
119a
17b
17b
268.1a
32.07a
0.51a
11.09b
C
108.2ab
110b
14c
13c
262.4a
31.04ab
0.50a
8.19c
D
108.1ab
106bc
14c
13c
264.9a
31.37ab
0.54a
8.16c
E
106.7b
104c
12d
12d
260.9a
30.75b
0.52a
7.26c
Wet
season
A
97.0c
117d
17e
15e
242.7b
30.78cd
0.57b
6.05de
B
91.9d
120d
19e
17e
234.4bc
31.71c
0.53bc
6.74d
C
88.6de
105d
15f
13f
223.9ce
30.33d
0.53bc
5.70e
D
84.7ef
82e
12g
11g
230.6c
29.98d
0.46cd
4.38f
E
82.5f
70e
10g
9h
215.8e
28.81e
0.40d
4.10f
(Mean values followed by different letters within similar columns differ significantly at p< 0.05 according to Duncan’s
Multiple-range test)
Plant height and leaves
For the dry season, the highest plant height was attained by A (110.0 cm) followed by B (109.4 cm), C (108.2 cm) and D
(108.1 cm) while E had the least plant height of 106.7 cm. A similar trend was observed under the wet season with plant
heights of 97.0, 91.9, 88.6, 84.7 and 82.5 cm for treatments A, B, C, D and E respectively. For the dry season, B had 1%, 8%,
12% and 14% more leaves than treatments A, C, D, and E respectively. However, there was no significant difference between
treatment B and A while a high significant difference (p<0.01) existed between treatment pairs (B, C), (B, D) and (B, E). For
the wet season, B had the highest number of leaves (120) while E had the least (70). There was no significant difference
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33
among treatments A, B and C with B having only 3% and 14% more leaves than A and C respectively. Treatment D had
17% more leaves than E but with no significant difference (p>0.05).
Total and effective tillers
Treatment B had the highest number of total and effective tillers followed by A, C, D and E in both seasons. For the dry
season, B had 13% more effective tillers than A, 31% than (C and D) and 42% than E. The post-hoc results indicate no
significant difference between treatments C and D while the rest of the fertilizer applications were significantly different
(p<0.05). For the wet season, treatments B, A, C and D had 90%, 70%, 50% and 20% more total tillers than E. While
considering effective tillers, there was no significant difference between treatments A and B while the rest of the treatments
were significantly different.
Panicle length and straw weight
For the dry season, panicle length ranged between 268.1 and 260.9 mm with B and E having the highest and least panicle
length respectively. For the wet season, A had the highest panicle length of 242.7 mm while E had the least panicle length of
215.8 mm. There was a significant difference between treatments (A, B), (B, C), (C, D) and (C, E). Dry season straw weight
ranged between 0.50 and 0.54 g with the highest and least weight being attained by D and C respectively with no significant
difference (p>0.05) between the various fertilizer applications. For the wet season, treatments A and E had the highest
(0.57g) and least (0.40g) straw weight respectively. Treatment A had 8%, 24% and 43% more straw than (B and C), D and E
respectively.
Dry weight of 1000 grains and yield
For the dry season, A had the highest 1000 grain weight of 32.08g while E had the least of 30.8g. However, there was no
significant difference between treatment pairs (A, B), (C, D) and (D, E). For the wet season, treatment B had the highest
average 1000 grain weight (31.7g) while E had the least (28.8g). There was no significant difference between treatment pairs
(A, B), (A, C) and (C, D). For the dry season, Treatment B had the highest yield (11.09 t/ha) followed by A, C, D and E with
9.41, 8.19, 8.16 and 7.26 t/ha respectively. Treatment B had 18% more yield than the conventional treatment A while
treatment C had 13% less yield than A hence justifying the no significant difference between treatment A and C. Treatment B
had 53% more yield than E and there was no significant difference between E and D. A similar trend was followed by the wet
season with B having the highest average yield of 6.74 t/ha followed by A, C, D and E with 6.05, 5.70, 4.38 and 4.10 t/ha
respectively. Treatment B had the best yield performance attributed to the combination of both basal and foliar fertilizers.
This is in agreement with Hashem (2019) who recommended combining basal and foliar fertilizers as a form of rice yield
enhancement. Treatment E had the least performance as no fertilizers were applied throughout the entire growing period.
However, its overall performance was still better than the conventional continuous flooding with average yield of 3.83 t/ha
(Kombe, 2012) due to the impact of SRI. The practice of alternate wetting and drying (AWD) facilitates about 80% of free
living bacteria and other microbes in and around rice roots (Berkelaar, 2007) which have nitrogen fixing ability thereby
supplying nutrients such as nitrogen, phosphorus and potassium in addition to micronutrients such as calcium, sulphur, iron,
copper, manganese and zinc to the soil hence the better performance. Further, AWD creates a moist but unsaturated soil
condition that facilitates deeper root growth in the search for water hence aiding crop growth and yield. This is in agreement
with Materu et al. (2018) and Dinesh et al. (2019). In addition, the large plant spacing under SRI (25 x 25 cm) creates ample
aeration therefore less competition for nutrients hence more growth. This is in agreement with Kahimba et al. (2014) and
Reuben et al. (2016).
The dry season had more yield than the wet season due to the differences in the cropping seasons. This was also observed by
Materu et al. (2018). Further, actual yield of rice depends on the amount of starch that fills the spikelets especially during the
ripening stage. Low temperatures affect crop development at the various growth stages and can lead to spikelet sterility
where no grain is produced (Ndiiri et al., 2017). Ndiiri et al. (2017) reported that minimum temperatures below 16 °C
yielded 100% sterility. The average minimum temperatures in this study for the wet season were 14.8 °C and 13.5 °C for the
months of May and June, the reproductive and ripening stages respectively which are most prone to sterility. This therefore
justifies the cause of the lower yields in the wet season than the dry season. However, the maximum yield attained in both
the dry and wet seasons was greater than the yield obtained by Kombe (2012) and Reuben et al. (2016) who reported a
maximum yield of 6.3 t/ha and 8.5 t/ha respectively under SRI with 25 x 25 cm spacing for Mkindo area. The increase in
yield is attributed to the effect of foliar fertilizers. Lithovit fertilizers contain calcium carbonate (CaCO3) (80%) which
decomposes to calcium oxide (CaO) and carbon dioxide (CO2) in the stomata of the leaves which accelerates photosynthesis
hence leading to increased carbon intake and assimilation.
Interaction effect between water and fertilizer applications
The interaction between water applications and fertilizer treatments for both seasons across all growth and yield attributes
was not significant (p> 0.05). These findings are similar to Zhang et al. (2012) who found no significant interaction among
rice varieties, water management and fertilizer application under AWD of rice.
Aseru et. al., /IJBAS/11(2); 2022 ; 26-36
International Journal of Basic and Applied Sciences
34
Conclusion
Generally, integrating deficit irrigation and carbonate foliar fertilizers into SRI had a positive impact on growth and yield
attributes. The IR80 had the best performance in terms of growth and yield attributes. Among fertilizer applications, treatment
B had the best overall performance in terms of growth and yield. Therefore, combining foliar treatments with conventional
fertilizers played a key role in the performance enhancement of treatment B. Foliar treatments C and D performed
considerably as good as the conventional fertilizer treatment A. This is attributed to the influence of Lithovit foliar fertilizer
which accelerates physiological and biological processes, avails micronutrients and reduces on impact of water stress.
Treatment E had the least performance in terms of all growth and yield attributes as no fertilizers were applied throughout the
entire growing period. However, its overall performance was still better than the conventional continuous flooding due to the
impact of AWD practice under SRI. The interaction between water and fertilizer applications was not significant due to
disruption of water regimes by heavy rainfall. Further, the dry season performed better than the wet season for all growth and
yield attributes due to low temperatures during the reproductive and ripening stages that affected crop growth and
development.
Acknowledgement
The authors wish to acknowledge the Department of Civil and Water Resources Engineering, Sokoine University of
Agriculture for their tremendous contribution towards this work. This research was funded by the KfW-East African
Community (EAC) scholarship program. This work is dedicated to the late Prof. Noble Ephraim Banadda who passed on
during the course of this research.
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